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Tumor Markers

Number: 0352



Policy
  1. Aetna considers any of the following serum tumor markers for the stated indication medically necessary:

    1. Prostate-specific antigen (PSA) for prostate cancer screening (see CPB 0521 - Prostate Cancer Screening), staging, monitoring response to therapy, and detecting disease recurrence. 
    2. Carcinoembryonic antigen (CEA) for any off the following:
       
      1. As a preoperative prognostic indicator in members with known colorectal carcinoma or mucinous appendiceal carcinoma when it will assist in staging and surgical treatment planning; or 
      2. Pancreatic cyst fluid CEA for distinguishing mucinous from non-mucinous malignant pancreatic cysts; or
      3. To detect asymptomatic recurrence of colorectal cancer after surgical and/or medical treatment for the diagnosis of colorectal cancer (not as a screening test for colorectal cancer); or
      4. To monitor response to treatment for metastatic cancer.
         
    3. 1p19q codeletion molecular cytogenetic analysis for astrocytoma and gliomas
    4. ALK gene fusion as a molecular biomarker in non-small cell lung cancer
    5. ALK gene rearrangement for diffuse large B cell lymphoma, peripheral T-cell lymphoma, and post-transplant lymphoproliferative disorder
    6. ALK translocations for selecting candidates for crizotinib (Xalkori) in inflammatory myofibroblastic tumor
    7. APC for familial adenomatous polyposis when criteria are met in CPB 140 - Genetic Testing; and for desmoid fibromatosis; experimental for other indications.
    8. Afirma Thyroid FNA analysis for assessing fine needle aspiration samples from thyroid nodules that are indeterminate; experimental for other indications.
    9. BCR/ABL fluorescent in situ hybridization (FISH) for lymphoblastic lymphoma, acute myeloid leukemia, acute lymphocytic leukemia and chronic myelogenous leukemia; experimental for other indications.
    10. BRAF V600 mutation for hairy cell leukemia; gastrointestinal stromal tumors; Lynch syndrome testing for persons meeting criteria in CPB 140 - Genetic Testing; melamoma for vemurafenib, dabrafenib, and trametinib (see CPB 715 - Pharmacogenomic and Pharmacodynamic Testing; and colorectal cancer if KRAS nonmutated; experimental for other indications.
    11. Cancer antigen 125 (CA 125) levels for any of the following:
       
      1. As a preoperative diagnostic aid in women with ovarian masses that are suspected to be malignant, such that arrangements can be made for intraoperative availability of a gynecological oncologist if the CA 125 is increased; or
      2. As a screening test for ovarian cancer when there is a history of hereditary cancer syndrome (a pattern of clusters of ovarian cancer within two or more generations); or
      3. Diagnosis of ovarian cancer in women with new symptoms (bloating, pelvic or abdominal pain, difficulty eating or feeling full quickly, or urinary frequency and urgency) that have persisted for three or more weeks, where the clinician has performed a pelvic and rectal examination and suspects ovarian cancer; or
      4. In members with adenocarcinoma of unknown primary, to rule out ovarian cancer; or
      5. In members with known ovarian cancer, as an aid in the monitoring of disease, response to treatment, detection of recurrent disease, or assessing value of performing second-look surgery.
         
    12. CA 19-9 to monitor the clinical response to therapy or detect early recurrence of disease in members with known gastric cancer, pancreatic cancer, gallbladder cancer, cholangiocarcinoma or adenocarcinoma of the ampulla of Vater.
    13. CA 19-9 to rule out cholangiocarcinoma in persons with primary sclerosing cholangitis undergoing liver transplantation.
    14. CA 19-9 as a tumor marker for mucinous appendiceal carcinoma.
    15. CD 20, for determining eligibility for anti-CD20 treatment (rituximab) -- see CPB 0314 - Rituximab (Rituxan).
    16. CD 25, for determining eligibility for denileukin diftitox (Ontak) treatment.
    17. CD 31 immunostaining, for diagnosis of angiosarcoma. 
    18. CD 33, for determining eligibility for anti-CD33 (gemtuzumab, Mylotarg) treatment.   
    19. CD 52, for determining eligibility for anti-CD52 (alemtuzumab, Campath) treatment. 
    20. CD117 (c-kit), for determining eligibility for treatment with imatinib mesylate (Gleevec).   
    21. Cyclin D1, for diagnosis and predicting disease recurrence of mantle cell lymphoma.
    22. Epidermal growth factor receptor (EGFR) testing for tyrosine kinase inhibitors (erlotinib (Tarceva), gefitinib (Iressa), afatinib (Gilotrif)) in non-small cell lung cancer.
    23. Human epidermal growth factor receptor 2 (HER2) evaluation in breast, gastric and esophageal cancer - see CPB 0313 - Trastuzumab (Herceptin), Ado-Trastuzumab (Kadcyla) and Pertuzumab (Perjeta).
    24. IGH@ (Immunoglobulin heavy chain locus), gene rearrangement analysis to detect abnormal clonal population(s) in non-Hodgkin’s lymphomas,hairy cell leukemia, and post-transplant lymphoproliferative disorder.
    25. IGK@ (Immunoglobulin kappa light chain locus), gene rearrangement analysis, evaluation to detect abnormal clonal population(s) for non-Hodgkin’s lymphoma, systemic light chain amyloidosis
    26. IDH mutation for glioma
    27. K-ras (KRAS) mutation analysis, with BRAF reflex testing, to predict non-response to cetuximab (Erbitux) and panitumumab (Vectibix) in the treatment of anal adenocarcinoma, metastatic colorectal cancer and small bowel adenocarcinoma; K-ras (KRAS) mutation analysis to predict non-response to erlotinib (Tarceva) in the treatment of non-small cell lung cancer; experimental for all other indications.
    28. Measurement of estrogen and progesterone receptors on primary breast cancers, and on metastatic lesions if the results would influence treatment planning.
    29. MLH1, MSH2, MSH6 for persons meeting HNPCC/Lynch Syndrome testing criteria in CPB 140 - Genetic Testing; colorectal cancer in persons under age 50; and all persons with Stage II colon cancer; experimental for all other indications,
    30. Mycosis fungoides, diagnosis: polymerase chain reaction (PCR) for T-cell receptor gamma chain gene rearrangement as an adjunct to the histopathologic diagnosis of mycosis fungoides.
    31. Myeloperoxidase (MPO) immunostaining, FLT3-ITD, CEBPA mutation, NPM1 mutation, and KIT mutation for diagnosis of acute myeloid leukemia.
    32. NPM1 in acute myeloid leukemia; experimental for other indications.
    33. PML/RARA for acute promyelocytic leukemia; experimental for all other indications.
    34. PTEN for persons meeting Cowden syndrome testing criteria in CPB 140 - Genetic Testing; experimental for all other indications.
    35. Placental alkaline phosphatase (PLAP), to diagnose germ cell seminoma and non-seminoma germ cell tumors in unknown primary cancers.
    36. ROS-1 to predict response to crizotinib (Xalkori) for the treatment of non-small cell lung cancer (NSCLC).
    37. Serial measurements of alpha fetoprotein (AFP) to diagnose germ cell tumors in members with adenocarcinoma, or carcinoma not otherwise specified, involving mediastinal nodes; or the diagnosis and monitoring of hepatocellular carcinoma (e.g., before considering liver transplantation).
    38. Serial measurements of CA 15-3 (also known as CA 27-29 or Truquant RIA) in following the course of treatment in women diagnosed with breast cancer, especially advanced metastatic breast cancer (an increasing CA 15-3 level may suggest treatment failure).
    39. Serial measurements of human chorionic gonadotropin (HCG) to diagnose germ cell tumors in members with adenocarcinoma, or carcinoma not otherwise specified, involving mediastinal nodes, or to monitor treatment in members with known trophoblastic tumors (invasive hydatidiform moles and choriocarcinomas) and germinal cell tumors (teratocarcinoma and embryonal cell carcinoma) of the ovaries or testes, or to monitor for relapse after remission is achieved.
    40. Serial measurements of AFP and HCG together to diagnose and monitor testicular cancer.
    41. Steroid hormone receptor status in both pre-menopausal and post-menopausal members to identify individuals most likely to benefit from endocrine forms of adjuvant therapy and therapy for recurrent or metastatic breast cancer.
    42. Targeted hematologic genomic sequencing panel (5-50 genes) for myelodysplastic syndromes
    43. Targeted solid organ genomic sequencing panel (5-50 genes) for non-small cell lung cancer
    44. TCB@ (T cell antigen receptor, beta), gene rearrangement analysis to detect abnormal clonal population(s); for T-cell prolymphocytic leukemia
    45. TCG@ (T cell receptor, gamma), gene rearrangement analysis for T-cell prolymphocytic leukemia
    46. ThyGenX (formerly Mirinform Thyroid) for assessing fine needle aspiration samples from thyroid nodules that are indeterminate; experimental for other indications
    47. Thyroseq for assessing fine needle aspiration samples from thyroid nodules that are indeterminate; experimental for other indications
    48. Oncotype Dx (also known as 21 gene RT-PCR test) to assess necessity of adjuvant chemotherapy in females or males with recently diagnosed breast tumors, where all of the following criteria are met:

      1. Breast cancer is nonmetastatic (node negative1) or with 1-3 involved ipsilateral axillary lymph nodes; and
      2. Breast tumor is estrogen receptor positive; and
      3. Breast tumor is HER2 receptor negative or breast tumor is HER2 receptor positive and less than 1 cm in diameter. (Rationale: adjuvant chemotherapy with trastuzumab (Herceptin) is considered to be medically necessary regardless of an Oncotype Dx score for HER2 receptor positive lesions 1 cm or more in diameter); and
      4. Adjuvant chemotherapy is not precluded due to any other factor (e.g., advanced age and/or significant co-morbidities); and
      5. Member and physician (prior to testing) have discussed the potential results of the test and agree to use the results to guide therapy (i.e., member will forgo adjuvant chemotherapy if Oncotype Dx score is low).
         
    49. Urokinase plasminogen activator (uPA) and plasminogen activator inhibitor 1 (PAI-1) for the determination of prognosis in patients with newly diagnosed, node negative breast cancer.
    50. Veristrat proteomic testing for patients with advanced NSCLC, whose tumors were without EGFR and anaplastic lymphoma kinase (ALK) mutations, who had progressed after at least one chemotherapy regimen), and for whom erlotinib was considered an appropriate treatment.
    51. ZAP-70, for assessing prognosis and need for aggressive therapy in persons with chronic lymphocytic leukemia.

    1 Either standard node dissection negative by hematoxylin and eosin (H&E) staining or sentinel node negative by H&E staining (if sentinel node is negative by H&E, but immunoassay is positive, then still considered node negative for this purpose). In addition, women with isolated tumor cells in lymph nodes (micrometastases) are considered node negative.

    More than one Oncotype Dx test may be medically necessary for persons with breast cancer who have two or more histologically distinct tumors that meet medical necessity criteria. Repeat Oncotype Dx testing or testing of multiple tumor sites in the same person has no proven value for other indications. Oncotype Dx is considered experimental and investigational for ductal carcinoma in situ (OncotypeDx DCIS), colon cancer (OncotypeDx Colon), prostate cancer (OncotypeDx Prostate) and all other indications.  

  2. Aetna considers the bladder tumor antigen (BTA) Stat test, the nuclear matrix protein (NMP22) test, the fibrin/fibrinogen degradation products (Aura-Tek FDfP) test, or the UroVysion fluorescent in situ hybridization (FISH) test medically necessary in any of the following conditions:

    1. Follow-up of treatment for bladder cancer; or 
    2. Monitoring for eradication of bladder cancer; or 
    3. Recurrences after eradication.

    Aetna considers the BTA Stat test, the NMP22 test, the Aura-Tek FDP test, or the UroVysion fluorescent in situ hybridization (FISH) test experimental and investigational for screening of bladder cancer, evaluation of hematuria, and all other indications.

  3. Aetna considers the use of the ImmunoCyte immunohistochemistry test medically necessary as an adjunct to cystoscopy or cytology in the monitoring of persons with bladder cancer.

    Aetna considers the ImmunoCyte immunohistochemistry test experimental and investigational in the diagnosis of bladder cancer or for screening for bladder cancer in asymptomatic persons.

  4. Aetna considers genetic testing for Janus Kinase 2 (JAK2) mutations in persons with chronic myeloproliferative disorders (CMPDs) medically necessary for the following indications: 1) qualitative assessment of JAK2-V617F sequence variant using methods with detection thresholds of up to 5% for initial diagnostic assessment of adult patients presenting with symptoms of CMPD; 2) diagnostic assessment of polycythemia vera in adults; and 3) differential diagnosis of essential thrombocytosis and primary myelofibrosis from reactive conditions in adults. 

    Aetna considers genetic testing for Janus Kinase 2 (JAK2) mutations in persons with chronic myeloproliferative disorders (CMPDs) experimental and investigational for any other indication including: 1) diagnostic assessment of myeloproliferative disorders in children; 2) quantitative assessment of JAK2-V617F allele burden subsequent to qualitative detection of JAK2-V617F.

  5. Aetna considers each of the following experimental and investigational.  The peer reviewed medical literature does not support these tests as having sufficient sensitivity or specificity necessary to define their clinical role:

      1. CEA used for all other indications including any of the following:

        1. As a screening test for colorectal cancer; or 
        2. As a sole determinant to treat a colorectal cancer member with adjuvant therapy or systemic therapy for presumed metastatic disease; or
        3. For diagnosis, prognosis, or monitoring of treatment in members with lung cancer; or 
        4. For diagnosis of esophageal carcinoma; or
        5. For routine use of CEA alone for monitoring response to treatment of colorectal when there are other simple tests available to indicate a response; or
        6. For screening, diagnosis, staging or routine surveillance of breast cancer.
           
      2. AFP for the diagnosis of trophoblastic tumors and other oncologic indications
      3. Assaying for loss of heterozygosity (LOH) on the long arm of chromosome 18 (18q) or deleted in colon cancer (DCC) protein (18q-LOH/DCC) for colorectal cancer
      4. Biomarker Translation (BT) test for breast cancer and other indications
      5. BluePrint molecular subtyping profile for breast cancer
      6. BRAF mutation analysis in lung cancer, thyroid cancer
      7. Breast Cancer Index/ Breast Cancer Gene Expression Ratio (HOXB13:IL17BR)
      8. BreastNext Next-Gen Cancer Panel
      9. CA 125 for all other indications including use as a screening test for colorectal cancer or ovarian cancer (other than as indicated above) or for differential diagnosis of members with symptoms of colonic disease
      10. CA 19-9 for all other indications including breast, colorectal, esophageal, gastro-esophageal, liver, or uterine cancer; pancreatic pseudocyst; screening persons with primary sclerosing cholangiitis without signs or symptoms of cholangiocarcinoma; or screening persons with primary sclerosing cholangitis for development of cholangiocarcinoma.
      11. CancerNext Next-Gen Cancer Panel
      12. Carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6) for predicting the risk of breast cancer.
      13. Carcinoembryonic antigen cellular adhesion molecule-7 (CEACAM-7) expression as a predictive marker for rectal cancer recurrence
      14. Caris Target Now Molecular Profiling Test
      15. CEA, Cyfra21-1 (a cytokeratin 19 fragment), p53, squamous cell carcinoma antigen (SCC-Ag) and vascular endothelial growth factor C (VEGF-C) for diagnosis of esophageal carcinoma
      16. CellSearch assay (for all cancers)
      17. CK5, CK14, p63, and Racemase P504S testing for prostate cancer
      18. c-Met expression for predicting prognosis in persons with advanced NSCLC and colorectal cancer, and other indications
      19. Cofilin (CFL1) as a prognostic and drug resistance marker in non-small cell lung cancer
      20. ColonSentry test for screening of colorectal cancer
      21. Colonext Next-Gen Cancer Panel
      22. ColoPrint, CIMP, LINE-1 hypomethylation, and Immune cells for colon cancer
      23. Colorectal Cancer DSA (Almac Diagnostics, Craigavon, UK)
      24. ConfirmMDx for prostate cancer (see CPB 698 - Prostate Cancer Biopsy)
      25. CxBladder Test
      26. Cyclin D1 and FADD (Fas-associated protein with death domain) for head and neck squamous cell carcinoma
      27. Decipher test (a RNA biomarkers assay) for prostate cancer
      28. DecisionDx-UM (uveal melanoma) (Castle Biosciences, Phoenix, AZ)
      29. DCIS Recurrence Score
      30. Des-gamma-carboxy prothrombin (DCP) (also known as "prothrombin produced by vitamin K absence or antagonism II" [PIVKA II]) for diagnosing and monitoring hepatocellular carcinoma and other indications
      31. EarlyCDT-Lung test
      32. EGFR gene expression analysis for transitional (urothelial) cell cancer
      33. EGFRVIII for glioblastoma multiforme
      34. EML4-ALK as a diagnostic tool for stage IV non-small-cell lung cancer
      35. Estrogen and progesterone receptors when used alone to assign a member with breast cancer to prognostic groupings since they are relatively weak predictors of long-term relapse and breast cancer related mortality rates
      36. Excision repair cross-complementation group 1 protein (ERCC1) for persons with NSCLC, colon or with gastric cancer who are being considered for treatment with platinum-based chemotherapy, and other indications
      37. FoundationOne and FoundationOne Heme
      38. Galectin-3 for prostate cancer
      39. Gene hypermethylation for prostate cancer
      40. GeneKey (GeneKey Corp., Boston, MA)
      41. GeneSearch Breast Lymph Node (BLN) assay
      42. Glutathione-S-transferase P1 (GSTP1) for screening, detection and management of prostate cancer
      43. HE4 for ovarian cancer and other indications
      44. HERmark testing for breast cancer and other indications
      45. Insight DX Breast Cancer Profile
      46. Ki67 for breast cancer
      47. Mammaprint
      48. Mammostrat
      49. Microarray-based gene expression profile testing using the MyPRS test for multiple myeloma
      50. Micro-RNAs (miRNAs) miRview mets and miRview mets2 (Rosetta Genomics Laboratories, Philadelphia, PA; Rosetta Genomics Ltd., Rehovot, Israel)
      51. MLH1 tumor promoter hypermethylation for endometrial cancer
      52. Mucin 4 expression as a predictor of survival in colorectal cancer
      53. Mucin 5AC (MUC5AC) as serum marker for biliary tract cancer
      54. My Prognostic Risk Signature (MyPRS) (Signal Genetics LLC, New York, NY)
      55. NRAS mutation for selecting persons with metastatic colorectal cancer who may benefit from (i) EGFR-targeted monoclonal antibody therapies cetuximab and panitumumab or (ii) anti-VEGF antibody bevacizumab; to predict disease prognosis and select persons with melanoma who may benefit from tyrosine kinase inhibitor therapies, and other indications
      56. OVA1 test
      57. OvaCheck test
      58. Ovanext Next-Gen Cancer Panel
      59. OvaSure
      60. OncInsights (Intervention Insights, Grand Rapids, MI)
      61. p16 protein expression as a prognostic marker in non-oropharyngeal squamous cell carcinoma (cancer of the oral cavity, hypopharynx, or larynx)
      62. Panexia test
      63. Pathwork Tissue of Origin test
      64. Phosphatidylinositol-4,5-bisphosphonate 3-kinase, catalytic subunit alpha polypeptide gene (PIK3CA) for predicting disease prognosis and selecting individuals with metastatic colorectal cancer who are being considered for treatment with EGFR antagonists cetuximab and panitumumab, and other indications
      65. PreOvar test for the KRAS-variant to determine ovarian cancer risk
      66. Previstage GCC for colorectal cancer
      67. Prolaris for prostate cancer
      68. ProOnc TumorSourceDx test (Prometheus Laboratories, San Diego, CA) to identify tissue or origin for metastatic tumor
      69. Prostate core mitotic test
      70. Prostate Px and Post-Op Px for predicting recurence of prostate cancer
      71. Proveri prostate cancer assay (PPCA)
      72. PTEN gene expression for non-small cell lung cancer
      73. Ras oncogenes (except KRAS and BRAF)
      74. ResponseDx Colon
      75. Ribonucleotide reductase subunit M1 (RRM1) for persons with NSCLC who are being considered for treatment with gemcitabine-based chemotherapy, and other indications
      76. ROMA (Risk of Ovarian Malignancy Algorithm) for ovarian cancer
      77. Rotterdam Signature 76-gene panel
      78. Serum amyloid A as a biomarker for endometrial endometrioid carcinoma to monitor disease recurrence and rtargetesponse to therapy
      79. Single nucleotide polymorphisms for breast cancer (Oncovue, Brevagen)
      80. TargetPrint gene expression test for evaluation of estrogen receptor, progesterone receptor, and HER2receptor status in breast cancer
      81. The 41-gene signature assay
      82. Theros Breast Cancer Index
      83. Theros CancerType ID (bioTheranostics Inc., San Diego, CA)
      84. Thymidylate synthase
      85. TMPRSS fusion genes for prostate cancer
      86. Topographic genotyping (Pancragen (formerly PathFinderTG))
      87. Total (whole) gene sequencing for cancer
      88. TP53 mutation analysis for ovarian cancer
      89. UroCor cytology panels (DD23 and P53) for bladder cancer
      90. Vascular Endothelial Growth Factor (VEGF)
      91. Vascular endothelial growth factor receptor 2 (VEGFR2) expression for identifying persons with colorectal cancer that is likely to respond to VEGF inhibition, and other indications
      92. WT1 mutation, RUNX1 mutation, MLL-PTD, IDH1 mutation, IDH2 R172, IDH2 codon 140 mutation
      93. Any of the following circulating tumor markers also is considered experimental and investigational for screening asymptomatic subjects for cancer, diagnosis, staging, routine surveillance of cancer and monitoring the response to treatment:
         

        a2-PAG

        CA-SCC

        MAM-6

        TAG12

        AMACR Cathepsin-D, Cathepsin-L Motility-related protein (MRP)

        TAG72

        Bcl-2 Cyclin E (fragments or whole length) Multidrug resistance glycoprotein (Mdr1)

        TAG72.3

        BCM DU-PAN-2 Murine double minute 2 (MDM2) TAG72.5
        CA195

        Early prostate cancer antigen (EPCA)

        NSE

        TATI

        CA242 Guanylyl cyclase C (Previstage GCC molecular test) p53 (TP53)

        Thrombospondin-1 (THBS-1)

        CA50 Hepsin PCA3 (DD3) / UpM3 Thymosin B15
        CA549 Human kallikrein 2 (HK2)

        PNA/ELLA

        TNF-a
        CA72-4 LASA

        Prostate stem cell antigen (PSCA)

        Topoisomerase II Alpha (TOP2A)
        CAM17-1

        LPA

        SCC TPA
        CAM26

        M 26

        SLEX

        Thymosin B15
        CAM29 M 29

        SPAN-1

        Nuclear Matrix Protein 66 (NMP66)

        CAR-3

        MSA

        SLX

        Anti-malignin antibody screen (AMAS) test

        CYFRA21-1

        MCA

        ST-439

         
Background

Tumor markers are substances normally produced in low quantities by cells in the body. Detection of a higher-than-normal serum level by radioimmunoassay or immunohistochemical techniques usually indicates the presence of a certain type of cancer.  Currently, the main use of tumor mfarkers is to assess a cancer's response to treatment and to check for recurrence. In some types of cancer, tumor marker levels may reflect the extent or stage of the disease and can be useful in predicting how well the disease will respond to treatment.  A decrease or return to normal in the level of a tumor marker may indicate that the cancer has responded favorably to therapy.  If the tumor marker level rises, it may indicate that the cancer is spreading.  Finally, measurements of tumor marker levels may be used after treatment has ended as a part of follow-up care to check for recurrence.

However, in many cases the literature states that measurements of tumor marker levels alone are insufficient to diagnose cancer for the following reasons: (1) tumor marker levels can be elevated in people with benign conditions; (2) tumor marker levels are not elevated in every person with cancer, especially in the early stages of the disease; and (3) many tumor markers are not specific to a particular type of cancer; and (4) the level of a tumor marker can be elevated by more than one type of cancer.

PSA

Elevated levels of Prostate-Specific Antigen (PSA) may be found in the blood of men with benign prostate conditions, such as prostatitis and benign prostatic hyperplasia (BPH), or with a malignant growth in the prostate. While PSA does not allow distinction between benign prostate conditions and cancer, an elevated PSA level may indicate that other tests are necessary to determine whether cancer is present. PSA levels have been shown to be useful in monitoring the effectiveness of prostate cancer treatment, and in checking for recurrence after treatment has ended. Use of PSA for screening remains very controversial.  Although researchers are in the process of studying the value of PSA along with digital rectal exams for routine screening of men ages 55 to 74 for prostate cancer; and the literature does not show at this time whether using PSA to screen for prostate cancer actually does reduce the number of deaths caused by this cancer.  The American Cancer Society recommends clinicians and patients consider screening with PSA and digital rectal exam for African American men and men with familial tendency age 40 or older and all men age 50 or older.

PCA3

In a review on biomarkers for prostate cancer detection, Parekh, et al. (2007) stated that prostate stem cell antigen, alpha-methyl coenzyme-A racemase, PCA3, early prostate cancer antigen, hepsin and human kallikrein 2 are promising markers that are currently undergoing validation. An assessment of PCA3 prepared for the Agency for Healthcare Research and Quality (2013) concluded: "For diagnostic accuracy, there was a low strength of evidence that PCA3 had better diagnostic accuracy for positive biopsy results than tPSA elevations, but insufficient evidence that this led to improved intermediate or long-term health outcomes. For all other settings, comparators, and outcomes, there was insufficient evidence."

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (2013) found insufficient evidence to recommend prostate cancer antigen 3 (PCA3) testing to inform decisions for when to rebiopsy previously biopsy-negative patients for prostate cancer or to inform decisions to conduct initial biopsies for prostate cancer in at-risk men (e.g., previous elevated prostate-specific antigen test or suspicious digital rectal examination). The EGAPP Working Group found insufficient evidence to recommend PCA3 testing in men with cancer-positive biopsies to determine if the disease is indolent or aggressive in order to develop an optimal treatment plan. The EGAPP Working Group concluded that, based on the available evidence, the overall certainty of clinical validity to predict the diagnosis of prostate cancer using PCA3 is deemed “low.” The EGAPP Working Group discouraged clinical use for diagnosis unless further evidence supports improved clinical validity. The EGAPP Working Group also found that, based on the available evidence, the overall certainty of net health benefit is deemed “low.” The EGAPP Working Group discourages clinical use unless further evidence supports improved clinical outcomes.

B15

Hutchinson et al (2005) stated that in tissue-based assays, thymosin beta15 (B15) has been shown to correlate with prostate cancer and with recurrence of malignancy. To be clinically effective, it must be shown that thymosin B15 is released by the tumor into body fluids in detectable concentrations.  These researchers developed a quantitative assay that can measure clinically relevant levels of thymosin B15 in human urine.  Sixteen antibodies were raised against recombinant thymosin B15 and/or peptide conjugates.  One antibody, having stable characteristics over the wide range of pH and salt concentrations found in urine and minimal cross-reactivity with other beta thymosins, was used to develop a competitive enzyme-linked immunosorbent assay (ELISA).  Urinary thymosin B15 concentration was determined for control groups; normal (n = 52), prostate intraepithelial neoplasia (PIN, n = 36), and patients with prostate cancer; untreated (n = 7) with subsequent biochemical failure, radiation therapy (n = 17) at risk of biochemical recurrence.  The operating range of the competition ELISA fell between 2.5 and 625 ng/ml.  Recoveries exceeded 75%, and the intra- and inter-assay coefficients of variability were 3.3% and 12.9%, respectively.  No cross-reactivity with other urine proteins was observed.  A stable thymosin B15 signal was recovered from urine specimens stored at -20 degrees C for up to 1 year.  At a threshold of 40 (ng/dl)/microg protein/mg creatinine), the assay had a sensitivity of 58% and a specificity of 94%.  Relative to the control groups, thymosin B15 levels were greater than this threshold in a significant fraction of patients with prostate cancer (p < 0.001), including 5 of the 7 patients who later experienced PSA recurrence.  The authors concluded that an ELISA that is able to detect thymosin B15 at clinically relevant concentrations in urine from patients with prostate cancer has been established.  They noted that the assay will provide a tool for future clinical studies to validate urinary thymosin B15 as a predictive marker for recurrent prostate cancer.

CEA

Carcinoembryonic antigen (CEA) is a normal cell product that is over-expressed by adenocarcinomas, primarily of the colon, rectum, breast, and lung. It is normally found in small amounts in the blood of most healthy people, but may become elevated in people who have cancer or some benign conditions. 

CEA is an oncofetal glycoprotein present in the gastrointestinal tract and body fluids of the embryo and fetus (Chin, et al., 2006). It is also present in certain adult gastrointestinal cells, including the mucosal cells of the colorectum, and small amounts are present in blood. Blood levels are often elevated in patients with disseminated cancers and in some patients with nonmalignant disease.

According to the available literature, the primary use of CEA is in monitoring colorectal cancer, especially when the disease has metastasized.  CEA is also used after treatment to check for recurrence of colorectal cancer.  However, the literature indicates a wide variety of other cancers can produce elevated levels of this tumor marker, including melanoma; lymphoma; and cancers of the breast, lung, pancreas, stomach, cervix, bladder, kidney, thyroid, liver, and ovary.  Elevated CEA levels can also occur in patients with non-cancerous conditions, including inflammatory bowel disease, pancreatitis, and liver disease.

The American Society of Clinical Oncology (ASCO)'s update of recommendations for the use of tumor markers in gastrointestinal cancer (Gershon, et al., 2006) stated that post-operative CEA levels should be performed every 3 months for stage II and III disease for at least 3 years if the patient is a potential candidate for surgery or chemotherapy of metastatic disease.

Ca-125

CA 125 is expressed by >80 percent of non-mucinous ovarian epithelial neoplasms (Chin, et al., 2006). Approximately half of women with metastatic ovarian cancer have an elevated CA 125 level.

The Gynecologic Cancer Foundation, the Society of Gynecologic Oncologists, and the American Cancer Society have issued a consensus statement to promote early detection of ovarian cancer, which recommends that women who have symptoms, including bloating, pelvic or abdominal pain, difficulty eating or feeling full quickly, and urinary frequency and urgency, are urged to see a gynecologist if symptoms are new and persist for more than three weeks (ACS, 2007; SGO, 2007).  Ovarian cancer is among the deadliest types of cancer because diagnosis usually comes very late, after the cancer has spread. If the cancer is found and surgically removed before it spreads outside the ovary, the five year survival rate is 93%. However, only 19% of cases are detected early enough for that kind of successful intervention. It is estimated that 22,430 new cases and 15,280 deaths will be reported in 2007 (ACS, 2007). The consensus statement recommendations are based on studies that show the above symptoms appeared in women with ovarian cancer more than in other women (Goff, et al., 2004; Daly & Ozols, 2004). The recommendations acknowledge that there is not consensus on what physicians should do when patients present with these symptoms. According to a consensus statement issued by the Gynecologic Cancer Foundation, pelvic and rectal examination in women with the symptoms is one first step. If there is a suspicion of cancer, the next step may be a transvaginal ultrasound to check the ovaries for abnormal growths, enlargement, or telltale pockets of fluid that can indicate cancer. Testing for CA-125 levels should also be considered.

There is no evidence available that measurement of CA-125 can be effectively used for widespread screening to reduce mortality from ovarian cancer, nor that the use of this test would result in decreased rather than increased morbidity and mortality.  According to the available literature, not all women with elevated CA 125 levels have ovarian cancer. CA 125 levels may also be elevated by cancers of the uterus, cervix, pancreas, liver, colon, breast, lung, and digestive tract. Non-cancerous conditions that can cause elevated CA 125 levels include endometriosis, pelvic inflammatory disease, peritonitis, pancreatitis, liver disease, and any condition that inflames the pleura.  Menstruation and pregnancy can also cause an increase in CA 125.  However, according to the available literature, changes in CA 125 levels can be effectively used in the management of treatment for ovarian cancer. In women with ovarian cancer being treated with chemotherapy, the literature suggests a falling CA 125 level generally indicates that the cancer is responding to treatment and increased survival is expected. Increasing CA 125 levels during or after treatment, on the other hand, may suggest that the cancer is not responding to therapy or that residual cancer remains.  According to the available literature, failure of the CA 125 level to return to normal after three cycles of chemotherapy indicates residual tumor, early treatment failure and decreased survival. Under accepted guidelines, CA 125 levels can also be used to monitor patients for recurrence of ovarian cancer.  Although an elevated CA 125 level is highly correlated with the presence of ovarian cancer, the literature suggests a normal value does not exclude residual or recurrent disease.

Aetna's preventive services guidelines are based on the recommendations of leading primary care medical professional organizations and federal public health agencies.  None of these organizations recommend routine screening of average-risk, asymptomatic women with serum CA-125 levels for ovarian cancer.  These organizations have concluded that serum CA-125 levels are not sufficiently sensitive or specific for use as a screening test for ovarian cancer, and that the harms of such screening outweigh the benefits.

The American College of Obstetricians and Gynecologists (2002) has stated that "[u]nfortunately, there is no screening test for ovarian cancer that has proved effective in screening low-risk asymptomatic women. Measurement of CA 125 levels and completion of pelvic ultrasonography (both abdominal and transvaginal) have been the two tests most thoroughly evaluated.... Data suggest that currently available tests do not appear to be beneficial for screening low-risk, asymptomatic women because their sensitivity, specificity, positive predictive value, and negative predictive value have all been modest at best. Because of the low incidence of disease, reported to be approximately one case per 2,500 women per year, it has been estimated that a test with even 100% sensitivity and 99% specificity would have a positive predictive value of only 4.8%, meaning 20 of 21 women undergoing surgery would not have primary ovarian cancer. Unfortunately, no test available approaches this level of sensitivity or specificity."

The National Cancer Institute (2004) has stated: "There is insufficient evidence to establish that screening for ovarian cancer with serum markers such as CA 125 levels, transvaginal ultrasound, or pelvic examinations would result in a decrease in mortality from ovarian cancer.  A serious potential harm is the false-positive test result, which may lead to anxiety and invasive diagnostic procedures. There is good evidence that screening for ovarian cancer with the tests above would result in more diagnostic laparoscopies and laparotomies than new ovarian cancers found. Unnecessary oophorectomies may also result."

The U.S. Preventive Services Task Force (2004) recommends against routine screening with serum CA-125 level for ovarian cancer.  The Task Force concluded that the potential harms of such screening outweigh the potential benefits.

HE4

A variety of other tumor markers have been investigated for early detection of ovarian cancer as well as different combinations of tumor markers complementary to CA 125 that could potentially offer greater sensitivity and specificity than CA 125 alone.  Preliminary studies on HE4 (human epididymis protein 4), a relatively new marker for ovarian cancer, reported similar sensitivity to CA 125 when comparing ovarian cancer cases to healthy controls, and a higher sensitivity when comparing ovarian cancer cases to benign gynecologic disease (Hellstrom, et al., 2003 & 2008; Moore, et al., 2008;)  However, an assessment on genomic tests for ovarian cancer prepared by Duke University for the Agency for Healthcare Research and Quality (AHRQ, 2006) stated, "Although research remains promising, adaptation of genomic tests into clinical practice must await appropriately designed and powered studies in relevant clinical settings."  Further studies are needed to determine if HE4 significantly adds to the sensitivity of CA 125 while maintaining a high specificity.

Ca 15-3

CA 15-3 is a serum cancer antigen that has been used in the management of patients with breast cancer.  According to the available literature, its low detection rate in early stage disease indicates that CA 15-3 cannot be used to screen or diagnose patients with breast cancer.  It has been widely used to monitor the effectiveness of treatment for metastatic cancer. Elevated serum CA 15-3 concentrations are found in 5 percent of stage I, 29 percent of stage II, 32 percent of stage III and 95 percent of stage IV carcinoma of the breast (Chin, et al, 2006). Most (96 percent) patients with a CA 15-3 increase of greater than 25 percent have disease progression. Most (nearly 100 percent) patients with a CA 15-3 decrease of greater than 50 percent are responding to treatment.

Cancers of the ovary, lung, and prostate may also raise CA 15-3 levels.  The literature indicates elevated levels of CA 15-3 may be associated with non-cancerous conditions, such as benign breast or ovarian disease, endometriosis, pelvic inflammatory disease, and hepatitis.

Similar to the CA 15-3 antigen, CA 27-29 is found in the blood of most breast cancer patients. The literature indicates CA 27-29 levels may be used in conjunction with other procedures (such as mammograms and measurements of other tumor marker levels) to check for recurrence in women previously treated for stage II and stage III breast cancer. CA 27-29 levels can also be elevated by cancers of the colon, stomach, kidney, lung, ovary, pancreas, uterus, and liver.  First trimester pregnancy, endometriosis, ovarian cysts, benign breast disease, kidney disease, and liver disease are non-cancerous conditions that can also elevate CA 27-29 levels.

Elevated CA 27.29 levels are primarily associated with metastatic breast cancer, where it can be used to monitor the course of disease, response to treatment, and detect disease recurrence (Chin, et al., 2006). Elevated serum CA 27.29 concentrations are found in 95 percent of stage IV breast cancer. In addition, CA 27.29 has been found to be elevated in lung (43 percent), pancreas (47 percent), ovarian (56 percent), and liver (55 percent) cancer.

Ca 19-9

CA 19-9 is a mucin-glycoprotein first identified from a human colorectal carcinoma cell line and is present in epithelial tissue of the stomach, gall bladder, pancreas and prostate (Chin, et al., 2006). Concentrations are increased in patients with pancreatic, gastric, and colon cancer as well as in some nonmalignant conditions. Increasing levels generally indicate disease progression, whereas decreasing levels suggest therapeutic response.

Initially found in colorectal cancer patients, CA 19-9 has also been identified in patients with pancreatic, stomach, hepatocellular cancer, and bile duct cancer. In those who have pancreatic cancer, the literature indicates higher levels of CA 19-9 tend to be associated with more advanced disease.  Although the sensitivity of the CA 19-9 level in patients with pancreatic cancer is relatively high, the specificity is lowered by elevations that occur in patients with benign pancreatic or liver disease.  Non-cancerous conditions that may elevate CA 19-9 levels include gallstones, pancreatitis, cirrhosis of the liver, and cholecystitis.  Although excellent correlations have been reported between CA 19-9 measurements and relapse in patients with pancreatic cancer who are followed after surgical resection, no patient has been salvaged by the earlier diagnosis of relapse, a fact that reflects the lack of effective therapy.

Guidelines from the National Comprehensive Cancer Network (NCCN, 2010) state that measurement of CA 19-9 should be considered in evaluating patients with intrahepatic or extrahepatic cholangiocarcinoma and gallbladder cancer. The guidelines note that CA 19-9 is often elevated in persons with cholangiocarcinoma or gallbladder cancer, although this marker is not specific for these cancers.  Nehls, et al. (2004) considered CA19-9 as one of the several new potential tumor markers for the diagnosis of cholangiocarcinoma.  Levy, et al. (2005) aimed to characterize the test properties of CA 19-9 and of a change in CA 19-9 over time in predicting cholangiocarcinoma in patients with primary sclerosing cholangitis. Charts of 208 patients were reviewed. Fourteen patients had cholangiocarcinoma. Median CA 19-9 was higher with cholangiocarcinoma (15 versus 290 U/ml, p < 0.0001). A cutoff of 129 U/ml provided: sensitivity 78.6%, specificity 98.5%, adjusted positive predictive value 56.6% and negative predictive value 99.4%. The median change over time was 664 U/ml in cholangiocarcinoma compared to 6.7 U/ml in primary sclerosing cholangitis alone (p < 0.0001). A cutoff of 63.2 U/ml for change in CA 19-9 provided: sensitivity 90%, specificity 98% and positive predictive value 42%.

CA 19-9 is produced by adenocarcinomas of the pancreas, stomach, gall-bladder, colon, ovary, and lung, and it is shed into the circulation.  Although numerous studies have addressed the potential utility of CA 19-9 in adenocarcinoma of the colon and rectum, the sensitivity of CA 19-9 was always less than that of the CEA test for all stages of disease. Its use for screening asymptomatic populations has been hampered by a false-positive rate of 15% to 30% in patients with non-neoplastic diseases of the pancreas, liver, and biliary tract.  Only a few studies have addressed the use of CA 19-9 in monitoring patients' post-primary therapy. Significant postsurgical decreases are observed for CA 19-9, but these decreases have not been correlated with survival or disease-free interval. In monitoring response to treatment, decreases in CEA have been found to more accurately reflect response to therapy than did decreases of CA 19-9. Progressive increases of the marker may signal disease progression in 25% of the patients who express the CA 19-9 marker, but this monitoring provides only a minimal lead time of 1 to 3 months. Monitoring with CA 19-9 has not been shown to improve the management of patients with colorectal cancer. The serum CA 19-9 level does not add significant information to that provided by CEA, which is currently regarded as the marker of choice for this neoplasm.

Sinakos and colleagues (2011) evaluated the long-term outcomes in Mayo Clinic patients presenting with primary sclerosing cholangitis (PSC)  between 2000 and 2010 (n= 73) for incidence of cholagiocarcinoma (CCA).    The results showed initial levels of CA 19-9 in patients without CCA were significantly lower than those from patients with CCA (p < 0.0001).  No factors known  to affect CA 19-9 levels were identified in 33% of the patients without CCA; endoscopic treatment and recurrent bacterial cholangitis were associated with levels of CA 19-9 in 26% and 22% of these patients, respectively.

Juntermanns (2011) prospectively analyzed a bile duct tumor database and retrieved records of 238 patinets who underwent surgery between 1999 and 2008.  Their findings included that pre-operative CA19-9 serum levels did not show a statically reliable differentiation between benign or malignant dignity.  The authors concluded that current diagnostics cannot differentiate malignant from benign tumor masses in the hepatic hilum with required reliability.  The authors further concluded that administration of CIK cells, thymus factor, IL-2 and IFN-alpha after AHSCT could improve the immunologic function of patients, and TH1/TH2 ratio may virtually reflect the immune status of patients, but that more information is required to make prognostic assessments of immune reconstruction and the long-term survival rate.

Sarbia et al (1993) investigated 69 adenocarcinomas of the esophagogastric junction and found high rates of antigen expression were found for the “intestinal” markers CA 19-9 (between 55.5% and 100%) and BW 494 (between 42.9 and 86.7%).  The authors concluded that these data, in combination with CK-20 expression, PGII, and 2B5 indicate that the distribution of adenocarcinomas with gastric and.or intestinal differentiation at the esophagogastric junction forms a continuum with out clear-cut borders.  This study has not been replicated and NCCN guidelines for Esophageal and Esophagogastric Junction Cancers does not include recommendations for CA 19-9 testing for these indications (NCCN, 2011).

The American Society of Clinical Oncology (ASCO)'s update of recommendations for the use of tumor markers in gastrointestinal cancer (Gershon, et al., 2006) stated that for pancreatic cancer, CA 19-9 can be measured every 1 to 3 months for patients with locally advanced or metastatic disease receiving active therapy.

Mucinous carcinoma of the appendix is a rare entity most commonly associated with primary tumors of the appendix and colon, and for which spread is generally confined to the abdominal cavity (Andreopoulou et al, 2007).  Imaging assessment of these mucinous lesions is difficult, and recent studies have explored the use of tumor markers as clinical tools in evaluation of mucinous carcinoma of the appendix. 

Carmignani et al (2004)  evaluated patients with synchronous systemic and intraperitoneal dissemination of appendix cancer greated with cytoreductive surgery and perioperative regional chemotherapy with a mean follow up time of 42.6 months.  Results of this study indicated that patients with elevated CEA and CA 19-9 levels had a shorter median survival time (p=0.0083 and p = 0.0193, respectively).  In a subsequent study, Carmingnani et al (2004) prospectively recorded tumor markers CEA and CA19-9 within 1 week prior to definitive treatment.  The investigators found CEA elevated in 56% of 532 patients and CA19-9 elevated in 67.1% of those patients.  They reported that “although the absolute level of tumor marker did not correlate with prognosis, a normal value indicated an improved survival.”  Their findings included an elevated CEA in 35.2% of 110 patients determined to have recurrent disease and an elevated CA 19-9 in 62.9%, while 68.2% of patients had at least one of the tumor markers elevated.

Current guidelines indicate that for liver transplantation for primary sclerosing cholangitis, stringent efforts should be made to detect superadded cholangiocarcinoma, including measurement of CA 19-9 (Devlin & O'Grady, 1999).

Carmignani et al (2004a) conducted a study to report the role of combined treatments, including cytoreductive surgery and perioperative regional chemotherapy, in patients with synchronous systemic and intraperitoneal dissemination of appendix cancer. Study subjects were treated with cytoreductive surgery and perioperative regional chemotherapy and statistical analysis of variables utilized survival as an end point and included demographic characteristics, prior surgical score (PSS), tumor marker levels, peritoneal cancer index (PCI), and completeness of cytoreduction (CC). With a mean follow-up of 42.6 months, median survival time (MST) for 15 patients was 28 months and 5-year survival rate was 29.4 %. Female patients had a longer MST than male patients (p = 0.0199) and survival was better in patients with PSS 0 and 1 (p = 0.0277). Patients with elevated CEA and CA 19-9 levels had a shorter MST (p = 0.0083 and p = 0.0193, respectively) while PCI and CC comparisons did not show significant differences. The morbidity rate (n = 2) was 13.3 % and the mortality (n = 2) rate was also 13.3 %. The authors concluded that “acceptable morbidity and mortality and a 29.4 % 5-year survival rate allows cytoreductive surgery and regional chemotherapy to be considered as a treatment option for selected patients with synchronous systemic and intraperitoneal dissemination of appendix cancer.”

Carmignani et al (2004b) in a further publication regarding gastrointestinal cancer, stated that carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) tumor markers have found selected clinical application. The authors remarked that the use of these tumor markers in mucinous epithelial tumors of the appendix has not been previously determined. Thus, the authors conducted a study in which, in patients with peritoneal dissemination of a mucinous epithelial malignancy of the appendix, tumor markers CEA and CA 19-9 were prospectively recorded preoperatively within 1 week prior to definitive treatment and if the appendiceal tumor recurred, the tumor marker was determined. The primary endpoint was the accuracy of these two tumor markers in the management of this disease for these two specific clinical situations. CEA was elevated in 56 % of 532 patients and CA 19-9 was elevated in 67.1 % of these patients. Although the absolute level of tumor marker did not correlate with prognosis, a normal value indicated an improved survival. CEA was elevated in 35.2 % of 110 patients determined to have recurrent disease and CA 19-9 was elevated in 62.9 %. At least one of the tumor markers was elevated in 68.2 % of patients. An elevated CEA tumor marker at the time of recurrence indicated a reduced prognosis and both CEA and CA 19-9 tumor markers were elevated in a majority of these patients. This should be a valuable diagnostic tool previously underutilized in this group of patients. These tumor markers were also of benefit in the assessment of prognosis in that a normal level indicated an improved prognosis. At the time of a reoperative procedure, CEA and CA 19-9 tumor markers gave information regarding the progression of disease and have practical value in the management of epithelial appendiceal malignancy with peritoneal dissemination.

Andreopoulou et al (2007) stated that mucinous carcinoma of the appendix is a rare entity with a distinct natural history that poses diagnostic and therapeutic challenges and that mucinous peritoneal carcinomatosis is most commonly associated with primary tumors of the appendix and colon. The authors stated that usually the spread remains confined to the abdominal cavity and that imaging assessment of these mucinous lesions is difficult, while tumor markers (CEA and CA19.9) may be surrogates for extent of disease. 

Recruitment for large scale studies given the rare nature of mucinous appendiceal carcinoma would be challenging.  However, available evidence does illustrate a benefit to use of CA 19-9 in patients with mucinous appendiceal carcinoma.

Cathepsins

This enzyme plays a critical role in protein catabolism and tissue remodeling (Chin, et al., 2006). Over-expression is associated with non-ductal carcinoma and metastasis at the time of breast cancer diagnosis.High levels may have clinical significance in predicting decreased metastasis-free survival and decreased overall survival in women with node-negative breast cancer.

Svatek et al (2008) examined the role of urinary cathepsin B and L in the detection of bladder urothelial cell carcinoma.  These investigators concluded that urinary cathepsin L is an independent predictor of bladder cancer presence and invasiveness in patients with a history of urothelial carcinoma of the bladder.  They stated that further evaluation of this marker is necessary before its use as an adjunct to cystoscopy for urothelial carcinoma of the bladder.

CD 20

CD 20 is used to determine eligibility for rituximab (Rituxan; anti-CD20) treatment in patients with B-cell non-Hodgkin's lymphomas (NHL) (Chin, et al., 2006). Rituximab is a genetically engineered, chimeric murine/human monoclonal antibody directed against the CD20 antigen found on the surface of normal and malignant B-cell lymphocytes. Since non-Hodgkin's Lymphoma (NHL) subtypes may differ in their response to rituximab, determination of drug sensitivity is important for choosing therapy.

CD 25

CD 25 is used to determine eligibility for denileukin diftitox treatment in patients with persistent or recurrent CTCL (Chin, et al., 2006). Denileukin diftitox (Ontak) is a cutaneous T-cell lymphoma (CTCL) therapy that targets the high-affinity interleukin-2 (IL-2) receptor. The IL-2 receptor may exist in a low-affinity form (CD25), an intermediate-affinity form (CD122/CD132), and a high-affinity form (CD25/CD122/CD132). Patients whose malignant cells express the CD25 component of the IL-2 receptor may respond to Ontak therapy.

CD 33

CD 33 is used to determine eligibility for gemtuzumab (Mylotarg, anti-CD33) treatment in patients with acute myeloid leukemia (Chen, et al., 2006). Gemtuzumab consists of a recombinant, humanized IgG kappa antibody conjugated to a cytotoxic anti-tumor antibiotic, calicheamicin, which binds specifically to the CD33 antigen. This antigen is found on the surface of leukemic blasts and immature normal cells of myelomonocytic lineage, but not in normal hematopoietic stem cells.

CD 52

CD 52 is used to determine eligibility for alemtuzumab (Campath, anti-CD52) treatment in patients with chronic lymphocytic leukemia (Chen, et al., 2006). CD52 is an antigen that can be expressed at high density on the surface of malignant CLL cells. Alemtuzumab is a humanized antibody targeted against CD52 and its binding is necessary for cell death and therapeutic response.

CD 117, c-kit

CD 117 is used to determine eligibility for treatment with imatinib mesylate in patients with c-kit-positive gastrointestinal stromal tumors (GISTs) (Chen, et al., 2006). The glycoprotein c-kit (CD117) is a member of the receptor tyrosine kinase subclass III family and has been implicated in a number of malignancies. Imatinib mesylate, a tyrosine kinase inhibitor, is effective in treating GISTs and other tumors that express c-kit.

HCG

Human chorionic gonadotropin (HCG) is normally produced in increasing quantities by the placenta during pregnancy. Accepted guidelines provide that HCG levels can be used to screen for choriocarcinoma in women who are at high risk for the disease, and to monitor the treatment of trophoblastic disease. The literature states that elevated HCG levels may also indicate the presence of cancers of the testis, ovary, liver, stomach, pancreas, and lung.

Accepted guidelines provide that alpha fetoprotein (AFP) and b-HCG measurements are valuable for determining prognosis and monitoring therapy in patients with non-seminomatous germ cell cancer. Because of the low incidence of elevated AFP and b-HCG levels in early-stage cancer, the literature suggests these markers have no value in screening for testicular cancer. However, the specificity of these markers is such that when determined simultaneously, at least one marker will be positive in 85% of patients with active cancer. The value of AFP and b-HCG as markers is enhanced by a low frequency of false-positive results and by the chemoresponsiveness of testicular cancer. The literature states that only rarely do patients with other types of cancer have elevated levels of AFP. Non-cancerous conditions that can cause elevated AFP levels include benign liver conditions, such as cirrhosis or hepatitis, ataxia telangiectasia, Wiscott-Aldrich syndrome, and pregnancy.

AFP

Alpha-fetoprotein is normally produced by a developing fetus.  Alpha fetoprotein levels begin to decrease soon after birth and are usually undetectable in the blood of healthy adults, except during pregnancy. According to accepted guidelines, an elevated level of AFP strongly suggests the presence of either primary liver cancer or germ cell cancer of the ovary or testicle. As AFP is an established test for the diagnosis and monitoring of hepatoma, it is used as a screening tool to rule out the presence of a liver neoplasm before considering liver transplantation. This is especially pertinent in cases (e.g., cirrhosis) where there is an increased risk of developing a primary liver tumor.

Elevated serum AFP levels are most closely associated with nonseminomatous testicular cancer and hepatocellular cancer (Chin, 2006). The rate of clearance from serum after treatment is an indicator of the effectiveness of therapy. Conversely, the growth rate of progressive disease can be monitored by serially measuring serum AFP concentrations over time.

ER, PR

Estrogen receptor (ER) and progesterone receptor (PR) predicts response to hormone therapy for women with advanced breast cancer and those receiving adjuvant treatment, and prognosticates the aggressiveness of a tumor (Chin, 2006).

The estrogen receptor and progesterone receptor are intracellular receptors that are measured directly in tumor tissue. These receptors are polypeptides that bind their respective hormones, translocate to the nucleus, and induce specific gene expression. Breast cancers are dependent upon estrogen and/or progesterone for growth and this effect is mediated through ERs and progesterone receptors (ER/PR) (Chin, et al., 2006). Both receptors may be over-expressed in malignant breast tissue. Most oncologists have used the estrogen receptor and also the progesterone receptor not only to predict the probability of response to hormonal therapy at the time of metastatic disease, but also to predict the likelihood of recurrent disease, and to predict the need for adjuvant hormonal therapy or chemotherapy. Although these latter uses for estrogen and progesterone receptors are commonly accepted by most oncologists, the data on which these conclusions are based are controversial.

NSE

Neuron-specific enolase (NSE) has been detected in patients with neuroblastoma, small cell lung cancer, Wilms' tumor, melanoma, and cancers of the thyroid, kidney, testicle, and pancreas. However, studies of NSE as a tumor marker have concentrated primarily on patients with neuroblastoma and small cell lung cancer. According to the available literature, measurement of NSE level in patients with these diseases cannot be correlated to the extent of the disease, the patient's prognosis, or the patient's response to treatment because of the poor sensitivity of this marker.

LASA

LASA is a complex marker that measures the amount of sialic acid in serum and can be elevated in serum from patients with any number of different neoplasms. Elevations in blood LASA levels have been reported in patients with mammary (63 percent), gastroenteric (65 percent), pulmonary (79 percent), and ovarian (94 percent) neoplasms as well as those with leukemia (86 percent), lymphoma (87 percent), melanoma (84 percent), sarcoma (97 percent), and Hodgkin disease (91 percent). As a result, this assay may not have high specificity or sensitivity necessary for cancer detection (Chen, et al., 2006). This serum cancer marker has not been widely accepted for use in the detection or prognosis of colorectal carcinoma. There is no practical information concerning outcome and the use of LASA in the medical literature. Although several articles describe the use of LASA in the diagnosis of colorectal cancer and its association with tumor-node-metastasis (TNM) stage, it has been shown that patients with colorectal polyps and colorectal carcinoma both have elevated LASA levels, and that the levels returned to baseline after removal of either polyps or carcinomas.

p53

p53 is a tumor suppressor gene on the short arm of chromosome 17 that encodes a protein that is important in the regulation of cell division. Although the full role of p53 in the normal and neoplastic cell is unknown, there is evidence that the gene product is important in preventing the division of cells containing damaged DNA. p53 gene deletion or mutation is a frequent event along with other molecular abnormalities in colorectal carcinogenesis. The literature on p53 abnormality and prognosis in colorectal cancer suffers from a paucity of reported data and the use of a variety of techniques in assay and statistical analysis in the small numbers of cases analyzed. For these reasons, the literature generally does not recommend p53 analysis as a routine approach to assisting in the management of patients with colorectal cancer.

Zap-70

Zap-70 is indicated to assess prognosis and need for aggressive therapy in patients with chronic lymphocytic leukemia (CLL) (Chin, et al., 2006). ZAP-70 is a 70-kD member of the Syk family of protein tyrosine kinases. It is expressed primarily in T-cells and natural killer (NK) cells and is critical for signal transduction following T-cell receptor engagement. In CLL B-cells, elevated ZAP-70 expression appears to predict the need for therapy as effectively as IgVH mutation status. Although ZAP-70 expression is strongly correlated with IgVH mutation status, the combination of the two markers may provide greater prognostic value than either marker alone. Positive ZAP-70 results predict an aggressive disease course.

uPA

The serine protease urokinase-type plasminogen activator (uPA) and its primary inhibitor, plasminogen activator inhibitor-1 (PAI-1), have shown promise for risk assessment and prediction of therapeutic response in primary breast cancer (Chin, et al., 2006). High levels of uPA or PAI-1 in primary tumor tissue are associated with an aggressive disease course and poor prognosis in both node-positive and node-negative breast cancer.

A report by the Belgian Healthcare Knowledge Centre (KCE) (San Miguel, et al., 2015) found no studies reporting on the impact of uPA/PAI-1 on clinical management (clinical utility). 

IgVh mutation status

Chronic lymphocytic leukemia (CLL) patients can be divided into two basic groups on the basis of the mutational status of the immunoglobulin heavy-chain variable-region (IgVH) gene in leukemic cells (Chin, 2006). Patients with IgVH mutations have longer survival than those without IgVH mutation. Thus, mutation analysis may be useful for planning management strategies.

Kappa/lambda light chain

Elevated serum levels of monoclonal free light chains are associated with malignant plasma cell proliferation (e.g., multiple myeloma), primary amyloidosis, and light chain deposition disease (Chen, et al., 2006). The appearance of higher levels of free light chains in the urine may be indicative of kidney disease or malignant lymphoproliferative disease such as multiple myeloma. These tests have been used for the detection of multiple myeloma.

KRAS

The ras proto-oncogenes are normal cellular components, which are thought to be important for transduction of signals required for proliferation and differentiation.   The ras oncogene family has 3 members: H-ras, K-ras, and N-ras.  Ras gene mutations can be found in a variety of tumor types, although the incidence varies greatly. The highest incidences are found in adenocarcinomas of the pancreas (90 %), colon (50 %), and lung (30 %); thyroid tumors (50 %), and myeloid leukemia (30 %).

Investigators have established an association between some genotypes of K-ras (KRAS) oncogenes and response to treatment with cetuximab or panitumumab (Lievre et al, 2006 and 2008; Di Fiore et al, 2007; Gonçalves et al, 2008; De Roock et al, 2008).  Patients whose tumors express specific forms of the KRAS gene exhibit considerably decreased responses to cetuximab and panitumumab.  It has been theorized that cetuximab and panitumumab do not target epidermal growth factor receptor (EGFR) associated with these specific KRAS mutations and thus are unable to block their activation.  It has been suggested that KRAS genotype be considered as a selection factor for cancer patients who are candidates for treatment with cetuximab or panitumumab.

Karapetis and colleagues (2008) stated that treatment with cetuximab improves overall survival (OS) and progression-free survival (PFS) and preserves the quality of life in patients with colorectal cancer that has not responded to chemotherapy. The mutation status of the K-ras gene in the tumor may affect the response to cetuximab and have treatment-independent prognostic value.  These investigators analyzed tumor samples, obtained from 394 of 572 patients (68.9 %) with colorectal cancer who were randomly assigned to receive cetuximab plus best supportive care or best supportive care alone, to look for activating mutations in exon 2 of the K-ras gene.  They evaluated if the mutation status of the K-ras gene was associated with survival in the cetuximab and supportive-care groups.  Of the tumors evaluated for K-ras mutations, 42.3 % had at least one mutation in exon 2 of the gene.  The effectiveness of cetuximab was significantly associated with K-ras mutation status (p = 0.01 and p < 0.001 for the interaction of K-ras mutation status with OS and PFS, respectively).  In patients with wild-type K-ras tumors, treatment with cetuximab as compared with supportive care alone significantly improved OS (median of 9.5 versus 4.8 months; hazard ratio for death, 0.55; 95 % confidence interval [CI], 0.41 to 0.74; p < 0.001) and PFS (median of 3.7 months versus 1.9 months; hazard ratio for progression or death, 0.40; 95 % CI, 0.30 to 0.54; p < 0.001).  Among patients with mutated K-ras tumors, there was no significant difference between those who were treated with cetuximab and those who received supportive care alone with respect to OS (hazard ratio, 0.98; p = 0.89) or PFS (hazard ratio, 0.99; p = 0.96).  In the group of patients receiving best supportive care alone, the mutation status of the K-ras gene was not significantly associated with OS (hazard ratio for death, 1.01; p = 0.97).  The authors concluded that patients with a colorectal tumor bearing mutated K-ras did not benefit from cetuximab, whereas patients with a tumor bearing wild-type K-ras did benefit from cetuximab.  The mutation status of the K-ras gene had no influence on survival among patients treated with best supportive care alone.

The ASCO's provisional clinical opinion on testing for KRAS gene mutations in patients with metastatic colorectal carcinoma to predict response to anti-EGFR monoclonal antibody therapy (Allegra et al, 2009) stated that based on systematic reviews of the relevant literature, all patients with metastatic colorectal carcinoma who are candidates for anti-EGFR antibody therapy should have their tumor tested for KRAS mutations in a CLIA-accredited laboratory.  If KRAS mutation in codon 12 or 13 is detected, then patients with metastatic colorectal carcinoma should not receive anti-EGFR antibody therapy as part of their treatment.

The KRAS oncogene mutation tests are intended to aid in the formulation of treatment decisions for patients who may be candidates for treatment of metastatic epithelial cancers with anti-EGFR therapies such as cetuximab or panitumumab.  Several tests for KRAS mutation are currently available in the United States; however, at this time, no KRAS genotype test kits have been approved by the FDA.

At the 2008 Annual Meeting of the American Society of Clinical Oncology (ASCO), data on 540 patients with metastatic colorectal cancer in the randomized, phase III CRYSTAL trial were presented.  Among 192 patients with KRAS mutations, there was no improvement in overall responses or PFS from the addition of cetuximab to standard chemotherapy.  In the patients with normal KRAS, the 1-year PFS rate was 43 % for patients receiving cetuximab versus 25 % for those receiving only standard chemotherapy, and the overall response rate was 59 % versus 43 %, respectively (van Cutsem, 2008).  Also at the 2008 ASCO meeting, data from 233 metastatic colorectal cancer patients were presented that confirmed the correlation of KRAS status with patient response to anti-EGFR therapy.  No benefit was found after addition of cetuximab to standard chemotherapy with FOLFOX (the combination of fluorouracil, leucovorin, and oxaliplatin) in patients with a mutated KRAS; however, addition of cetuximab to FOLFOX increased both response rate and PFS in patients with a wild-type (i.e., un-mutated) KRAS gene (Bokemeyer, 2008).  Response to panitumumab was correlated to KRAS status in a published phase III trial.  A total of 427 patients with metastatic colorectal cancer received either panitumumab or best supportive care.  Panitumumab exhibited a 17% response rate among patients with normal KRAS, but 0% response among patients with KRAS mutations (Amado, 2008).

A meta-analysis of results from 8 studies involving 817 patients with colorectal cancer found that the presence of KRAS mutation predicted lack of response to treatment with anti-EGFR monoclonal antibodies (e.g., panitumumab or cetuximab), whether as stand-alone therapy or in combination with chemotherapy (Linardou et al, 2008).  This analysis also provided empirical evidence that k-RAS mutations are highly specific negative predictors of response (de-novo resistance) to single-agent EGFR tyrosine-kinase inhibitors in advanced non-small cell lung cancer; and similarly to anti-EGFR monoclonal antibodies alone or in combination with chemotherapy in patients with metastatic colorectal cancer.

The Blue Cross and Blue Shield Association (BCBSA, 2008) Technology Evaluation Center Medical Advisory Panel concluded that use of KRAS mutation analysis meets TEC criteria to predict non-response to anti-EGFR monoclonal antibodies cetuximab and panitumumab to treat metastatic colorectal cancer. The TEC assessment found that the evidence is sufficient to conclude that patients with mutated KRAS tumors in the setting of metastatic colorectal cancer do not respond to anti-EGFR monoclonal antibody therapy. The assessment explained that the data show that the clinical benefit of using EGFR inhibitors in treating metastatic colorectal cancer, either as monotherapy or in combination with other treatment regimens, is not seen in patients with KRAS-mutated tumors.  The assessment found: "This data supports knowing a patient's tumor mutation status before consideration of use of an EGFR inhibitor in the treatment regimen.  Identifying patients whose tumors express mutated KRAS will avoid exposing patients to ineffective drugs, avoid exposure to unnecessary drug toxicities, and expedite the use of the best available alternative therapy."

Colorectal cancer guidelines from the National Comprehensive Cancer Network (NCCN, 2010) recommend consideration of reflex BRAF testing in patients with wild type KRAS. The NCCN guidelines explain that several small studies suggest that patients with wild-type KRAS and a BRAF mutation are unlikely to respond to anti-EGFR therapies such as cetuximab and panitumumab. The guidelines explain that patients with a known BRAF mutation are unlikely to respond to anti-EGFR antibodies, although the data are somewhat inconsistent. Studies demonstrate that in patients with metastatic colorectal cancer, about 8 percent have mutations in the BRAF gene. Testing for the BRAF V600E mutation is performed by PCR amplification and direct DNA sequence analysis.

Ratner et al (2010) stated that ovarian cancer (OC) is the single most deadly form of women's cancer, typically presenting as an advanced disease at diagnosis in part due to a lack of known risk factors or genetic markers of risk.  The KRAS oncogene and altered levels of the microRNA (miRNA) let-7 are associated with an increased risk of developing solid tumors.  In this study, these researchers investigated a hypothesized association between an increased risk of OC and a variant allele of KRAS at rs61764370, referred to as the KRAS-variant, which disrupts a let-7 miRNA binding site in this oncogene.  Specimens obtained were tested for the presence of the KRAS-variant from non-selected OC patients in 3 independent cohorts, 2 independent ovarian case-control studies, and OC patients with hereditary breast and ovarian cancer syndrome (HBOC) as well as their family members.  The results indicated that the KRAS-variant is associated with more than 25 % of non-selected OC cases.  Furthermore, these researchers found that it is a marker for a significant increased risk of developing OC, as confirmed by 2 independent case-control analyses.  Lastly, they determined that the KRAS-variant was present in 61 % of HBOC patients without BRCA1 or BRCA2 mutations, previously considered uninformative, as well as in their family members with cancer.  These findings supported the hypothesis that the KRAS-variant is a genetic marker for increased risk of developing OC, and they suggested that the KRAS-variant may be a new genetic marker of cancer risk for HBOC families without other known genetic abnormalities.

Hollestelle et al (2011) noted that recently, a variant allele in the 3'UTR of the KRAS gene (rs61764370 T>G) was shown to be associated with an increased risk for developing non-small cell lung cancer, as well as OC, and was most enriched in OC patients from HBOC families.  This functional variant has been shown to disrupt a let-7 miRNA binding site leading to increased expression of KRAS in vitro.  In the current study, these investigators genotyped this KRAS-variant in breast cancer index cases from 268 BRCA1 families, 89 BRCA2 families, 685 non-BRCA1/BRCA2 families, and 797 geographically matched controls.  The allele frequency of the KRAS-variant was found to be increased among patients with breast cancer from BRCA1, but not BRCA2 or non-BRCA1/BRCA2 families as compared to controls.  As BRCA1 carriers mostly develop ER-negative breast cancers, these researchers also examined the variant allele frequency among indexes from non-BRCA1/BRCA2 families with ER-negative breast cancer.  The prevalence of the KRAS-variant was, however, not significantly increased as compared to controls, suggesting that the variant allele not just simply associates with ER-negative breast cancer.  Subsequent expansion of the number of BRCA1 carriers with breast cancer by including other family members in addition to the index cases resulted in loss of significance for the association between the variant allele and mutant BRCA1 breast cancer.  In this same cohort, the KRAS-variant did not appear to modify breast cancer risk for BRCA1 carriers.  More importantly, results from the current study suggested that KRAS-variant frequencies might be increased among BRCA1 carriers, but solid proof requires confirmation in a larger cohort of BRCA1 carriers. 

Therascreen KRAS RGQ PCR Kit (Qiagen) is intended to detect 7 mutations in codons 12 and 13 of the KRAS gene (Raman, et al., 2013). The kit utilizes two technologies — ARMS and Scorpions — for detection of mutations in real-time PCR. The therascreen KRAS RGQ PCR kit is being developed as a companion diagnostic to aid clinicians, through detection of KRAS mutations, in the identification of patients with metastatic colorectal cancer (mCRC) who are more likely to benefit from cetuximab.

PreOvar™ tests (Mira Dx) for the KRAS-variant, and will help identify ovarian cancer patients whose female relatives should also be evaluated for the KRAS-variant (Raman, et al., 2013). PreOvar™ may also help assess the relative risk of developing ovarian cancer for women who have a family history of ovarian cancer without a living proband (ancestor with the disease). The KRAS-Variant is present in 6-10% of the general population and 25% of non-selected women with epithelial ovarian cancer. Additionally, the KRAS-variant was identified in over 60% of Hereditary Breast and Ovarian Cancer (HBOC) patients that were previously classified as “uninformative,” or negative for other known genetic markers of ovarian cancer risk. The test determines if KRAS-variant may put someone at increased risk for developing ovarian cancer.

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (EWG) (2013) found that, for patients with metastatic colorectal cancer (mCRC) who are being considered for treatment with cetuximab or panitumumab, there is convincing evidence to recommend clinical use of KRAS mutation analysis to determine which patients are KRAS mutation positive and therefore unlikely to benefit from these agents before initiation of therapy. The level of certainty of the evidence was deemed high, and the magnitude of net health benefit from avoiding potentially ineffective and harmful treatment, along with promoting more immediate access to what could be the next most effective treatment, is at least moderate.

The EWG found insufficient evidence to recommend for or against BRAF V600E testing for the same clinical scenario (EGAPP, 2013). The level of certainty for BRAF V600E testing to guide antiepidermal growth factor receptor (EGFR) therapy was deemed low. The EWG encourages further studies of the potential value of testing in patients with mCRC who were found to have tumors that are wild type (mutation negative) for KRAS to predict responsiveness to therapy.

Bladder cancer: BTA-stat, NMP22, Urovysion, ImmunoCyt

In the United States, bladder malignancy is the 4th commonest cancer in men and the 8th commonest in women.  Patients usually present with urinary tract symptoms (e.g., gross or microscopic hematuria or irritative voiding symptoms such as frequency, dysuria, and urgency).  Evaluations of these patients usually entail voided-urine cytology, cystoscopy, and upper urinary tract imaging such as intravenous pyelography, renal sonography, or retrograde pyelography.  Most newly diagnosed bladder cancers are superficial (i.e., not invading beyond the lamina propria on histological examination), and are known as transitional cell carcinoma (TCC).  These superficial bladder cancers are usually managed by transurethral resection.  However, the literature shows that approximately 50 to 75 % of treated TCC recur.  Furthermore, 10 to 15 % of TCC progress to muscle-invasive bladder cancer.  According to the literature, the prevalence of recurrence after initial treatment as well as the natural history of TCC necessitates long-term follow-up.  Following treatment, accepted guidelines provide that patients who have previously been diagnosed with TCC should usually undergo urine cytology/cystoscopy every 3 months in the 1st year, every 6 months in the 2nd year, and once-yearly afterwards.

Currently, urine cytology with confirmatory cystoscopy represents the cornerstone for the identification of bladder tumors. However, the subjectivity and low sensitivity of cytology led to the development of several urine-based tests as adjuncts to cytology/cystoscopy for the diagnosis and follow-up of patients with TCC. These tests include the BTA Stat test (Bard Diagnostic, Redmond, WA), the NMP22 test (Matritech, Newton, MA), the Aura-Tek FDP test (PerImmune, Rockville, MD), and the Vysis UroVysion FISH Test (Vysis, Inc., Downers Grove, IL). They are usually objective, qualitative (BTA Stat and Aura-Tek FDP), or quantitative (NMP22, UroVysion), and have higher sensitivity than cytology, but some have lower specificity. So far, no single bladder tumor marker has emerged as the generally accepted test of choice, and none has been established as a screening tool for bladder malignancy.

The UroVysion Bladder Cancer Kit (UroVysion Kit) (Baycare Laboratories) is designed to detect aneuploidy for chromosomes 3, 7, 17, and loss of the 9p21 locus via fluorescence in situ hybridization (FISH) in urine specimens from persons with hematuria suspected of having bladder cancer (Raman, et al., 2013). FISH analysis is used in conjunction with cystoscopy to monitor for recurrence among those with previously diagnosed bladder cancer. FISH analysis is a surveillance tool in established primary and secondary bladder adenocarcinoma.

The ImmunoCyt is an immunocytochemistry assay for the detection of tumor cells shed in the urine of patients previously diagnosed with bladder cancer (Chen, et al., 2006). This test is intended to augment the sensitivity of cytology for the detection of tumor cells in the urine of individuals previously diagnosed with bladder cancer. The test has been used for detection of tumor cells in the urine of individuals previously diagnosed with bladder cancer, and for use in conjunction with cytoscopy as an aid in the management of bladder cancer.

Although urine cytology has been shown to be less accurate than urinary biomarker tests, familiarity with the method as well as ease of performance justify the continued routine use of the former by primary care physicians, especially in patients who have no history of bladder malignancy. The urine-based biomarker tests have been shown to be accurate in detecting low-grade bladder tumors. In particular, these tests may be of help in deciding the need for further diagnostic assessment of patients with a history of bladder cancer and negative results on urine cytology. For example, elevated levels of urinary bladder tumor markers in patients with a history of TCC may warrant earlier, rather than delayed, cystoscopic examination. On the other hand, consideration may be given to lengthening the intervals between cystoscopic investigations when values of these tumor markers are normal.

An assessment by the Adelaide Health Technology Assessment (Mundy & Hiller, 2009) concluded that the NMP BladderCheck and UroVysion FISH assay, designed for the detection of bladder cancer in high risk patients, have poor sensitivity and poor positive predictive values. The assessment recommended that these assays not be used in asymptomatic patients. The assessment suggested, however, that these tests may be useful in the monitoring of patients with transitional cell carcinoma between cytoscopies. The AHTA recommended that this technology not be assessed further.

An assessment prepared for the Agency for Healthcare Research and Quality (Meleth, et al., 2014) found: "Although UroVysion is marketed as a diagnostic rather than a prognostic test, limited evidence from two small studies (total N=168) rated as low or medium risk of bias supported associations between test result and prognosis for risk of recurrence. We found no studies that directly assessed the impact of a test of interest on both physician decision-making and downstream health outcomes to establish clinical utility. We attempted to construct an indirect chain of evidence to answer the overarching question, but we were unable to do so. Even in the cases where the tests seemed to add value in determining prognosis (i.e., evidence of clinical validity), we found no evidence that using the test was related to improved outcomes for patients."

The American Urologic Association’s guideline on “Diagnosis, evaluation and follow-up of asymptomatic microhematuria (AMH) in adults” (Davis et al, 2012) stated that “The use of urine cytology and urine markers (Nuclear Matrix Protein 22 [NMP22], bladder tumor antigen [BTA]-stat, and UroVysion fluorescence in situ hybridization assay [FISH]) is not recommended as a part of the routine evaluation of the asymptomatic microhematuria patient”.

In summary, urine-based bladder tumor marker tests have been shown to be useful as an adjunct to urine cytology and cystoscopy in monitoring for recurrences of bladder cancer, but according to the available literature should not be used as a screening tool for bladder malignancy.  The U.S. Preventive Services Task Force (USPSTF, 2004) has concluded that the potential harms of screening for bladder cancer using available tests, such as microscopic urinalysis, urine dipstick, urine cytology, or such new tests as bladder tumor antigen (BTA) or nuclear matrix protein (NMP22) immunoassay, outweigh any potential benefits.

Cxbladder

O'Sullivan and colleagues (2012) examined if the RNA assay uRNA® and its derivative Cxbladder® have greater sensitivity for the detection of bladder cancer than cytology, NMP22™ BladderChek™ and NMP22™ ELISA, and whether they are useful in risk stratification.  A total of 485 patients presenting with gross hematuria but without a history of urothelial cancer were recruited prospectively from 11 urology clinics in Australasia.  Voided urine samples were obtained before cystoscopy.  The sensitivity and specificity of the RNA tests were compared to cytology and the NMP22 assays using cystoscopy as the reference.  The ability of Cxbladder to distinguish between low grade, stage Ta urothelial carcinoma and more advanced urothelial carcinoma was also determined.  uRNA detected 41 of 66 urothelial carcinoma cases (62.1 % sensitivity, 95 % confidence interval [CI]: 49.3 to 73.8) compared with NMP22 ELISA (50.0 %, 95 % CI: 37.4 to 62.6), BladderChek (37.9 %, 95 % CI: 26.2 to 50.7) and cytology (56.1 %, 95 % CI: 43.8 to 68.3).  Cxbladder, which was developed on the study data, detected 82 %, including 97 % of the high grade tumors and 100 % of tumors stage 1 or greater.  The cut-offs for uRNA and Cxbladder were pre-specified to give a specificity of 85 %.  The specificity of cytology was 94.5 % (95 % CI: 91.9 to 96.5), NMP22 ELISA 88.0 %, (95 % CI: 84.6 to 91.0) and BladderChek 96.4 % (95 % CI: 94.2 to 98.0).  Cxbladder distinguished between low-grade Ta tumors and other detected urothelial carcinoma with a sensitivity of 91 % and a specificity of 90 %.  The authors concluded that uRNA and Cxbladder showed improved sensitivity for the detection of urothelial carcinoma compared to the NMP22 assays.  Stratification with Cxbladder provides a potential method to prioritize patients for the management of waiting lists.

An UpToDate review on “Clinical presentation, diagnosis, and staging of bladder cancer” (Lotan and Choueiri, 2013) does not mention the use of mRNA biomarkers/PCR testing as a management tool for bladder cancer.  Furthermore, NCCN’s clinical practice guideline on “Bladder cancer” (Version 1.2014) does not mention the use of mRNA biomarkers/PCR testing as a management tool for bladder cancer.

OncotypeDx Breast

Oncotype Dx (Genomic Health, Inc., Redwood City, CA) is a diagnostic laboratory-developed assay that quantifies the likelihood of breast cancer recurrence in women with newly diagnosed, stage I or II, node negative, estrogen receptor positive breast cancer, who will be treated with tamoxifen.  The assay analyzes the expression of a panel of 21 genes, and is intended for use in conjunction with other conventional methods of breast cancer analysis.  Together with staging, grading, and other tumor marker analyses, Oncotype Dx is intended to provide greater insight into the likelihood of systemic disease recurrence.  Clinical studies have evaluated the prognostic significance of the Oncotype Dx multigene assay in breast cancer (Paik et al, 2004; Esteva et al, 2003). 

Oncotype Dx analyses the patterns of 21 genes is being applied as a quantification tool for likelihood of breast cancer recurrence within 10 years of newly diagnosed, stage I or II, lymph node-negative, hormone receptor-positive breast cancer in women who will be treated with tamoxifen (Raman, et a., 2013). Oncotype is being applied as a quantification tool for likelihood of breast cancer recurrence in 10 years in women with newly diagnosed breast cancer. It is also intended to assist in making decisions regarding adjuvant chemotherapy based on recurrence likelihood.

There currently is a lack of evidence from prospective clinical studies of the impact of this test on the management of women with breast cancer demonstrating improvements in clinical outcomes (Lopez, et al., 2010; Romeo, et al., 2010; Tiwana, et al., 2013; IETS, 2013),  Bast and Hortobagyi (2004) commented that “[b]efore use of the recurrence score [from the Oncotype Dx multigene assay] is applied to general patient care, however, additional studies are needed.” The National Cancer Institute is sponsoring a prospective, randomized controlled clinical study, the TAILORx study, using the Oncotype Dx assay to help identify a group of patients with a mid-range risk of recurrence to determine whether treating patients with hormonal therapy only is equivalent to treating them with hormonal therapy in combination with adjuvant chemotherapy.

However, there is indirect evidence of the clinical utility of the Oncotype Dx. Paik et al (2006) used banked tumor samples from previous clinical studies of tamoxifen and adjuvant chemotherapy in early breast cancer to assess the performance of the Oncotype Dx multigene assay in predicting response to adjuvant chemotherapy. These investigators examined tumor samples from subjects enrolled in the National Surgical Adjuvant Breast and Bowel Project (NSABP) B20 trial to determine whether there is a correlation between the recurrence score (RS) determined by Oncotype Dx in tumor samples and subsequent response to adjuvant chemotherapy. A total of 651 patients were assessable (227 randomly assigned to tamoxifen and 424 randomly assigned to tamoxifen plus chemotherapy). The test for interaction between chemotherapy treatment and RS was statistically significant (p = 0.038). Patients with high-RS (RS greater than or equal to 31) tumors (ie, high risk of recurrence) had a large benefit from chemotherapy (relative risk, 0.26; 95% confidence interval 0.13 to 0.53; absolute decrease in 10-year distant recurrence rate: mean, 27.6%; standard error, 8.0%). Patients with low-RS (less than 18) tumors derived minimal, if any, benefit from chemotherapy treatment (relative risk, 1.31; 95% confidence interval, 0.46 to 3.78; absolute decrease in distant recurrence rate at 10 years: mean, -1.1%; standard error, 2.2%). The investigators found that patients with intermediate-RS tumors did not appear to have a large benefit, but the investigators concluded that the uncertainty in the estimate cannot exclude a clinically important benefit.

One limitation of the study by Paik et al (2006) is that the NASBP B20 trial was conducted before the advent of important advances in breast cancer chemotherapy, including the introduction of trastuzumab (Herceptin), which has been demonstrated to improve overall and disease-free survival in breast cancer patients with HER2 positive tumors. Current guidelines recommend the use of trastuzumab adjuvant chemotherapy in women with metastatic HER2 positive breast cancer, and women with HER2 positive nonmetastatic breast cancers 1 cm or more in diameter. Thus, the Oncotype Dx score would not influence the decision to use adjuvant trastuzumab in women with HER2 positive tumors 1 cm or more in diameter.

Commenting on an early report of this study by Paik et al, of the Oncotype Dx presented in abstract form, the BlueCross BlueShield Association Technology Evaluation Center assessment stated that “additional studies in different populations are needed to confirm whether risk prediction is sufficiently accurate for physicians and patients to choose with confidence whether to withhold adjuvant chemotherapy.”

An international consensus group (Azim, et al., 2013) found the available evidence on the analytical and clinical validity of Oncotype Dx Breast to be convincing. However, neither the Oncotype Dx or none of the other genomic tests the evaluated demonstrated robust evidence of clinical utility: they stated that it was not clear from the current evidence that modifying treatment decisions based on the results of a given genomic test could result in improving clinical outcome.

The selection criteria for the TailorRx prospective trial of OncotypeDx state that candidates should have negative axillary nodes as determined by a sentinel lymph node biopsy and/or axillary dissection as defined by the American Joint Committee on Cancer 6th Edition Staging System (NCI, 2009). The AJCC 6th Edition criteria redefined isolated tumor cells as node negative (the prior version of the criteria, AJCC 5th Edition, classified isolated tumor cells as node positive). "Isolated tumor cells (single cells or cell deposits) will now be defined as tumor cell deposits no larger than 0.2 mm in diameter that may or may not (but usually do not) show histologic evidence of malignant activity. Pending further information, isolated tumor cells will be classified as node-negative, because it is believed that the unknown benefits of providing treatment for these small lesions would not outweigh the morbidity caused by the treatment itself." (Singletary, et al., 2002). However, the banked tumor samples used in the study by Paik, et al. (2006) to validate the OncotypeDx were classified based on AJCC 5th Ed. criteria. In addition, there is new evidence demonstrating that women with isolated tumor cells are at a significantly increased risk of breast cancer. Investigators from the Netherlands found an association between isolated tumor cells and micrometastases in regional lymph nodes and clinical outcome of breast cancer (de Boer, et al., 2009). These investigators identified all patients in the Netherlands who underwent a sentinel-node biopsy for breast cancer before 2006 and had breast cancer with favorable primary-tumor characteristics and isolated tumor cells or micrometastases in the regional lymph nodes. Patients with node-negative disease were randomly selected from the years 2000 and 2001. The primary end point was disease-free survival. The investigators identified 856 patients with node-negative disease who had not received systemic adjuvant therapy (the node-negative, no-adjuvant-therapy cohort), 856 patients with isolated tumor cells or micrometastases who had not received systemic adjuvant therapy (the node-positive, no-adjuvant-therapy cohort), and 995 patients with isolated tumor cells or micrometastases who had received such treatment (the node-positive, adjuvant-therapy cohort). The median follow-up was 5.1 years. The adjusted hazard ratio for disease events among patients with isolated tumor cells who did not receive systemic therapy, as compared with women with node-negative disease, was 1.50 (95% confidence interval [CI], 1.15 to 1.94); among patients with micrometastases, the adjusted hazard ratio was 1.56 (95% CI, 1.15 to 2.13). Among patients with isolated tumor cells or micrometastases, the adjusted hazard ratio was 0.57 (95% CI, 0.45 to 0.73) in the node-positive, adjuvant-therapy cohort, as compared with the node-positive, no-adjuvant-therapy cohort. The investigators concluded that isolated tumor cells or micrometastases in regional lymph nodes were associated with a reduced 5-year rate of disease-free survival among women with favorable early-stage breast cancer who did not receive adjuvant therapy. In patients with isolated tumor cells or micrometastases who received adjuvant therapy, disease-free survival was improved.

The Medical Advisory Panel of the BlueCross BlueShield Association Technology Evaluation Center (BCBCA, 2014) concluded that use of Oncotype DX to determine recurrence risk for deciding whether to undergo adjuvant chemotherapy in women with unilateral, nonfixed, hormone receptor‒positive, lymph node‒negative breast cancer who will receive hormonal therapy meets the Blue Cross and Blue Shield Association Technology Evaluation Center (TEC) criteria. A technology assessment by the BlueCross BlueShield Association (2014) stated: "Technical performance of the assay is well documented and is unlikely to be a major source of variability; rather, tissue sampling is likely the greatest source of variability. Retrospective epidemiologic analyses indicated strong, independent associations between Oncotype DX recurrence score (RS) result and distant disease recurrence or death from breast cancer. The evidence identified a subset of conventionally classified, high-risk patients who are at sufficiently low risk of recurrence by Oncotype DX that they might reasonably decide that the harms (toxicity) of chemotherapy outweigh the very small absolute benefit. Two studies of the original validation data, in which conventionally classified patients were reclassified by Oncotype DX result, indicated that the test provides significant recurrence risk information in addition to conventional criteria for individual patient risk classification. Additional evidence indicated that Oncotype DX results are significantly associated with breast cancer death in a community-based patient population, and that RS high-risk patients benefit from chemotherapy, whereas benefits for other RS categories were not statistically significant. Thus, the evidence was judged sufficient to permit conclusions regarding probable health outcomes."

The Oncotype Dx has also been promoted for use in women with node-positive, ER-positive breast cancer. An assessment by the BlueCross BlueShield Association (2010) concluded that it has not yet been demonstrated whether use of the Oncotype Dx for selecting adjuvant chemotherapy in patients with lymph-node-positive breast cancer improves health outcomes. The report explained that the evidence for not selecting chemotherapy for women with low RS values is based on low event rates and wide confidence intervals that include the possibility of benefit from chemotherapy.  Because the data allow for a possible benefit of chemotherapy in patients with low RS results, it is unknown if health outcomes would be improved, the same, or worse, if chemotherapy was withheld in these women. The report stated that, due to the lack of clear and sufficient information, there is a need for a second, confirmatory study.  The report stated that the Fred Hutchinson Cancer Research Center will conduct a nationwide, NCI-sponsored, Phase III clinical trial to determine the predictive ability of the Oncotype Dx to identify which patients with lymph-node-positive breast cancer will benefit from chemotherapy.

The clinical evidence base for OncotypeDX is considered to be the most robust. There was some evidence on the impact of the test on decision-making and to support the case that OncotypeDX predicts chemotherapy benefit; however, few studies were UK based and limitations in relation to study design were identified. OncotypeDX has a more robust evidence base, but further evidence on its impact on decision-making in the UK and the predictive ability of the test in an ER+, LN-, HER- population receiving current drug regimens is needed.

Guidelines from the National Comprehensive Cancer Network (NCCN, 2015) state that "the 21-gene RT-PCR assay recurrence score can be considered in select patients with 1-3 involved ipsilateral axillary lymph nodes to guide the addition of combination chemotherapy to standard hormone therapy. A retrospective analysis of a prospective randomized trial suggests that the test is predictive in this group similar to its performance in node-negative disease.” The NCCN guidelines (2015) explained: “Unplanned, retrospective subset analysis from a single randomized clinical trial in post-menopausal, ALN-positive, ER-positive breast cancer found that the 21-gene RT-PCR assay may provide predictive information for chemotherapy in addition to tamoxifen [citing Albain, et al., 2010]. Patients with a high score in the study benefited from chemotherapy, whereas patients with a low score did not appear to benefit from the addition of chemotherapy regardless of the number of positive lymph nodes. Patient selection for assay use remains controversial.” “The RxPONDER trial will confirm the SWOG-8814 trial data for women with ER-positive, node-positive disease treated with endocrine therapy with or without chemotherapy based on risk scores.”

Guidance from the National Institute for Health and Care Excellence (2013) stated: "Oncotype DX is recommended as an option for guiding adjuvant chemotherapy decisions for people with oestrogen receptor positive (ER+), lymph node negative (LN−) and human epidermal growth factor receptor 2 negative (HER2−) early breast cancer if: The person is assessed as being at intermediate risk; and information on the biological features of the cancer provided by Oncotype DX is likely to help in predicting the course of the disease and would therefore help when making the decision about prescribing chemotherapy; and the manufacturer provides Oncotype DX to National Health Service (NHS) organisations according to the confidential arrangement agreed with the National Institute for Health and Care Excellence (NICE). NICE encourages further data collection on the use of Oncotype DX in the NHS."

An assessment by the Belgian Healthcare Knowledge Center (KCE) (San Miguel, et al., 2015) concluded that "the evidence for Oncotype DX is more robust than the evidence for other tests." The KCE Report noted, however, that important evidence gaps are still present. The KCE review mostly identified studies supporting the prognostic ability (clinical validity) of the test. The KCE judged these studies to be of moderate to high quality. The KCE found no prospective studies reporting on the impact of Oncotype DX on long-term outcomes such as overall survival, while four studies indicated that Oncotype DX leads to changes in decision making. The KCE identified two studies on the predictive benefit of the test, one for lymph node patients. The KCE reported also noted that the first evidence relating to improvements in quality of life and reductions in patient anxiety as a result of using the test has been reported, but this is based on small patient numbers and further evidence is required.

Acceptance of 21-gene recurrence score assays as tools for clinical decision making in women or men with early stage breast cancer is controversial due to the lack of prospective validation studies, nevertheless, 2007 guidelines from an expert panel convened by ASCO on tumor markers in breast cancer concluded that multiparameter gene expression analysis (i.e., Oncotype Dx assay) can be used to predict the risk of recurrence in women with newly diagnosed, node-negative, ER-positive breast cancer.  Although it is reasonable to consider the use of a 21-gene recurrence score assay in males, none of the data generated to date have been in men with breast cancer (Gradishar, 2010). 

A 2009 abstract that looked at cases of male breast cancer (BC) with Oncotype Dx, concluded, “This large genomic study of male BC reveals a heterogeneous biology as measured by the standardized quantitative oncotype Dx breast cancer assay, similar to that observed in female BC.  Some differences, which may reflect the differences in hormone biology between males and females, were noted and deserve further study.” (Shak et al, 2009).

Mammaprint

MammaPrint a 70-gene profile that classifies breast cancer into Low Risk or High Risk of recurrence, by measuring genes representative of all the pathways of cancer metastases which were selected for their predictive relationship to 10-year recurrence probability (Raman, et al., 2013). MammaPrint is indicated for women who have stage I or II breast cancer, are lymph node positive or negative, are ER-positive or negative and tumor size of less than five centimeters. MammaPrint determines if the patient is a candidate for chemotherapy.

In February 2007, the Food and Drug Administration (FDA) approved Mammaprint (Agendia,  Amsterdam), a DNA microarray-based test used to predict whether women with early breast cancer might face the disease again. The test measures the activity of 70 genes, providing information about the likelihood that cancer will recur. It measures each of these genes in a sample of a woman's breast-cancer tumor and then uses a specific formula to produce a score that determines if the patient is deemed low-risk or high-risk for metastasis. In clinical trials, 1 in 4 women found to be at high risk by Mammaprint had recurrence of their cancer within 5 years. However, there are questions regarding the accuracy of this test. The positive predictive values at 5 and 10 years were 23 % and 29 %, respectively, while the corresponding negative predictive values were 95 % and 90 %, respectively.

Mammaprint was tested on 307 patients under the age of 61 years who underwent surgery for stage I or stage II breast cancer, and who have tumor size equal to or less than 5 cm, and lymph node-negative. The study found that Mammaprint more than doubled physicians' ability to predict breast cancer recurrence. Furthermore, a major clinical study is now underway to determine if the test really helps patients avoid needless chemotherapy. The European study will recruit 6,000 patients with early-stage breast cancer.

In reviewing gene expression profiling as a guide for the management of early stage breast cancer, the California Technology Assessment Forum (CTAF, 2007) stated that the Oncotype Dx recurrence score meets CTAF Technology Assessment Criteria 1 through 5 for safety, effectiveness and improvement in health outcomes when used with other tools to inform the decision to use chemotherapy in patients recently diagnosed with invasive breast cancer meeting the following criteria:

  • Estrogen or progesterone receptor positive
  • Lymph node negative
  • Tumor size less than 5 cm.

On the other hand, the CTAF stated that the use of other forms of gene expression profiling, including the 70-gene prognostic signature (Mammaprint), do not meet CTAF Technology Assessment Criteria 3 through 5 for safety, effectiveness and improvement in health outcomes. 

A report prepared by the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group evaluated the evidence for three gene expression assays on the market; Oncotype Dx, MammaPrint and the Breast Cancer Profiling (BCP or H/I ratio) test, and for gene expression signatures underlying the assays. The report found that, for clinical validity, studies differed according to whether they examined the actual test that is currently being offered to patients or the underlying gene signature. The report found that almost all of the Oncotype Dx evidence was for the marketed test, the strongest validation study being from one arm of a randomized controlled trial (NSABP-14) with a clinically homogeneous population. This study showed that the test, added in a clinically meaningful manner to standard prognostic indices. The MammaPrint signature and test itself was examined in studies with clinically heterogeneous populations (e.g., mix of ER positivity and tamoxifen treatment) and showed a clinically relevant separation of patients into risk categories, but it was not clear exactly how many predictions would be shifted across decision thresholds if this were used in combination with traditional indices.The BCP test itself was examined in one study, and the signature was tested in a variety of formulations in several studies. The report identified one randomized controlled trial that provided high quality retrospective evidence of the clinical utility of Oncotype Dx to predict chemotherapy treatment benefit, but evidence for clinical utility was not found for MammaPrint or the H/I ratio. The report concluded that Oncotype Dx is furthest along the validation pathway, with strong retrospective evidence that it predicts distant spread and chemotherapy benefit to a clinically relevant extent over standard predictors, in a well-defined clinical subgroup with clear treatment implications. The report concluded that the evidence for clinical implications of using MammaPrint was not as clear as with Oncotype Dx, and the ability to predict chemotherapy benefit does not yet exist. The report concluded that the H/I ratio test requires further validation. For all tests, the relationship of predicted to observed risk in different populations still needs further study, as does their incremental contribution, optimal implementation, and relevance to patients on current therapies.

The EGAPP Working Group (2009) reported that they found adequate evidence regarding the association of the Oncotype Dx Recurrence Score with disease recurrence and adequate evidence for response to chemotherapy. The EWG found adequate evidence to characterize the association of MammaPrint with future metastases, but inadequate evidence to assess the added value to standard risk stratification, and could not determine the population to which the test would best apply. The evidence was inadequate to characterize the clinical validity of the Quest H:I Test. The EGAPP Working Group reported that they found no evidence regarding the clinical utility of the MammaPrint and Quest H:I Ratio tests, and inadequate evidence regarding Oncotype Dx. The EGAPP Working Group noted that these technologies have potential for both benefit and harm.

More recently, the California Technology Assessment Forum (CTAF) reassessed the Mammaprint, and concluded that it did not meet CTAF criteria (Tice, 2010). The report concluded that "it remains unclear how the 70-gene prognostic signature should be used in managing patients with early stage breast cancer." The report noted that a large, randomized clinical trial (MINDACT) enrolling 6000 patients in Europe will test the hypothesis that use of the 70-gene prognostic score can improve outcomes for women with early stage breast cancer.

Other technology assessments (e.g., CvZ, 2010; Smartt, 2009; Lopez, et al., 2010; SBU, 2010) and guidelines (e.g., Harris et al, 2007; Azim, et al., 2013) have also found insufficient evidence for use of the Mammaprint. ASCO's 2006 update of the breast cancer follow-up and management guidelines in the adjuvant setting stated that the use of CBCs, chemistry panels, bone scans, chest radiographs, liver ultrasounds, computed tomography scans, [18F]fluorodeoxyglucose-positron emission tomography scanning, magnetic resonance imaging, or tumor markers (CEA, CA 15-3, and CA 27.29) is not recommended for routine breast cancer follow-up in an otherwise asymptomatic patient with no specific findings on clinical examination. It stated that careful history taking, physical examination, and regular mammography are appropriate for detecting breast cancer recurrence. Currently, there is a lack of evidence that the use of Mammaprint would influence the decisions that women and their physicians make with regard to adjuvant therapy. The clinical value of this test has yet to be established.

The BlueCross BlueShield Association Technology Evaluation Center Medical Advisory Panel voted that the Mammaprint to determine recurrence risk in women with early stage breast cancer does not meet the TEC criteria (BCBSA, 2014). An assessment by the BlueCross BlueShield Association (2014) stated: "MammaPrint is associated with recurrence and survival outcomes with prognostic discrimination that is at least as good as clinical risk prediction models and accuracy that may be better. Ten-year disease-free survival of patients classified as low risk was 80% to 89%, with lower confidence limits of 74% and 79%, likely too low for most women and physicians to consider forgoing chemotherapy. A prospective, randomized trial (Microarray In Node-Negative and 1 to 3 Positive Lymph Node Disease May Avoid Chemotherapy [MINDACT]) is underway to evaluate outcomes using MammaPrint to guide treatment."

Guidelines from the National Comprehensive Cancer Network (NCCN, 2015) state: “Studies using Mammaprint as a prognostic and predictive tool are small and/or retrospective in nature… Currently, prospective randomized clinical trials are addressing the use of Oncotype DX and MammaPrint as predictive and/or prognostic tools in pupulations of women with early-stage, lymph node-negative breast cancer… ” “The MINDACT trials is underway in Europe to compare the 70-gene signature with the commonly used clinicopathologic criteria in selecting patients for adjuvant chemotherapy in breast cancer with 0 to 3 positive nodes. The findings from this trial will help determine the prognostic value of MammaPrint and the benefit of treating intermediate-risk patients with adjuvant chemotherapy.”

Guidance from the National Institute for Health and Clinical Excellence (NICE, 2013) states that MammaPrint is "only recommended for use in research in people with ER+, LN− and HER2− early breast cancer, to collect evidence about potentially important clinical outcomes and to determine the ability of the tests to predict the benefit of chemotherapy. The tests are not recommended for general use in these people because of uncertainty about their overall clinical benefit and consequently their cost effectiveness."

An assessment preparted for the Agency for Healthcare Research and Quality (Meleth, et al., 2014) concluded: "We found modest evidence supporting added prognostic value (i.e., clinical validity), beyond traditional prognostic factors, for MammaPrint,. evidence was insufficient to determine the impact of MammaPrint on treatment decisions, primarily because of unknown consistency and imprecision."

An assessment by the Andalusian Agency for Health Technology Assessment (AETSA, 2014) concluded: "The MammaPrint is an independent prognosis factor in EBC, but there is insufficient evidence of its predictive ability in patients with ER-positive cancer treated with tamoxifen."

An assessment by the Belgian Healthcare Knowledge Centre (KCE) (San Miguel, et al., 2015) found that "the evidence base, in particular in relation to the prognostic ability of the test, is developing but is based on small sample sizes (≤ 272)." The KCE found that the test appears to be prognostic at 5 years although the validity of the test to predict longer-term outcomes does not seem to have been established. The KCE report stated that "it is not yet clear to what extent the use of the MammaPrint test will change the management of patients and to what extent chemotherapy would be offered to patients classified as having a good or a poor prognosis with MammaPrint." The KCE report also stated that it is unclear to what extent MammaPrint risk groups are predictive of chemotherapy benefit or how the use of MammaPrint will improve patient outcomes through increases in disease-free and overall survival. The KCE reported that the evidence for MammaPrint to date is mainly derived from premenopausal women, but younger women are more likely to be classified as having a poor prognosis using MammaPrint, which might overestimate the benefit of the test.

BluePrint

Agendia BluePrint is an 80-gene profile that classifies breast cancer into molecular subtypes (Raman, et al., 2013). The profile separates tumors into Basal-type, Luminal-type and ERBB2-type subgroups by measuring the functionality of downstream genes for each of these molecular pathways to inform the physician of the potential effect of adjuvant therapy.

Krijgsman et al (2012) noted that classification of breast cancer into molecular subtypes maybe important for the proper selection of therapy, as tumors with seemingly similar histopathological features can have strikingly different clinical outcomes.  Herein, these researchers reported the development of a molecular subtyping profile (BluePrint), which enables rationalization in patient selection for either chemotherapy or endocrine therapy prescription.  An 80-Gene Molecular Subtyping Profile (BluePrint) was developed using 200 breast cancer patient specimens and confirmed on 4 independent validation cohorts (n = 784).  Additionally, the profile was tested as a predictor of chemotherapy response in 133 breast cancer patients, treated with T/FAC neoadjuvant chemotherapy.  BluePrint classification of a patient cohort that was treated with neoadjuvant chemotherapy (n = 133) shows improved distribution of pathological Complete Response (pCR), among molecular subgroups compared with local pathology: 56 % of the patients had a pCR in the Basal-type subgroup, 3 % in the MammaPrint low-risk, luminal-type subgroup, 11 % in the MammaPrint high-risk, luminal-type subgroup, and 50 % in the HER2-type subgroup.  The group of genes identifying luminal-type breast cancer is highly enriched for genes having an Estrogen Receptor binding site proximal to the promoter-region, suggesting that these genes are direct targets of the Estrogen Receptor.  Implementation of this profile may improve the clinical management of breast cancer patients, by enabling the selection of patients who are most likely to benefit from either chemotherapy or from endocrine therapy.

An assessment by the National Institute for Health Research (Ward, et al., 2013) found the evidence for Blueprint was limited. Because of the limited available data identified for this test, the NIHR was unable to draw firm conclusions about its analytical validity, clinical validity (prognostic ability) and clinical utility. The report stated that further evidence on the prognostic and predictive ability of this test was required.

A report by the Belgian Healthcare Knowledge Centre (KCE) (San Miguel, et al., 2015) found that limited evidence for the prognostic ability (clinical validity) of BluePrint. The KCE found insufficient evidence on the impact of BluePrint on clinical management (clinical utility).

Furthermore, there is no information regarding BluePrint/molecular subtyping from NCCN’s clinical practice guideline on “Breast cancer” (Version 2.2013).

TargetPrint

TargetPrint®, ER/PR/HER2 Expression Assay (Agendia) is a microarray-based gene expression test which offers a quantitative assessment of the patient’s level of estrogen receptor (ER), progesterone receptor (PR) and HER2/neu overexpression within her breast cancer (Raman, et al., 2013). TargetPrint is offered in conjunction with MammaPrint to provide the physician an even more complete basis for treatment decisions. TargetPrint delivers an added benefit to the diagnostic process. Immunohistochemistry provides a semi-quantitative positive or negative result, whereas the gene expression result provided by TargetPrint allows physicians to integrate the absolute level of ER, PR and HER2 gene expression into treatment planning. TargetPrint determines if the patient is a candidate for hormonal therapy.

TargetPrint is a microarray-based gene expression test which offers a quantitative assessment of the patient’s level of estrogen receptor (ER), progesterone receptor (PR) and HER2/neu overexpression in breast cancer. The manufacturer states that TargetPrint is offered in conjunction with MammaPrint gene expression profiling to provide the physician an even more complete basis for treatment decisions. The manufacturer states that, as compared to Immunohistochemistry (IHC), TargetPrint provides additional information. Whereas IHC provides a semi-quantitative positive or negative result, the gene expression result provided by TargetPrint provides data on the absolute level of ER, PR and HER2 gene expression. Published information on the TargetPrint is limited to studies examining its correlation with measurements of ER, PR, and HER2 receptors (Gunven et al, 2011; Gevensleben et al, 2010; Roepman et al, 2009).  There is a lack of evidence from published prospective clinical studies that demonstrates that quantification of ER, PR, and HER2 gene expression by TargetPrint alters management such that clinical outcomes are improved.

Symphony

Symphony (Agendia) provides complete tumor profiling and is used to support therapeutic choices for breast cancer (Raman, 2013). SYMPHONY includes four assays to support breast cancer treatment decisions: MammaPrint® determines the risk of recurrence. BluePrint™ determines molecular subtypes and TargetPrint® determines estrogen receptor (ER), progesterone receptor (PR), and HER2 status. TheraPrint™ identifies alternative types of therapy for metastatic disease. SYMPHONY provides genomic information assisting with therapeutic decisions even for cases that have been otherwise classified as indeterminate, such as grade 2, small tumors, HER2 and/or lymph node positive. MammaPrint® determines if the patient is a candidate for chemotherapy. TargetPrint® determines if the patient is a candidate for hormonal therapy. BluePrint® provides information on the sub-classification of the tumor which guides the choice of therapies and combinations of therapies. TheraPrint® identifies alternative types of therapy for metastatic disease.

Rotterdam Signature 76-gene panel

The Rotterdam Signature test (Veridex) is a 76-gene expression assay (Raman, 2013). Sixty genes are intended to evaluate estrogen-receptor positive samples and 16 genes to evaluate estrogen-receptor negative samples. In a validation study that tested the signature on samples from 148 women, 50 fell into the low-risk group and 98 into the high-risk group. The test had 88% specificity and 39% sensitivity for the low-risk group, with a hazard ratio for distant relapse within 5 years of 5.74 comparing the high-risk group to the low-risk group. The Rotterdam Signature identifies women at high and low risk of disease recurrence.

The Rotterdam Signature 76-gene panel (Veridex, LLC) is a multivariate index assay that is intended to assist in assessing a patient’s risk of systemic recurrence of cancer following successful initial treatment of localized node-negative breast cancer with surgery and tamoxifen alone. This multigene assay is intended for use in lymph-node negative breast cancer patients. The Rotterdam Signature panel uses microarray processing to measure cellular concentrations of mRNA in fresh tissue samples. The Rotterdam Signature panel uses the Human Genome U133a GeneChip (Affymetrix, Inc.) to identify patients that have gene expression signatures associated with either a low or high risk of developing metastatic disease.  A multicenter study investigated the ability of the Rotterdam 76-gene signature to identify patients at risk of distant metastases within 5 and 10 years of first diagnosis, using frozen tissue samples from 180 patients with node-negative breast cancer who had not received systemic chemotherapy (Foekens, et al., 2006). The Rotterdam 76-gene signature correctly identified 27 out of 30 cases of relapse within 5 years (90% sensitivity) and 75 out of 150 patients who did not relapse (50% specificity). An earlier summary of the same study (Foekens, et al., 2005) reported a hazard ratio for distant metastasis-free survival comparing favorable versus unfavorable signature = 7.41 (95% confidence interval 2.63-20.9); p = 8.5 x 10-6). The hazard ratio of overall survival comparing favorable versus unfavorable signature = 5.45 (95% confidence interval 1.62-18.3); p = .002. There are no published studies that have assessed the clinical utility of the Rotterdam 76-gene signature by monitoring the long-term outcomes of the patients selected and not selected for chemotherapy on the basis of assay results.

Breast Cancer Gene Expression Ratio / Breast Cancer Index

The Breast Cancer Gene Expression Ratio (HOXB13:IL17BR, also known as H/I) (AviaraDx, Inc., Carlsbad, CA) is intended to predict the risk of disease recurrence in women with estrogen receptor (ER)-positive, lymph node-negative breast cancer. The Breast Cancer Gene Expression Ratio is based on the ratio of the expression of two genes: the homeobox gene-B13 (HOXB13) and the interleukin- 17B receptor gene (IL17BR). In breast cancers that are more likely to recur, the HOXB13 gene tends to be over-expressed, while the IL-17BR gene tends to be under-expressed.

Ma, et al. (2004) reported on the early validation of the HOXB13:IL17BR gene expression ratio. The investigators generated gene expression profiles of hormone receptor-positive primary breast cancers in a set of 60 patients treated with adjuvant tamoxifen monotherapy. An expression signature predictive of disease-free survival was reduced to a two-gene ratio, HOXB13 versus IL17BR, which outperformed existing biomarkers. The investigators concluded that ectopic expression of HOXB13 in MCF10A breast epithelial cells enhances motility and invasion in vitro, and its expression is increased in both preinvasive and invasive primary breast cancer. The investigators suggested that HOXB13:IL17BR expression ratio may be useful for identifying patients appropriate for alternative therapeutic regimens in early-stage breast cancer.

In an 852-patient retrospective study, Ma, et al (2006) found that the HOXB13:IL17BR ratio (H:I expression ratio) independently predicted breast cancer recurrence in patients with ER-positive, lymph-node negative cancer. The H:I expression ratio was found to be predictive in patients who received tamoxifen therapy as well as in those who did not. Expression of HOXB13, IL17BR, CHDH, estrogen receptor (ER) and progesterone receptor (PR) were quantified by real-time polymerase chain reaction (PCR) in 852 formalin-fixed, paraffin-embedded primary breast cancers from 566 untreated and 286 tamoxifen-treated breast cancer patients. Gene expression and clinical variables were analyzed for association with relapse-free survival (RFS) by Cox proportional hazards regression models. The investigators reported that, in the entire cohort, expression of HOXB13 was associated with shorter RFS (p = .008), and expression of IL17BR and CHDH was associated with longer RFS (p < 0.0001 for IL17BR and p = 0.0002 for CHDH). In ER-positive patients, the HOXB13:IL17BR index predicted clinical outcome independently of treatment, but more strongly in node-negative patients. In multivariate analysis of the ER-positive node-negative subgroup including age, PR status, tumor size, S phase fraction, and tamoxifen treatment, the two-gene index remained a significant predictor of RFS (hazard ratio [HR] = 3.9; 95 % CI:1.5 to 10.3; p = .007).

The value of the Breast Cancer Gene Expression Ratio was also evaluated in a study by Goetz et al (2006). That study found that a high H:I expression ratio is associated with an increased rate of relapse and mortality in ER-positive, lymph node-negative cancer patients treated with surgery and tamoxifen. Goetz et al (2006) examined the association between the ratio of the HOXB13 to IL17BR expression and the clinical outcomes of relapse and survival in women with ER-positive breast cancer enrolled onto a North Central Cancer Treatment Group adjuvant tamoxifen trial (NCCTG 89-30-52). Tumor blocks were obtained from 211 of 256 eligible patients, and quantitative reverse transcription-PCR profiles for HOXB13 and IL-17BR were obtained from 206 patients.  In the node-positive cohort (n = 86), the HOXB13/IL-17BR ratio was not associated with relapse or survival. In contrast, in the node-negative cohort (n = 130), a high HOXB13/IL-17BR ratio was associated with significantly worse RFS [HR, 1.98; p = 0.031], DFS (HR, 2.03; p = 0.015), and OS (HR, 2.4; p = 0.014), independent of standard prognostic markers.

The Blue Cross and Blue Shield Association Technology Evaluation Center (BCBSA, 2007) announced that its Medical Advisory Panel (MAP) concluded that the use of the Breast Cancer Gene Expression Ratio gene expression profiling does not meet the TEC criteria.

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group (2009) found insufficient evidence to make a recommendation for or against the use of the H:I ratio test to improve outcomes in defined populations of women with breast cancer. EGAPP concluded that the evidence is insufficient to assess the balance of benefits and harms of the proposed uses of this test. The EWG encouraged further development and evaluation of these technologies.

In a systematic review on gene expression profiling assays in early-stage breast cancer, Marchionni, et al. (2008) summarized evidence on the validity and utility of 3 gene expression-based prognostic breast cancer tests: Oncotype Dx, MammaPrint, and H/I.  The authors concluded that gene expression technologies show great promise to improve predictions of prognosis and treatment benefit for women with early-stage breast cancer.  However, more information is needed on the extent of improvement in prediction, characteristics of women in whom the tests should be used, and how best to incorporate test results into decision making about breast cancer treatment. 

Guidelines from the American Society for Clinical Oncology (Harris, et al., 2007) found that, in newly diagnosed patients with node-negative, estrogen-receptor positive breast cancer, the Oncotype Dx assay can be used to predict the risk of recurrence in patients treated with tamoxifen. The ASCO guidelines concluded that Oncotype Dx may be used to identify patients who are predicted to obtain the most therapeutic benefit from adjuvant tamoxifen and may not require adjuvant chemotherapy. The ASCO guidelines found, in addition, that patients with high recurrence scores appear to achieve relatively more benefit from adjuvant chemotherapy than from tamoxifen. ASCO found that there are insufficient data at present to comment on whether these conclusions generalize to hormonal therapies other than tamoxifen, or whether this assay applies to other chemotherapy regimens.  Guidelines from the American Society for Clinical Oncology (Harris, et al., 2007) concluded that the precise clinical utility and appropriate application for other multiparameter assays, such as the MammaPrint assay, the Rotterdam Signature, and the Breast Cancer Gene Expression Ratio are under investigation. ASCO also found insufficient data to recommend use of proteomic patterns for management of patients with breast cancer. 

Sgori, et al. (2013) found that, in the absence of extended letrozole therapy, high H/I identifies a subgroup of ER-positive patients disease-free after 5 years of tamoxifen who are at risk for late recurrence. The investigators also found that, when extended endocrine therapy with letrozole is prescribed, high H/I predicts benefit from therapy and a decreased probability of late disease recurrence. Sgori, et al. conducted a prospective-retrospective, nested case-control design of 83 recurrences matched to 166 nonrecurrences from letrozole- and placebo-treated patients within MA.17 trial. Expression of H/I within primary tumors was determined by reverse-transcription polymerase chain reaction with a prespecified cutpoint. The investigators determined the predictive ability of H/I for ascertaining benefit from letrozole using multivariable conditional logistic regression including standard clinicopathological factors as covariates. All statistical tests were two-sided. The investigators reported that high H/I was statistically significantly associated with a decrease in late recurrence in patients receiving extended letrozole therapy (odds ratio [OR] = 0.35; 95% confidence interval [CI] = 0.16 to 0.75; P = .007). In an adjusted model with standard clinicopathological factors, high H/I remained statistically significantly associated with patient benefit from letrozole (OR = 0.33; 95% CI = 0.15 to 0.73; P = .006). Reduction in the absolute risk of recurrence at 5 years was 16.5% for patients with high H/I (P = .007). The interaction between H/I and letrozole treatment was statistically significant (P = .03).

BioTheranostics Breast Cancer Index (BCI) is a prognostic biomarker that provides quantitative assessment of the likelihood of distant recurrence in patients diagnosed with estrogen receptor-positive, lymph node-negative breast cancer (Raman, et al., 2013). In development and validation studies, BCI stratified about 50% of tamoxifen treated ER+, node-negative breast cancer patients into a low risk group for 10-year distant recurrence. BCI is a molecular assay developed from the combination of two indices: HOXB13:IL17BR and five cell cycle-associate gene index (BUB1B, CENPA, NEK2, RACGAP1, RRM2) that assesses tumor grade. The test is performed on a formalin-fixed, paraffin-embedded (FFPE) tissue block.

Ma, et al. (2008) reported on the development and early validation of a five-gene reverse transcription PCR assay for molecular grade index (MGI) that has subsequently been incorporated into BCI and is suitable for analyzing routine formalin-fixed paraffin-embedded clinical samples. The investigators found that the combination of MGI and HOXB13:IL17BR outperformed either alone and identifies a subgroup (approximately 30%) of early stage estrogen receptor-positive breast cancer patients with very poor outcome despite endocrine therapy. From their previously published list of genes whose expression correlates with both tumor grade and tumor stage progression, the investigators selected five cell cycle-related genes to build MGI and evaluated MGI in two publicly available microarray data sets totaling 410 patients. Using two additional cohorts (n =323), the investigators developed a real-time reverse transcription PCR assay for MGI, validated its prognostic utility, and examined its interaction with HOXB13:IL17BR. The investigators reported that MGI performed consistently as a strong prognostic factor and was comparable with a more complex 97-gene genomic grade index in multiple data sets. In patients treated with endocrine therapy, MGI and HOXB13:IL17BR modified each other's prognostic performance. High MGI was associated with significantly worse outcome only in combination with high HOXB13:IL17BR, and likewise, high HOXB13:IL17BR was significantly associated with poor outcome only in combination with high MGI.

Jerevall, et al. (2011) reported on the development of the Breast Cancer Index, a dichotomous index combining two gene expression assays, HOXB13:IL17BR (H:I) and molecular grade index (MGI), to assess risk of recurrence in breast cancer patients. The study objective was to demonstrate the prognostic utility of the combined index in early-stage breast cancer. In a blinded retrospective analysis of 588 ER-positive tamoxifen-treated and untreated breast cancer patients from the randomized prospective Stockholm trial which was conducted during 1976 to 1990, H:I and MGI were measured using real-time RT-PCR. Association with patient outcome was evaluated by Kaplan-Meier analysis and Cox proportional hazard regression. A continuous risk index was developed using Cox modelling. The investigators found that the dichotomous H:I+MGI was significantly associated with distant recurrence and breast cancer death. The greater than 50% of tamoxifen-treated patients categorized as low-risk had less than 3% 10-year distant recurrence risk. A continuous risk model (Breast Cancer Index (BCI)) was developed with the tamoxifen-treated group and the prognostic performance tested in the untreated group was 53% of patients categorized as low risk with an 8.3% 10-year distant recurrence risk. 

Jankowitz, et al. (2011) reported on a study to validate the prognostic performance of BCI in estrogen-receptor positive, lymph node negative breast cancer patients. The investigators found that, in this characteristically low-risk cohort, BCI classified high versus low-risk groups with about a five-fold difference in 10-year risk of distant recurrence and breast cancer-specific death. The investigators identified tumor samples from 265 estrogen-receptor positive, lymph-node negative tamoxifen-treated patients from a single academic institution's cancer research registry. They performed the BCI assay and assigned scores based on a predetermined risk model. The investigators assessed risk by BCI and Adjuvant Online! (AO) and correlated these to clinical outcomes in the patient cohort. The investigators found that BCI was a significant predictor of outcome in this cohort of estrogen-receptor positive, lymph-node negative patients (median age: 56-y; median follow-up: 10.3-y), treated with adjuvant tamoxifen alone or tamoxifen with chemotherapy (32%). BCI categorized 55%, 21%, and 24% of patients as low, intermediate and high-risk, respectively. The 10-year rates of distant recurrence were 6.6%, 12.1% and 31.9% and of breast cancer-specific mortality were 3.8%, 3.6% and 22.1% in low, intermediate, and high-risk groups, respectively. In a multivariate analysis including clinicopathological factors, BCI was a significant predictor of distant recurrence (HR for 5-unit increase = 5.32 [CI 2.18-13.01; P = 0.0002]) and breast cancer-specific mortality (HR for a 5-unit increase = 9.60 [CI 3.20-28.80; P < 0.0001]). AO was significantly associated with risk of recurrence. In a separate multivariate analysis, both BCI and AO were significantly predictive of outcome. In a time-dependent (10-year) ROC curve accuracy analysis of recurrence risk, the addition of BCI and AO increased predictive accuracy in all patients from 66% (AO only) to 76% (AO+BCI) and in tamoxifen-only treated patients from 65% to 81%. The authors concluded that BCI and AO are independent predictors with BCI having additive utility beyond standard of care parameters that are encompassed in AO. The authors acknowledge that this study is limited by the fact that it was a retrospective, single-institution study and that results may have been biased on the basis of specimen availability and patterns of referral to the tertiary academic center.

Mathieu, et al. (2012) assessed the performance of BCI to predict chemosensitivity based on pathological complete response (pCR) and breast conservation surgery (BCS). The authors performed the BCI assay on tumor samples from 150 breast cancer patients from a single institution treated with neoadjuvant chemotherapy. The authors used logistical regression and c-index to assess predictive strength and additive accuracy of BCI beyond clinicopathologic factors. BCI classified 42% of patients as low, 35% as intermediate and 23% as high risk. Low BCI risk group had 98.4% negative predictive value (NPV) for pCR and 86% NPV for BCS. High versus low BCI group had a 34 and 5.8 greater likelihood of achieving pCR and BCS, respectively (P=0.0055; P=0.0022). BCI increased c-index for pCR (0.875-0.924; p=0.017) and BCS prediction (0.788-0.843; p=0.027) beyond clinicopathologic factors. The authors concluded that BCI significantly predicted pCR and BCS beyond clinicopathologic factors. High NPVs indicate that BCI could be a useful tool to identify breast cancer patients who are not eligible for neoadjuvant chemotherapy. The authors concluded that "these results suggest that BCI could be used to assess both chemosensitivity and eligibility for BCS." The authors stated that an important limitation of this study is that,  in this retrospective analysis, patients were not selected based on ER or HER2 expression for the indications of neoadjuvant chemotherapy. The authors explained that this could have increased the predictive strength of BCI given that this biomarker was initially developed and validated in ER + node-negative patients

Zhang, et al. (2013) examined the prognostic performance of BCI for prediction of early (0-5 years) and late (more than 5 years) risk of distant recurrence in patients with estrogen receptor-positive (ER(+)), lymph node-negative (LN(-)) tumors. The BCI model was validated by retrospective analyses of tumor samples from tamoxifen-treated patients from a randomized prospective trial (Stockholm TAM, n = 317) and a multi-institutional cohort (n = 358). Within the Stockholm TAM cohort, BCI risk groups stratified the majority (approximately 65%) of patients as low risk with less than 3% distant recurrence rate for 0 to 5 years and 5 to 10 years. In the multi-institutional cohort, which had larger tumors, 55% of patients were classified as BCI low risk with less than 5% distant recurrence rate for 0 to 5 years and 5 to 10 years. Zhang and colleagues found that, for both cohorts, continuous BCI was the most significant prognostic factor beyond standard clinicopathologic factors for 0 to 5 years and more than five years. The authors concluded that the prognostic sustainability of BCI to assess early- and late-distant recurrence risk at diagnosis has clinical use for decisions of chemotherapy at diagnosis and for decisions for extended adjuvant endocrine therapy beyond five years.

Sgori, et al. (2013) compared the prognostic ability of the BCI assay, the Oncotype DX Breast, and IHC4 for both early and late recurrence in patients with estrogen-receptor-positive, node-negative (N0) disease who took part in the Arimidex, Tamoxifen, Alone or in Combination (ATAC) clinical trial. In this prospective comparison study, Sgori and colleagues obtained archival tumor blocks from the TransATAC tissue bank from all postmenopausal patients with estrogen-receptor-positive breast cancer from whom the Oncotype DX and IHC4 values had already been derived. The investigators did BCI analysis in matched samples with sufficient residual RNA using two BCI models -- cubic (BCI-C) and linear (BCI-L)-using previously validated cutoffs. The prospectively-defined primary study objective was to evaluate overall (0–10y) prognostic performance of the BCI-C model for DR in ER+ N0 patients. Secondary objectives were: 1) assessment of the prognostic performance of the BCI-L model and its components, H/I and MGI, for overall (0–10y), early (0–5y) and late (5–10y) DR; 2) comparative performance of BCI-L versus the Oncotype DX RS and IHC4. To assess the ability of the biomarkers to predict recurrence beyond standard clinicopathological variables, the investigators calculated the change in the likelihood-ratio from Cox proportional hazards models. Suitable tissue was available from 665 patients with estrogen-receptor-positive, N0 breast cancer for BCI analysis. The primary analysis showed significant differences in risk of distant recurrence over 10 years in the categorical BCI-C risk groups (p<0·0001) with 6·8% (95% CI 4·4-10·0) of patients in the low-risk group, 17·3% (12·0-24·7) in the intermediate group, and 22·2% (15·3-31·5) in the high-risk group having distant recurrence. BCI-C analyzed as a continuous variable was not significantly associated with overall (0–10y) risk of DR when adjusted for CTS (inter-quartile HR=1·39; 95% CI, 0·99 to 3·70; LR-Δχ2=3·70; P=0·054). Comparison of the prognostic performance of BCI-L to BCI-C indicated that unlike BCI-C, BCI-L was a significant predictor of risk of recurrence as a continuous variable, and the HR after adjustment with CTS was 2·19 versus 4.86 between high- and low-risk groups for BCI-C and BCI-L, respectively. Thus, all subsequent analyses were performed utilizing BCI-L. The secondary analysis showed that BCI-L was a much stronger predictor for overall (0-10 year) distant recurrence compared with BCI-C (interquartile HR 2·30 [95% CI 1·62-3·27]; likelihood ratio (LR)-Δχ(2)=22·69; p<0·0001). When compared with BCI-L, the Oncotype Dx breast score was less predictive (HR 1·48 [95% CI 1·22-1·78]; LR-Δχ(2)=13·68; p=0·0002) and IHC4 was similar (HR 1·69 [95% CI 1·51-2·56]; LR-Δχ(2)=22·83; p<0·0001). All further analyses were done with the BCI-L model. In a multivariable analysis, all assays had significant prognostic ability for early distant recurrence (BCI-L HR 2·77 [95% CI 1·63-4·70], LR-Δχ(2)=15·42, p<0·0001; Oncotype Dx Breast score HR 1·80 [1·42-2·29], LR-Δχ(2)=18·48, p<0·0001; IHC4 HR 2·90 [2·01-4·18], LR-Δχ(2)=29·14, p<0·0001); however, only BCI-L was significant for late distant recurrence (BCI-L HR 1·95 [95% CI 1·22-3·14], LR-Δχ(2)=7·97, p=0·0048; 21-gene recurrence score HR 1·13 [0·82-1·56], LR-Δχ(2)=0·48, p=0·47; IHC4 HR 1·30 [0·88-1·94], LR-Δχ(2)=1·59, p=0·20). The authors concluded that BCI-L was the only significant prognostic test for risk of both early and late distant recurrence and identified two risk populations for each timeframe. BCI-L could help to identify patients at high risk for late distant recurrence who might benefit from extended endocrine or other therapy. An important limitation is that the evaluation of BCI-L was a secondary objective of this study; the primary objective was evaluation of BCI-C.

An editorial (Ignatiadis, 2013) accompanying the study by Sgroi, et al. stated that the BCI test is “ready for prime time” in treatment decision making for post-menopausal, estrogen-receptor positive women who have undergone 5 years of hormonal therapy. The editorial noted that there are other molecular diagnostic assays that also have been shown to predict late recurrence. For support, the editorial cited a study by Sestak, et al. (2013), which found that, in the last follow-up phase, Clinical Treatment Score (CTS) added most prognostic information for distant recurrence in years 5 to 10 for breast cancer patients in the ATAC trial. Sestak, et al. reported that, in a multivariate model that incorporated CTS, PAM50 provided the strongest additional prognostic factor in the 5 to 10 year followup phase, followed by BCI, and with IHC4 and RS adding the least prognostic information.

A manufacturer funded study (Gustavsen, et al., 2014) reported on a model that found BCI to be cost saving from a third-party payer perspective, based upon assumptions about the impact of BCI on adjuvant chemotherapy use, extended endocrine therapy use, and endocrine therapy compliance. The authors developed two economic models to project the cost-effectivenss of BCI in a hypothetical population of patients with estrogen-receptor postive, lymph-node negative breast cancer compared with standard clinicopathologic diagnostic modalities. The authors modeled costs associated with adjuvant chemotherapy, toxicity, followup, endocrine therapy, and recurrence over 10 years. The models examined cost utility compared with standard practice when used at diagnosis and in patients disease-free at 5 years post diagnosis. The authors reported that use of BCI was projected to be cost saving in both models. In the newly diagnosed population, net cost savings were $3803 per patient tested. In the 5 years post diagnosis population, BCI was projected to yield a net cost savings of $1803 per patient tested. The authors reported that sensitivity analyses demonstrated that BCI was cost saving across a wide range of clinically relevant input assumptions.

Preliminary data suggest that molecular approaches including gene expression platforms such as BCI may add to classical clinical parameters including tumor size and node status at diagnosis, but further research is needed (Smith, et al., 2014; Bianchini & Gianni, 2013; Ignatiadis and Sotiriou, 2013). The clinical utility of BCI and other molecular diagnostics in predicting late recurrence has yet to be established (Foukakis and Bergh, 2015). It also remains to be established which of several molecular diagnostic tests in development are the most appropriate for detecting late recurrrence (Sestak & Kuzick, 2015).

An assessment by the National Institute for Health Research (Ward, et al., 2013) found that, based on the limited available data, no firm conclusions can be drawn about the analytical validity, clinical validity (prognostic ability) and clinical utility of the Breast Cancer Index. The assessment stated that further evidence on the prognostic and predictive ability of this test is required. An assessment by IETS (2013) and a consensus statement (Azim, et al., 2013) reached similar conclusions.

An assessment by the BlueCross BlueShield Association (2015) concluded that the evidence is insufficient to permit conclusions about the Breast Cancer Index on health outcomes. Although evidence supports the association of risk classes defined by the Breast Cancer Index and recurrence and survival outcomes, it remains to be shown whether the Breast Cancer Index adds incremental prognostic information to standard clinical risk classifiers.

An assessment by the Belgian Healthcare Knowledge Centre (KCE) (San Miguel, et al.,2015) found that the evidence for the H/I ratio assay is limited to studies supporting the prognostic ability (clinical validity) of the test. They found insufficient evidence for the impact of the H/I ratio assay on clinical management (clinical utility).

A review published in the ASCO Educational Book (Smith, et al., 2014) reviewed the BCI and other currently available molecular diagnostics for selecting and determining the optimal duration of endocrine adjuvant therapy in women with early stage estrogen receptor positive breast cancer: "Further research into applying molecular features and gene expression scores to standard clinico-pathologic criteria for tailoring extended endocrine therapy is now a high priority.... An important research challenge is now to identify which patients are likely to benefit from this type of long-term therapy. Preliminary data suggest that molecular approaches including gene expression platforms such as ROR may add to classical clinical parameters including tumor size and node status at diagnosis."

A Palmetto Medicare Local Coverage Determination (LCD) allows coverage of the Breast Cancer Index in certain post-menopausal women with estrogen-receptor positive breast cancer, reasoning that the data defined benefit of the BCI test appears to be when a woman is having significant side effects or has other concerns regarding adjuvant tamoxifen therapy and is opposed to taking more than 5 years of tamoxifen or starting on an AI (letrazole) after tamoxifen (CMS, 2014). The LCD noted, however, that, there is an increase in recurrence risk with increasing BCI score such that, "at the 95% confidence interval (CI), the risk in some individuals categorized in the BCI-low group could be as high as 20%. Due to the data complexity, there is a significant possibility that a physician might consider all BCI-L patients at negligible risk, and thus not consider extended hormone therapy and consequently lead women from the NCCN recommended interventions. Given the low toxicity and low cost of extended therapy, the false sense of security could deny many women from lifesaving therapy."

There is a lack of consensus among guidelines regarding the value of molecular assays in determining whether longer durations of adjuvant endocrine therapy beyond 5 years are clinically indicated. Guidelines from the American Society for Clinical Oncology (Burstein, et al., 2014) on adjuvant endocrine therapy for hormone-receptor positive breast cancer state: "Well-established clinical factors including tumor size; nodal status; ER, PgR, and HER2 biomarkers; and molecular diagostic assays serve as prognostic factors for breast cancer recurrence. However, there are no robust specific clinical or biomarker measures that selectively predict early versus late recurrence, nor predict whether tamoxifen or AI therapy would be appropriate treatment, nor determine whether longer durations of adjuvant endocrine therapy are clinically indicated." The National Comprehensive Cancer Network guidelines for breast cancer version 2, 2015 states: "Multiple other multi-gene mor multi-gene expression assay systems have been developed. These systems are generally based upon small, retrospectie studies, and the Panel believes that none are currently sufficiently validated to warrant inclusion in the guideline." The St. Gallen guideline panel (Coates, et al., 2015) found that Oncotype DX, MammaPrint, PAM-50 ROR score, EndoPredict and the Breast Cancer Index were all considered usefully prognostic for years 1-5, but only the Oncotype Dx commanded a majority in favor of its value in predicting the usefulness of chemotherapy. The Panel agreed that the PAM50 ROR score was clearly prognostic beyond five years, and that the Mammaprint was not prognostic beyond 5 years. The Panel was divided about the prognostic value of the Breast Cancer Index, the Oncotype DX, and EndoPredict in this time period. ESMO guidelines (Senkus, et al., 2013) state: "Molecular signatures for ER-positive breast cancer such as OncotypeDx, EndoPredict, Breast Cancer Index or for all types of breast cancer (pNO-1) such as MammaPrint and Genomic Grade Index are commercially available, but none of them have proven robust clinical utility so far. In some cases of difficult decision, such as grade 2 ER-positive HER-2 negative and node-negative breast cancer, MammaPrint and Oncotype DX may be used in conjunction with all clinicopathological factors, to help in treatment decision-making." 

Mammostrat  

Mammostrat (Clarient) is a novel test for estimating the risk for recurrence in hormone-receptor positive, early stage breast cancer that is independent of proliferation and grade (Raman, et al., 2013). Five biomarkers are combined with a defined mathematical algorithm resulting in a risk index. Mammostrat is clinically validated and has been studied on more than 4,500 total patients in numerous independent cohorts that include the NSABP B14 and B20 trials. Clinicians and patients are faced with difficult choices as to whether to add toxic adjuvant chemotherapy in addition to standard endocrine treatment. Mammostrat may help clinicians understand the inherent aggressiveness of the tumor and the likelihood of tumor recurrence.

The Mammostrat is a prognostic immunohistochemistry (IHC) test that measures the risk of breast cancer recurrence in post-menopausal, node-negative, estrogen receptor-expressing breast cancer patients who will receive hormonal therapy and are considering adjuvant chemotherapy. The test analyzes five monoclonal antibody biomarkers and applies a diagnostic algorithm to assess whether patients have a high, moderate, or low risk of recurrence after they have had their breast cancer tumor surgically removed and have been treated with tamoxifen.

Bartlett et al (2010) tested the efficacy of the Mammostrat in a mixed population of cases treated in a single center with breast-conserving surgery and long-term follow-up.  Tissue microarrays from a consecutive series of 1,812 women managed by wide local excision and post-operative radiotherapy were collected.  Of 1,390 cases stained, 197 received no adjuvant hormonal or chemotherapy, 1,044 received tamoxifen only, and 149 received a combination of hormonal therapy and chemotherapy.  Median age at diagnosis was 57 years, 71% were post-menopausal, 23.9% were node-positive and median tumor size was 1.5 cm.  Samples were stained using triplicate 0.6 mm2 tissue microarray cores, and positivity for p53, HTF9C, CEACAM5, NDRG1 and SLC7A5 was assessed.  Each case was assigned a Mammostrat risk score, and distant recurrence-free survival (DRFS), relapse-free survival (RFS) and overall survival (OS) were analyzed by marker positivity and risk score.  Increased Mammostrat scores were significantly associated with reduced DRFS, RFS and OS in ER-positive breast cancer (p < 0.00001).  In multivariate analyses the risk score was independent of conventional risk factors for DRFS, RFS and OS (p < 0.05).  In node-negative, tamoxifen-treated patients, 10-year recurrence rates were 7.6 +/- 1.5% in the low-risk group versus 20.0 +/- 4.4% in the high-risk group.  Further, exploratory analyses revealed associations with outcome in both ER-negative and un-treated patients.  The authors concluded that the Mammostrat can act as an independent prognostic tool for ER-positive, tamoxifen-treated breast cancer and the results of the study revealed a possible association with outcome regardless of node status and ER-negative tumors.

There is insufficient evidence to determine whether the Mammostrat test is better than conventional risk assessment tools in predicting the recurrence of breast cancer.  Furthermore, neither NCCN or ASCO have incorporated the test into their guidelines as a management tool. Guidance from the National Institute for Health and Clinical Excellence (NICE, 2013) states that the Mammostrat is "only recommended for use in research in people with ER+, LN− and HER2− early breast cancer, to collect evidence about potentially important clinical outcomes and to determine the ability of the tests to predict the benefit of chemotherapy ... The tests are not recommended for general use in these people because of uncertainty about their overall clinical benefit and consequently their cost effectiveness."

An assessment by the Belgian Healthcare Knowledge Centre (KCE) (San Miguel, et al., 2015) found that the evidence for Mammostrat is mainly limited to studies supporting the prognostic ability (clinical validity) of the test. The KCE stated that these studies include a large sample size and appear to be of reasonable quality. The KCE cited one study reporting on clinical utility in terms of the predictive ability of the test by risk group. "However, further evidence is required."

OvaChek

The OvaCheck™ (Correlogic Systems, Inc.) is a proteomic analysis of blood for the early detection of ovarian cancer.  A similar test, which involved a different molecular pattern, was the subject of a 2002 study of 216 women with ovarian cancer.  That study showed that the proteomic test had a specificity of 100% and a sensitivity of 95%, with a positive predictive value of 94% (Petricoin, et al., 2002).  While this study showed that a proteomic test detected ovarian cancers even where CA-125 levels were normal, this study included only women who had been detected with ovarian cancer by other means.  There is inadequate evidence that this test will be effective for screening women with undetected ovarian cancer. 

In addition, there is concern, given the low prevalence of ovarian cancer, that this test is not sufficiently specific for use in screening.  The National Cancer Institute explains that even an ovarian cancer test with a specificity of 99% means that 1% of those who did not have cancer would test positive, which is “far too high a rate for commercial use” (NCI, 2004). For a rare disease such as ovarian cancer, which has an approximate prevalence of 1 in 2,500 in the general population, a 99% specificity and 100% sensitivity translates into 25 women falsely identified for every one true cancer found.

The OvaCheck™ test employs electrospray ionization (ESI) type of mass spectrometry using highly diluted denatured blood samples.  This method differs from a matrix-assisted laser desorption ionization (MALDI) analysis of undiluted native sera samples that was used in the Lancet study and is currently under investigation by the National Cancer Institute and Food and Drug Administration (NCI, 2004).  The NCI notes that “[t]he class of molecules analyzed by these two approaches, and thus the molecules that constitute the diagnostic patterns, would be expected to be entirely different.” Neither the NCI nor FDA has been involved in the design or validation of OvaCheck™ methodology. 

As the Ovacheck test is performed as a “home-brewed” test by two national laboratories instead of as a commercially available kit, FDA approval of the OvaCheck test may not be required.  The Society for Gynecologic Oncologists (SGO, 2004) has reviewed the literature regarding OvaCheck and concluded that “more research is needed to validate the test’s effectiveness before offering it to the public.”  Similarly, the American College of Obstetricians and Gynecologists (2004) has stated that "more research is needed to validate the test's effectiveness before recommending it to the public."

An assessment of the Ovacheck test and other genomic tests for ovarian cancer prepared for the Agency for Healthcare Research and Quality by the Duke Evidence-Based Practice Center (Myers, et al., 2006) reached the following conclusions:  "Genomic test sensitivity/specificity estimates are limited by small sample sizes, spectrum bias, and unrealistically large prevalences of ovarian cancer; in particular, estimates of positive predictive values derived from most of the studies are substantially higher than would be expected in most screening or diagnostic settings. We found no evidence relevant to the question of the impact of genomic tests on health outcomes in asymptomatic women. Although there is a relatively large literature on the association of test results and various clinical outcomes, the clinical utility of changing management based on these results has not been evaluated."  Specifically regarding Ovacheck and other proteomic tests for ovarian cancer, the assessment found that, "[a] lthough all studies reported good discrimination for the particular protein profile studied, there were several recurrent issues that limit the ability to draw inferences about potential clinical applicability," in particular technical issues with the assays themselves, variations in analytic methods used among studies, and an unrealistically high prevalence of ovarian cancer in the datasets compared to what would be expected in a normal screening population.

OvaSure

OvaSure is an ovarian cancer screening test that entails the use of 6 biomarkers (leptin, prolactin, osteopontin, insulin-like growth factor II, macrophage inhibitory factor and CA-125) to assess the presence of early stage ovarian cancer in high-risk women.  Visintin et al (2008) characterized and validated the OvaSure for discriminating between disease-free and ovarian cancer patients.  These researchers analyzed 362 healthy controls and 156 newly diagnosed ovarian cancer patients.  Concentrations of leptin, prolactin, osteopontin, insulin-like growth factor II, macrophage inhibitory factor, and CA-125 were determined using a multiplex, bead-based, immunoassay system.  All 6 markers were evaluated in a training set (181 samples from the control group and 113 samples from ovarian cancer patients) and a test set (181 sample control group and 43 ovarian cancer).  Multiplex and ELISA exhibited the same pattern of expression for all the biomarkers.  None of the biomarkers by themselves was good enough to differentiate healthy versus cancer cells.  However, the combination of the 6 markers provided a better differentiation than CA-125.  Four models with less than 2% classification error in training sets all had significant improvement (sensitivity 84 % to 98% at specificity 95%) over CA-125 (sensitivity 72% at specificity 95%) in the test set.  The chosen model correctly classified 221 out of 224 specimens in the test set, with a classification accuracy of 98.7%.  The authors noted that the OvaSure is the first blood biomarker test with a sensitivity of 95.3% and a specificity of 99.4% for the detection of ovarian cancer.  Six markers provided a significant improvement over CA-125 alone for ovarian cancer detection.  Validation was performed with a blinded cohort.  They stated that this novel multiplex platform has the potential for efficient screening in patients who are at high risk for ovarian cancer.

However, the Society of Gynecologic Oncologists (SGO, 2008) released an opinion regarding OvaSure, which stated that additional research is needed before the test should be offered to women outside the context of a research study.  Moreover, SGO stated that it will "await the results of further clinical validation of OvaSure with great interest".

Furthermore, according to the FDA’s web site, the FDA sent the Laboratory Corporation of America a warning letter stating that it is illegally marketing OvaSure to detect ovarian cancer.  According to the FDA warning letter, their review indicates that this product is a device under section 201(h) of the Food, Drug, and Cosmetic Act (FDCA or Act), 21 U.S.C. 321(h), because it is intended for use in the diagnosis of disease or other conditions, or in the cure, treatment, prevention, or mitigation of disease. The Act requires that manufacturers of devices that are not exempt obtain marketing approval or clearance for their products from the FDA before they may offer them for sale. This helps protect the public health by ensuring that new devices are shown to be both safe and effective or substantially equivalent to other devices already legally marketed in this country for which approval is not required.  According to the FDA warning letter, no such determination has been made for OvaSure.

Thrombospondin-1

Thrombospondin-1 (THBS-1), an angiogenesis inhibitor, has been identified as a potential monitoring marker in gynecologic malignancies.  In a randomized phase III study on the co-expression of angiogenic markers and their associations with prognosis in advanced epithelial ovarian cancer, Secord, et al. (2007) reported that high THBS-1 may be an independent predictor of worse progression-free and overall survival in women with advanced-stage EOC.  However, the authors stated, "A larger prospective study is warranted for validation of these findings."

Previstage GCC

Guanylyl Cyclase C (GCC or GUCY2C) (Diagnocure) a gene coding for a protein found in cells, lining the intestine from the duodenum to the rectum (Raman, et al., 2013). It is involved in water transport, crypt morphology and suppression of tumorigenesis. It is not normally found in tissue in other parts of the body, and therefore, GCC detected outside of the intestine, indicates presence of colorectal cancer metastases. Early studies have indicated that the presence of GCC in the blood may be an early indicator of micrometastases that would otherwise escape detection by the current standard methods of monitoring. Earlier detection provides an opportunity for more immediate treatment or surgical intervention to potentially improve patient outcomes and survival rates. This is a  diagnostic test for recurrence by identification of micrometastasis in the blood.

Guanyl cyclase C (GCC) is a receptor protein normally expressed in high concentrations on the luminal surface of the gastrointestinal epithelium.  Expression of GCC persists on mucosal cells that have undergone malignant transformation.  Thus, GCC has potential use as a marker to determine spread of colorectal cancer to lymph nodes.  A retrospective study of 21 patients post surgical resection of colorectal cancer found that all 11 of 21 patients who were free of cancer for 5 years or more were negative for GCC in lymph nodes, whereas all 10 of 21 patients whose cancer returned within 3 years of surgery were positive for GCC.  However, the value of the GCC marker test in the management of colorectal cancer needs to be evaluated in prospective clinical outcome studies.  A large prospective study is currently being conducted to compare standard histological examination of lymph nodes to the GCC marker test.

Previstage™ Guanylyl Cyclase C (GCC or GUCY2C) (Diagnocure) is a gene coding for a protein found in cells, lining the intestine from the duodenum to the rectum (Raman, et al., 2013). It is involved in water transport, crypt morphology and suppression of tumorigenesis. It is not normally found in tissue in other parts of the body, and therefore, GCC detected outside of the intestine, indicates presence of colorectal cancer metastases. GCC mRNA has shown to be highly accurate in detecting the spread and recurrence of colorectal cancer, respectively in lymph nodes and blood, thereby representing a significant improvement over traditional detection methods. Previstage is a predictive test for risk stratification of recurrence and prognostic marker for recurrence.

Thymidylate synthase

Thymidylate synthase is a DNA synthesis related gene.  According to Compton (2008), the prognostic value of this promising and potentially clinically applicable molecular marker has been studied in colorectal cancer.  Compton found that the independent influence of this marker on prognosis remains unproven.  Compton explained that "[v]ariability in assay methodology, conflicting results from various studies examining the same factor, and the prevalence of multiple small studies that lack statistically robust, multivariate analyses all contribute to the lack of conclusive data."  Compton concluded that before this marker can be incorporated into clinically meaningful prognostic stratification systems, more studies are required using multivariate analysis, well-characterized patient populations, reproducible and current methodology, and standardized reagents.

In a special report on pharmacogenomics of cancer, the BlueCross and BlueShield Association's Technology Evaluation Center (TEC) (2007) described the results of a meta-analysis on thymidylate synthase protein expression and survival in colorectal cancer that stated low thymidylate synthase expression was significantly associated with better survival, but heterogeneity and possible bias prevented firm conclusions.

Current guidelines from the American Society for Colon and Rectal Surgeons (2004) stated: "In the future, DNA analysis and the intratumoral expression of specific chemical substances", including thymidylate synthase, "may be used routinely to further assess prognosis or response to therapy."  In addition, Shankaran et al (2008) stated in a review on the role of molecular markers in predicting response to therapy in patients with colorectal cancer, "Although to date no molecular characteristics have emerged as consistent predictors of response to therapy, retrospective studies have investigated the role of a variety of biomarkers, including microsatellite instability, loss of heterozygosity of 18q, type II transforming growth factor beta receptor, thymidylate synthase, epidermal growth factor receptor, and Kirsten-ras (KRAS)."

VEGF

Tumour angiogenesis is associated with invasiveness and the metastatic potential of various cancers.  Vascular endothelial growth factor (VEGF), the most potent and specific angiogenic factor identified to date, regulates normal and pathologic angiogenesis.  An evidence report from Cancer Care Ontario (Welch et al, 2008) on the use of the VEGF inhibitor bevacizumab in colorectal cancer explained that the increased expression of VEGF has been correlated with metastasis, recurrence, and poor prognosis in many cancers, including colorectal cancer. Guidelines from the National Institute for Health and Clinical Excellence (NICE, 2007) explained that bevacizumab (Avastin) is a recombinant humanised monoclonal IgG1 antibody that acts as an angiogenesis inhibitor.  It targets the biological activity of VEGF, which stimulates new blood vessel formation in the tumour.  However, neither the FDA approved labeling of bevacizumab or evidence-based guidelines recommend measurement of VEGF to diagnose colorectal cancer or to select patients for treatment.  In a special report on pharmacogenomics of cancer, the BlueCross and BlueShield Association's Technology Evaluation Center (TEC) (2007) stated that pre-treatment VEGF levels do not appear to be predictive of response to anti-angiogenic therapy.

Shin and colleagues (2013) evaluated inhibitory effects of bevacizumab on VEGF signaling and tumor growth in-vitro and in-vivo, and assessed phosphorylation of VEGF receptor 2 (VEGFR2) and downstream signaling in endothelial cells as pharmacodynamic markers using phospho-flow cytometry.  These researchers also validated markers in patients with mCRC treated with bevacizumab-based chemotherapy.  In in-vitro studies, bevacizumab inhibited proliferation of human umbilical vein endothelial cells in association with reduced VEGF signaling.  Notably, bevacizumab inhibited VEGF-induced phosphorylation of VEGFR-2, Akt, and extra-cellular signal-regulated kinase (ERK).  In-vivo, treatment with bevacizumab inhibited growth of xenografted tumors and attenuated VEGF-induced phosphorylation of Akt and ERK.  The median percentages of VEGFR2 + pAkt + and VEGFR2 + pERK + cells, determined by phospho-flow cytometry, were approximately 3-fold higher in mCRC patients than in healthy controls.  Bevacizumab treatment decreased VEGFR2 + pAkt + cells in 18 of 24 patients on day 3.  The authors concluded that bevacizumab combined with chemotherapy decreased the number of VEGFR2 + pAkt + cells, reflecting impaired VEGFR2 signaling.  Together, these data suggested that changes in the proportion of circulating VEGFR2 + pAkt + cells may be a potential pharmacodynamic marker of the effectiveness of anti-angiogenic agents, and could prove valuable in determining drug dosage and administration schedule.

PCA3

PCA3 (DD3) is a gene that has been found to be highly overexpressed in prostate cancer.  This gene has been investigated as a potential diagnostic marker for prostate cancer.  However, there are no published clinical outcome studies of the effectiveness of the PCA3 gene in screening, diagnosis or management of prostate cancer.

Prostate cancer antigen 3 (PCA3) (Progensa, Gene-Probe, Inc.) encodes a prostate-specific mRNA. It is one of the most prostate cancer-specific genes identified, with over-expression in about 95% of cancers tested. The PCA3 urine assay is an amplified nucleic acid assay, which uses transcription-mediated amplification (TMA) to quantify PCA3 and PSA mRNA in prostate cells found in urine samples. The PCA3 score is calculated as the ratio between PCA3 and PSA mRNA. The main target population of this non-invasive test is men with raised PSA but a negative prostate biopsy. Other target groups include men with a slightly raised PSA, as well as men with signs and symptoms suggestive of prostate cancer.

van Gils and colleagues (2007) stated that the recently discovered PCA3 is a promising prostate cancer marker. These investigators performed a multi-center study to validate the diagnostic performance of the PCA3 urine test established in an earlier single-institution study. The first voided urine after DRE was collected from a total of 583 men with serum PSA levels between 3 and 15 ng/ml who were to undergo prostate biopsies. These researchers determined the PCA3 score in these samples and correlated the results with the results of the prostate biopsies. A total of 534 men (92 %) had an informative sample. The area under the receiver-operating characteristic curve, a measure of the diagnostic accuracy of a test, was 0.66 for the PCA3 urine test and 0.57 for serum PSA. The sensitivity for the PCA3 urine test was 65 %, the specificity was 66 % (versus 47 % for serum PSA), and the negative predictive value was 80 %. The authors concluded that the findings of this multi-center study validated the diagnostic performance of the PCA3 urine test in the largest group studied thus far using a PCA3 gene-based test.

Marks and associates (2007) examined the potential utility of the investigational PCA3 urine assay to predict the repeat biopsy outcome. Urine was collected after DRE (3 strokes per lobe) from 233 men with serum PSA levels persistently 2.5 ng/ml or greater and at least one previous negative biopsy. The PCA3 scores were determined using a highly sensitive quantitative assay with TMA. The ability of the PCA3 score to predict the biopsy outcome was assessed and compared with the serum PSA levels. The RNA yield was adequate for analysis in the urine samples from 226 of 233 men (i.e., the informative specimen rate was 97 %). Repeat biopsy revealed prostate cancer in 60 (27 %) of the 226 remaining subjects. Receiver operating characteristic curve analysis yielded an area under the curve of 0.68 for the PCA3 score. In contrast, the area under the curve for serum PSA was 0.52. Using a PCA3 score cutoff of 35, the assay sensitivity was 58 % and specificity 72 %, with an odds ratio of 3.6. At PCA3 scores of less than 5, only 12 % of men had prostate cancer on repeat biopsy; at PCA3 scores of greater than 100, the risk of positive biopsy was 50 %. The authors concluded that in men undergoing repeat prostate biopsy to rule out cancer, the urinary PCA3 score was superior to serum PSA determination for predicting the biopsy outcome. The high specificity and informative rate suggest that the PCA3 assay could have an important role in prostate cancer diagnosis.

Groskopf et al (2007) reported that the PCA3 score is independent of prostate volume and was highly correlated with the risk of positive biopsy. The PCA3 test was performed on 529 men scheduled for prostate biopsy. Overall, the PCA3 score had a sensitivity of 54% and a specificity of 74%. A PCA3 score of less than 5 was associated with a 14% risk of positive biopsy, while a PCA3 score of greater than 100 was associated with a 69% risk of positive biopsy.

Haese et al (2007) presented preliminary results from a European multicenter study of PCA3. Enrolled patients had a PSA level of less than or equal to 2.5 ng/mL, had 1 or 2 previous negative biopsies, and were scheduled for repeat biopsy. The specificity of the PCA3 score (cutoff 35) was found to be 78%, and the sensitivity was 67%. Patients with a PCA3 score of greater than or equal to 35 had a 33% probability of a positive repeat biopsy, compared to a 6% probability for those with a PCA3 score of less than 35.

An assessment by the BlueCross BlueShield Association Technology Evaluation Center (BCBSA, 2008) found that, in general, PCA3 assay results to date are preliminary; interpretation of results has not been standardized and clinical utility studies of decision-making for initial biopsy, repeat biopsy or treatment have not been reported.

Tosoian et al (2010) evaluated the relationship between PCA3 and prostate biopsy results in men in a surveillance program. Urine specimens were obtained from 294 men with prostate cancer enrolled in the Johns Hopkins surveillance program. The follow-up protocol included semi-annual free and total PSA measurements, digital rectal examination and annual surveillance prostate biopsy. Cox proportional hazards regression was used to evaluate the association between PCA3 results and progression on surveillance biopsy (defined as Gleason pattern 4 or 5, more than 2 positive biopsy cores or more than 50% involvement of any core with cancer). Patients with progression on biopsy (12.9%) had a mean PCA3 score similar to that of those without progression (60.0 versus 50.8, p = 0.131). Receiver operating characteristics analysis suggested that PCA3 alone could not be used to identify men with progression on biopsy (area under the curve = 0.589, 95% CI 0.496 to 0.683, p = 0.076). After adjustment for age and date of diagnosis PCA3 was not significantly associated with progression on biopsy (p = 0.15). The authors concluded that in men with low risk prostate cancer who were carefully selected for surveillance the PCA3 score was not significantly associated with short-term biopsy progression. They stated that further analysis is necessary to assess the usefulness of PCA3 in combination with other biomarkers or in selected subsets of patients undergoing surveillance.

While there are studies examining the positive and negative predictive values of the PCA3 urine assay, there is currently a lack of evidence of the effect of this test on management of individuals with or suspected of prostate cancer. The PCA3 urine assay shows promise as a prostate cancer diagnostic tool, however, more research is needed to ascertain the clinical value of this assay for screening and diagnostic purposes.

ProstatePx

Donovan et al (2008) from Aureon, the manufacturer of Prostate Px, reported on the development and validation of their systems pathology model for predicting prostate cancer recurrence after prostatectomy. The clinical utility of defining high risk for failure after radical prostatectomy is to decide whether patients require closer follow-up than average or whether adjuvant radiotherapy, hormone therapy, or chemotherapy would be of benefit. In this analysis, the concordance index for the systems pathology approach used by Aureon was 0.83, but was only slightly better than a 10-variable model that used only the usual clinical parameters, with a concordance index of 0.80. The corresponding hazard ratios for clinical failure were 6.37 for the 10-variable clinical model, and 9.11 for the systems pathology approach. In an accompanying editorial, Klein, et al. (2009)  questioned the clinical significance of these differences. They noted that "[a]lthough the difference in concordance indices was statistically significant, the question is whether there is sufficient clinical relevance to justify the extra effort, expense, and clinical expertise needed for the systems approach ... In contemporary clinical practice, a patient with a hazard ratio of 6.37 generated by the model using easily derived, routinely reported clinical and pathological parameters is just as likely to be a candidate for closer monitoring or adjuvant therapy than one with a hazard ratio of 9.11 generated by the systems approach".

Sutcliffe et al (2009) provided an evidence-based perspective on the prognostic value of novel markers in localized prostate cancer and identified the best prognostic model including the 3 classical markers and investigated if models incorporating novel markers are better. Eight electronic bibliographic databases were searched. The reference lists of relevant articles were checked and various health services research-related resources consulted via the internet. The search was restricted to publications from 1970 onwards in the English language. Selected studies were assessed, data extracted using a standard template, and quality assessed using an adaptation of published criteria. Because of the heterogeneity regarding populations, outcomes and study type, meta-analyses were not undertaken and the results are presented in tabulated format with a narrative synthesis of the results. A total of 30 papers met the inclusion criteria, of which 28 reported on prognostic novel markers and 5 on prognostic models. A total of 21 novel markers were identified from the 28 novel marker studies. There was considerable variability in the results reported, the quality of the studies was generally poor and there was a shortage of studies in some categories. The marker with the strongest evidence for its prognostic significance was PSA velocity (or doubling time). There was a particularly strong association between PSA velocity and prostate cancer death in both clinical and pathological models. In the clinical model the hazard ratio for death from prostate cancer was 9.8 (95 % CI 2.8 to 34.3, p < 0.001) in men with an annual PSA velocity of more than 2 ng/ml versus an annual PSA velocity of 2 ng/ml or less; similarly, the hazard ratio was 12.8 (95 % CI 3.7 to 43.7, p < 0.001) in the pathological model. The quality of the prognostic model studies was adequate and overall better than the quality of the prognostic marker studies. Two issues were poorly dealt with in most or all of the prognostic model studies: (i) inclusion of established markers, and (ii) consideration of the possible biases from study attrition. Given the heterogeneity of the models, they can not be considered comparable. Only 2 models did not include a novel marker, and 1 of these included several demographical and co-morbidity variables to predict all-cause mortality. Only 2 models reported a measure of model performance, the C-statistic, and for neither was it calculated in an external data set. It was not possible to assess whether the models that included novel markers performed better than those without. This review highlighted the poor quality and heterogeneity of studies, which render much of the results inconclusive. It also pinpointed the small proportion of models reported in the literature that are based on patient cohorts with a mean or median follow-up of at least 5 years, thus making long-term predictions unreliable. Prostate-specific antigen velocity, however, stood out in terms of the strength of the evidence supporting its prognostic value and the relatively high hazard ratios. There is great interest in PSA velocity as a monitoring tool for active surveillance but there is as yet no consensus on how it should be used and, in particular, what threshold should indicate the need for radical treatment.

In an editorial on clinically relevant prognostic markers for prostate cancer, Gelmann and Henshall (2009) stated that "[u]ntil we have sufficiently discriminating markers to inform treatment decisions, the problem of whom to treat will continue to grow exponentially as the number of cases of screening-detected low-risk cancer increases".

CellSearch

The CellSearch™ Epithelial Cell Kit, along with the CellSpotter™ Analyzer (Veridex, LLC, Warren, NJ) is a device designed to automate the detection and enumeration of circulating tumor cells (CTCs) of epithelial origin (CD45-, EpCAM+, and cytokeratins 8, 18+ and/or 19+) in whole blood in patients with advanced breast cancer (Ellery, et al., 2010; Raman, et al., 2011).  It is intended for use in adjunctively monitoring and predicting cancer disease progression and response to therapy. 

The CellSearch Epithelial Cell Kit received FDA 510(k) clearance on January 21, 2004.  The FDA concluded that the device is substantially equivalent to immunomagnetic circulating cancer cell selection and enumeration systems.  These devices consist of biological probes, fluorochromes and other reagents, preservation and preparation devices and semi-automated analytical instruments to select and count circulating cancer cells in a prepared sample of whole blood. 

The CellSearch Epithelial Cell Kit quantifies CTCs by marking cancerous cells with tiny, protein-coated magnetic balls in whole blood.  These cells are stained with fluorescent markers for identification and then dispensed into a cartridge for analysis where a strong magnetic field is applied to the mixture causing the magnetically marked cells to move to the cartridge surface.  The cartridge is then analyzed by the CellSpotter Analyzer.  A medical professional rechecks the CTCs and the CellSpotter Analyzer tallies the final CTC count. 

In a prospective, multicenter study, Cristofanilli et al (2004) used the CellSearch System on 177 patients with measurable metastatic breast cancer for levels of CTCs both before the patients started a new line of therapy and at follow-up.  The progression of the disease or the response to treatment was determined with the use of standard imaging studies at the participating centers every nine to twelve weeks.  Outcomes were assessed according to levels of CTCs at baseline, before the patients started a new therapy.  In the first test, patients with 5 or more CTCs per 7.5 ml of blood compared to a group with fewer than 5 CTCs had a shorter median progression-free survival (2.7 months vs. 7.0 months) and shorter overall survival (10.1 months vs. greater than 18 months).  At the follow-up visit, approximately three to four weeks after the initiation of therapy, the percentage of patients with more than 5 CTC was reduced from 49 percent to 30 percent, suggesting a benefit from therapy.  The difference in progression-free survival between the two groups remained consistent (2.1 months for women with 5 or more CTCs vs. 7 months for women with less than 5 CTCs).  Overall, survival in the women with more than 5 CTCs was 8.2 months compared to greater than 18 months in the cohort with less than 5 CTCs.  Cristofanilli concluded that the number of CTCs before treatment was an independent predictor of progression-free survival and overall survival in patients with metastatic breast cancer.  However, Cristofanilli also concluded that the results may not be valid for patients who do not have measurable disease or for those starting a new regimen of hormone therapy, immunotherapy, or both.  He states, “The prognostic implications of an elevated level of circulating tumor cells for patients with metastatic disease who are starting a new treatment may be an opportunity to stratify these patients in investigational studies”.  Furthermore, the study did not address whether patients with an elevated number of circulating tumor cells might benefit from other therapies.  Thus, this minimally invasive assay requires further evaluation as a prognostic marker of disease progression and response to therapy. 

The clinical application of quantifying CTCs in the peripheral blood of breast cancer patients remains unclear.  Published data in the peer-reviewed medical literature are needed to determine how such measurements would guide treatment decisions and whether these decisions would result in beneficial patient outcomes (Kahn, et al., 2004; Abeloff, et al., 2004). An assessment of CellSearch by AETSA (2006) concluded "In the current stage of development of this technology, there is no evidence that it provides any advantage over existing technology for CTC identification or indeed any additional clinical use." Guidelines from the American Society for Clinical Oncology (Harris, et al., 2007) found: "The measurement of circulating tumor cells (CTCs) should not be used to make the diagnosis of breast cancer or to influence any treatment decisions in patients with breast cancer. Similarly, the use of the recently U.S. Food and Drug Administration (FDA)-cleared test for CTC (CellSearch Assay) in patients with metastatic breast cancer cannot be recommended until further validation confirms the clinical value of this test."

An assessment by the Canadian Agency for Drugs and Technologies in Health (CADTH, 2012) found that studies indicate that measurement of CTCs using the CellSearch system could be used as prognostic factors for progression of the disease and the potential treatment of patients with ovarian cancer. No economic studies were identified, therefore the cost-effectiveness of the CellSearch system could not be summarized.

Although studies relate circulating tumor cells to prognostic indicators (see, e.g., Cohen, et al., 2008; De Giorgi, et al., 2009), there are a lack of published prospective clinical studies demonstrating that measurement of CTCs alters management such that clinical outcomes are improved. Such clinical outcome studies are currently ongoing. Current guidelines from the National Comprehensive Cancer Network (NCCN) and the American Society for Clinical Oncology (ASCO) make no recommendation for use of circulating tumor cells.

Her-2/neu

Estrogen and progestin receptors are important prognostic markers in breast cancer, and the higher the percentage of overall cells positive as well as the greater the intensity, the better the prognosis. Estrogen and progesterone receptor positivity in breast cancer cells is an indication the patient may be a good candidate for hormone therapy. HER-2/neu is an oncogene. Its gene product, a protein, is over-expressed in approximately 20 to 30% of breast cancers. The over-expressed protein is present in unusually high concentration on the surface of some malignant breast cancer cells, causing these cells to rapidly proliferate. It is important because these tumors are susceptible to treatment with Herceptin (trastuzumab), which specifically binds to this over-expressed protein. Herceptin blocks these protein receptors, inhibiting continued replication and tumor growth. HER2/neu may also be expressed in ovarian, gastric, colorectal, endometrial, lung, bladder, prostate, and salivary gland (Chen, et al., 2006).

HER-2/neu is an oncogene encoding a growth factor receptor related to epidermal growth factor receptor (EGFR) and is amplified in approximately 25-30 percent of node-positive breast cancers (Chin, et al. 2006). Overexpression of HER-2/neu is associated with decreased disease-free and overall survival. Over-expression of HER-2/neu may be used to identify patients who may be may benefit from trastuzumab (Herceptin™ ) and/or high dose chemotherapy. Trastuzumab is a humanized monoclonal antibody targeting the HER 2/neu (c-erbB-2) oncogene.

Her-2 has been used to: assess prognosis of stage II, node positive breast cancer patients; predict disease-free and overall survival in patients with stage II, node positive breast cancer treated with adjuvant cyclophosphamide, doxorubicin, 5-fluorouracil chemotherapy; and determine patient eligibility for Herceptin treatment (Chen, et al., 2006). The College of American Pathologists (CAP) recommends FISH as an optimal method for HER2/neu testing; therefore, positive IHC results are usually confirmed by FISH testing.

There are additional tests that may be used in breast cancer cases, such as DNA ploidy, Ki-67 or other proliferation markers. However, most authorities believe that HER-2/neu, estrogen and progesterone receptor status are the most important to evaluate first. The other tests do not have therapeutic implications and, when compared with grade and stage of the disease, are not independently significant with respect to prognosis.

Harris et al (2007) updated ASCO's recommendations for the use of tumor marker tests in the prevention, screening, treatment, and surveillance of breast cancer. Thirteen categories of breast tumor markers were considered, 6 of which were new for the guideline. The following categories showed evidence of clinical utility and were recommended for use in practice: CA 15-3, CA 27.29, CEA, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, urokinase plasminogen activator, plasminogen activator inhibitor 1, and certain multi-parameter gene expression assays. Not all applications for these markers were supported, however. The following categories demonstrated insufficient evidence to support routine use in clinical practice: DNA/ploidy by flow cytometry, p53, cathepsin D, cyclin E (fragments or whole length), proteomics, certain multi-parameter assays, detection of bone marrow micrometastases, and circulating tumor cells (e.g., CellSearch assay). These guidelines found present data insufficient to recommend measurement of Ki67, cyclin D, cyclin E, p27, p21, thymidine kinase, topoisomerase II, or other markers of proliferation to assign patients to prognostic groups. The guidelines also found insufficient data to recommend assessment of bone marrow micrometastases for management of patients with breast cancer.

PancraGen (formerly PathFinderTG - Pancreas)

PathFinderTG (RedPath Integrated Pathology, Pittsburgh, PA), also known as topographic genotyping, is described by the manufacturer as a quantitative genetic mutational analysis platform for resolving “indeterminate, atypical, suspicious, equivocal and non-diagnostic specimen” diagnoses from pathology specimens (RedPath, 2007). The manufacturer states that PathFinder TG "focuses on acquired mutational damage rather than inherited genetic predisposition for certain diseases, although there are certain NIH recommended inherited conditions for which we do test."  The manufacturer states that the temporal sequence of acquired mutational damage revealed by the PathFinderTG test is an earlier demonstration of tumor biological aggressiveness than current staging systems that rely on the depth of invasion already achieved by the tumor.  Most available published evidence for topographic genotyping focuses on retrospective analyses of pathology specimens examining correlations of test results with tumor characteristics (e.g., Saad et al, 2008; Lin et al, 2008; Finkelstein et al, 2003; Pollack et al, 2001; Riberio et al, 1998; Kounelis et al, 1998; Finkelstein et al, 1998; Holst et al, 1998; Jones et al, 1997; Holst et al, 1997; Pricolo et al, 1997; Przygodzki et al, 1997; Finkelstein et al, 1996; Kanbour-shakir et al, 1996; Ribeiro et al, 1996; Pryzgodzki et al, 1996; Safatle-Ribeiro et al, 1996; Papadaki et al, 1996; Przygodzki et al, 1996; Pricolo et al, 1996; Finkelstein et al, 1994). There are no prospective clinical outcome studies on the use of topographic genotyping in guiding patient management. Current evidence-based guidelines from leading medical professional organizations and public health agencies do not include recommendations for topographic genotyping. In a review on molecular analysis of pancreatic cyst fluid, Shen and colleagues (2009) stated that a large study with validation of PathFinderTG molecular testing of pancreatic fluid will be needed before a firm conclusion can be drawn.

A systematic evidence review of the PathFinderTG prepared for the Agency for Healthcare Research and Quality (Trikalinos, et al., 2010) found that most studies on loss-of-heterozygosity based topographic genotyping with PathfinderTG were excluded because they only described the molecular profile of different tumors, without assessing the ability of the method to help make diagnosis, prognosis or treatment guidance. The review found no studies that directly measured whether using loss-of-heterozygosity based topographic genotyping with PathfinderTG improves patient-relevant clinical outcomes. The review reported that eligible studies on the diagnostic and prognostic ability of loss-of-heterozygosity based topographic genotyping with PathfinderTG were small in sample sizes and had overt methodological limitations. The review reported that important characteristics of their designs were not clearly reported. The report noted that loss-of-heterozygosity based topographic genotyping with PathfinderTG is claimed to be particularly useful in cases where conventional pathology is unable to provide a conclusive diagnosis. However, the included studies were not designed to address this question. Therefore, it is unclear if the findings of the reviewed studies are directly applicable to patients with the same cancers but with inconclusive diagnosis.

The manufacturer has announced that the PathginderTG - Pancreas has been rebranded Pancragen.

An American Gastroenterological Association Technical Review (Scheiman, et al., 2014) stated: "Testing for molecular alterations in pancreatic cyst fluid is currently available and reimbursed by Medicare under certain circumstances. Case series have confirmed malignant cysts have greater number and quality of molecular alterations, but no study has been properly designed to identify how the test performs in predicting outcome with regard need to surgery, surveillance or predicts interventions leading to improved survival.  This adjunct to FNA may provide value in distinct clinical circumstances, such as confirmation of a serous lesion due to a lack of KRAS or GNAS mutation in a macrocystic serous cystadenoma, but its routine use is not supported at the present time."

Guidelines published in April 2015 by the American Gastroenterological Association (Vege, et al., 2015) have no recommendations for use of topographic genotyping for evaluating pancreatic cysts. Other guidelines (NCCN, 2015; Vege, et al., 2015; Del Chiaro, et al., 2013; Sahani, et al., 2013; Tanaka, et al., 2012) have no firm recommendations for topographic genotyping for assessing indeterminate pancreatic cysts.

The International consensus guidelines for “The management intraductal papillary mucinous neoplasm (IPMN) and mucinous cystic neoplasm (MCN) of the pancreas” (Tanaka et al, 2012) stated that endoscopic ultrasound (EUS) is recommended for all cysts with worrisome features or for cysts greater than 3 cm without these features.  Endoscopic US confirmation of a mural nodule, any features of main duct involvement (intraductal mucin or thickened main duct wall), or suspicious or positive cytology for malignancy is an indication for surgical resection.  Cysts with high-risk stigmata should be resected in patients medically fit for surgery, although EUS is optional.  Endoscopic US can be considered in smaller cysts without worrisome features but is not required.  Endoscopic US analysis should include at least cytology, amylase level, and CEA.  The guidelines stated that elevated CEA is a marker that distinguishes mucinous from non-mucinous cysts, but not benign from malignant cysts.

Gene expression profiling for cancer of unknown primary

Carcinoma of unknown primary (CUP) is a biopsy-proven metastatic solid tumor with no primary tumor identified and represents approximately 2% to 4% of all cancer cases.  The diagnosis of CUP is made following inconclusive results from standard tests (e.g., biopsy, immunochemistry and other blood work, chest x-rays, and occult blood stool test).  The absence of a known primary tumor presents challenges to the selection of appropriate treatment strategies.  As a result, patients have a poor prognosis, and fewer than 25% survive 1 year from the time of diagnosis.  A variety of tissue-biopsy testing techniques currently are used to determine the origin of the CUP, including immunochemistry; histological examination of specimens stained with eosin and hematoxylin, and electron microscopy.  These techniques definitively identify the type of carcinoma in less than 20% to 30% of CUP.

Gene expression profiling is a technique used to identify the genetic makeup of a tissue sample by characterizing the patterns of mRNA transcribed, or "expressed", by its DNA.  Specific patterns of gene expression, reflected in unique configurations of mRNA, are associated with different tumor types.  By comparing the gene expression profile (GEP) of an unknown tumor to the profiles of known primary cancers ("referent" profiles), it may be possible to determine the type of tumor from which the CUP originated.

In July 2008, the FDA cleared for marketing the Pathwork Tissue of Origin test (Pathwork Diagnostics, Sunnyvale, CA), a gene expression profiling test that uses microarray processing to determine the type of cancer cells present in a tumor of unknown origin.  The test uses the PathChip (Affymetrix Inc., Santa Clara, CA), a custom-designed gene expression array, to measure the expression from 1,668 probe sets to quantify the similarity of tumor specimens to 15 common malignant tumor types, including: bladder, breast, colorectal, gastric, germ cell, hepatocellular, kidney, non-small cell lung, non-Hodgkin's lymphoma, melanoma, ovarian, pancreatic, prostate, soft tissue sarcoma, and thyroid.  The degree of correspondence between the tissue sample's GEP and a referent profile is quantified and expressed as a probability-based score.

A multi-center, clinical validation study reported on comparisons of diagnoses based on GEP from 477 banked tissue samples of undifferentiated and poorly differentiated metastases versus standard of care pathology based diagnoses.  Comparison of the GEP based diagnoses versus pathology based diagnoses yielded an 89 % agreement and the concurrence was greater than 92 % for 8 out of 15 types of primary tumors.  The overall accuracy of the test was approximately 95 % and 98 % for positive and negative determinations, respectively (Monzon et al, 2007).

Gene expression profiling is a promising technology in the management of CUP; however, there is insufficient evidence of its clinical utility compared to that achieved by expert pathologists using current standards of practice. A draft clinical guideline on metastatic malignant disease of unknown origin by the National Institute for Clinical Excellence (NICE, 2010) recommends against using gene expression profiling (e.g., Pathwork TOT, CupPrint, Theros CancerTypeID, miRview Mets) to identify primary tumors in patients with CUP. The guideline explained that currently there is no evidence that gene-expression based profiling improves the management or changes the outcomes for patients with CUP. Guidelines on occult primary from the National Comprehensive Cancer Network (NCCN, 2010) state that, while gene expression profiling looks promising, "prospective clinical trials are necessary to confirm whether this approach can be used in choosing treatment options which would improve the prognosis of patients with occult primary cancers." 

A technology assessment prepared for the Agency for Healthcare Research and Quality (Meleth et al, 2013) found that the clinical accuracy of the PathworkDx, miRview, and CancerTypeID are similar, ranging from 85 percent to 88 percent, and that the evidence that the tests contribute to identifying a tumor of unknown origin was moderate. The assessment concluded that we do not have sufficient evidence to assess the effect of the tests on treatment decisions and outcomes. The assessment noted that most studies of these tests were funded wholly or partially by the manufacturers of these tests, and that the most urgent need in the literature is to have the clinical utility of the tests evaluated by research groups that have no evidence conflict of interest.

Monzon et al (2009) stated that malignancies found in unexpected locations or with poorly differentiated morphologies can pose a significant challenge for tissue of origin determination.  Current histologic and imaging techniques fail to yield definitive identification of the tissue of origin in a significant number of cases.  The aim of this study was to validate a predefined 1,550-gene expression profile for this purpose.  Four institutions processed 547 frozen specimens representing 15 tissues of origin using oligonucleotide microarrays were used in this study.  Half of the specimens were metastatic tumors, with the remainder being poorly differentiated and undifferentiated primary cancers chosen to resemble those that present as a clinical challenge.  In this blinded multi-center validation study the 1,550-gene expression profile was highly informative in tissue determination.  The study found overall sensitivity (positive percent agreement with reference diagnosis) of 87.8 % (95 % CI: 84.7 % to 90.4 %) and overall specificity (negative percent agreement with reference diagnosis) of 99.4 % (95 % CI: 98.3 % to 99.9 %).  Performance within the subgroup of metastatic tumors (n = 258) was found to be slightly lower than that of the poorly differentiated and undifferentiated primary tumor subgroup, 84.5 % and 90.7 %, respectively (p = 0.04).  Differences between individual laboratories were not statistically significant.  The authors concluded that this study represents the first adequately sized, multi-center validation of a gene-expression profile for tissue of origin determination restricted to poorly differentiated and undifferentiated primary cancers and metastatic tumors.  These results indicate that this profile should be a valuable addition or alternative to currently available diagnostic methods for the evaluation of uncertain primary cancers.

Monzon and Koen (2010) stated that tumors of uncertain or unknown origin are estimated to constitute 3 % to 5 % of all metastatic cancer cases.  Patients with these types of tumors show worse outcomes when compared to patients in which a primary tumor is identified.  New molecular tests that identify molecular signatures of a tissue of origin have become available.  The authors reviewed the literature on existing molecular approaches to the diagnosis of metastatic tumors of uncertain origin and discuss the current status and future developments in this area.  Published peer-reviewed literature, available information from medical organizations (NCCN), and other publicly available information from tissue-of-origin test providers and/or manufacturers were used in this review.  The authors concluded that molecular tests for tissue-of-origin determination in metastatic tumors are available and have the potential to significantly impact patient management.  However, available validation data indicate that not all tests have shown adequate performance characteristics for clinical use.  Pathologists and oncologists should carefully evaluate claims for accuracy and clinical utility for tissue-of-origin tests before using test results in patient management.  The personalized medicine revolution includes the use of molecular tools for identification/confirmation of the site of origin for metastatic tumors, and in the future, this strategy might also be used to determine specific therapeutic approaches.

Anderson and Weiss (2010) noted that pathologists use various panels of IHC stains to identify the site of tissue of origin for metastatic tumors, particularly poorly or undifferentiated cancers of unknown or uncertain origin.  Although clinicians believe that immunostains contribute greatly to determining the probable primary site among 3 or more possibilities, objective evidence has not been convincingly presented.  This meta-analysis reviews the objective evidence supporting this practice and summarizes the performance reported in 5 studies published between 1993 and 2007.  A literature search was conducted to identify IHC performance studies published since 1990 that were masked, included more than 3 tissues types, and used more than 50 specimens.  The 5 studies found in this search were separated into 2 subgroups for analysis: those, which included only metastatic tumors (n = 368 specimens) and the blended studies, which combined primary tumors and metastases (n = 289 specimens).  The meta-analysis found that IHCs provided the correct tissue identification for 82.3 % (95 % CI: 77.4 % to 86.3 %) of the blended primary and metastatic samples and 65.6 % (95 % CI: 60.1 % to 70.7 %) of metastatic cancers.  This difference is both clinically and statistically significant.  The authors concluded that this literature review confirms that there is still an unmet medical need in identification of the primary site of metastatic tumors.  It establishes minimum performance requirements for any new diagnostic test intended to aid the pathologist and oncologist in tissue of origin determination.

GeneSearch BLN

The presence of breast tumor cells in axillary lymph nodes is a key prognostic indicator in breast cancer.  During surgery to remove breast tumors, patients often undergo biopsy of the sentinel (i.e., first) node(s) that receive lymphatic fluid from the breast.  Excised sentinel lymph nodes are currently evaluated post-operatively by formalin-fixed paraffin-embedded Hematoxylin and Eosin (H&E) histology and IHC.  GeneSearch™ Breast Lymph Node (BLN) assay (Veridex, LLC, Warren, NJ) is a novel method to examine the extracted sentinel lymph nodes for metastases and can provide information during surgery within 30 to 40 minutes from the time the sentinel node is removed, potentially avoiding a second operation for some patients.  The GeneSearch BLN assay received FDA pre-market approval on July 16, 2007 as a qualitative in vitro diagnostic test for the rapid detection of metastases larger than 0.2 mm in nodal tissue removed from sentinel lymph node biopsies of breast cancer patients.  GeneSearch BLN assay uses real time reverse transcriptase polymerase chain reaction (RT-PCR) to detect the gene expression markers, mammaglobin (MG) and cytokeratin 10 (CI19), which are abundant in breast tissue but scarce in lymph node cells.  In the clinical trial conducted by Veridex, which was submitted to the FDA, the sensitivity of the GeneSearch BLN Assay was reported to be 87.6 % and the specificity was 94.2 % (Julian et al, 2008).  According to the product labeling,"The GeneSearch™ Breast Lymph Node (BLN) assay may be used in conjunction with sentinel lymph node biopsy for a patient who has been counseled on use of this test and has been informed of its performance.  False positive results may be associated with increased morbidity.  False negative and inconclusive test results may be associated with delayed axillary node dissection.  Clinical studies so far are inconclusive about a benefit from treatment based on findings of breast cancer micro-metastases in sentinel lymph nodes."

Blumencranz et al (2007) compared the GeneSearch BLN assay with results from conventional histologic evaluation from 416 patients at 11 clinical sites and reported that the GeneSearch BLN assay detected 98 % of metastases greater than 2 mm in size and 57 % of metastasis less than 0.2 mm.  False positives were reported in 4 % of the cases.  However, there were several limitations of this study, including the lack of a description of patient recruitment, inadequate descriptions of several analyses performed, substantial variations in test performance across sites, and ad hoc comparison of the assay to other intra-operative techniques.

Viale et al (2008) analyzed 293 lymph nodes from 293 patients utilizing the GeneSearch BLN assay.  Using histopathology as the reference standard, the authors reported that the BLN assay correctly identified 51 of 52 macro-metastatic and 5 of 20 micro-metastatic sentinel lymph nodes (SLNs), with a sensitivity of 98.1 % to detect metastases larger than 2 mm, 94.7 % for metastases larger than 1 mm, and 77.8 % for metastases larger than 0.2 mm.  The overall concordance with histopathology was 90.8 %, with a specificity of 95.0 %, a positive predictive value of 83.6 %, and a negative predictive value of 92.9 %.  When the results were evaluated according to the occurrence of additional metastases to non-SLN in patients with histologically positive SLNs, the assay was positive in 33 (91.7 %) of the 36 patients with additional metastases and in 22 (66.6 %) of the 33 patients without further echelon involvement.  The authors concluded that the sensitivity of the GeneSearch BLN assay is comparable to that of the histopathologic examination of the entire SLN by serial sectioning at 1.5 to 2 mm.

Although treatment for metastases larger than 2.0 mm is widely accepted as beneficial, clinical studies have not yet provided data for a consensus on benefit from treatment based on very small breast cancer metastases (between 0.2 mm and 2.0 mm) in SLNs.  False positive results may be associated with increased morbidity, usually due to effects of axillary node dissection surgery.  Patients who undergo axillary lymph node dissection (ALND) have significantly higher rates of increased swelling in the upper arm and forearm (lymphedema), pain, numbness, and motion restriction about the shoulder when compared with patients who undergo only sentinel lymph node dissection (SLND).  False negative and inconclusive test results may be associated with delayed axillary node dissection.  Clinical studies so far are inconclusive regarding a benefit from treatment based on findings of breast cancer micro-metastases in SLNs.  Preliminary data suggest that the GeneSearch BLN assay has high specificity and moderate sensitivity when only macro-metastases are included in the analysis.  The clinical significance of micro-metastases is still being debated in the literature, thus, the failure of the GeneSearch BLN assay to perform adequately in the detection of micro-metastases is of unknown significance.

A systematic evidence review by the BlueCross BlueShield Association Technology Evaluation Center (BCBSA, 2007) determined that the use of the GeneSearch BLN assay to detect sentinel node metastases in early stage breast cancer does not meet the TEC criteria.  The assessment stated, "There are several operational issues that add difficulty to the use of the GeneSearch assay, including the need for fresh specimens (rather than putting them in formalin for permanent fixation), the learning curve involved in reducing both the percentage of invalid results (from about 15% initially to 4 - 8% for more experienced technicians) and the time to perform the test compared to alternative intra-operative techniques (which take less than 15 minutes)."  Furthermore, the assessment stated "The GeneSearch assay also provides less information for staging than other intra-operative procedures, since it cannot distinguish between micro- and macro-metases.  Nor can it indicate the location of the metastasis (inside or outside the node).  Post-operative histology is therefore required in all cases.  It is less crucial when frozen section histology is performed, since pathologists can judge the size of the metastasis and its location from this test, although distortion is possible.  To summarize, the data available is inadequate to assess the clinical utility of the GeneSearch assay compared to either post-operative histology alone or to the alternative intra-operative tests such as imprint cytology and frozen section histology.  In addition, the balance of benefits versus harms may require higher specificity to avoid unnecessary ALNDs and their sequelae, whereas the GeneSearch design emphasizes sensitivity."

A report by Adelaide Health Technology Assessment stated that, if the GeneSearch BLN Assay is to play a role in reducing the mortality of breast cancer patients, it will be through more accurate diagnosis of breast cancer metastasis during SNB (Ellery, et al., 2010). The report noted, however, that, as yet there are no data to indicate whether SNB itself lowers the mortality rate among breast cancer patients. Hence, it is unclear whether the GeneSearch BLN Assay would have any indirect effect on breast cancer mortality until further investigation into SNB concludes.

Thus, there is insufficient evidence to make a conclusion about the effectiveness of the GeneSearch BLN assay.  The FDA is requiring the manufacturer to conduct two post-approval studies.  The primary objective of the first study is to estimate the positive predictive concordance between the GeneSearch BLN assay and histology as routinely practiced and the objectives of the second clinical study are (i) determine the assay turn-around-time from the time of node removal to the report of the assay result to the surgeon and (ii) determine whether the assay result was or was not received in time to make an intra-operative decision and (iii) collect data in relation to other surgical procedures during the sentinel lymph node dissection/breast surgery to determine if the assay turn-around-time resulted in longer surgery time.

BT Test

Provista Life Sciences (Phoenix, AZ) has developed a laboratory test called the Biomarker Translation Test, or the BT Test, which is a test score based on a multi-protein biomarker analysis (i.e., IL-2, -6,-8,-12, TNFa, EGF, FGF, HGF, VEGF) and medical profile of an individual's risk factors for breast cancer.  It is intended to be used as an adjunctive test along with other breast cancer detection modalities, however, there are no published studies of the effectiveness of this test.

Bcl-2

Bcl-2 (B-cell CLL/lymphoma 2; BCL2) is a proto-oncogene whose protein product, bcl-2, suppresses programmed cell death (apoptosis), resulting in prolonged cellular survival without increasing cellular proliferation.  Dysregulation of programmed cell death mechanisms plays a role in the pathogenesis and progression of cancer as well as in the responses of tumors to therapeutic interventions.  Many members of the Bcl-2 family of apoptosis-related genes have been found to be differentially expressed in various malignancies (Reed, 1997).

Salgia (2008) reviewed the evidence for detection of Bcl-2 in lung cancer.  The author observed that Bcl-2 over-expression has been reported in 22 to 56% of lung cancers with a higher expression in squamous cell carcinoma as compared to adenocarcinoma histology.  The author concluded, however, that the association of Bcl-2 expression and prognosis in non-small cell lung cancer is unclear.  Multiple reports have demonstrated that Bcl-2-positive lung cancers are associated with a superior prognosis compared to those that are Bcl-2 negative.  However, other studies have failed to demonstrate any survival impact with bcl-2 positivity, while over-expression has also been associated with a poorer outcome.  A meta-analysis that included 28 studies examining the prognostic influence of Bcl-2 in non-small cell lung cancer concluded that over-expression of Bcl-2 was associated with a significantly better prognosis in surgically resected (hazard ratio 0.5, 95% CI 0.39-0.65).

Compton (2008) recently reviewed the evidence on the Bcl-2 oncogene and other tumor markers in colon cancer.  Compton explained that Bcl-2 is a gene related to aptosis/cell suicide.  Bcl-2 over-expression leading to inhibition of cell death signaling has been observed as a relatively early event in colorectal cancer development.  The author concluded that the independent influence of the Bcl-2 oncogene on prognosis remains unproven, and explained that the variability in assay methodology, conflicting results from various studies examining the same factor, and the prevalence of multiple small studies that lack statistically robust, multivariate analyses all contribute to the lack of conclusive data.  Compton concluded that before the Bcl-2 oncogene and certain other tumor markers can be incorporated into clinically meaningful prognostic stratification systems,"more studies are required using multivariate analysis, well-characterized patient populations, reproducible and current methodology, and standardized reagents."

CD31

Compton (2008) reviewed the evidence for intratumor microvessel density (MVD) and antibodies against CD31 in colorectal cancer.  The author explained that intratumoral MVD is a reflection of tumor-induced angiogenesis.  Microvessel density has been independently associated with shorter survival in some, but not all studies.  A meta-analysis of all studies relating MVD expression to prognosis concluded that at least some of the variability could be explained by the different methods of MVD assessment.  The author noted that there was a significant inverse correlation between immunohistochemical expression and survival when MVD was assessed using antibodies against CD31 or CD34, but not factor VIII.  The author concluded, however, that there is a need for evaluation of MVD in large studies of prognostic factors using multivariate analysis; however, standard guidelines for staining, evaluation, and interpretation of MVD are lacking.

In a review, Hayes (2008) reviewed the evidence for assessing angiogenesis factors in breast cancer.  The author noted that, in an early report, MVD count (as indicated by IHC staining for endothelial cells, such as factor VIII-related antigen or CD31) was a statistically significant independent predictor of both disease-free and overall survival in women with both node-negative and node-positive breast cancer.  The author noted, however, that subsequent data are conflicting, with some studies confirming and others refuting the initial findings.  The author stated that, "As with many of the other tumor marker studies, evaluation of angiogenesis is complicated by technical variation, reader inconsistency, and potential interaction with therapy."

Burgdorf (2006) reviewed the use of CD31 in acquired progressive lymphangioma.  The author stated that special staining techniques reveal that the cells are variably positive for CD31, but that the staining patterns are too variable to be of diagnostic importance.

Some authorities have stated that CD31 staining may be useful for diagnosing angiosarcomas (Schwartz, 2008; Carsi and Sim, 2008; Fernandez and Schwartz, 2007; McMains and Gourin, 2007).  CD31 immunostaining can help confirm that the tumor originates from blood vessels.

TOP2A

The topoisomerase II alpha gene (TOP2A) is located adjacent to the HER-2 oncogene at the chromosome location 17q12-q21 and is either amplified or deleted (with equal frequency) in a great majority of HER-2 amplified primary breast tumors and also in tumors without HER-2 amplification.  Recent experimental as well as numerous, large, multi-center trials suggest that amplification (and/or deletion) of TOP2A may account for both sensitivity or resistance to commonly used cytotoxic drugs (e.g., anthracyclines) depending on the specific genetic defect at the TOP2A locus.  An analysis of TOP2A aberrations in the Danish Breast Cancer Cooperative Group trial 89D (Nielsen, et al., 2008) suggested a differential benefit of adjuvant chemotherapy in patients with primary breast cancer, favoring treatment with epirubicin in patients with TOP2A amplifications, and perhaps deletions; however, the authors concluded that, "Additional studies are needed to clarify the exact importance of TOP2A deletions on outcome, but deletions have proven to be associated with a very poor prognosis."

The National Comprehensive Cancer Network (NCCN, 2008) guideline on breast cancer does not address the use of TOP2A testing.

TSP-1

Ghoneim et al (2008) explained that thrombospondin-1 (TSP-1) is a member of a family of five structurally related extracellular glycoproteins that plays a major role in cell-matrix and cell to cell interactions.  Due to its multifunctional nature and its ability to bind to a variety of cell surface receptors and matrix proteins, TSP-1 has been identified as a potential regulator of angiogenesis and tumor progression.  Data collected by Secord, et al. (2007) suggested that high THBS-1 levels may be an independent predictor of worse progression-free and overall survival in women with advanced-stage epithelial ovarian cancer.  However, a phase II clinical trail (Garcia, et al., 2008) of bevacizumab and low-dose metronomic oral cyclophosphamide in recurrent ovarian cancer reported that levels of TSP-1 were not associated with clinical outcome.

mdr1

In a review on multidrug resistance in acute leukemia, List and Spier (1992) explained that the mdr1 gene or its glycoprotein product, P-glycoprotein, is detected with high frequency in secondary acute myeloid leukemia (AML) and poor-risk subsets of acute lymphoblastic leukemia.  Investigations of mdr1 regulation in normal hematopoietic elements have shown a pattern that corresponds to its regulation in acute leukemia, explaining the linkage of mdr1 to specific cellular phenotypes.  Therapeutic trials are now in progress to test the ability of various MDR-reversal agents to restore chemotherapy sensitivity in high-risk acute leukemias.

In a phase III multi-center randomized study to determine whether quinine would improve the survival of adult patients with de novo AML, Soary et al (2003) reported that neither mdr1 gene or P-glycoprotein expression influenced clinical outcome.

A phase I/II study of the MDR modulator Valspodar (PSC 833, Novartis Pharma) combined with daunorubicin and cytarabine in patients with relapsed and primary refractory acute myeloid leukemia (Gruber et al, 2003) reported that P-glycoprotein did not give an obvious improvement to the treatment results.

MRP-1

Motility-related protein (MRP-1) is a glycoprotein with a sequence identical to that of CD9, a white blood cell differentiation antigen.  The level of MRP-1/CD9 expression has been found in investigational studies to inhibit cell motility and low MRP-1/CD9 expression may be associated with the metastatic potential of breast cancer (Miyake et al, 1995).  CD9 immuno-expression is also being investigated as a potential new predictor of tumor behavior in patients with squamous cell carcinoma of the head and neck (Mhawech et al, 2004) as well as other tumors (e.g., urothelial bladder carcinoma, colon cancer, lung cancer); however, prospective studies are needed to determine the clinical role of MRP-1/CD9 expression in tumors.

PLAP

The National Comprehensive Cancer Network's guideline on occult primary tumors includes placental alkaline phosphatase (PLAP) as a useful marker to assist in identifying germ cell seminoma and non-seminoma germ cell tumors in unknown primary cancer (NCCN, 2009).

MPO

Myeloperoxidase (MPO), a blood protein, is a major component of azurophilic granules of neutrophils.  Myeloperoxidase analysis has been used to distinguish between the immature cells in acute myeloblastic leukemia (cells stain positive) and those in acute lymphoblastic leukemia (cells stain negative).  The National Comprehensive Cancer Network guidelines on acute myeloid leukemia (AML) include MPO analysis in the classification of AML (NCCN, 2008).

Matsuo et al (2003) examined the prognostic factor of the percentage of MPO-positive blast cells for AML.  Cytochemical analysis of MPO was performed in 491 patients who were registered to the Japan Adult Leukemia Study Group (AML92 study).  Patients were divided into two groups using the percentage of MPO-positive blast (high [ > or = 50%] and low [< 50%]).  Complete remission rates were 85.4% in the former and 64.1% in the latter (p = 0.001).  The OS and the disease-free survival (DFS) were significantly better in the high MPO group (48.3 versus 18.7% for OS, and 36.3 versus 20.1% for DFS, p < 0.001, respectively).  Multi-variate analysis showed that both karyotype and the percentage of MPO-positive blast cells were equally important prognostic factors.  The high MPO group still showed a better survival even when restricted to the intermediate chromosomal risk group or the patients with normal karyotype (p < 0.001).  The OS of patients with normal karyotype in the high MPO group was almost equal to that of the favorable chromosomal risk group.  The authors concluded that the percentage of MPO-positive blast cells is a simple and highly significant prognostic factor for AML patients, and especially useful to stratify patients with normal karyotype. 

DCP

The most commonly used marker for hepatocellular carcinoma (HCC) is the AFP level.  Des-gamma-carboxy prothrombin (DCP) (also known as "prothrombin produced by vitamin K absence or antagonism II" [PIVKA II]) has also shown promise in the diagnosis of HCC (Toyoda et al, 2006; Ikoma et al, 2002; Nomura et al, 1996; Liebman et al, 1984).  In one series of 76 patients with HCC, this marker was elevated in 69 patients with a mean serum concentration of 900 mcg/L.  Much lower mean values were seen in patients with chronic active hepatitis, metastatic disease to the liver, and normal subjects (10 and 42 mcg/L and undetectable, respectively) (Liebman et al, 1984).  Elevations in serum levels of DCP are less frequent in tumors less than 3 cm in size (Nakamura et al, 2006; Weitz and Liebman, 1993;).  Aoyagi et al (1996) as well as Weitz and Liebman (1993) reported that abnormal prothrombin levels do not correlate well with serum AFP.

Toyoda at al (2006) measured AFP, lens culinaris agglutinin A-reactive fraction of AFP (AFP-L3), and DCP for the evaluation of tumor progression and prognosis of patients with HCC (n = 685) at the time of initial diagnosis.  Positivity for AFP > 20 ng/dL, AFP-L3 > 10% of total AFP, and/or DCP > 40 mAU/mL was determined.  In addition, tumor markers were measured after treatment of HCC.  Of the 685 patients, 337 (55.8%) were positive for AFP, 206 (34.1%) were positive for AFP-L3, and 371 (54.2%) were positive for DCP.  In a comparison of patients positive for only 1 tumor marker, patients positive for AFP-L3 alone had a greater number of tumors, whereas patients positive for DCP alone had larger tumors and a higher prevalence of portal vein invasion.  When patients were compared according to the number of tumor markers present, the number of markers present clearly reflected the extent of HCC and patient outcomes.  The number of markers present significantly decreased after treatment.  The authors concluded that tumor markers AFP-L3 and DCP appeared to represent different features of tumor progression in patients with HCC and that the number of tumor markers present could be useful for the evaluation of tumor progression, prediction of patient outcome, and treatment efficacy.

The National Comprehensive Cancer Network's guideline on HCC (NCCN, 2008) does not include measurement of DCP among the surveillance test options for HCC.  According to NCCN guidelines, proposed surveillance for the early detection of HCC among high-risk populations (e.g., chronic hepatitis C virus-infected patients) includes liver ultrasonography every 3 to 6 months and evaluation of alkaline phosphatase, albumin, and AFP.  The guidelines stated, "It is not yet clear if early detection of hepatocellular cancer with routine screening improves the percentage of patients detected with disease at a potentially curative stage, but high-risk chronic hepatitis C virus - infected patients should be considered for ongoing recurrent screening until these issues have been resolved.  The level of des-gamma-carboxy-prothrombin protein induced by vitamin K absence (PIVKA-II) is also increased in many patients with hepatocellular carcinoma.  However, as is true with AFP, PIVKA-II may be elevated in patients with chronic hepatitis."  Furthermore, according to Sherman (2008), DCP has not been adequately studied as a screening test for HCC and cannot be recommended at this time.

NMP66

Researchers at Matritech (Newton, MA) have detected the presence of nuclear matrix protein (NMP) in the blood of women at the early stage of breast cancer, which is absent in the blood of healthy women, as well as those with fibroadenoma.  NMP66 has been selected as a marker for further development and clinical trials of a test for use in the detection and monitoring of women with, or at risk for, breast cancer have been initiated (Wright and McGechan, 2003).  However, there are no published studies on the effectiveness of NMP66 testing at this time.

HERmark

HERmark Breast Cancer Assay ( biosciences monogram) is used to help determine prognosis and therapeutic choices for metastatic breast cancer (Raman, et al., 2013). Clinical practice guidelines recommend determining HER2 status in patients with all invasive breast cancer, but caution that current HER2 testing methods such as central immunohistochemistry and Fluorescence in situ Hybridization test may be inaccurate in approximately 20% of cases. According to the HERmark Web site, their method precisely quantifies HER2 total protein and HER2 homodimer levels in formalin-fixed, paraffin-embedded tissue sections and outperformed Fluorescence in situ Hybridization at determining patient outcomes in patients with metastatic breast cancer.

HERmark testing has been proposed for a number of indications, including use to predict response to trastuzumab in the treatment of metastatic breast cancer.  Monogram, the manufacturer of the HERmark test, claims that the test can provide a more precise and quantitative measurement of the HER2 gene than IHC and fluorescent in-situ hybridization (FISH) tests. The HERmark provides a quantitative measurement of HER2 total protein and HER2 homodimer levels, while conventional methods are an indirect measure of the HER2 gene, the manufacturer claims. The HERmark test will be offered as a CLIA-validated assay through Monogram's CAP-certified clinical laboratory.  Other proposed indications for HERmark include determining the prognosis for breast cancer, and predicting treatment results in cancers other than breast cancer (e.g., ovarian prostate, head and neck, etc.).  There are no current recommendations from leading medical professional organizations for the use of HERmark testing for breast cancer.

MDM2

Noon et al (2010) stated that renal cell carcinoma (RCC) is the most common type of kidney cancer and follows an unpredictable disease course.  These researchers reviewed 2 critical genes associated with disease progression -- p53 and murine double minute 2 (MDM2) -- and provided a comprehensive summary and critical analysis of the literature regarding these genes in RCC.  Information was compiled by searching the PubMed database for articles that were published or e-published up to April 1, 2009. Search terms included renal cancer, renal cell carcinoma, p53, and MDM2.  Full articles and any supplementary data were examined; and, when appropriate, references were checked for additional material.  All studies that described assessment of p53 and/or MDM2 in renal cancer were included.  The authors concluded that increased p53 expression, but not p53 mutation, is associated with reduced overall survival/more rapid disease progression in RCC.  There also was evidence that MDM2 up-regulation is associated with decreased disease-specific survival.  Two features of RCC stood out as unusual and will require further investigation: (i)increased p53 expression is tightly linked with increased MDM2 expression; and (ii) patients who have tumors that display increased p53 and MDM2 expression may have the poorest overall survival.  Because there was no evidence to support the conclusion that p53 mutation is associated with poorer survival, it seemed clear that increased p53 expression in RCC occurs independent of mutation.  The authors stated that further investigation of the mechanisms leading to increased p53/MDM2 expression in RCC may lead to improved prognostication and to the identification of novel therapeutic interventions.

OVA1

The OVA1 Test (Vermillion Inc. and Quest Diagnostics) is a serum test that is intended to help physicians determine if a woman is at risk for a malignant pelvic mass prior to biopsy or exploratory surgery, when the physician’s independent clinical and radiological evaluation does not indicate malignancy (Mundy, et al., 2010). The OVA1 Test employs an in vitro diagnostic multivariate index (IVDMIA) that combines the results of five immunoassays to produce a numerical score indicating a women's likelihood of malignancy. The OVA1 Test is intended to help physicians assess if a pelvic mass is benign or malignant in order to help determine whether to refer a woman to a gynecologic oncologist for surgery. The OVA1 Test was cleared by the FDA for use in women who meet the following criteria: over age 18, ovarian adnexal mass present for which surgery is planned, and not yet referred to an oncologist. The intended use of the OVA1 Test is an aid to further assess the likelihood that malignancy is present when the physician’s independent clinical and radiological evaluation does not indicate malignancy. According to the product labeling, the OVA1 Test is not intended as a screening or stand-alone diagnostic assay. There is a lack of evidence in the peer-reviewed published medical literature on the OVA1 Test.

In an editorial on the OVA1 Test, Muller (2010) stated that the role of OVA1 in a generalized practice setting and cost-benefit ratio has yet to be determined. Furthermore, the ACOG Committee Opinion on the role of the obstetrician-gynecologist in the early detection of epithelial ovarian cancer (2011) noted that the clinical utility of the OVA1 Test "is not yet established".

The National Horizon Scanning Centre (2012) stated that more studies are needed to show whether using this test routinely would really benefit women.

An assessment by the BlueCross BlueShield Association Technology Evaluation Center (BCBSA, 2013) stated: "The evidence regarding the effect of OVA1 ...on health outcomes is indirect and based on studies of diagnostic performance of the tests in patients undergoing surgery for adnexal masses. Although the studies show improvements in sensitivity and worsening of specificity with the use of the tests in conjunction with clinical assessment, there are problems in concluding that this results in improved health outcomes. The clinical assessment performed in the studies is not well characterized. Although OVA1 improves sensitivity, specificity declines so much that most patients test positive."

The National Institute for Health and Care Excellence is developing a Medtech Briefing on Ova1.

ColonSentry

The ColonSentry test (GeneNews, Toronto, Canada) measures the expression of seven genes, which serve as biomarkers to detect colorectal cancer. Interpretation of the status of these seven biomarkers is intended to assist physicians in identifying patients who have an increased current risk. According to the manufacturer, individuals assessed as having an increased current risk of colorectal cancer should consider having a colonoscopy.  Individuals assessed as having a decreased current risk of colorectal cancer should discuss with their doctor further screening, including repeating ColonSentry at regular intervals. There is a lack of evidence in the peer-reviewed published medical literature on the effectiveness of colorectal cancer screening with ColonSentry. No current evidence-based guidelines from medical professional organizations or public health agencies recommend ColonSentry for colorectal cancer screening.

Prostate Px

Prostate Px (Aureon) uses a prostate cancer patient's biopsy tissue to provide an assessment of disease severity and disease recurrence. Clinical data is integrated with an analysis of each patient’s cancer using tissue histology and molecular biomarkers, such as androgen receptor, associated with disease progression. Although the manufacturer states that the results of the Prostate Px can be used in decision-making, there is a lack of evidence of the clinical utility of this test in altering the management of patients such that clinical outcomes are improved.

Post-Op Px

Post-Op Px is a prognostic test that utilizes a patented systems pathology approach to analyze prostatectomy tissue by combining cellular, molecular and clinical information to provide a thorough and more accurate picture of each patient's individual risk of prostate cancer recurrence. (Aureon, 2010).   Donovan et al  (2011) evaluated the performance of a systems-based risk assessment tool with standard defined risk groups and the 10 year postoperative normogram for predicting disease progression. The systems model was found to be more accurate than standard risk groups both to predict significant disease progression (p <  0.001) and for predicting prostate-specific antigen recurrence (p < 0.001).  However, this study has not been replicated in the peer-reviewed literature.

EGFR

An assessment by the BlueCross BlueShield Association Technology Evaluation Center (2010) concluded that tumor-cell epidermal growth factor receptor (EGFR) mutation analysis to predict response to erlotinib (Tarceva) in patients with advanced non-small cell lung cancer (NSCLC) meets the Blue Cross and Blue Shield Association Technology Evaluation Center (TEC) criteria.  Furthermore, guidelines from the National Comprehensive Cancer Network (NCCN, 2010) recommend EGFR testing for the following histologic subtypes of NSCLC: (i) adenocarcinoma, (ii) large cell, and (iii) NSCLC not otherwise specified.  Epidermal growth factor receptor testing is not recommended for squamous cell carcinoma.

The Alberta Provincial Thoracic Tumour Team’s clinical practice guideline on “Non-small cell lung cancer stage IV” (2011) stated that “First-line monotherapy with the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib is recommended for patients with EGFR mutation-positive NSCLC.  Testing for EGFR mutations should take place for all eligible patients with advanced NSCLC and adenocarcinoma histology who are being considered for first-line therapy with gefitinib, irrespective of their gender, ethnicity, and smoking status”.

NCCN non-small cell lung cancer guidelines (2015) state that EGFR and ALK testing should be conducted as part of a multiplex/next generation sequencing. The NCCN NSCLC Guidelines Panel "strongly endorses broader molecular profiling with the goal of identifying rare mutations for which effective drugs may already be available, or to appropriately counsel patients regarding the availability of clinical trials. Broad molecular profiling is a key component of the improvement of care of patients with NSCLC.”

Gao et al (2012) stated that gefiinib and erlotinib are 2 similar small molecules of selective and reversible epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs), which have been approved for second-line or third-line indication in previously treated advanced NSCLC patients.  The results of comparing the EGFR-TKI with standard platinum-based doublet chemotherapy as the first-line treatment in advanced NSCLC patients with activated EGFR mutation were still controversial.  A meta-analysis was performed to derive a more precise estimation of these regimens.  Finally, 6 eligible trials involved 1,021 patients were identified.  The patients receiving EGFR-TKI as front-line therapy had a significantly longer PFS than patients treated with chemotherapy [median PFS was 9.5 versus 5.9 months; HR = 0.37; 95 % CI: 0.27 to 0.52; p < 0.001].  The overall response rate (ORR) of EGFR-TKI was 66.60 %, whereas the ORR of chemotherapy regimen was 30.62 %, which was also a statistically significant favor for EGFR-TKI [relative risk (RR) = 5.68; 95 % CI: 3.17 to 10.18; p < 0.001].  The OS was numerically longer in the patients received EGFR-TKI than patients treated by chemotherapy, although the difference did not reach a statistical significance (median OS was 30.5 versus 23.6 months; HR = 0.94; 95 % CI: 0.77 to 1.15; p = 0.57).  Comparing with first-line chemotherapy, treatment of EGFR-TKI achieved a statistical significantly longer PFS, higher ORR and numerically longer OS in the advanced NSCLC patients harboring activated EGFR mutations, thus, it should be the first choice in the previously untreated NSCLC patients with activated EGFR mutation.

CEACAM-7

Messick et al (2010) evaluated carcinoembryonic antigen cellular adhesion molecule-7 (CEACAM-7) expression in rectal cancer as a predictive recurrence factor.  A single-institution colorectal cancer database and a frozen tissue biobank were queried for rectal cancer patients.  CEACAM-7 messenger RNA (mRNA) expression from normal rectal mucosa and rectal cancers was analyzed using quantitative real-time polymerase chain reaction (PCR).  Expression-level differences among normal tissue, disease-free survivors, and those that developed recurrence were analyzed.  A total of 84 patients were included in the study, which consisted of 37 patients with non-recurrent disease (median follow-up of 170 months), 29 patients with recurrent disease, and 18 patients with stage IV disease.  CEACAM-7 expression was decreased 21-fold in rectal cancers compared with normal mucosa (p = 0.002).  The expression levels of CEACAM-7 were relatively decreased in tumors that developed recurrence compared with non-recurrence, significantly for stage II patients (14-fold relative decrease, p = 0.002).  For stages I-III, disease-free survival segregates were based on relative CEACAM-7 expression values (p = 0.036), specifically for stage II (p = 0.018).  The authors concluded that CEACAM-7 expression is significantly decreased in rectal cancer.  Expression differences between long-term survivors and those with recurrent disease introduce a potential tumor marker to define a subset of patients who benefit most from adjuvant therapy.  Moreover, they stated that additional study and validation are needed before CEACAM-7 can be applied in clinical settings.

CFL1

Castro et al (2010) assessed the potential value of cofilin (CFL1) gene (main member of the invasion/metastasis pathway) as a prognostic and predictive NSCLC biomarker.  Meta-analysis of tumor tissue microarray was applied to examine expression of CFL1 in archival lung cancer samples from 111 patients, and its clinicopathologic significance was investigated.  The robustness of the finding was validated using another independent data set.  Finally, the authors assayed in vitro the role of CFL1 levels in tumor invasiveness and drug resistance using 6 human NSCLC cell lines with different basal degrees of CFL1 gene expression.  Cofilin levels in biopsies discriminated between good and bad prognosis at early tumor stages (IA, IB, and IIA/B), where high CFL1 levels are correlated with lower overall survival rate (p < 0.0001).  Biomarker performance was further analyzed by IHC, hazard ratio (p < 0.001), and receiver-operating characteristic curve (area = 0.787; p < 0.001).  High CFL1 mRNA levels and protein content are positively correlated with cellular invasiveness (determined by Matrigel Invasion Chamber System) and resistance (2-fold increase in drug 50 % growth inhibition dose) against a list of 22 alkylating agents.  Hierarchical clustering analysis of the CFL1 gene network had the same robustness for stratified NSCLC patients.  The authors concluded that these findings indicated that the CFL1 gene and its functional gene network can be used as prognostic biomarkers for NSCLC and could also guide chemotherapeutic interventions.  Moreover, prospective, large-scale, randomized clinical trials are needed to establish the role of CFL1 as a prognostic and drug resistance marker for NSCLC.

EarlyCDT-Lung

The EarlyCDT-Lung (Oncimmune, De Soto, KS) test measures antibodies to 6 tumor-associated antigens: p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1, and SOX2.  Elevation of any one of the panel of immuno-biomarkers above a predetermined cut-off value suggests that a tumor might be present.  The test is designed to be used in conjunction with diagnostic imaging.  High-risk individuals with a positive EarlyCDT-Lung would have additional testing such as a CT scan or the test would be used as a follow-up test for indeterminate lung nodules identified by CT.

Boyle et al (2011) reported the sensitivity and specificity of an autoantibody panel of 6 tumor-related antigens (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) in patients with lung cancer.  Three cohorts of patients with newly diagnosed lung cancer were identified: group 1 (n = 145), group 2 (n = 241) and group 3 (n = 269).  Patients were individually matched by gender, age and smoking history to a control individual with no history of malignant disease.  Serum samples were obtained after diagnosis but before any anticancer treatment.  Autoantibody levels were measured against the panel of 6 tumor-related antigens (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2).  Assay sensitivity was tested in relation to demographic variables and cancer type/stage.  The autoantibody panel demonstrated a sensitivity/specificity of 36 %/91 %, 39 %/89 % and 37 %/90 % in groups 1, 2 and 3, respectively, with good reproducibility.  There was no significant difference between different lung cancer stages, indicating that the antigens included covered the different types of lung cancer well.   The authors concluded that the assay confirms the value of an autoantibody panel as a diagnostic tool and offers a potential system for monitoring patients at high-risk of lung cancer.

There is insufficient evidence of the effectiveness of the EarlyCDT-Lung as a screening test for the early detection of lung cancer.  Systematic screening for lung cancer is not unequivocally recommended by any major professional organization.  The USPSTF (2004) concluded that current evidence was insufficient to recommend for, or against, screening for lung cancer.  Whether earlier detection of lung cancer will translate to a mortality benefit remains unclear.

E-cad

Deeb et al (2004) stated that E-cadherin (E-cad) and epidermal growth factor receptor (EGFR) are important cell adhesion and signaling pathway mediators. Theyr reported the results of a study which aimed to assess their expression in lung adenocarcinoma (AdC) and squamous cell carcinoma (SCC) and their association with clinicopathologic variables.  Two to three cores from 130 resectable lung cancers (stages I-IIIA) were arrayed into three blocks using a Beecher system. Markers expression and coexpression were analyzed against clinicopathologic variables (age, gender, smoking status, performance status, weight loss, histology, grade, stage, and lymph node involvement) and patient survival. For E-cad, 65 cases (55%) were positive (+), 53 (45%) were negative (-); and for EGRF, 43 cases (34%) were (+), and 83 (66%) were (-). There was no significant association between E-cad or EGFR, and any of the clinicopathologic variables except for an association between EGFR(+) and SCC histologic type. Both negative and cytoplasmic staining of E-cad correlated with shorter patient survival with P=0.008 and 0.002, respectively. EGFR expression did not correlate with patient survival, but, patients with E-cad(-)/EGFR(+) phenotype had poorer survival than those with E-cad(+)/EGFR(-) (P=0.026). The authors concluded that lung AdC and SCC may be stratified based on expression of E-cad and EGFR with the E-cad(-)/EGFR(+) expression having a worse disease outcome.

EML4-ALK

Yoshida et al (2011) report that a subset of lung cancers harbors an EML4-ALK (echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase) gene fusion, and they examined 15 lung adenocarcinomas with reverse-transcriptase polymerase chain reaction-proven EML4-ALK fusion transcripts and 30 ALK-negative cases. Positive rearrangement signals (splits or isolated 3' signals) were identified in 13 to 78% (mean ± SD, 41% ± 19%) of tumor cells in the ALK-positive cohort and in 0 to 15% (mean ± SD, 6% ± 4%) of cells in the ALK-negative cohort. Sensitivity was at 93% and specificity at 100%. The only false-negative tumor having only 13% CISH-positive cells displayed predominantly (76%) isolated 5' signals unaccompanied by 3' signals. FISH showed largely similar signal profiles, and the results were completely concordant with CISH.The authors stated that they have successfully introduced CISH for diagnosing EML4-ALK-positive lung adenocarcinoma. This method allows simultaneous visualization of genetics and tumor cytomorphology and facilitates the molecular evaluation and could be applicable in clinical practice to detect lung cancer that may be responsive to ALK inhibitors.

Ellis et al (2011) conducted a systematic review and a consensus meeting of Canadian lung cancer oncologists and pathologists to make recommendations on the use of biomarkers in NSCLC.  The articles were reviewed by pairs of oncologists and pathologists to determine eligibility for inclusion.  Ten oncologists and pathologists reviewed and summarized the literature at a meeting attended by 37 individuals.  The findings included that there is some evidence that histology is prognostic for survival as well as evidence from multiple randomized clinical trials to recommend the following: histologic subtype is predictive of treatment efficacy and for some agents toxicity. Immunohistochemistry testing should be performed on NSCLC specimens that cannot be classified accurately with conventional H&E staining. As EGFR mutations are predictive of benefit from tyrosine kinase inhibitors, diagnostic NSCLC samples should be routinely tested for EGFR-activating mutations. Clinical data on K-RAS mutations are inconsistent, therefore testing is not recommended. There is insufficient evidence to recommend other biomarker testing. No biomarkers to date reliably predict improved efficacy for anti-VEGF therapy. The authors concluded that outine assessment for EML4/ALK mutations is not recommended at present, although emerging data suggest that it may become valuable in the near future. 

MUC4

Shanmugan and co-workers (2010) stated that mucin 4 (MUC4) is aberrantly expressed in colorectal adenocarcinomas (CRCs) but its prognostic value is unknown.  Archival tissue specimens collected from 132 CRC patients who underwent surgical resection without pre-surgery or pos-tsurgery therapy were evaluated for expression of MUC4 by using a mouse monoclonal antibody and horseradish peroxidase.  MUC4 expression levels were correlated with clinicopathologic features and patient survival.  Survival was estimated by both uni-variate Kaplan-Meier and multi-variate Cox regression methods.  In both normal colonic epithelium and CRCs, MUC4 staining was localized primarily in the cytoplasm.  The optimal immunostaining cut-off value (greater than or equal to 75 % positive cells and an immunostaining score greater than or equal to 2.0), which was derived by using the bootstrap method, was used to categorize CRCs into groups of high expression (33 of 132 patients; 25 %) or low expression (99 of 132 patients; 75 %).  Patients who had early stage tumors (stages I and II) with high MUC4 expression had a shorter disease-specific survival (log-rank; p = 0.007) than patients who had with low expression.  Patients who had advanced-stage CRCs (stages III and IV) did not demonstrate such a difference (log-rank; p = 0.108).  Multi-variate regression models that were generated separately for patients with early stage and advanced-stage CRC confirmed that increased expression of MUC4 was an independent indicator of a poor prognosis only for patients who had early stage CRCs (HR 3.77; 95 % CI: 1.46 to 9.73).  The authors stated that aftr validating these findings in larger retrospective and prospective studies, a stage-based anayses could establish the utility of MUC4 as a prognostic molecular marker of early stage CRC.

ProOnc TumorSourceDx

ProOnc TumorSourceDx test is designed to identify tissue or origin for metastastic tumor.  It identifies 25 possible classes of tissue origin corresponding to 17 distinct tissues and organs.  It requires only 48 microRNAs to identify tissue of origin based on microRNA expression levels.  However, there is insufficient evidence regarding its clinical value as tumor markers.

SAA

Cocco and associates (2010) examined the expression of serum amyloid A (SAA) in endometrial endometrioid carcinoma and evaluated its potential as a serum biomarker.  SAA gene and protein expression levels were evaluated in endometrial endometrioid carcinoma and normal endometrial tissues, by real-time PCR, IHC, and flow cytometry.  SAA concentration in 194 serum samples from 50 healthy women, 42 women with benign diseases, and 102 patients including 49 grade 1, 38 grade 2, and 15 grade 3 endometrial endometrioid carcinoma was also studied by a sensitive bead-based immunoassay.  SAA gene expression levels were significantly higher in endometrial endometrioid carcinoma when compared with normal endometrial tissues (mean copy number by real-time PCR = 182 versus 1.9; p = 0.001).  IHC revealed diffuse cytoplasmic SAA protein staining in poorly differentiated endometrial endometrioid carcinoma tissues.  High intra-cellular levels of SAA were identified in primary endometrial endometrioid carcinoma cell lines evaluated by flow cytometry, and SAA was found to be actively secreted in vitro.  SAA concentrations (microg/ml) had medians of 6.0 in normal healthy women and 6.0 in patients with benign disease (p = 0.92).  In contrast, SAA values in the serum of endometrial endometrioid carcinoma patients had a median of 23.7, significantly higher than those of the healthy group (p = 0.001) and benign group (p = 0.001).  Patients harboring G3 endometrial endometrioid carcinoma were found to have SAA concentrations significantly higher than those of G1/G2 patients.  The authors concluded that SAA is not only a liver-secreted protein, but is also an endometrial endometrioid carcinoma cell product.  SAA is expressed and actively secreted by G3 endometrial endometrioid carcinoma, and it is present in high concentration in the serum of endometrial endometrioid carcinoma patients.  SAA may represent a novel biomarker for endometrial endometrioid carcinoma to monitor disease recurrence and response to therapy.  They stated that additional studies are needed to validate these findings.

Caris Target Now / Caris Molecular Profiling Service

According to the manufacturer, the Caris Life Sciences molecular profiling test, Caris Target Now, examines the genetic and molecular changes unique to a patient's tumor so that treatment options may be matched to the tumor's molecular profile. The manufacturer states that the Caris Target Now test is performed after a cancer diagnosis has been established and the patient has exhausted standard of care therapies or if questions in therapeutic management exist. Using tumor samples obtained from a biopsy, the tumor is examined to identify biomarkers that may have an influence on therapy. Using this information, Caris Target Now is intended to provide information on the drugs that will be more likely to produce a positive response. The manufacturer states that Caris Target Now can be used with any solid cancer such as lung cancer, breast cancer, and prostate cancer.

There is insufficient evidence to support the use of Caris Target Now molecular profiling. A study (Von Hoff et al, 2010) compared the progression-free survival (PFS) of patients with refractory metastatic cancers using a treatment regimen selected by Caris Target Now molecular profiling of the patient's tumor with the PFS for the most recent regimen on which the patient had experienced progression. The investigators prespecified that a molecular profiling approach would be deemed of clinical benefit for the individual patient who had a PFS ratio (defined as a ratio of PFS on molecular profiling-selected therapy to PFS on prior therapy) of greater than or equal to 1.3. In 86 patients who had molecular profiling attempted, there was a molecular target detected in 84 (98 %). Sixty-six of the 84 patients were treated according to molecular profiling results.  Eighteen (27 %) of 66 patients had a PFS ratio of greater than or equal 1.3 (95 % CI:17 % to 38 %). Therefore, the null hypothesis (that less than or equal to 15 % of this patient population would have a PFS ratio of greater than or equal to 1.3) was rejected. The authors concluded that, in 27 % of patients, the molecular profiling approach resulted in a longer PFS on an molecular profiling-suggested regimen than on the regimen on which the patient had just experienced progression. An accompanying editorial (Doroshow, 2010) noted that the trial had a number of significant limitations, including uncertainty surrounding the achievement of time to progression (the study’s primary endpoint), and a lack of a randomized design for this trial. 

A report by the National Horizon Scanning Centre (2013) stated that the company stated that the tumor profiling service provided by Caris Life Sciences has been extensively altered with the addition of several new technologies. The new service is named Caris Life Sciences Molecular Intelligence Services. The NHSC stated that randomized controlled trials comparing clinical outcomes for patients using Caris molecular profiling to those receiving standard specialist care are needed to determine whether this testing service is effective and cost-effective.

CoA racemase (P504S) and HMWCK (34betaE12)

Kumaresan et al (2010) reviewed 1034 cases of morphologically difficult prostate cancer, which were divided into benign (585), malignant (399) and suspicious (50) and evaluated using CoA racemase (P504S) and HMWCK (34betaE12).  Forty nine suspicious cases were resolved by using both markers whereas 1 case was resolved by further support with CD68.  The original diagnosis was changed in 15 of 50 suspicious cases from benign to malignant, one case from benign to high grade PIN, and in one case from malignant to benign.  The authors concluded that a combination of HMWCK and AMACR is of value in combating morphologically suspicious cases and that although the sensitivity and specificity of HMWCK and AMACR in this study were high, “it should be used with caution, keeping in mind all their pitfalls and limitations.”

P504S

Murray et al (2010) studied P504S expressing circulating prostate cells as a marker for prostate cancer.  The authors stated that PSA is the only biomarker routinely used in screening.  This study aimed to develop a system to test the presence of circulating prostate cells in men without a diagnosis of prostate cancer in realation with age, serum PSA levels and prostate biopsy by determining the co-expression of several markers such as CD82, HER-2 and matrix metalloproteinase 2 MMP-20.  The results indicated that among 409 men screened for prostate cancer 16.6% were positive for circulating prostate cells.  The authors concluded that the study of circulating prostate cells with various markers could be a useful complementary screening test for prostate cancer in men with increased PSA level.

FLT3

FLT3 has been used to predict prognosis in acute myelogenous leukemia (Chin, et al, 2006). Mutations in FLT3 are common in AML and have been associated with poorer survival in children and in younger adults with normal cytogenetics receiving intensive chemotherapy.

The NCCN Task Force issued a report in November of 2011 which updated their position regarding molecular markers for diagnosis, prognosis, prediction, and companion diagnostic markers (Febbo et. al., 2011).  As a result of these recommendations, use of MGMT, IDH mutation and 1p/19q codeletion are now established for glioma.  Also, use of ALK gene fusion has been established for non-small cell lung cancer.  The updated NCCN guidelines have not yet established the efficacy of ColoPrint, CIMP, LINE-1 hypomethylation, or Immune cells for colon cancer.  Similarly, the efficacy of FLT3-TKD mutation, WT1 mutation, RUNX1 mutation, MLL-PTD, IDH1 mutation, IDH2 R172, and IDH2 codon 140 mutation has not been established for use in acute myeloid leukemia.

ColoPrint

ColoPrint (Agendia) is an 18-gene profile that classifies colon cancer into Low Risk or High Risk of relapse, by measuring genes representative of the metastatic pathways of colon cancer metastases which were selected for their predictive relationship to 5-year distant metastases probability (Raman, et al., 2013). ColoPrint is indicated for stage II colon cancer, and provides relapse risk stratification independent of clinical and pathologic factors such as T4-stage and MSI status. ColoPrint determines if the patient is a candidate for chemotherapy. An NCCN Task Force report (NCCN, 2011) concluded that the efficacy of ColoPrint has not been established.

DecisionDx

The DecisionDx test is a gene expression profile that determines the molecular signature of a patient's melanoma. The results of the test provide knowledge regarding the risk of near term metastasis (5 years). Tumors with a Class 1 signature are associated with a good prognosis and a low potential to spread (or metastasize), while tumors with a Class 2 signature have a high potential to spread. There is a lack of adequate published evidence on the clinical utility of this test. Current guidelines on melanoma from the National Comprehensive Cancer Network make no recommendation for this test. 

Gerami, et al. (2015) reported on the DecisionDx predictive genetic signature for classifying tumors as class 1 (low risk) or class 2 (high risk) for metastasis. Using earlier studies, they compared differences in the levels of 28 genes, including some control genes, using RT-PCR. The 5-year disease-free survival (DFS) rate for the 164 sample training set was 91% for class 1 and 25% for class 2 (P< 0.0001), while the 5-year DFS rate for the 104 sample validation set (stage I–IV) was 97% for class 1 and 31% for class 2 (P< 0.0001). The signature was used to classify stage I and stage IIA tumors, accurately predicting 120 of 134 tumors without metastases as class 1 (90%) and 24 of 30 tumors with metastases as class 2 (80%).

Molecular Diagnostics for Thyroid Cancer

Guidelines on thyroid carcinoma from the National Comprehensive Cancer Network (NCCN, 2014) state: "Molecular diagnostic testing to detect individual mutations (e.g., BRAF, RET/PTC, RAS, PAX8/PPAR [peroxisome proliferator-activated receptors] gamma) or pattern recognition approaches using molecular classifiers may be useful in the evaluation of FNA samples that are indeterminate to assist in management decisions. The choice of the precise molecular test depends on the cytology and the clinical question being asked." Indeterminate groups include: 1) follicular or Hurthle cell neoplasms; and 2) AUS/FLUS. The NCCN Panel recommends (category 2B) molecular diagnostic testing for evaluating FNA results that are suspicious for: 1) follicular or Hurthle cell neoplasms; or 2) AUS/FLUS (see Nodule Evaluation in the NCCN Guidelines for Thyroid Carcinoma). For the 2014 update, the NCCN Panel revised the recommendation for molecular diagnostic testing from category 2A to category 2B for indeterminate FNA results based on a series of panel votes. The panel noted that the molecular testing (both the Gene Expression Classifier and the individual mutation analysis) was available in the majority of NCCN Member Institutions (>75%). About 70% of the panelists would recommend using a gene expression classifier in the evaluation of follicular lesions. The gene expression classifier measures the expression of at least 140 genes. BRAF mutation analysis was recommended by 50% of the panelists in the evaluation of thyroid nodules (not restricted to the follicular lesions). Furthermore, about 60% of the panelists would recommend BRAF testing in the evaluation of follicular lesions. A minority of panelists expressed concern regarding observation of follicular lesions because they were perceived as potentially pre-malignant lesions with a very low, but unknown, malignant potential if not surgically resected (leading to a recommendation for either observation or definitive surgical resection in lesions classified as benign by molecular testing). Rather than proceeding to immediate surgical resection to obtain a definitive diagnosis for these intermediate FNA cytology groups (follicular lesions), patients can be followed with observation if the application of a specific molecular diagnostic tests results in a predicted risk of malignancy that is comparable to the rate seen in cytologically benign thyroid FNAs (approximately < 5%). NCCN guidelines state that it is important to note that the predictive value of molecular diagnostics may be significantly influenced by the pre-test probability of disease associated with the various FNA cytology groups. Furthermore, in the cytologically indeterminate groups, the risk of malignancy for FNA can vary widely between institutions. Because the published studies have focused primarily on adult patients with thyroid nodules, the diagnostic utility of molecular diagnostics in pediatric patients remains to be defined. Therefore, proper implementation of molecular diagnostics into clinical care requires an understanding of both the performance characteristics of the specific molecular test and its clinical meaning across a range of pre-test disease probabilities.

For support for use of a gene classifier, the NCCN guidelines reference validation studies of the Afirma Thyroid FNA Analysis (Alexander et al, 2012; Chudova et al, 2010; Kloos, et al., 2013; McIver, et al., 2014) and Thyroseq (Nikiforov, et al., 2009; Ohori, et al., 2010; Nikiforov, et al., 2011). These studies demonstrate that this molecular diagnostic meets NCCN threshold of predicting malignancy of 5 % or less (i.e., a negative predictive value of 95 %), allowing physicians to observe an indeterminate thyroid nodule in lieu of surgery.

Quest Diagnostics offers a molecular test panel designed to help physicians determine if a thyroid gland is cancerous and requires surgical removal. The test includes mutations associated with four gene markers indicated by the American Thyroid Association for the clinical management of indeterminate thyroid biopsies. According to Quest Diagnostics, the Quest Diagnostics Thyroid Cancer Mutation Panel aids in detecting cancer in thyroid biopsies which are found to be indeterminate for cancer by current cytology test methods. Approximately 15% to 20% of these biopsies, which are collected by fine needle aspiration (FNA), produce indeterminate results. An unclear result may increase the risk that a physician, in an abundance of caution, will biopsy additional tissue using a larger needle or surgically remove part or all of a thyroid suspected of having cancer that is later diagnosed as healthy. About 300,000 thyroid FNA biopsy procedures are performed annually in the United States. The panel identifies mutations of the molecular markers BRAF V600E, RAS, RET/PTC, and PAX8/PPAR gamma, which are associated with papillary and follicular thyroid cancer, two common forms of the disease. The manufacturer states that practice guidelines from the American Thyroid Association recommend that physicians consider these markers as aids in clinical management of patients with indeterminate biopsy test results. Results of a Quest Diagnostics study found that 90 of 149 FNA specimens, or about 60%, had mutations of one or more of the four markers tested by the new panel (Reitz, et al., 2014). The authors of the study stated that the presence of the four markers was generally mutually exclusive, suggesting potential value in a hierarchical screening strategy for samples with limited tissue. According to the American Cancer Society, about two tests in every 10 may need to be repeated because the sample does not contain enough cells for testing.

ROMA

The BCBS TEC’s assessment on “Multi-Analyte Testing for the Evaluation of Adnexal Masses” (2013) concluded that ROMA does not meet TEC criteria.  It noted that “evidence regarding the effect of ... ROMA and effects on health outcomes is indirect, and based on studies of diagnostic performance of the tests in patients undergoing surgery for adnexal masses.  Although the studies show improvements in sensitivity and worsening of specificity with the use of the tests in conjunction with clinical assessment, there are problems in concluding that this results in improved health outcomes. The clinical assessment performed in the studies is not well characterized... ROMA does not improve the sensitivity of testing to a great extent. Underlying these issues is some uncertainty regarding the benefit of initial treatment by a gynecologic oncologist beyond the need for reoperation is some cases”.

ERCC1

Yu and colleagues (2012) stated that the excision repair cross-complementation group 1 (ERCC1) plays an essential role in DNA repair and has been linked to resistance to platinum-based anticancer drugs among advanced NSCLC patients.  These investigators examined if ERCC1 Asn118Asn and C8092A genetic variants are associated with treatment response of platinum chemotherapy.  They performed a meta-analysis using 10 eligible cohort studies (including 11 datasets) with a total of 1,252 NSCLC patients to summarize the existing data on the association between the ERCC1 Asn118Asn and C8092A polymorphisms and response to platinum regiments.  Odds ratio or hazard ratio with 95 % CI were calculated to estimate the correlation.  These researchers found that neither ERCC1 C8092A polymorphism nor Asn118Asn variant is associated with different response of platinum-based treatment among advanced NSCLC patients.  Additionally, these 2 genetic variants are not related to treatment response in either Caucasian patients or Asian patients.  The authors concluded that the findings of this meta-analysis indicated that the ERCC1 Asn118Asn and C8092A polymorphisms may not be good prognostic biomarkers for platinum-based chemotherapy in patients with stage III-IV NSCLC.

Wang et al (2012) performed a meta-analysis by using 20 eligible studies to examine polymorphisms of ERCC1, GSTs, TS and MTHFR in predicting clinical outcomes (response rate, OS and toxicity) of gastric cancer (GC) patients treated with platinum/5-Fu-based chemotherapy.  The association was measured using random/fixed effect odds ratios (ORs) or hazard ratios (HRs) combined with their 95 % CIs according to the studies' heterogeneity.  Statistical analysis was performed with the software STATA 9.0 package.  No significant association was found between response rate and genetic polymorphism in TS, MTHFR, ERCC1, GSTM1 and GSTP1.  However, response rate was higher in GSTT1 (+) genotype compared with GSTT1 (-) genotype (T-/T+: OR = 0.67, 95 % CI: 0.47 to 0.97).  With regard to long-term outcomes, these researchers observed a significant longer OS in TS 3R/3R [(2R2R+2R3R)/3R3R: HR = 1.29, 95 % CI: 1.02 to 1.64] and GSTP1 GG/GA [(GG+AG)/AA: HR = 0.51, 95 % CI: 0.39 to 0.67] genotypes.  In addition, significant association was demonstrated between toxicity and genetic polymorphism in TS, MTHFR and GSTP1 in included studies.  The authors concluded that polymorphisms of ERCC1, GSTs, TS and MTHFR were closely associated with clinical outcomes of GC patients treated with platinum/5-Fu-based chemotherapy.  Moreover, they state that studies with large sample size using the method of multi-variant analyses may help us to give more persuasive data on the putative association in future.

In a meta-analysis, Gong and colleagues (2012) examined if RRM1 expression is associated with the clinical outcome of gemcitabine-containing regimen in advanced NSCLC.  An electronic search was conducted using the databases PubMed, Medline, EMBASE, Cochrane library and CNKI, from inception to May, 2011.  A systemic review of the studies on the association between RRM1 expression in advanced NSCLC and clinical outcome of gemcitabine-containing regimen was performed.  Pooled odds ratios (OR) for the response rate, weighted median survival and time to progression were calculated using the software Revman 5.0.  The search strategy identified 18 eligible studies (n = 1,243).  Response rate to gemcitabine-containing regimen was significantly higher in patients with low/negative RRM1 (OR = 0.31, 95 % CI: 0.21 to 0.45, p < 0.00001).  Non-small cell lung cancer SCLC patients with low/negative RRM1 who were treated with gemicitabine-containing regimen survived 3.94 months longer (95 % CI: 2.15 to 5.73, p < 0.0001) and had longer time to progression for 2.64 months (95 % CI: 0.39 to 4.89, p = 0.02) than those with high/positive RRM1.  The authors concluded that low/negative RRM1 expression in advanced NSCLC was associated with higher response rate to gemcitabine-containing regimen and better prognosis.  Moreover, they stated that large phase III randomized trials are needed to identify whether RRM1 detection is clinically valuable for predicting the prognosis and sensitivity to gemcitabine-containing regimen in advanced NSCLC.

Friboulet et al (2013) stated that the ERCC1 protein is a potential prognostic biomarker of the effectiveness of cisplatin-based chemotherapy in NSCLC.  Although several ongoing trials are evaluating the level of expression of ERCC1, no consensus has been reached regarding a method for evaluation.

Besse et al (2013) noted that somatic ERCC1 and ribonucleotide reductase M1 (RRM1) expression levels have been extensively explored as markers of DNA repair capacity in tumor cells.  Although low ERCC1 and/or RRM1 expression is generally associated with sensitivity to platinum, the results published in retrospective and prospective studies are not always consistent.  These researchers examined the function of these 2 biomarkers as well as the tools available for their assessment and the associated technical issues.  Their prognostic and predictive values were summarized and considered in terms of customizing systemic therapy according to biomarker (ERCC1 and RRM1) expression levels.  The authors discussed why the use of both markers should at this point be restricted to clinical research.

GSTP1

Prostate cancer is the most common cancer in men and the second leading cause of cancer-related deaths in the US. Due to the reportedly high false-negative rate of initial biopsy results after elevated PSA level, new approaches for improved detection in prostate cancer are needed. Several studies have shown that hypermethylation of the promoter regions of the GST-P1 and APC genes occurs at a significantly higher frequency in prostate cancer samples than in benign conditions of the prostate gland. Hypermethylation of the promoter regions of the GST-P1 and APC genes can aid in prognosticating for prostate cancer (Raman, et al., 2013).

Trock et al (2012) noted that hyper-methylation of genes such as glutathione-S-transferase P1 (GSTP1) and adenomatous polyposis coli (APC) occurs with high frequency in prostate tumor tissue but is much less common in the benign prostate; however, the potential value of gene methylation biomarkers as an adjunct to biopsy histopathology has had little study.  When measured in histologically benign prostate biopsy tissue, APC gene hyper-methylation was found to have high negative-predictive value (NPV) and high sensitivity.  GSTP1 hype-rmethylation was found to have lower performance than APC.  These investigators evaluated the performance of DNA methylation biomarkers in the setting of repeat biopsy in men with an initially negative prostate biopsy but a high index of suspicion for missed prostate cancer.  They prospectively evaluated 86 men with an initial histologically negative prostate biopsy and high-risk features.  All men underwent repeat 12-core ultrasonography-guided biopsy.  DNA methylation of GSTP1 and APC was determined using tissue from the initially negative biopsy and compared with histology of the repeat biopsy.  The primary outcome was the relative NPV of APC compared with GSTP1, and its 95 % CI.  On repeat biopsy, 21/86 (24 %) men had prostate cancer.  APC and GSTP1 methylation ratios below the threshold (predicting no cancer) produced a NPV of 0.96 and 0.80, respectively.  The relative NPV was 1.2 (95 % CI: 1.06 to 1.36), indicating APC has significantly higher NPV.  Methylation ratios above the threshold yielded a sensitivity of 0.95 for APC and 0.43 for GSTP1.  Combining both methylation markers produced a performance similar to that of APC alone.  APC methylation patterns were consistent with a possible field effect or occurrence early in carcinogenesis.  The authors concluded that APC methylation provided a very high NPV with a low percentage of false-negatives, in the first prospective study to evaluate performance of DNA methylation markers in a clinical cohort of men undergoing repeat biopsy.  They stated that the potential of APC methylation to reduce unnecessary repeat biopsies warrants validation in a larger prospective cohort.

In a systematic review and meta-analysis, Yu and colleagues (2013) examined the association between GSTP1 Ile105Val polymorphism and prostate cancer (PCa) in different inheritance models.  A total of 13 eligible studies were pooled into this meta-analysis.  There was significant association between the GSTP1 Ile158Val variant genotypes and PCa for Ile/Ile versus Val/Val comparison [odds ratio (OR) = 0.705; I 2 = 63.7 %; 95 % CI: 0.508 to 0.977], Ile/Val versus Val/Val comparison (OR = 0.736; I 2 = 8.0 %; 95 % CI: 0.613 to 0.883), and dominant model (OR = 0.712; I 2 = 45.5 %; 95 % CI: 0.555 to 0.913).  However, no associations were detected for other genetic models.  In the stratified analysis by ethnicity, significant associations between GSTP1 Ile105Val polymorphism and PCa risk were also found among Caucasians (Ile/Ile versus Val/Val comparison OR = 0.818, I 2 = 0.0 %, 95 % CI: 0.681 to 0.982; Ile/Val versus Val/Val comparison OR = 0.779, I 2 = 0.0 %, 95 % CI: 0.651 to 0.933; and dominant model OR = 0.794, I 2 = 0.0 %, 95 % CI: 0.670 to 0.941), while there were no associations found for other genetic models.  However, no associations were found in Asians and African-Americans for all genetic models when stratified by ethnicity. The authors concluded that the findings of this meta-analysis indicated that GSTP1 Ile105Val polymorphisms contributed to the PCa susceptibility.  However, they stated that a study with the larger sample size is needed to further evaluate gene-environment interaction on GSTP1 Ile105Val polymorphisms and PCa risk.

An assessment by the Swedish Office of Heath Technology Assessment (SBU, 2011) concluded that the scientific evidence is insufficient to determine the diagnostic accuracy of the me-GSTP1 urine test.

CEACAM6

An UpToDate review on "Screening for breast cancer" (Fletcher, 2013) does NOT mention the use of carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6).  Also, the NCCN's clinical practice guideline on "Breast Cancer" (Version 2.2013) does NOT mention the use of carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6).

DCIS Recurrence Score

An UpToDate review on “Ductal carcinoma in situ: Treatment and prognosis” (Collins et al, 2013) states that “A DCIS Recurrence Score utilizing a multigene assay has been developed and a prospective evaluation of this assay was performed using tumors from 327 patients who participated in the aforementioned E5194 trial.  In a preliminary analysis, patients were stratified by recurrence score into three groups that were associated the following risks of an ipsilateral breast event (DCIS or invasive breast cancer) or invasive breast cancer:

  • Low (less than 39) -- 12 and 5 %, respectively
  • Intermediate (39 to 54) -- 25 and 9 %, respectively
  • High (greater than or equal to 55) -- 27 and 19 %, respectively

These results suggest that the DCIS score may help select patients who should undergo adjuvant radiation.  However, further validation of these results is required before the multigene assay can become a part of clinical practice.  It is also worth noting that a 12 percent risk of an ipsilateral breast event at 10 years in the lowest risk category may not be low enough to justify the routine omission of post-excision RT”.

MyPRS

MyPRS Plus (Signal Genetics) analyzes all of the nearly 25,000 genes in a patient’s genome to determine the gene expression profile that is associated with their condition (Raman, et al., 2013). In the case of myeloma, the gene expression profile is made up of the 70 most relevant genes which aid in the prediction of the patient’s outcome. MyPRS helps patients and physicians determine the best treatment for patients with Myeloma.

The NCCN’s clinical practice guideline on multiple myeloma (MM) (Version 2.2013) stated that “Further understanding of the molecular subtypes of MM is emerging from the application of high-throughput genomic tools such as gene expression profiling (GEP).  With the currently available novel treatment approaches, a majority of patients with MM can now anticipate long-term disease control.  However, patients with cytogenetically and molecularly defined high-risk disease do not receive the same benefit from current approaches as low-risk patients.  GEP is a powerful and fast tool with the potential to provide additional prognostic value to further define risk-stratification, help therapeutic decisions, and inform novel drug design and development.  At the present time, standardized testing for GEP is not available and there is inadequate data to determine how this prognostic information should be used to direct patient management”.  The NCCN guideline does not include a specific recommendation for the use of the MyPRS test in risk-stratification or determining prognosis in the clinical management of patients with MM.

Oxnard et al (2013) stated that the identification of oncogenic driver mutations underlying sensitivity to EGFR and anaplastic lymphoma kinase tyrosine kinase inhibitors has led to a surge of interest in identifying additional targetable oncogenes in NSCLC.  A number of new potentially oncogenic gene alterations have been characterized in recent years, including BRAF mutations, HER2 insertions, phosphatidylinositol-4,5-bisphosphonate 3-kinase, catalytic subunit alpha polypeptide gene (PIK3CA) mutations, fibroblast growth factor receptor 1 (FGFR1) amplifications, discoidin domain receptor 2 (DDR2) mutations, ROS1 re-arrangements, and RET re-arrangements.  These investigators discussed the techniques used to discover each of these candidate oncogenes, the prevalence of each in NSCLC, the pre-clinical data supporting their role in lung cancer, and data on small molecular inhibitors in development.

NRAS

Janku et al (2013) noted that despite development of new therapies, metastatic colorectal cancer (mCRC) largely remains an incurable disease.  Approximately 2 to 6 % of colorectal cancers harbor NRAS mutations.  The anti-VEGF antibody bevacizumab is a backbone of most therapeutic regimens; however, biomarkers predicting its activity are not known.  These investigators reported 2 cases of mCRC with a Q61K NRAS mutation that had a favorable response to bevacizumab and the histone deacetylase inhibitor valproic acid.  In contrast, none of 10 patients with wild-type NRAS or unknown NRAS status and mutated KRAS (NRAS and KRAS mutations are mutually exclusive) responded to the same regimen.  The authors concluded that these results suggested that NRAS mutation merits further investigation as a potential biomarker predicting the efficacy of bevacizumab-based treatment.

The EGAPP EWG (2013) found insufficient evidence to recommend for or against testing for mutations in NRAS, or PIK3CA, and/or loss of expression of PTEN or AKT proteins. The level of certainty for this evidence was low. In the absence of supporting evidence, and with consideration of other contextual issues, the EWG discourages the use of these tests in guiding decisions on initiating anti-EGFR therapy with cetuximab or panitumumab unless further evidence supports improved clinical outcomes.

Cyclin D1 and FADD

Cyclin D1 is used to diagnose of mantle cell lymphoma and predict recurrence of disease (Chin, et al., 2006). D-type cyclins are predominantly expressed in the G1 phase of the cell cycle. The expression pattern of cyclin D1 has been extensively studied in certain cancer types including lymphoma and non-small cell lung cancer. Approximately 30 percent of breast carcinomas are Cyclin D1 positive. Over expression of Cyclin D1 is now a well established criterion for the diagnosis of Mantle Cell Lymphoma, a malignant, non-Hodgkin's lymphoma which is characterized by a unique chromosomal translocation t(11;14).

Rasamny et al (2012) stated that cyclin D1 and FADD (Fas-associated protein with death domain) regulate the cell cycle and apoptosis, respectively, and are located on chromosome 11q13, which is frequently amplified in head and neck squamous cell carcinoma (HNSCC).  This study evaluated these proteins as predictors of clinical outcomes for HNSCC.  A total of 222 patients with upper aero-digestive HNSCC were included in this study.  Patients with tumors that were strongly positive for cyclin D1 and FADD had reduced OS (p = 0.003 and p < 0.001), disease-specific survival (DSS; p = 0.039 and p < 0.001), and DFS (p = 0.026 and p < 0.001) survival, respectively.  Together, the 2 markers effectively stratified OS (p < 0.001), DSS (p < 0.001), and DFS (p = 0.002).  Strong FADD staining correlated with greater alcohol consumption and varied significantly with primary tumor site: 56 % of hypopharynx tumors expressed high levels of FADD but only 7 % of glottis tumors.  Using Cox regression analysis, FADD and N stage were significant independent predictors of DSS and DFS, whereas cyclin D1, FADD, and N stage were independently significant for OS.  The authors concluded that cyclin D1 and FADD may have utility as predictors of long-term outcomes for patients with HNSCC.  Moreover, they stated that further study is needed to determine if these proteins predict response to different treatment approaches or assist in selecting patients for multi-modality therapy.

Prolaris

Prolaris (Myriad Genetics, Salt Lake City, UT) uses archived tumor specimens as the mRNA source, reverse transcriptase polymerase chain reaction amplification, and a low density RTPCR array platform. Prolaris is used to quantify expression levels of 31 cell cycle progression (CCP) genes and 15 housekeeper genes to generate a CCP score. An assessment by the BlueCross BlueShield Association Technology Evaluation Center (TEC) concluded that direct evidence is insufficient to establish the analytic validity, clinical validity, or clinical utility of the Prolaris test. The BlueCross BlueShield Association assessment (BCBSA, 2015) stated: "Published evidence is sparse and insufficient to draw conclusions on the analytic validity, clinical validity, or clinical utility of Prolaris ... in patients under active surveillance program."

An assessment by the Adelaide Health Technology Assessment (Ellery, et al., 2014) found that there is currently uncertainty around the clinical utility of Prolaris. Citing a study by Shore, et al. (2014) showning that only a small percent of urologist would definitely change treatment based on the test results, "it would appear that there is hesitancy about the use of the technology in clinical practice, and it appears that changes to clinical management based on the prognostic information provided by these genetic tests are unlikely to occur. Therefore HealthPACT recommends that no further research be conducted on their behalf at this point in time."

NCCN prostate cancer guidelines (2015) state: "The Prolaris assay produces a cell cycle progression (CCP) score from RNA expression levels of 31 genes involved in CCP. . . .For example, Prolaris has been successful in 93% of radical prostatectomy specimens, and 70% of diagnostic prostate biopsy specimens. The Prolaris CCP score has been demonstrated predictive when applied in prospective-retrospective designs for biochemical recurrence or metastasis after radical prostatectomy, for survival when men were observed after diagnosis on transurethral resection of prostate or diagnostic needle biopsy, and for biochemical recurrence and survival after external beam radiation therapy. .. Prolaris has changed treatment recommendations in 32% to 65% of cases and may enhance adherence to the treatment recommended. .. Both [Prolaris and Oncotype DX Prostate] molecular biomarker tests have been developed with extensive industry support, guidance, and involvement, and have been marketed under the less rigorous FDA regulatory pathway for biomarkers. Their clinical utility awaits evaluation by prospective, randomized clinical trials, which are unlikely to be done. The marketplace and comparative effectiveness research may be the only means for these tests and others like them to gain their proper place for better risk stratification for men with clinically localized prostate cancer.”

Oncotype Dx Prostate

The Oncotype DX test for prostate cancer (Genomic Health) is a genomic test that determines the risk of the cancer before treatment begins (Raman, et al., 2013). The test predicts how likely it is that the cancer is low risk and contained within the prostate, or higher risk and more likely to grow and spread. With this information, the patient and their doctor can choose the most appropriate treatment option. For example, a lower risk prostate cancer with more favorable pathology, one that may not need invasive treatment and can be safely managed through close and careful monitoring – a treatment approach called active surveillance. This genomic test measures biology through the expression of 17 genes across multiple key biological pathways in prostate cancer which can predict the aggressiveness of prostate cancer providing an individualized risk assessment.

Oncotype Dx Prostate Cancer Assay (Genomic Health, Redwood City, CA) is used to quantify expression levels of 12 cancer-related and 5 reference genes to generate a Genomic Prostate Score (GPS). In the final analysis, the cell cycle progression (CCP) score (median 1.03, interquartile range 0.41 to 1.74) and GPS (range of 0 to 100) are combined in proprietary algorithms with clinical risk criteria (PSA, Gleason grade, tumor stage) to generate new risk categories (i.e., reclassification) intended to reflect biological indolence or aggressiveness of individual lesions, and thus inform management decisions. An assessment by the BlueCross BlueShield Technology Evaluation Center (TEC, 2014) concluded that direct evidence is insufficient to establish the analytic validity, clinical validity, or clinical utility of the Oncotype Dx Prostate.

The BlueCross BlueShield Technology Evaluation Center’s assessment on “Gene Expression Analysis for Prostate Cancer Management” (BCBSA, 2015) concluded that “Evidence is insufficient to determine whether . . . Oncotype Dx Prostate testing improves health outcomes in the investigational setting.  Based on the above, neither the Prolaris nor Oncotype Dx Prostate array-based gene expression test meets the TEC criteria”.  The assessment stated: Published evidence is sparse and insufficient to draw conclusions on the . . . clinical validity or utility of Oncotype Dx Prostate in patients under active surveillance program."

An assessment by Adelaide Health Technology Assessment (Ellery, et al., 2014) concluded that "there is uncertainty about the clinical utility" of the Oncotype Dx Prostate and the Prolaris tests, "even when taking into account the highest level of evidence available" The assessment stated that it remains to be verified whether genetic expression of the unique gene panels involved are robust to heterogeneous sampling of prostate tissue at the time of biopsy. Also, the need for tissue which has previously been fixed for histological analysis is of some concern. The assessment observed that this is the most obvious reason for the relatively high number of patients for whom a valid test results could not be obtained.

NCCN guidelines on prostate cancer (NCCN, 2015) state: "The Oncotype DX Prostate Cancer assay produces a Genomic Prostate Score (GPS) from RNA expression levels of 17 genes from 4 different molecular pathways (stromal response, cellular organization, androgen signaling and cell proliferation). These tissue-based molecular assays can be performed on most formalin-fixed, paraffin-embedded prostate specimens. . . . The Oncotype DX GPS was developed form evaluation of a diagnostic prostate biopsy and radical prostatectomy series from Cleveland Clinic and validated in a diagnostic prostate biopsy and radical prostatectomy series from University of California, San Francisco. GPS performed in the diagnostic prostate biopsy has provided information beyond usual clinical information that predict the likelihood of Gleason sum 7 or extraprostatic disease on radical prostatectomy. . . . Oncotype DX GPS improved upon NCCN risk group assignment, which may enhance rates of compliance with recommended active surveillance or diminish the number of surveillance prostate biopsies. Both [Oncotype Dx Prostate and Prolaris] molecular biomarker tests have been developed with extensive industry support, guidance, and involvement, and have been marketed under the less rigorous FDA regulatory pathway for biomarkers. Their clinical utility awaits evaluation by prospective, randomized clinical trials, which are unlikely to be done. The marketplace and comparative effectiveness research may be the only means for these tests and others like them to gain their proper place for better risk stratification for men with clinically localized prostate cancer.”

Prostavysion

ProstaVysion (Bostwick Labs) is a prognostic genetic panel for prostate cancer (Raman, et al., 2013). This test examines two major mechanisms of prostate carcinogenesis: ERG gene fusion/translocation and the loss of the PTEN tumor suppressor gene. This test is a tissue-based panel. By examining these two markers, ProstaVysion is able to provide a molecular analysis of prostate cancer aggressiveness and long-term patient prognosis. ERG gene fusions are found in 40% of primary prostate cancers and are associated with a more aggressive phenotype. Deletion of PTEN occurs in both localized prostate cancers and 60% of metastases.

PAM50 and Prosigna

PAM50 Breast Cancer Intrinsic Classifier (University of Utah) examines 50 genes and sorts breast cancer into four subtypes (Raman, et al., 2013). Each subtype responds differently to standard therapies, and knowing the subtype allows doctors to tailor treatment for each patient. PAM50 assay can aid profiling for both prognosis and prediction of benefit from adjuvant tamoxifen and has been found superior to immunohistochemistry.

A National Institute for Health Research assessment (Ward, et al., 2013) found the evidence for PAM50 to be limited. The report concluded that "the evidence base for PAM50 is still relatively immature."

An international working group (Azim, et al, 2013) found insufficient evidence of the analytic and clinical validity of the PAM50. They found insufficient evidence of the clinical utility of the PAM50 or the other breast cancer genomic tests that they assessed.

A report by the Belgian Healthcare Knowledge Centre (KCE) (San MIguel, et al., 2015) found that the evidence for PAM50 is limited to studies supporting the prognostic ability (clinical validity) of the test. Most of the evidence is in node-positive patients. The KCE found insufficient evidence on the impact of PAM50 on clinical management (clinical utility).

Prosigna is intended for use as a prognostic indicator in conjunction with other clinicopathologic factors for distant recurrence‐free survival at 10 years in postmenopausal women with hormone receptor (HR)–positive, lymph node‒negative/stage I or II, or lymph node‒positive (1‐3 positive nodes)/stage II breast cancer to be treated with adjuvant endocrine therapy alone. The assay measures the expression profiles of genes included in the PAM50 gene signature, as well as 8 housekeeping genes (for normalization), 6 positive controls and 8 negative controls.

The BlueCross BlueShield Association (2015) concluded that the use of Prosigna to determine recurrence risk in women with early-stage breast cancer does not meet the TEC criteria. The evidence is insufficient to permit conclusions regarding health outcomes. Assay performance characteristics of the commercially available version of the test indicate high reproducibility.

A medical technology innovation briefing by the National Institute for Health and Clinical Excellence (NICE, 2015) noted that none of the women analyzed in the clinical validation studies (citing Gnant, et al. (2014), Sestak, et al. (2014) and Dowsett et al. (2013)) had chemotherapy as part of their initial treatment. As a result, the prognostic value of the Prosigna ROR score in a chemotherapy-treated population is unknown. Sestak. The briefing also noted that the populations included in the patient cohorts included in these clinical validation studies. Sestak, et al. (2014) combined data previously analysed by Dowsett et al. (2013) and Gnant et al. (2014). Dowsett et al. (2013) and Sestak et al. (2014) used the clinical treatment score as a comparator rather than the online tools Adjuvant! Online and PREDICT, or the NPI, which are standard practice in the UK. Similarly, Gnant et al. (2014) used a combination score of clinicopathologic parameters as the comparator for Prosigna. NICE stated that such indices are always incomplete because they may not include all parameters used by clinicians in other health systems to aid clinical decision-making. The NICE briefing also pointed out that all included studies received financial support or disclosed competing interests from the manufacturer, and this introduces the potential for bias in the reporting of outcomes.

OncotypeDx Colon

The Oncotype Dx Colon has been promoted for use in colorectal cancer. However, there is a lack of evidence establishing the clinical utility of this test in colorectal cancer.

The results of the Quick and Simple and Reliable Study (QUASAR) were published by Gray et al (2011).  The purpose of the QUASAR study was develop quantitative gene expression assays to assess recurrence risk and benefits from chemotherapy in patients with stage II colon cancer.  Recurrence score (RS) and treatment score (TS) were calculated from gene expression levels of 13 cancer-related genes and from five reference genes.  The results of the study showed risk of recurrence to be significantly associated with RS (95 % confidence interval [CI]: 1.11 to 1.74; p = 0.004).  Recurrence risks at 3 years were 12 %, 18 %, and 22 % for predefined low, intermediate, and high recurrence risk groups, respectively.  Continuous RS was associated with risk of recurrence (p = 0.006), but there was no trend for increased benefit from chemotherapy at higher TS (p = 0.95).  The continuous 12-gene RS has been validated in a prospective study for assessment of recurrence risk in patients with stage II colon cancer after surgery.  RS was also found to provide prognostic value that complements T stage and mismatch repair.

The NCCN’s clinical practice guideline on “Colon cancer” (Version 2.2015) states that there are insufficient data to recommend the use of multi-gene assays (e.g., the Oncotype DX colon cancer assay) to determine adjuvant therapy.

An assessment prepared for the Agency for Healthcare Research and Quality (Meleth,, 2014) stated: "For CRC, evidence did not adequately support added prognostic value for Oncotype DX Colon. evidence either did not support added prognostic value or we found no studies with sufficiently low RoB to support a conclusion about prognostic value."

Decipher

The Decipher test appears to be a RNA biomarkers “assay” for prostate cancer.  Decipher does this by measuring the expression levels of 22 RNA biomarkers involved in multiple biological pathways across the genome that are associated with aggressive prostate cancer.

Studies of the Decipher genetic test reported on the use of this gene panel to predict biochemical recurrence, metastatic progression, and disease-specific survival after radical prostatectomy with or without external beam radiotherapy (Ehro, et al., 2013; Cooperberg, et al., 2015; Ross, et al., 2014; Klein, et al., 2015; Karnes, et al., 2013; Den, et al., 2014; Den, et al., 2015). The impact of Decipher was evaluated in a clinical utility study where 21 uro-oncologists were presented 24 patient cases (12 potential candidates for adjuvant and 12 for salvage external beam radiation therapy) and were asked for treatment recommendations with and without information from the genetic test (Badani, et al., 2013). The recommendation changed in 43% of the adjuvant cases and 53% in the salvage setting, suggesting a potentially significant impact on treatment decisions after radical prostatectoy. Michalopoulos, et al. (2014) reported that the Decipher genomic classifier was useful in the clinic when used as a part of the risk stratification in recommending adjuvant radiation to patients with high-risk pathologic features. In that study, 43% of patients shifted to observation based on information of Decipher genomic classifier after radical prostatectomy. However, the long-term impact of these changes in management is unknown (Bostrom, et al., 2015). 

In a review of genomic predictors of outcome in prostate cancer, Bostrom, et al. (2015) noted that the Decipher test, like other gene panels (Prolaris, Oncotype DX Genomic Prostate Score) have been evaluated in terms of potential prognostic value after RP. The future will tell if this additional information is considered sufficient by the urologic community and prostate cancer patients to change practice (Bostrom, et al., 2015; Nguyen, et al., 2015). Bostrom, et al. (2015) commented: “Although clinical studies have suggested potential benefits with these tests, real clinical use and long-term data are needed to judge the added value.”

miRNAs

Maugeri-Sacca et al (2013) stated that prostate cancer is one of the most common causes of cancer-related death.  The management of prostate cancer patients has become increasingly complex, consequently calling on the need for identifying and validating prognostic and predictive biomarkers.  Growing evidence indicates that microRNAs play a crucial role in the pathobiology of neoplastic diseases.  The deregulation of the cellular "miRNome" in prostate cancer has been connected with multiple tumor-promoting activities such as aberrant activation of growth signals, anti-apoptotic effects, pro-metastatic mechanisms, alteration of the androgen receptor pathway, and regulation of the cancer stem cell phenotype.  With the elucidation of molecular mechanisms controlled by microRNAs, investigations have been conducted in an attempt to exploit these molecules in the clinical setting.  Moreover, the multi-faceted biological activity of microRNAs makes them an attractive candidate as anti-cancer agents.  This review summarized the current knowledge on microRNA deregulation in prostate cancer, and the rationale underlying their exploitation as cancer biomarkers and therapeutics.

Yu and Xia (2013) discussed the novel biomarkers of microRNAs in prostate cancer.  The literatures about microRNAs and prostate cancer cited in this review were obtained mainly from PubMed published in English from 2004 to 2012.  Original articles regarding the novel role of microRNAs in prostate cancer were selected.  MicroRNAs play an important role in prostate cancer such as cell differentiation, proliferation, apoptosis, and invasion. Especially microRNAs correlate with prostate cancer cell epithelial-mesenchymal transition (EMT), cancer stem cells (CSCs), drug sensitivity, cancer microenvironment, energy metabolism, androgen independence transformation, and diagnosis prediction.  The authors concluded that microRNAs are involved in various aspects of prostate cancer biology.  Moreover, they state that the role of microRNA in the initiation and development of prostate cancer deserves further study.

Chiam et al (2014) noted that epigenome alterations are characteristic of nearly all human malignancies and include changes in DNA methylation, histone modifications and microRNAs (miRNAs).  However, what induces these epigenetic alterations in cancer is largely unknown and their mechanistic role in prostate tumorigenesis is just beginning to be evaluated.  Identification of the epigenetic modifications involved in the development and progression of prostate cancer will not only identify novel therapeutic targets but also prognostic and diagnostic markers.  This review focused on the use of epigenetic modifications as biomarkers for prostate cancer.

Furthermore, the National Comprehensive Cancer Network’s clinical practice guideline on “Prostate cancer” (Version 1.2014) does not mention the use of RNA/microRNA biomarker as a management tool.

Galectin-3

There has been emerging evidence for galectin-3 in the pathogenesis and progression of prostate cancer.  However, there is insufficient evidence for its impact in screening, diagnosis or management.  National Comprehensive Cancer Network’s clinical practice guideline on “Prostate cancer” (Version 1.2015) as well as its Biomarkers Compendium has no recommendation for galectin-3 in prostate cancer. 

MLH1 promotor methylation

Metcalf et al (2014) stated that colorectal cancer (CRC) that displays high microsatellite instability (MSI-H) can be caused by either germline mutations in mismatch repair (MMR) genes, or non-inherited transcriptional silencing of the MLH1 promoter.  A correlation between MLH1 promoter methylation, specifically the 'C' region, and BRAF V600E status has been reported in CRC studies.  Germline MMR mutations also greatly increase risk of endometrial cancer (EC), but no systematic review has been undertaken to determine if these tumor markers may be useful predictors of MMR mutation status in EC patients.  Endometrial cancer cohorts meeting review inclusion criteria encompassed 2,675 tumors from 20 studies for BRAF V600E, and 447 tumors from 11 studies for MLH1 methylation testing.  BRAF V600E mutations were reported in 4/2,675 (0.1 %) endometrial tumors of unknown MMR mutation status, and there were 7/823 (0.9 %) total sequence variants in exon 11 and 27/1012 (2.7 %) in exon 15.  Promoter MLH1 methylation was not observed in tumors from 32 MLH1 mutation carriers, or for 13 MSH2 or MSH6 mutation carriers.  MMR mutation-negative individuals with tumor MLH1 and PMS2 IHC loss displayed MLH1 methylation in 48/51 (94 %) of tumors.  These researchers had also detailed specific examples that showed the importance of MLH1 promoter region, assay design, and quantification of methylation.  The authors concluded that this review showed that BRAF mutations occurs so infrequently in endometrial tumors they can be discounted as a useful marker for predicting MMR-negative mutation status, and further studies of endometrial cohorts with known MMR mutation status are needed to quantify the utility of tumor MLH1 promoter methylation as a marker of negative germline MMR mutation status in EC patients.

Furthermore, UpToDate reviews on “Endometrial carcinoma: Clinical features and diagnosis” (Chen ad Berek, 2015) and “Overview of endometrial carcinoma” (Plaxe and Mundt, 2015) as well as NCCN’s clinical practice guideline on “Uterine neoplasms” (Version 2.2015) do not mention testing of MLH1 promoter methylation.

p16

p16 is a tumor suppressor gene that regulates cellular proliferation and growth by acting as a cyclin-dependent kinase 4 (CDK4) inhibitor (Chen, et al. 2006). This test determines if a patient has a p16 gene mutation, indicating a predisposition for melanoma and pancreatic cancer.

Chung et al (2014) noted that although p16 protein expression, a surrogate marker of oncogenic human papillomavirus (HPV) infection, is recognized as a prognostic marker in oropharyngeal squamous cell carcinoma (OPSCC), its prevalence and significance have not been well-established in cancer of the oral cavity, hypopharynx, or larynx, collectively referred as non-OPSCC, where HPV infection is less common than in the oropharynx.  p16 expression and high-risk HPV status in non-OPSCCs from RTOG 0129, 0234, and 0522 studies were determined by immunohistochemistry (IHC) and in-situ hybridization (ISH).  Hazard ratios from Cox models were expressed as positive or negative, stratified by trial, and adjusted for clinical characteristics.  p16 expression was positive in 14.1 % (12 of 85), 24.2 % (23 of 95), and 19.0 % (27 of 142) and HPV ISH was positive in 6.5 % (6 of 93), 14.6 % (15 of 103), and 6.9 % (7 of 101) of non-OPSCCs from RTOG 0129, 0234, and 0522 studies, respectively.  Hazard ratios for p16 expression were 0.63 (95 % CI: 0.42 to 0.95; p = 0.03) and 0.56 (95 % CI: 0.35 to 0.89; p = 0.01) for PFS and OS, respectively.  Comparing OPSCC and non-OPSCC, patients with p16-positive OPSCC have better PFS and OS than patients with p16-positive non-OPSCC, but patients with p16-negative OPSCC and non-OPSCC have similar outcomes.  The authors concluded that similar to results in patients with OPSCC, patients with p16-negative non-OPSCC have worse outcomes than patients with p16-positive non-OPSCC, and HPV may also have a role in outcome in a subset of non-OPSCC.  However, these investigators stated that further development of a p16 IHC scoring system in non-OPSCC and improvement of HPV detection methods are needed before broad application in the clinical setting; they noted that additional research using multi-modality testing in non-OPSCC and development of more accurate HPV testing are indicated.

MUC5AC

Ruzzenente et al (2014) stated that mucin 5AC (MUC5AC) is a glycoprotein found in different epithelial cancers, including biliary tract cancer (BTC).  These researchers examined the role of MUC5AC as serum marker for BTC and its prognostic value after operation with curative intent.  From January 2007 to July 2012, a quantitative assessment of serum MUC5AC was performed with enzyme-linked immunoassay in a total of 88 subjects.  Clinical and biochemical data (including CEA and Ca 19-9) of 49 patients with BTC were compared with a control population that included 23 patients with benign biliary disease (BBD) and 16 healthy control subjects (HCS).  Serum MUC5AC was greater in BTC patients (mean 17.93 ± 10.39 ng/ml) compared with BBD (mean 5.95 ± 5.39 ng/ml; p < 0.01) and HCS (mean 2.74 ± 1.35 ng/ml) (p < 0.01).  Multi-variate analysis showed that MUC5AC was related with the presence of BTC compared with Ca 19-9 and CEA: p < 0.01, p = 0.080, and p = 0.463, respectively.  In the BTC group, serum MUC5AC greater than or equal to 14 ng/ml was associated with lymph-node metastasis (p = 0.050) and American Joint Committee on Cancer and International Union for Cancer Control stage IVb disease (p = 0.047).  Moreover, in patients who underwent operation with curative intent, serum MUC5AC greater than or equal to 14 ng/ml was related to a worse prognosis compared with patients with lesser levels, with 3-year survival rates of 21.5 % and 59.3 %, respectively (p = .039).  The authors concluded that MUC5AC could be proposed as new serum marker for BTC.  Moreover, the quantitative assessment of serum MUC5AC could be related to tumor stage and long-term survival in patients with BTC undergoing operation with curative intent.

The authors stated that “Limitations of this study include the lack of data on serum levels of MUC5AC in patients with obstructive jaundice and with premalignant biliary lesions such as hepatolithiasis, sclerosing cholangitis, and choledochal cysts …. Therefore, further studies should be addressed to clarify the diagnostic value of serum MUC5AC also in patients with obstructive jaundice and with premalignant lesions …. Our data should be confirmed by well-designed large-scale prospective studies”. 

Furthermore, NCCN’s clinical practice guideline on “Hepatobiliary cancers” (Version 2.2015) does not mention mucin 5AC (MUC5AC) as a management tool.

Tp53

In a pilot study, Erickson et al (2014) examined if tumor cells could be detected in the vagina of women with serous ovarian cancer through TP53 analysis of DNA samples collected by placement of a vaginal tampon.  Women undergoing surgery for a pelvic mass were identified in the gynecologic oncology clinic.  They placed a vaginal tampon before surgery, which was removed in the operating room.  Cells were isolated and DNA was extracted from both the cells trapped within the tampon and the primary tumor.  In patients with serous carcinoma, the DNA was interrogated for the presence of TP53 mutations using a method capable of detecting rare mutant alleles in a mixture of mutant and wild-type DNA.  A total of 33 patients were enrolled; 8 patients with advanced serous ovarian cancer were included for analysis; and 3 had a prior tubal ligation.  TP53 mutations were identified in all 8 tumor samples.  Analysis of the DNA from the tampons revealed mutations in 3 of the 5 patients with intact tubes (sensitivity 60 %) and in none of the 3 patients with tubal ligation.  In all 3 participants with mutation detected in the tampon specimen, the tumor and the vaginal DNA harbored the exact same TP53 mutation.  The fraction of DNA derived from exfoliated tumor cells ranged from 0.01 % to 0.07 %.  The authors concluded that in this pilot study, DNA derived from tumor was detected in the vaginas of 60 % of patients with ovarian cancer with intact fallopian tubes.  They stated that with further development, this approach may hold promise for the early detection of this deadly disease.  They stated that for this method to ultimately be clinically useful, several factors should be considered -- this approach will have to be shown to be able to adequately detect early states of disease to provide sufficient lead time for an effective intervention.  In this regard, one of the drawbacks of this study was that all samples were obtained from patients with late-stage cancer.  Another limitation was that these researchers did not sequence the DNA from tampons from patients with benign disease.  Thus, specificity could not be calculated.  These investigators stated that larger studies are needed to further validate this method and identify a more precise detection rate.

In an editorial that accompanied the afore-mentioned study, Mulch (2014) stated that “In terms of clinical utility, the sensitivity of this test may be around 60 % in patients with intact tubes and with clinically obvious cancer, but we do not know what it will be in patients with less advanced disease …. However, the barrier to ovarian cancer screening is the fact that the prevalence of the disease is so low in the general population that any screening test must have an unrealistic sensitivity and specificity …. This technology shows great promise …. The technology represented here has the potential to do what other screening tests have not …. We must be careful not to endorse it until its usefulness is fully validated”.

Furthermore, NCCN’s clinical practice guideline on “Ovarian cancers” (Version 3.2014) does not mention TP53 mutation analysis as a management tool.

Zhang et al (2015) summarized the potential diagnostic value of 5 serum tumor markers in esophageal cancer.  These researchers systematically searched PubMed, Embase, Chinese National Knowledge Infrastructure (CNKI) and Chinese Biomedical Database (CBM), through February 28, 2013, without language restriction.  Studies were assessed for quality using QUADAS (quality assessment of studies of diagnostic accuracy).  The positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were pooled separately and compared with overall accuracy measures using diagnostic odds ratios (DORs) and symmetric summary receiver operating characteristic (SROC) curves.  Of 4,391 studies initially identified, 44 eligible studies including 5 tumor markers met the inclusion criteria for the meta-analysis, while meta-analysis could not be conducted for 12 other tumor markers.  Approximately 79.55 % (35/44) of the included studies were of relatively high quality (QUADAS score greater than or equal to 7).  The summary estimates of PLR, NLR and DOR for diagnosing EC were as follows: CEA, 5.94/0.76/9.26; Cyfra21-1 (a cytokeratin 19 fragment), 12.110.59/22.27; p53 antibody, 6.71/0.75/9.60; squamous cell carcinoma antigen (SCC-Ag), 7.66/0.68/12.41; and vascular endothelial growth factor C (VEGF-C), 0.74/0.37/8.12.  The estimated SROC curves showed that the performance of all 5 tumor markers was reasonable.  The authors concluded that the current evidence suggested that CEA, Cyfra21-1, p53, SCC-Ag and VEGF-C have a potential diagnostic value for esophageal carcinoma.

Ki67

There is a strong correlation between proliferation rate and clinical outcome in a variety of tumor types and measurement of cell proliferative activity is an important prognostic marker (Chen, et al., 2006). This marker correlates with flow cytometric S-phase.

There is insufficient evidence for Ki67. NCCN guidelines on breast cancer (2015) state: "The measurement of nuclear antigen, Ki-67 by IHC, gives an estimate of the tumor cells in the proliferative phase (G1, G2 and M phases) of the cell cycle. Studies have demonstrated the prognostic value of Ki-67 as a biomarker and its usefulness in predicting response and clinical outcome. One small study suggests that measurement of Ki-67 after short-term exposure to endocrine treatment may be useful to select patients resistant to endocrine therapy and those who may benefit from additional interventions. However, these data require larger analytic and clinical validation. In addition, standardization of tissue handling and processing is required to improve the reliability and value of Ki-67 testing. At this time, there is no conclusive evidence that Ki-67 alone, especially baseline Ki-67 as an individual biomarker, helps to select the type of endocrine therapy for an individual patient. Therefore, the NCCN Breast Cancer Panel does not currently recommend assessment of Ki-67.”

The p16/KI-67 Dual Stain test (CINtec PLUS) claims to detect virally induced oncogenic molecular changes in the cell through the immune cytochemical double staining of the tumor suppressor gene p16INK4a and the proliferation marker Ki-67 and thereby to improve the triage of women with equivocal cytological results (Kisser, et al., 2014). The Ludwig Boltzmann Institut conducted a systematic review of studies assessing utlity of the p16/Ki-67 Dual Stain test in the triage of equivocal or mild to moderate dysplasia results in cervical cancer screening. The authors of the assessment stated that they could not identify any studies assessing clinical outcomes such as mortality or morbidity and only one high quality study assessing diagnostic accuracy of the test: the evaluation of the clinical utility of the test was therefore not possible (Kisser, et al., 2014). Consequently the test was not recommended for inclusion in the benefits catalogue of public health insurances.

Veristrat

NCCN guidelines on non-small cell lung cancer (NCCN, 2015) recommend proteomic testing for patients with NSCLC and wild-type EGFR or with unknown EGFR status. The guidelines state that a patient with a “poor” classification should not be offered erlotinib in the second-line setting. For support, NCCN guidelines reference a study by Gregorc, et al. (2014), who reported that serum protein test status (Veristrat) is predictive of differential benefit in overall survival for erlotinib versus chemotherapy in the second-line setting, and that patients classified as likely to have a poor outcome have better outcomes on chemotherapy than on erlotinib. From Feb 26, 2008, to April 11, 2012, patients (aged ≥18 years) with histologically or cytologically confirmed, second-line, stage IIIB or IV non-small-cell lung cancer were enrolled in 14 centrers in Italy. Patients were stratified according to a minimization algorithm by Eastern Cooperative Oncology Group performance status, smoking history, center, and masked pretreatment serum protein test classification, and randomly assigned centrally in a 1:1 ratio to receive erlotinib (150 mg/day, orally) or chemotherapy (pemetrexed 500 mg/m2, intravenously, every 21 days, or docetaxel 75 mg/m2, intravenously, every 21 days). The proteomic test classification was masked for patients and investigators who gave treatments, and treatment allocation was masked for investigators who generated the proteomic classification. The primary endpoint was overall survival and the primary hypothesis was the existence of a significant interaction between the serum protein test classification and treatment. Analyses were done on the per-protocol population.  Investigators randomly assigned 142 patients to chemotherapy and 143 to erlotinib, and 129 (91%) and 134 (94%), respectively, were included in the per-protocol analysis. 88 (68%) patients in the chemotherapy group and 96 (72%) in the erlotinib group had a proteomic test classification of good. Median overall survival was 9·0 months (95% CI 6·8–10·9) in the chemotherapy group and 7·7 months (5·9–10·4) in the erlotinib group. The investigators noted a significant interaction between treatment and proteomic classification (pinteraction = 0·017 when adjusted for stratification factors; pinteraction=0·031 when unadjusted for stratification factors). The investigators found that patients with a proteomic test classification of poor had worse survival on erlotinib than on chemotherapy (hazard ratio 1·72 [95% CI 1·08–2·74], p=0·022). There was no significant difference in overall survival between treatments for patients with a proteomic test classification of good (adjusted HR 1·06 [0·77–1·46], p=0·714). In the group of patients who received chemotherapy, the most common grade 3 or 4 toxic effect was neutropenia (19 [15%] vs one [<1%] in the erlotinib group), whereas skin toxicity (one [<1%] vs 22 [16%]) was the most frequent in the erlotinib group.

Multiplex testing for myeloid hematopathologic disorders

Multiplex testing/next generation sequencing can assist in the diagnosis of various myeloid hematopathologic disorders, particularly myelodysplastic syndrome (MDS). The International Consensus Working Group (ICWG) (Valent, et al., 2007) recommends that minimal diagnostic criteria for MDS include: A) Prerequisite criteria, including stable cytopenia in one or more cell line, and exclusion of other potential disorders as a primary reason for dysplasia and/or cytopenia; B) MDS-related (decisive) criteria, including significant dysplasia, a blast count of 5-19%, and/or specific MDS cytogenetic abnormalities; and co-criteria for patients fulfilling A) but not B), including clear signs of a monoclonal population utilizing molecular markers (such as DNA mutations) or flow cytometry, or markedly reduced colony formation. In addition, many of the genes have independent prognostic value in various myeloid malignancies including ASXL1, RUNX1, ETV6, EZH2, TP53 in multivariable analysis in MDS. Other critical disease genes such as DNMT3A, CBL, IDH2, IDH1, SRSF2, ZRSR2, NRAS, U2AF1, and SF3B1 have also been shown to be independent predictors of survival in MDS as well as ASXL1, SRSF2, CBL, and IDH2 in chronic myelomonocytic leukemia (CMML), IDH1/2, EZH2, SRSF2, ASXL1 in primary myelofibrosis (PMF), and SETBP1 in atypical chronic myeloid leukemia (aCML).

CancerNext

CancerNext™ (Ambry Genetics) utilizes next generation sequencing to offer a comprehensive testing panel for hereditary colon cancer and targets detection of mutations in 22 genes (APC, BMPR1A, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH, PMS2, PTEN, SMAD4, STK11, and TP53) (Raman, et al., 2013). Gross deletion/duplication analysis is performed for all 22 genes. CancerNext™ is a next-generation cancer panel that simultaneously analyzes selected genes associated with a wide range of cancers. While mutations in each gene on this panel may be individually rare, they may collectively account for a significant amount of hereditary cancer susceptibility.

OvaNext 

OvaNext (Ambry Genetics) is a next generation (next-gen) sequencing panel that simultaneously analyses 19 genes that contribute to increased risk for breast, ovarian, and/or uterine cancers (Raman, et al., 2013). The test is intended to determine if a woman has an increase chance of developing breast, ovarian, and/or uterus cancer.

BreastNext

BreastNext utilizes next generation sequencing to offer a comprehensive testing panel for hereditary breast and/or ovarian cancer and targets detection of mutations in 14 genes (ATM, BARD1, BRIP1, CDH1, CHEK2,MRE11A, MUTYH, NBN, PALB2, PTEN, RAD50, RAD51C, STK11 and TP53), excluding BRCA1 and BRCA2 (Raman, et al., 2013). Gross deletion/duplication analysis is performed for all 14 genes. Mutations in BRCA1 and BRCA2 explain hereditary breast cancer occurrence ~25–50% of the time, additional genes associated with hereditary breast cancer are emerging. Studies suggest that mutations in the genes on the BreastNext™ panel may confer an estimated 25–70% lifetime risk for breast cancer.

ColoNext

ColoNext™ (Ambry Genetics) utilizes next generation sequencing to offer a comprehensive testing panel for hereditary colon cancer and targets detection of mutations in 14 genes (APC, BMPR1A, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH, PMS2, PTEN, SMAD4, STK11, and TP53) (Raman, et al., 2013). Gross deletion/duplication analysis is performed for all 14 genes. ColoNext™ is a next-generation cancer panel that simultaneously analyzes selected genes associated with a wide range of cancers. While mutations in each gene on this panel may be individually rare, they may collectively account for a significant amount of hereditary cancer susceptibility.

Coloseq

ColoSeq™ (University of Washington Laboratory Medicine Genetics Lab) is a comprehensive genetic test for hereditary colon cancer that uses next-generation sequencing to detect mutations in multiple genes associated with Lynch syndrome (hereditary non-polyposis colorectal cancer, HNPCC), familial adenomatous polyposis (FAP), MUTYH-associated polyposis (MAP), hereditary diffuse gastric cancer (HDGC), Cowden syndrome, Li-Fraumeni syndrome, Peutz-Jeghers syndrome, Muir-Torre syndrome, Turcot syndrome, and Juvenile Polyposis syndrome (Raman, et al., 2013). The assay sequences all exons, introns, and flanking sequences of the 13 genes. Large deletions, duplications, and mosaicism are also detected by the assay and reported.

ResponseDx

ResponseDX: Colon® (Response Genetics) panel utilizes testing of multiple genes including KRAS mutation, BRAF mutation, ERCC1 expression, MSI, c-Met expression, EGFR expression, VEGFR2 expression, NRAS mutation, PIK3CA mutation, and Thymidylate synthetase (Raman, et al., 2013).  The test predicts disease prognosis and selects patients who might benefit from alternative therapies and aids in selection of metastatic colorectal cancer patients that might benefit from EGFR-targeted monoclonal antibody therapies.

ResponseDX:Lung® panel (Response Genetics) utilizes testing of multiple genes including ROS1 rearrangements, EGFR mutation, EML4-ALK rearrangement, ALK, ERCC1 expression, RRM1 expression, c-MET expression, TS expression, KRAS mutation, and PIK3CA mutation (Raman, et al., 2013) The test is used in patients with non-small cell lung cancer who are being considered for treatment with the tyrosine kinase inhibitor (TKI) Crizotinib.

ResponseDX:Melanoma® panel (Response Genetics) utilizes testing of multiple genes including BRAF mutation, and NRAS mutation (Raman, et al., 2013). The test is performed on formalin-fixed, paraffin embedded (FFPE) biopsy specimen, using fluorescence in situ hybridization (FISH) and polymerase chain reaction (PCR). The test is intended for patients with melanoma who are being considered for treatment with the tyrosine kinase inhibitor (TKI) and EGFR antagonists cetuximab and panitumumab. 

ResponseDX: Gastric® panel (Response Genetics) utilizes testing of multiple genes including HER2 gene amplification, ERCC1 expression, and Thymidilate Synthetase expression (Raman, et al., 2013). This is a PCR-based test performed on formalin-fixed, paraffin-embedded biopsy specimens.   Amplification of the HER2 gene is associated with increased disease recurrence and a worse prognosis. ERCC1 expression predicts the best therapeutic combination of agents including platinum and select patients who might benefit from platinum-based therapies. Thymidylate synthetase (TS) expression predicts the best therapeutic combination of agents including pemetrexed or 5-FU and select patients who might benefit from pemetrexed-based therapies.

Panexia

PANEXIA® (Myriad Genetics) detects mutations in genes that result in an increased risk of pancreatic cancer, offering insight about the risk of future hereditary cancers for patients and their families (Raman, et al., 2013). PANEXIA, via a simple blood test, analyzes the PALB2 and BRCA2 genes, the two genes most commonly identified in families with hereditary pancreatic cancer. The PANEXIA test results provide information for patients and their family members about the inherited risks of pancreatic cancer as well as breast, ovarian, and other cancers. This knowledge may allow at-risk family members the opportunity to lower their risks for some of these cancers through surveillance, preventative options, or lifestyle choices. The test is intended to determine if a person has an increase risk of developing pancreatic and/or breast cancer. The test determines the presence of the PALB2 and BRCA2 genes. The results of the test enable the development of a patient-specific medical management plan to reduce the risk of cancer.

Glossary of Terms:

a2-PAG Pregnancy-associated alpha2 glycoprotein
BCM Breast cancer mucin
BTA Bladder tumor antigen
CA19-9 Cancer antigen 19-9
CA50 Cancer antigen 50
CA72-4 Cancer antigen 72-4
CA195 Cancer antigen 195
CA242 Cancer antigen 242
CA549 Cancer antigen 549
CA-SCC Squamous cell carcinoma
CAM17-1 Monoclonal antimucin antibody 17-1
CAM26 Monoclonal antimucin antibody 26
CAM29 Monoclonal antimucin antibody 29
CAR3 Antigenic determinant recognized by monoclonal antibody AR3
DU-PAN-2 Sialylated carbohydrate antigen DU-PAN-2
FDP Fibrin/fibrinogen degradation products
GCC Guanylyl cyclase C
MCA Mucin-like carcinoma-associated antigen
NMP22 Nuclear matrix protein22
NSE Neuron-specific enolase
PLAP Placental alkaline phosphatase
PNA-ELLA Peanut lectin-bonding assay
SLEX Sialylated Lewis X-antigen
SLX Sialylated SSEA-1 antigen
SPAN-1 Sialylated carbonated antigen SPAN-1
ST-439 Sialylated carbonated antigen ST-439
TAG12 Tumor-associated glycoprotein 12
TAG72 Tumor-associated glycoprotein 72
TAG72.3 Tumor-associated glycoprotein 72.3
TATI Tumor-associated trypsin inhibitor
TNF-a Tumor necrosis factor alpha
TPA Tissue polypeptide antigen
CPT Codes / HCPCS Codes / ICD-9 Codes
Prostate-specific antigen (PSA):
CPT codes covered if selection criteria are met:
84152 Prostate specific antigen (PSA);complexed (direct measurement)
84153     total
84154     free
CPT codes not covered for indications listed in the CPB:
81313 PCA3/KLK3 (prostate cancer antigen 3 [non-protein coding]/kallikrein-related peptidase 3 [prostate specific antigen]) ratio (eg, prostate cancer)
HCPCS codes covered if selection criteria are met:
G0103 Prostate cancer screening; prostate specific antigen test (PSA)
HCPCS codes not covered for indications listed in the CPB:
S3721 Prostate cancer antigen 3 (PCA3) testing
ICD-9 codes covered if selection criteria are met:
185 Malignant neoplasm of prostate
233.4 Carcinoma in situ of prostate
236.5 Neoplasm of uncertain behavior of prostate
790.93 Elevated prostate specific antigen (PSA)
V10.46 Personal history of malignant neoplasm of prostate
V76.44 Special screening for malignant neoplasm of prostate
Carcinoembryonic antigen (CEA):
CPT codes covered if selection criteria are met:
82378 Carcinoembryonic antigen (CEA)
ICD-9 codes covered if selection criteria are met:
153.0 - 154.1 Malignant neoplasm of colon and rectum
157.0 - 157.9 Malignant neoplasm of pancreas
211.6 Benign neoplasm of pancreas, except Islets of Langerhans
211.7 Benign neoplasm of Islets of Langerhans
230.3 Carcinoma in situ of colon
577.2 Cyst and pseudocyst of pancreas
V10.05 Personal history of malignant neoplasm of large intestine
V10.06 Personal history of malignant neoplasm of rectum, rectosigmoid junction, and anus
ICD-9 codes not covered for indications listed in the CPB:
150.0 - 150.9 Malignant neoplasm of esophagus
162.2 - 162.9 Malignant neoplasm of bronchus and lung
174.0 - 175.9 Malignant neoplasm of breast
217 Benign neoplasm of breast
231.2 Carcinoma in situ of bronchus and lung
233.0 Carcinoma in situ of breast
238.3 Neoplasm of uncertain behavior of breast
239.3 Neoplasm of unspecified nature of breast
V76.0 Special screening for malignant neoplasm of respiratory organs
V76.10 Breast screening for malignant neoplasms, unspecified
V76.19 Other screening breast examination for malignant neoplasms
V76.41 Special screening for malignant neoplasm of rectum
V76.51 Special screening for malignant neoplasm of colon
Other ICD-9 codes related to the CPB:
795.81 Elevated carcinoembryonic antigen [CEA]
Adenomatous polyposis coli (APC):
CPT codes covered if selection criteria are met:
81201 - 81203 APC (adenomatous polyposis coli) (eg, familial adenomatosis polyposis [FAP], attenuated FAP) gene analysis
ICD-9 covered if selection criteria are met:
211.3 Benign neoplasm of colon
238.1 Neoplasm of uncertain behavior of connective and other soft tissue
V18.51 Family history, colonic polyps [familial adenomatous polyposis]
Afirma Thyroid FNA analysis:
No specific code
ICD-9 covered if selection criteria are met:
237.4 Neoplasm of uncertain behavior of other and unspecified endocrine glands [indeterminate thyroid nodules]
FISH assay of the BCR/ABL gene:
CPT codes covered if selection criteria are met:
81206 - 81208 BCR/ABL1 (t(9;22)) (eg, chronic myelogenous leukemia) translocation analysis
88271 Molecular cytogenetics; DNA probe, each (eg, FISH)
88275     interphase in situ hybridization, analyze 100-300 cells
ICD-9 codes covered if selection criteria are met:
200.10 - 200.18 Lymphosarcoma [Lymphoblastic lymphoma]
204.00 - 204.02 Acute lymphoid leukemia
205.00 - 205.02 Myeloid leukemia, acute
205.10 - 205.12 Chronic myeloid leukemia
Cancer antigen 125 (CA 125):
CPT codes covered if selection criteria are met:
86304 Immunoassay for tumor antigen, quantitative; CA 125
ICD-9 codes covered if selection criteria are met:
183.0 Malignant neoplasm of ovary
199.1 Malignant neoplasm without specification of site, other
236.2 Neoplasm of uncertain behavior of ovary
V10.43 Personal history of malignant neoplasm of ovary
V16.41 Family history of malignant neoplasm of ovary
ICD-9 codes not covered for indications listed in the CPB:
V76.41 Special screening for malignant neoplasm of rectum
V76.46 Special screening for malignant neoplasm of ovary
V76.51 Special screening for malignant neoplasm of colon
Other ICD-9 codes related to the CPB:
795.82 Elevated cancer antigen 125 [CA 125]
Serial measurements of CA 15-3 (also known as CA 27-29 or Truquant RIA):
CPT codes covered if selection criteria are met:
86300 Immunoassay for tumor antigen, quantitative; CA 15-3 (27.29)
ICD-9 codes covered if selection criteria are met:
174.0 - 174.9 Malignant neoplasm of the female breast
233.0 Carcinoma in situ of breast
V10.3 Personal history of malignant neoplasm of breast
ICD-9 codes not covered for indications listed in the CPB:
V76.10 Breast screening, unspecified
CA 19-9:
CPT codes covered if selection criteria are met:
86301 Immunoassay for tumor antigen, quantitative; CA 19-9
ICD-9 codes covered if selection criteria are met:
151.0 - 151.9 Malignant neoplasm of stomach [not covered for gastro-esophageal cancer]
153.5 Malignant neoplasm of appendix vermiformis [mucinous appendiceal carcinoma]
155.1 Malignant neoplasm of intrahepatic bile ducts [cholangiocarcinoma]
156.0 - 156.9 Malignant neoplasm of gallbladder and extrahepatic bile ducts
157.0 - 157.9 Malignant neoplasm of pancreas
230.2 Carcinoma in situ of stomach
230.8 Carcinoma in situ of liver and biliary system [covered for gallbladder and bile duct]
230.9 Carcinoma in situ of other and unspecified digestive organs
V10.04 Personal history of malignant neoplasm of stomach
V10.09 Personal history of malignant neoplasm of gastrointestinal tract, other
V49.83 Awaiting organ transplant status [liver transplant]
ICD-9 codes not covered for indications listed in the CPB (not all-inclusive):
150.0 - 150.9 Malignant neoplasm of esophagus
153.0 - 154.1 Malignant neoplasm of colon and rectum
155.0, 155.2 Malignant neoplasm of liver [primary and not specified as primary or secondary]
174.0 - 175.9 Malignant neoplasm of the breast
179 - 182.8 Malignant neoplasm of uterus
230.3 Carcinoma in situ of colon
230.8 Carcinoma in situ of liver and biliary system [not covered for liver]
233.0 Carcinoma in situ of breast
577.2 Cyst and pseudocyst of pancreas
Other ICD-9 codes related to the CPB:
576.1 Cholangitis [primary sclerosing] [only covered for persons undergoing liver transplantation]
Cardioembryonic antigen cellular adhesion modecule-7 (CEACAM-7):
There is no specific code for Cardioembryonic antigen cellular adhesion molecule-7 (CEACAM-7)
ICD-9 codes not covered if selection criteria are met:
154.0 - 154.8 Malignant neoplasm of rectum, rectosigmoid junction and anus
230.4 Carcinoma in situ of digestive organs (rectum)
V10.06 Personal history of malignant neoplasm of rectum, rectosigmoid junction, and anus
Caris Target Now Molecular Profiling Test:
No specific code
Cyfra21-1 (a cytokeratin 19 fragment,) p53, & Squamous cell carcinoma antigen (SCC-Ag):
No specific code
ICD-9 codes not covered for indications listed in the CPB:
150.0 - 150.9 Malignant neoplasm of esophagus
Vascular endothelial growth factor C (VEGF-C):
No specific code
ICD-9 codes not covered for indications listed in the CPB:
150.0 - 150.9 Malignant neoplasm of esophagus
Human epidermal growth factor receptor 2 (HER2) evaluation:
CPT codes covered if selection criteria are met:
83950 Oncoprotein; Her-2/neu
ICD-9 codes covered if selection criteria are met:
150.0 - 150.9 Malignant neoplasm of esophagus
151.0 - 151.9 Malignant neoplasm of stomach
174.0 - 175.9 Malignant neoplasm of breast [see criteria]
IGH@ (Immunoglobulin heavy chain locus):
CPT codes covered if selection criteria are met:
81261 IGH@ (Immunoglobulin heavy chain locus) (eg, leukemias and lymphomas, B-cell), gene rearrangement analysis to detect abnormal clonal population(s); amplified methodology (eg, polymerase chain reaction)
ICD-9 codes covered if selection criteria are met:
200.00 - 202.98 Malignant neoplasm of lymphatic and hematopoietic tissue [non- hodgkin lymphoma, code range includes hairy-cell leukemia]
IGK@ (Immunoglobulin kappa light chain locus):
CPT codes covered if selection criteria are met:
81264 IGK@ (Immunoglobulin kappa light chain locus) (eg, leukemia and lymphoma, B-cell), gene rearrangement analysis, evaluation to detect abnormal clonal population(s)
ICD-9 codes covered if selection criteria are met:
200.00 - 202.98 Malignant neoplasm of lymphatic and hematopoietic tissue [non-hodgkin lymphoma]
277.30 - 277.39 Amyloidosis [systemic light chain]
Serial measurements of human chorionic gonadotropin (HCG):
CPT codes covered if selection criteria are met:
84702 Gonadotropin, chorionic (hCG); quantitative
ICD-9 codes covered if selection criteria are met:
181 Malignant neoplasm of placenta (e.g., choriocarcinoma)
183.0 Malignant neoplasm of ovary
186.0 - 186.9 Malignant neoplasm of testis
196.1 Secondary malignant neoplasm of intrathoracic lymph nodes [mediastinal nodes]
233.39 Carcinoma in situ of other and unspecified female genital organs [germinal cell tumors (teratocarcinoma and embryonal cell carcinoma) of the ovaries]
233.6 Carcinoma in situ of other and unspecified male genital organs
236.1 Neoplasm of uncertain behavior of placenta
630 Hydatidiform mole
V10.43 Personal history of malignant neoplasm of ovary
V10.47 Personal history of malignant neoplasm of testis
Serial measurements of AFP to diagnose germ cell tumors or the diagnosis and monitoring of hepatocellular carcinoma:
CPT codes covered if selection criteria are met:
82105 Alpha-fetoprotein (AFP); serum
ICD-9 codes covered if selection criteria are met:
155.0 - 155.2 Malignant neoplasm of the liver and intrahepatic bile ducts
183.0 Malignant neoplasm of ovary
186.0 - 186.9 Malignant neoplasm of testis
196.1 Secondary malignant neoplasm of intrathoracic lymph nodes [mediastinal nodes]
230.8 Carcinoma in situ of liver and biliary system
233.39 Carcinoma in situ of other and unspecified female genital organs [germ cell tumors]
233.6 Carcinoma in situ of other and unspecified male genital organs
V10.43 Personal history of malignant neoplasm of ovary
V10.47 Personal history of malignant neoplasm of testis
V76.49 Special screening for malignant neoplasm of other sites
V76.89 Special screening for malignant neoplasm, other
ICD-9 codes not covered for indications listed in the CPB (not all-inclusive):
181 Malignant neoplasm of placenta (e.g., choriocarcinoma)
236.1 Neoplasm of uncertain behavior of placenta
630 Hydatidiform mole
Serial measurements of AFP and HCG together to diagnose and monitor testicular cancer:
CPT codes covered if selection criteria are met:
82105 Alpha-fetoprotein (AFP); serum
84702 Gonadotropin, chorionic (hCG); quantitative
ICD-9 codes covered if selection criteria are met:
186.0 - 186.9 Malignant neoplasm of testis
233.6 Carcinoma in situ of other and unspecified male genital organs
V76.45 Special screening for malignant neoplasm of testis
Measurement of estrogen and progesterone receptors and steroid receptor status:
CPT codes covered if selection criteria are met:
84233 Receptor assay; estrogen
84234     progesterone
ICD-9 codes covered if selection criteria are met:
174.0 - 175.9 Malignant neoplasm of breast
233.0 Carcinoma in situ of breast
Other ICD-9 codes related to the CPB:
627.2 Symptomatic menopausal or female climacteric states
V49.81 Asymptomatic postmenopausal status (age-related) (natural)
Targeted hematologic genomic sequencing panel (5-50 genes) for myelodysplastic syndromes:
CPT codes covered if selection criteria are met:
81450 Targeted genomic sequence analysis panel, hematolymphoid neoplasm or disorder, dna and rna analysis when performed, 5-50 genes (eg, braf, cebpa, dnmt3a, ezh2, flt3, idh1, idh2, jak2, kras, kit, mll, nras, npm1, notch1), interrogation for sequence variants, and copy number variants or rearrangements, or isoform expression or mrna expression levels, if performed
ICD-9 codes covered if selection criteria are met:
238.72 - 238.75 Myelodysplastic syndromes
Targeted hematologic genomic sequencing panel (5-50 genes) for non-small cell lung cancer:
CPT codes covered if selection criteria are met:
81445 Targeted genomic sequence analysis panel, solid organ neoplasm, dna analysis, 5-50 genes (eg, alk, braf, cdkn2a, egfr, erbb2, kit, kras, nras, met, pdgfra, pdgfrb, pgr, pik3ca, pten, ret), interrogation for sequence variants and copy number variants or rearrangements, if performed
ICD-9 codes covered if selection criteria are met:
162.2 - 162.9 Malignant neoplasm of bronchus and lung [non-small cell]
TCB@ (T cell antigen receptor, beta):
CPT codes covered if selection criteria are met:
81340 TRB@ (T cell antigen receptor, beta) (eg, leukemia and lymphoma), gene rearrangement analysis to detect abnormal clonal population(s); using amplification methodology (eg, polymerase chain reaction) [TCB@]
81341  :   using direct probe methodology (eg, Southern blot) [TCB@]
ICD-9 codes covered if selection criteria are met:
204.00 - 204.92 Lymphoid leukemia [T-cell prolymphocytic leukemia]
ThyGenX (formerly MirInform Thyroid) and Thyroseq:
No specific code
ICD-9 codes covered if selection criteria are met:
241.0 - 241.9 Nontoxic nodular goiter [thyroid nodules]
K-ras (KRAS) with BRAF reflex testing:
CPT codes covered if selection criteria are met:
81210 BRAF (v-raf murine sarcoma viral oncogene homolog B1) (eg, colon cancer), gene analysis, V600E variant
81275 KRAS (v-Ki-ras2 Kirsten rat sarcoma viral oncogene) (eg, carcinoma) gene analysis, variants in codons 12 and 13
Other CPT codes related to the CPB:
88363 Examination and selection of retrieved archival (ie, previously diagnosed) tissue(s) for molecular analysis (eg, KRAS mutational analysis)
Other HCPCS codes related to the CPB:
J9055 Injection, cetuximab, 10 mg [to predict non-response to cetuximab (Erbitux) and panitumumab (Vectibix) in the treatment of anal adenocarcinoma]
J9303 Injection, panitumumab, 10 mg [to predict non-response to cetuximab (Erbitux) and panitumumab (Vectibix) in the treatment of anal adenocarcinoma]
ICD-9 codes covered if selection criteria are met:
152.0 - 152.9 Malignant neoplasm of small intestine, including duodenum [small bowel adenocarcinoma]
153.0 - 154.1 Malignant neoplasm of colon, rectum and rectosigmoid junction [metastatic colorectal cancer]
154.2 - 154.3 Malignant neoplasm of anal canal and anus [anal adenocarcinoma]
162.2 - 162.9 Malignant neoplasm of trachea, bronchus, and lung
211.4 Benign neoplasm of rectum and anal canal [if KRAS nonmutated] [Lynch syndrome (HNPCC)]
230.4 Carcinoma in situ of rectum [if KRAS nonmutated] [Lynch syndrome (HNPCC)]
MLH1, MSH2, MSH6:
CPT codes covered if selection criteria are met:
81292 - 81294 MLH1 gene analysis
81295 - 81297 MSH2 gene analysis
81298 - 81300 MSH6 gene analysis
ICD-9 codes covered if selection criteria are met:
153.0 - 153.9 Malignant neoplasm of colon [Lynch syndrome (HNPCC)] [all persons with Stage 2 colon cancer]
154.0 - 154.8 Malignant neoplasm of rectum, rectosigmoid junction, and anus [Lynch syndrome (HNPCC)] [all persons with Stage 2 colon cancer] [under age 50]
211.4 Benign neoplasm of rectum and anal canal [under age 50]
230.4 Carcinoma in situ of rectum [under age 50]
ALK Gene Fusion:
No specific code
ICD-9 codes covered if selection criteria are met:
162.2 - 162.9 Malignant of neoplasm of bronchus and lung [non-small-cell lung cancer]
ALK Gene Rearrangement:
No specific code
ICD-9 codes covered if selection criteria are met:
200.70 - 200.78 Large cell lymphoma [B cell]
202.70 - 202.78 Peripheral T-cell lymphoma
238.77 Post-transplant lymphoproliferative disorder (PTLD)
ALK Translocations :
No specific code
Other CPT codes related to CPB:
81401 Molecular pathology procedure, Level 2 (eg, 2-10 SNPs, 1 methylated variant, or 1 somatic variant [typically using nonsequencing target variant analysis], or detection of a dynamic mutation disorder/triplet repeat) (EML4/ALK inv(2)) (eg, non-small-cell lung cancer), translocation or inversion analysis
ICD-9 codes covered if selection criteria are met:
162.2 - 162.9 Malignant of neoplasm of bronchus and lung [non-small-cell lung cancer]
Urokinase plasminogen activator (uPA) and plasminogen activator inhibitor 1 (PAI-1):
CPT codes covered if selection criteria are met:
85415 Fibrinolytic factors and inhibitors; plasminogen activator
ICD-9 codes covered if selection criteria are met:
174.0 - 175.9 Malignant neoplasm of breast [node negative]
233.0 Carcinoma in situ of breast
Veristrat:
No specific code
ICD-9 codes covered if selection criteria are met:
162.2 - 162.9 Malignant neoplasm of bronchus and lung [for persons with advanced NSCLC, whose tumors are without EGFR and ALK mutations, who have progressed after at least one chemotherapy regimen, and for whom erlotinib is considered an appropriate treatment]
CD 117 (c-kit):
CPT codes covered if selection criteria are met:
88184 Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185     each additional marker (List separately in addition to code for first marker)
ICD-9 codes covered if selection criteria are met:
[for determining eligibility for treatment with Gleevac]
150.0 - 159.9 Malignant neoplasm of esophagus
205.10 - 205.12 Chronic myeloid leukemia
CD 20:
CPT codes covered if selection criteria are met:
88184 Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185     each additional marker (List separately in addition to code for first marker)
ICD-9 codes covered if selection criteria are met:
[for determining eligibility for treatment with Rituxan]
200.00 - 202.98 Lymphosarcoma and reticulosarcoma and other specified malignant tumors of lymphatic tissue, hodgkin's disease, and other malignant neoplasms of lymphoid and histiocytic tissue
204.10 - 204.12 Chronic lymphoid leukemia
CD 25:
CPT codes covered if selection criteria are met:
88184 Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185     each additional marker (List separately in addition to code for first marker)
ICD-9 codes covered if selection criteria are met:
[for determining eligibility for treatment with Ontak]
202.10 - 202.18 Mycosis fungoides
202.20 - 202.28 Sezary's disease
202.70 - 202.78 Peripheral T-cell lymphoma
CD 31:
No specific code
Other CPT codes related to the CPB:
88341 - 88344 Immunohistochemistry or immunocytochemistry, per specimen
Other HCPCS codes related to the CPB:
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
ICD-9 codes covered if selection criteria are met:
171.0 - 171.9 Malignant neoplasm of connective and other soft tissue [angiosarcoma]
CD 33:
CPT codes covered if selection criteria are met:
88184 Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185     each additional marker (List separately in addition to code for first marker)
ICD-9 codes covered if selection criteria are met:
[for determining eligibility for treatment with Mylotarg]
204.00 - 204.02 Acute lymphoid leukemia
205.00 - 205.02 Acute myeloid leukemia
206.00 - 206.02 Acute monocytic leukemia
207.00 - 207.02 Acute erythremia and erythroleukemia
208.00 - 208.02 Acute leukemia of unspecified cell type
CD 52:
CPT codes covered if selection criteria are met:
88184 Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185     each additional marker (List separately in addition to code for first marker)
ICD-9 codes covered if selection criteria are met:
[for determining eligibility for treatment with Campath]
200.20 - 200.48 Burkitt's tumor or lymphoma, marginal zone lymphoma, or mantle cell lymphoma
200.70 - 200.78 Large cell lymphoma
202.00 - 202.88 Other malignant neoplasms of lymphoid and histiocytic tissue
204.10 - 204.12 Chronic lymphoid leukemia
Cyclin D1:
CPT codes covered if selection criteria are met:
81401 Molecular pathology procedure, Level 2 (eg, 2-10 SNPs, 1 methylated variant, or 1 somatic variant [typically using nonsequencing target variant analysis], or detection of a dynamic mutation disorder/triplet repeat) (EML4/ALK inv(2)) (eg, non-small-cell lung cancer), translocation or inversion analysis
ICD-9 codes covered if selection criteria are met:
200.40 - 200.48 Mantle cell lymphoma [diagnosing and predicting disease recurrence]
ICD-9 codes not covered if selection criteria are met:
173.02, 173.12, 173.22, 173.32, 173.42 Squamous cell carcinoma of lip, eyelid including canthus, ear and external auditory canal, face scalp and skin of neck
Fas-Associated Protein with Death Domain FADD:
No specific code
ICD-9 codes not covered if selection criteria are met:
173.02, 173.12, 173.22, 173.32, 173.42 Squamous cell carcinoma of lip, eyelid including canthus, ear and external auditory canal, face scalp and skin of neck
Prostate PX, Post-op PX:
Other CPT codes related to the CPB:
88305 Level IV - Surgical pathology, gross and microscopic examination
88313 Special stain including interpretation and report; Group II, all other (eg, iron, trichrome), except stain for microorganisms, stains for enzyme constituents, or immunocytochemistry and immunohistochemistry
88323 Consultation and report on referred material requiring preparation of slides
88341 - 88344 Immunohistochemistry or immunocytochemistry, per specimen
88347 Immunofoluorescent study, each antibody; indirect method
Other HCPCS codes related to the CPB:
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
ICD-9 codes not covered for indications listed in the CPB:
185 Malignant neoplasm of prostate
NRAS mutation:
Other CPT codes related to the CPB:
81404 Molecular pathology procedure, Level 5 (eg, analysis of 2-5 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 6-10 exons, or characterization of a dynamic mutation disorder/triplet repeat by Southern blot analysis)
Ras oncogenes (except KRASand BRAF):
There is no specific code for ras oncogenes
Epidermal growth factor receptor (EGFR) Testing:
CPT codes covered if selection criteria are met:
81235 EGFR (epidermal growth factor receptor) (eg, non-small cell lung cancer) gene analysis, common variants (eg, exon 19 LREA deletion, L858R, T790M, G719A, G719S, L861Q)
Other CPT codes related to the CPB:
88271 Molecular cytogenetics; DNA probe, each (eg, FISH)
88275     interphase in situ hybridization, analyze 100-300 cells
88291 Cytogenetics and molecular cytogenetics, interpretation and report
88313 Special stain including interpretation and report; Group II, all other (eg, iron, trichrome), except stain for microorganisms, stains for enzyme constituents, or immunocytochemistry and immunohistochemistry
88323 Consultation and report on referred material requiring preparation of slides
88341 - 88344 Immunohistochemistry or immunocytochemistry, per specimen
88358 Morphometric analysis; tumor (eg, DNAS ploidy)
88360 Morphometric analysis, tumor immunohistochemistry (eg, Her-2/neu, estrogen receptor/progesterone receptor), quantitative or semiquantitative, per specimen, each single antibody stain procedure; manual
88361     using computer-assisted technology
88381 Microdissection (ie, sample preparation of microscopically identified target); manual
Other HCPCS codes related to the CPB:
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
J8565 Gefitinib (Iressa), oral, 250 mg
ICD-9 codes covered if selection criteria are met:
162.2 - 162.9 Malignant neoplasm of bronchus and lung [non small cell lung cancer]
ICD-9 codes not covered if selection criteria are met:
191.0 - 191.9 Malignant neoplasm of brain [Glioblastoma multiforme]
233.7 Carcinoma in situ of bladder [urothelial carcinoma]
233.9 Carcinoma in situ of other and unspecified urinary organs (ureter, renal pelvis) [urothelial carcinoma]
ROS-1:
No specific code
ICD-9 codes covered if selection criteria are met:
162.2 - 162.9 Malignant neoplasm of bronchus and lung [non small cell lung cancer]
ZAP-70:
CPT codes covered if selection criteria are met:
88184 Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185     each additional marker (List separately in addition to code for first marker)
ICD-9 codes covered if selection criteria are met :
204.10 - 204.12 Chronic lymphoid leukemia [assessing prognosis and need for aggressive therapy]
Oncotype Dx:
CPT codes covered if selection criteria are met:
81519 Oncology (breast), mRNA, gene expression profiling by real-time RT-PCR of 21 genes, utilizing formalin-fixed paraffin embedded tissue, algorithm reported as recurrence score
Other CPT codes related to the CPB:
88360 Morphometric analysis, tumor immunohistochemistry (eg, Her-2/neu, estrogen receptor/progesterone receptor), quantitative or semiquantitative, per specimen, each single antibody stain procedure; manual
88361     using computer-assisted technology
88367 - 88377 Morphometric analysis, in situ hybridization, (quantitative or semi-quantitative)
88368     manual
HCPCS codes covered if selection criteria are met:
S3854 Gene expression profiling panel for use in the management of breast cancer treatment [not covered for Mammaprint, Rotterdam Signature 76-gene Panel, or Breast Cancer Gene Expression Ratio (HOXB13:IL17BR), or TargetPrint Gene Expression]
ICD-9 codes covered if selection criteria are met:
174.0 - 174.9 Malignant neoplasm of female breast [except node positive - see criteria]
175.0 - 175.9 Malignant neoplasm of male breast
196.3 Secondary and unspecified malignant neoplasm of lymph nodes of axilla and upper limb [1-3 involved ipsilateral axillary lymph nodes]
ICD-9 codes not covered for indications listed in the CPB:
153.0 - 154.1 Malignant neoplasm of colon and rectum
185 Malignant neoplasm of prostate
230.3 Carcinoma in situ of colon
233.0 Carcinoma in situ of breast [ductal carcinoma in situ (DCIS)]
233.4 Carcinoma in situ of prostate
V10.05 Personal history of malignant neoplasm of large intestine
V10.06 Personal history of malignant neoplasm of rectum, rectosigmoid junction, and anus
Other ICD-9 codes related to the CPB:
V86.0 Estrogen receptor positive status [ER+]
V86.1 Estrogen receptor negative status [ER-]
T-cell receptor gamma chain gene rearrangement:
CPT codes covered if selection criteria are met:
81342 TRG@ (T cell antigen receptor, gamma) (eg, leukemia and lymphoma), gene rearrangement analysis, evaluation to detect abnormal clonal population(s) [TCG@]
ICD-9 codes covered if selection criteria are met:
202.10 - 202.18 Mycosis fungoides
204.00 - 204.92 Lymphoid leukemia [T-cell prolymphocytic leukemia]
Myeloperoxidase (MPO) immunostaining FLT3-ITD, CEBPA mutation, NPM1 mutation, and KIT mutation:
CPT codes covered if selection criteria are met:
81244 FMR1 (Fragile X mental retardation 1) (eg, fragile x mental retardation) gene analysis; characterization of alleles (eg, expanded size and methylation status)
81245 FLT3 (fms-related tyrosine kinase 3) (eg, acute myeloid leukemia), gene analysis; internal tandem duplication (ITD) variants (ie, exons 14, 15)
81246 FLT3 (fms-related tyrosine kinase 3) (eg, acute myeloid leukemia), gene analysis; tyrosine kinase domain (TKD) variants (eg, D835, I836)
83876 Myeloperoxidase (MPO)
ICD-9 codes covered if selection criteria are met:
205.00 - 205.02 Acute myeloid leukemia
PML/RARA:
CPT codes covered if selection criteria are met:
81315 - 81316 PML/RARalpha, (t(15;17)), (promyelocytic leukemia/retinoic acid receptor alpha) (eg, promyelocytic leukemia) translocation analysis
ICD-9 codes covered if selection criteria are met:
205.00 - 205.02 Myeloid leukemia, acute
Placental alkaline phosphatase (PLAP):
CPT codes covered if selection criteria are met:
84080 Phosphatase, alkaline; isoenzymes
ICD-9 codes covered if selection criteria are met:
183.0 Malignant neoplasm of ovary
186.0 - 186.9 Malignant neoplasm of testes
233.39 Carcinoma in situ of other and unspecified female genital organs [germ cell tumors]
233.6 Carcinoma in situ of other and unspecified male genital organs
V10.43 Personal history of malignant neoplasm of ovary
V10.47 Personal history of malignant neoplasm of testis
Bladder tumor antigen (BTA) Stat Test, the nuclear matrix protein (NMP22) test, the fibrin/fibrinogen degradation products (Aura-Tek FDP) test, or the UroVysion fluorescent in situ hybridization (FISH) test:
CPT codes covered if selection criteria are met:
85362 - 85380 Fibrin degradation products
86294 Immunoassay for tumor antigen, qualitative or semiquantitative (e.g., bladder tumor antigen)
86386 Nuclear Matrix Protein 22 (NMP22) qualitative
88120 Cytopathology, in situ hybridization (eg, FISH), urinary tract specimen with morphometric analysis, 3-5 molecular probes, each specimen; manual
88121     using computer-assisted technology
88364 - 88366 In situ hybridization (eg, FISH), per specimen
ICD-9 codes covered if selection criteria are met:
188.0 - 188.9 Malignant neoplasm of bladder
233.7 Carcinoma in situ of bladder
V10.51 Personal history of malignant neoplasm of bladder
ICD-9 codes not covered for indications listed in the CPB (not all-inclusive):
599.70 - 599.72 Hematuria
V76.3 Special screening for malignant neoplasm of bladder
ImmunoCyte:
No specific code
ICD-9 codes covered if selection criteria are met:
188.0 - 188.9 Malignant neoplasm of bladder [as an adjunct to cystoscopy or cytology in monitoring]
ICD-9 codes not covered for indications listed in the CPB:
V76.3 Special screening for malignant neoplasm of bladder [diagnosis or screening in asymptomatic persons]
Janus Kinase 2 (JAK2) mutations:
CPT codes covered if selection criteria are met:
81270 JAK2 (Janus kinase 2) (eg, myeloproliferative disorder) gene analysis, p.Val617Phe (V617F) variant [not covered for diagnostic assessment of myeloproliferative disorders in children; and quantitative assessment of JAK2-V617F allele burden subsequent to qualitative detection of JAK2-V617F]
ICD-9 codes covered if selection criteria are met:
205.10 - 205.12 Chronic myeloid leukemia
238.4 Polycythemia vera
238.71 Essential thrombocythemia
238.76 Myelofibrosis with myeloid metaplasia (Primary myelofibrosis)
238.79 Other lymphatic and hematopoietic tissues (Chronic myeloproliferative disease)
289.83 Myelofibrosis
BRAF mutation analysis:
CPT codes covered if selection criteria are met:
81210 BRAF (v-raf murine sarcoma viral oncogene homolog B1) (eg, colon cancer), gene analysis, V600E variant
ICD-9 codes covered if selection criteria are met:
153.0 - 153.9 Malignant neoplasm of colon [Lynch syndrome (HNPCC)]
154.0 - 154.8 Malignant neoplasm of rectum, rectosigmoid junction, and anus [Lynch syndrome (HNPCC)]
171.5 Malignant neoplasm of connective and other soft tissue of abdomen [gastrointestinal stromal tumors ]
172.0 - 172.9 Melanoma of skin [for consideration of Vemurafenib, Dabrafenib and Trametinib]
202.40 - 202.48 Leukemic reticuloendotheliosis
ICD-9 codes not covered if selection criteria are met:
162.2 - 162.9 Malignant neoplasm of bronchus, and lung
193 Malignant neoplasm of thyroid gland
Assaying for loss of heterozygosity (LOH) on the long arm of chromosome 18 (18q) or deleted in colon cancer (DCC) protein (18q-LOH/DCC) for colorectal cancer:
There is no specific code for 18q-LOH/DCC
ICD-9 codes not covered for indications listed in the CPB:
153.0 - 154.1 Malignant neoplasm of colon, rectum, and rectosigmoid junction
OvaCheck test:
There is no specific code for OvaCheck
ICD-9 codes not covered for indications listed in the CPB:
183.0 Malignant neoplasm of ovary
V76.46 Special screening for malignant neoplasm of ovary
Ovasure:
There is no specific code for Ovasure
Other CPT codes related to the CPB:
82985 Glycated protein
83520 Immunoassay, analyte quantitative; not otherwise specified
84146 Prolactin
84305 Somatomedin
86304 Immunoassay for tumor antigen, quantitative; CA 125
CellSearch assay:
CPT codes not covered for indications listed in the CPB:
86152 - 86153 Cell enumeration using immunologic selection and identification in fluid specimen (eg, circulating tumor cells in blood
88346 Immunofluorescent study, each antibody; direct method
88361 Morphometric analysis, tumor immunohistochemistry (e.g., Her-2/neu, estrogen receptor/progesterone receptor), quantitative or semiquantitative, each antibody; using computer-assisted technology
Cofilin (CFL1):
There is no specific code for cofilin (CFL1)
162.2 - 162.9 Malignant neoplasm of lung [non-small cell lung carcinoma]
ColonSentry:
There is no specific code for ColonSentry
ICD-9 codes not covered for indications listed in the CPB:
V76.41 Special screening for malignant neoplasms; rectum
V76.51 Special screening for malignant neoplasms; colon
Decipher test (a RNA biomarkers assay):
No specific code
ICD-9 codes not covered for indications listed in the CPB:
185 Malignant neoplasm of prostate
Early CDT-Lung Test:
CPT codes not covered for indications listed in the CPB:
83520 Immunoassay for analyte other than infectious agent antibody or infectious agent antigen; quantitative, not otherwise specified [as a screening for the early detection of lung cancer]
Galectin-3:
CPT codes not covered for indications listed in the CPB:
82777 Galectin-3
ICD-9 codes not covered for indications listed in the CPB (not all-inclusive):
185 Malignant neoplasm of prostate
Ki67:
No specific code
ICD-9 codes not covered for indications listed in the CPB:
174.0 - 175.9 Malignant neoplasm of breast
Mammaprint:
HCPCS codes not covered for indications listed in the CPB:
S3854 Gene expression profiling panel for use in the management of breast cancer treatment
Mammostrat:
There is no specific code for Mammostrat
MLH1 tumor promoter hypermethylation:
CPT codes not covered for indications listed in the CPB:
81288 MLH1 (mutl homolog 1, colon cancer, nonpolyposis type 2) (eg, hereditary non-polyposis colorectal cancer, Lynch syndrome) gene analysis; promoter methylation analysis
ICD-9 codes not covered for indications listed in the CPB:
182.0 Malignant neoplasm of corpus uteri, except isthmus [endometrium]
Mucin 4 expression:
CPT codes not covered for indications listed in the CPB:
88313 Group II, all other (eg, iron, trichrome), except immunocytochemistry and immunoperoxidase stains, including interpretation and report, each
ICD-9 codes not covered for indications listed in the CPB:
153.0 - 154.1 Malignant neoplasm of colon, rectum and rectosigmoid junction
Mucin 5AC (MUC5AC):
No specific code
ICD-9 codes not covered for indications listed in the CPB:
155.1, 156.1 - 156.9 Malignant neoplasm of biliary tract
Microarray-based gene expression profile testing:
Other CPT codes related to the CPB:
81406 Molecular pathology procedure, Level 7 (eg, analysis of 11-25 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 26-50 exons, cytogenomic array analysis for neoplasia)
OVA1:
There is no specific code for OVA1
CPT codes not covered for indications listed in the CPB:
81503 Oncology (ovarian), biochemical assays of five proteins (CA-125, apolipoprotein A1, beta-2 microglobulin, transferrin and pre-albumin), utilizing serum, algorithm reported as a risk score
p16 protein expression:
No specific code
ICD-9 codes not covered for indications listed in the CPB:
140.0 - 149.9 Malignant neoplasm of lip, oral cavity, and pharynx [non-oropharyngeal squamous cell carcinoma]
Pathwork Tissue of Origin Test:
CPT codes not covered for indications listed in the CPB:
81504 Oncology (tissue of origin), microarray gene expression profiling of > 2000 genes, utilizing formalin-fixed paraffin-embedded tissue, algorithm reported as tissue similarity scores
PreOvar Test for the KRAS-variant [to determine ovarian cancer risk]:
No specific code
ICD-9 codes not covered for indications listed in the CPB:
183.0 Malignant neoplasm of ovary
V10.43 Personal history of malignant neoplasm of ovary
ProOnc Tumor Source Dx Test:
No specific code
ROMA:
CPT codes not covered for indications listed in the CPB:
81500 Oncology (ovarian), biochemical assays of two proteins (CA-125 and HE4), utilizing serum, with menopausal status, algorithm reported as a risk score
86304 Immunoassay for tumor antigen, quantitative; CA 125
86305 Human epididymis protein 4 (HE4)
ICD-9 codes not covered for indications listed in the CPB (not all-inclusive):
183.0 Malignant neoplasm of ovary
Rotterdam Signature 76-gene Panel:
HCPCS codes not covered for indications listed in the CPB:
S3854 Gene expression profiling panel for use in the management of breast cancer treatment
Serum amyloid A:
CPT codes not covered for indications listed in the CPB:
88342 Immunohistochemistry or immunocytochemistry, each separately identifiable antibody per block, cytologic preparation, or hematologic smear; first separately identifiable antibody per slide
88343     each additional separately identifiable antibody per slide (List separately in addition to code for primary procedure)
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
Other CPT codes related to the CPB:
88341 - 88344 Immunohistochemistry or immunocytochemistry, per specimen
ICD-9 codes not covered for indications listed in the CPB:
182.0 - 182.8 Malignant neoplasm of corpus uteri, isthmus and uterus
V10.42 Personal history of malignant neoplasm of uterus
Breast Cancer Gene Expression Ratio (HOXB13:IL17BR):
HCPCS codes not covered for indications listed in the CPB:
S3854 Gene expression profiling panel for use in the management of breast cancer treatment
Panexia:
CPT codes not covered for indications listed in the CPB:
81406 Molecular pathology procedure, Level 7 (eg, analysis of 11-25 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 26-50 exons, cytogenomic array analysis for neoplasia) [when specified as the following]: PALB2 (partner and localizer of BRCA2) (eg, breast and pancreatic cancer), full gene sequence
ICD-9 codes not covered for indications listed in the CPB:
185 Malignant neoplasm of prostate
PTEN gene expression:
CPT codes covered if selection criteria are met:
81321 - 81323 PTEN (phosphatase and tensin homolog) (eg, Cowden syndrome, PTEN hamartoma tumor syndrome) gene analysis
ICD-9 codes covered if selection criteria are met:
759.6 Other congenital hamartoses, NEC [Cowden syndrome]
ICD-9 codes not covered for indications listed in the CPB:
162.2 - 162.9 Malignant neoplasm of bronchus and lung [non-small cell lung cancer]
GeneSearch Breast Lymph Node (BLN) assay:
There is no specific code for GeneSearch Breast Lymph Node (BLN) assay
Thymidylate synthase:
There is no specific code for Thymidylate synthase
Other CPT codes related to the CPB:
88341 - 88344 Immunohistochemistry or immunocytochemistry, per specimen
88360 Morphometric analysis, tumor immunohistochemistry (eg, Her-2/neu, estrogen receptor/progesterone receptor), quantitative or semiquantitative, per specimen, each single antibody stain procedure; manual
88361     using computer-assisted technology
Other HCPCS codes related to the CPB:
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
Topographic genotyping (PathfinderTG):
No specific code
Biomarker Translation (BT):
No specific code
ICD-9 codes not covered for indications listed in the CPB:
174.0 - 175.9 Malignant neoplasm of breast
HE4:
CPT codes not covered for indications listed in the CPB:
81500 Oncology (ovarian), biochemical assays of two proteins (CA-125 and HE4), utilizing serum, with menopausal status, algorithm reported as a risk score
86305 Human epididymis protein 4 (HE4)
Other CPT codes related to the CPB:
86316 Immunoassay for tumor antigen; other antigen, quantitative (e.g., CA 50, 72-4, 549), each
ICD-9 codes not covered for indications listed in the CPB:
183.0 Malignant neoplasm of ovary
HERmark:
There is no specific code for HERmark
ICD-9 codes not covered for indications listed in the CPB:
174.0 - 175.9 Malignant neoplasm of breast
233.0 Carcinoma in situ of breast
TargetPrint Gene Expression:
Other CPT codes related to the CPB:
88360 Morphometric analysis, tumor immunohistochemistry (eg, Her-2/neu, estrogen receptor/progesterone receptor), quantitative or semiquantitative, per specimen, each single antibody stain procedure; manual
88361     using computer-assisted technology
88367 - 88377 Morphometric analysis, in situ hybridization, (quantitative or semiquantitative)
HCPCS codes not covered for indications listed in the CPB:
S3854 Gene expression profiling panel for use in the management of breast cancer treatment
ICD-9 codes not covered for indications listed in the CPB:
174.0 - 174.9 Malignant neoplasm of female breast
175.0 - 175.9 Malignant neoplasm of male breast
Other ICD-9 codes related to the CPB:
V86.0 Estrogen receptor positive status [ER+]
V86.1 Estrogen receptor negative status [ER-]
TP53:
No specific code
ICD-9 codes not covered for indications listed in the CPB:
183.0 Malignant neoplasm of ovary
CK5, CK14, p63 and Racemase P504S:
Other CPT codes related to the CPB:
88341 - 88344 Immunohistochemistry or immunocytochemistry, per specimen
Other HCPCS codes related to the CPB:
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
ICD-9 codes not covered for indications listed in the CPB:
185 Malignant neoplasm of prostate
EML4-ALK:
Other CPT codes related to the CPB:
88381 Microdissection (ie, sample preparation of microscopically identified target); manual
ICD-9 codes not covered for indications listed in the CPB:
162.2 - 162.9 Malignant neoplasm of bronchus and lung [non-small-cell lung cancer]
Coloprint, CIMP, Line-1 hypomethylation and immune cells:
There are no specific codes for Coloprint, CIMP, Line-1 hypomethylation and immune cells
ICD-9 codes not covered for indications listed in the CPB:
153.0 - 154.1 Malignant neoplasm of colon and rectum
WT1 mutation, RUNX1 mutation, MLL-PTD mutation, IDH2 R172, and IDH2 codon 140 mutation:
Des-gamma-carboxyl prothrombin (DCP):
CPT codes not covered for indications listed in the CPB:
83951 Oncoprotein; des-gamma-carboxy-prothrombin (DCP)
ICD-9 codes not covered for indications listed in the CPB (not all-inclusive):
155.0, 155.2 Malignant neoplasm of the liver [primary or unspecified as primary or secondary]
230.8 Carcinoma in situ of liver and biliary system
Experimental and investigational circulating tumor markers:
CPT codes not covered for indications listed in the CPB:
0006M Oncology (hepatic), MRNA expression levels of 161 genes, utilizing fresh hepatocellular carcinoma tumor tissue, with alpha-fetoprotein level, algorithm reported as a risk classifier [Heprodx]
0007M Oncology (gastrointestinal neuroendocrine tumors), real-time PCR expression analysis of 51 genes, utilizing whole peripheral blood, algorithm reported as a nomogram of tumor disease index [Netest]
0008M Oncology (breast), MRNA analysis of 58 genes using hybrid capture, on formalin-fixed paraffin-embedded (FFPE) tissue, prognostic algorithm reported as a risk score [Prosigna]
82387 Cathepsin-D
84275 Sialic acid
86316 Immunoassay for tumor antigen; other antigen, quantitative (e.g., CA 50, 72-4, 549), each
88342 Immunohistochemistry (including tissue immunoperoxidase), each antibody [cyclin E (fragments or whole length)]
88343     each additional separately identifiable antibody per slide (List separately in addition to code for primary procedure)
G0461 Immunohistochemistry or immunocytochemistry, per specimen; first single or multiplex antibody stain
G0462     each additional single or multiplex antibody stain (list separately in addition to code for primary procedure)
There are no specific codes for the circulating tumor markers listed below:
Affirma Thyroid FNA Analysis; anti-VEGF antibody bevacizumab; BluePrint molecular subtyping profile for breast cancer; Catalytic subunit alpha polypeptide gene (PIK3CA); C-Met expression; DCIS Recurrence Score; Glutathione-S-transferase P1 (GSTP1); Phosphatidylinositol-4,5-bisphosphonate 3-kinase; Proveri prostate cancer assay (PPCA); Ribonucleotide reductase subunit M1 (RRM1); ROS1 re-arrangements; BreastNext Next-Gen Cancer Panel; CancerNext Next-Gen Cancer Panel; ColoNext Next-Gen Cancer Panel; Ovanext Next-Gen Cancer Panel; Previstage GCC; Prostate core mitotic test; Prolaris; Oncovue; BREVAgen; UroCor cytology assay (DD23 and P53); CXBladder Test;


The above policy is based on the following references:
    1. Lein M, Stephan C, Jung K, et al. Relation of free PSA/total PSA in serum for differentiating between patients with prostatic cancer and benign hyperplasia of the prostate: Which cutoff should be used? Cancer Invest. 1998;16(1):45-49.
    2. Littrup PJ. Future benefits and cost-effectiveness of prostate carcinoma screening. American Cancer Society. Cancer. 1997;80(9):1864-1870.
    3. Gao X, Porter AT, Grignon DJ, et al. Diagnostic and prognostic markers for human prostate cancer. Prostate. 1997;31(4):264-281.
    4. Duffy MJ. PSA as a marker for prostate cancer: A critical review. Ann Clin Biochem. 1996;33(Pt 6):511-519.
    5. No authors listed. Ovarian cancer: Screening, treatment, and followup. NIH Consens Statement. 1994;12(3):1-30.
    6. Watine J, Charet JC. Are the ATS (American Thoracic Society) and the ERS (European Respiratory Society) correct in not recommending routine tfumor marker assays for screening, staging, or evaluation of non-small cell lung cancer? Rev Mal Respir. 1999;16(2):139-149.
    7. Seifert JK Morris DI. Indicators of recurrence following cryotherapy for hepatic metastases from colorectal cancer. Br J Surg. 1999;86(2):234-240.
    8. Lagautriere F, Valvano L, Chaazl M, et al. Prognostic factors in colorectal adenocarcinoma. Ann Ital Chir. 1998;69(4):491-497.
    9. Hamm CM, Cripps C. Carcinoembryonic antigen in metastatic colorectal cancer. Clin Invest Med. 1998;21(4-5):186-191.
    10. Jessup JM, Loda M. Prognostic markers in rectal carcinoma. Semin Surg Oncol. 1998;15(2):131-140.
    11. Mazurek A. Niklinski J. Laudanski T. et al. Clinical tumour markers in ovarian cancer. Eur J Cancer Prev. 1998;7(1):23-35.
    12. American Society of Clinical Oncology. Clinical practice guidelines for the use of tumor markers in breast and colorectal cancer. Adopted on May 17, 1996 by the American Society of Clinical Oncology. J Clin Oncol. 1996;14(10):2843-2877.
    13. American Society of Clinical Oncology. 1997 update of recommendations for the use of tumor markers in breast and colorectal cancer. Adopted on November 7, 1997 by the American Society of Clinical Oncology. J Clin Oncol. 1998;16(2):793-795.
    14. Harrison LE, Guillem JG, Paty P, et al. Preoperative carcinoembryonic antigen predicts outcomes in node-negative colon cancer patients: A multivariate analysis of 572 patients. J Am Coll Surg. 1997;185(1):55-59.
    15. Lamerz R, Stieber P, Fateh-Moghadam A. Serum marker combinations in human breast cancer. In Vivo. 1993;7(6B):607-613.
    16. American College of Physicians. Screening for ovarian cancer: Recommendations and rationale. Ann Intern Med. 1994 J;121(2):141-142.
    17. Carlson KJ. Screening for ovarian cancer. Ann Intern Med. 1994;121(2):124-132
    18. Mogenson O. Prognostic value of CA 125 in advanced ovarian cancer. Gynecol Oncol. 1992;44:207-212.
    19. Patsner B, Mann WJ, Vissicchio M, Loesch M. Comparison of serum CA-125 and lipid-associated sialic acid (LASA-P) in monitoring patients with invasive ovarian adenocarcinoma. Gynecol Oncol. 1988;30(1):98-103.
    20. Makar AP, Kristensen GB, Bormer OP, Trope CG. CA 125 measured before a second-look laparotomy us an independent prognostic factor for survival in patients with epithelial ovarian cancer. Gynecol Oncol. 1992;45(3):323-328.
    21. Werner M, Faser C, Silverberg M. Clinical utility and validation of emerging biochemical markers for mammary adenocarcinoma. Clin Chem. 1993;39(11 Pt 2):2386-2396.
    22. Bates SE. Clinical Applications of serum tumor markers. Ann Intern Med. 1991;115(8):623-638.
    23. Steinberg W. The clinical utility of the CA19-9 tumor associated antigen. Am J Gastroenterol. 1990;85:350-355.
    24. Devlin J, O'Grady J. Indications for referral and assessment in adult liver transplantation: A clinical guideline. British Society of Gastroenterology. Gut.
      1999;45 Suppl 6:VI1-VI22.
    25. Jorgensen LG,, Osterlind K, Hansen HH, Cooper EH. Serum neuron specific enolase (NSE) is a determinant of response duration in small cell lung cancer. Br J Cancer. 1992;66(3):594-598.
    26. Johnson PW, Joel SP, Love S, et al. Tumour markers for prediction of survival and monitoring of remission in small cell lung cancer. Br J Cancer. 1993;67(4):760-766.
    27. Wobbes T, Thomas CM, Segers MF, Nagengast FM. Evaluation of seven tumor markers in the treatment sera of patients with gastric carcinoma. Cancer. 1992;69(8):2036-2041.
    28. Hayes DF. Serum tumor markers for breast cancer. Anticancer Drugs. 1995;6(Suppl 2):26-27.
    29. Coveney EC, Geraghty JG, Sherry F, et al. The clinical value of CEA and CA 15-3 in breast cancer management. Int J Biol Markers. 1995;10(1):35-41.
    30. Sharma S, Zippe CD, Pandrangi L, et al. Exclusion criteria enhance the specificity and positive predictive value of NMP22 and BTA Stat. J Urol. 1999;162(1):53-57.
    31. Pirtskalaishvili G, Konety BR, Getzenberg RH. Update on urine-based markers for bladder cancer. How sensitive and specific are the new noninvasive tests? Postgrad Med. 1999;106(6):85-86, 91-94.
    32. Sawczuk IS, Lee B. The mechanism and clinical applications of the NMP22 tumor marker immunoassay: A review. Am Clin Lab. 1999;18(3):24-26.
    33. Burchardt M, Burchardt T, Shabsigh A, et al. Current concepts in biomarker technology for bladder cancer. Clin Chem. 2000;46(5):595-605.
    34. Grocela JA, McDougal WS. Utility of nuclear matrix protein (NMP22) in the detection of recurrent bladder cancer. Urol Clin North Am. 2000;27(1):47-51.
    35. Brown FM. Urine cytology. Is it still the gold standard for screening? Urol Clin North Am. 2000;27(1):25-37.
    36. Bast RC Jr, Ravdin P, Hayes DF, et al. 2000 update of recommendations for the use of tumor markers in breast and colorectal cancer: Clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol. 2001;19(6):1865-1878.
    37. Smith RA, Cokkinides V, von Eschenbach AC, et al. American Cancer Society guidelines for the early detection of cancer. CA Cancer J Clin. 2002;52(1):8-22.
    38. Morabito A, Magnani E, Gion M, et al. Prognostic and predictive indicators in operable breast cancer. Clin Breast Cancer. 2003;3(6):381-390.
    39. Duffy MJ, van Dalen A, Haglund C, et al. Clinical utility of biochemical markers in colorectal cancer: European Group on Tumour Markers (EGTM) guidelines. Eur J Cancer. 2003;39(6):718-727.
    40. Bubendorf L, Grilli B, Sauter G, et al. Multiprobe FISH for enhanced detection of bladder cancer in voided urine specimens and bladder washings. Am J Clin Pathol. 2001;116(1):79-86.
    41. Sarosdy MF, Schellhammer P, Bokinsky G, et al. Clinical evaluation of a multi-target fluorescent in situ hybridization assay for detection of bladder cancer. J Urol. 2002;168(5):1950-1954.
    42. Kruger S, Mess F, Bohle A, Feller AC. Numerical aberrations of chromosome 17 and the 9p21 locus are independent predictors of tumor recurrence in non-invasive transitional cell carcinoma of the urinary bladder. Int J Oncol. 2003;23(1):41-48.
    43. Society of Gynecologic Oncologists (SGO). Society of Gynecologic Oncologists statement regarding OvaCheck™. Position Statements. Chicago, IL: SGO; February 7, 2004. Available at: http://www.sgo.org/policy/position_statement.cfm. Accessed June 4, 2004.
    44. National Cancer Institute (NCI). Questions and answers: OvaCheck ™ and NCI/FDA Ovarian Cancer Clinical Trials using proteomics technology. NCI News. Bethesda, MD: NCI; March22, 2004.Available at: http://www.cancer.gov/newscenter/pressreleases/ProteomicsOvarian. Accessed June 4, 2004.
    45. Permanente Medical Group. Ovacheck. Permanente Medical Group Physician Home Pages. San Francisco, CA: Kaiser Permanente; 2004. Available at: http://www.permanente.net/kaiser/pages/f21815.html. Accessed June 4, 2004.
    46. Sullivan MG. Validity testing indefinitely delays Ovacheck release. FDA raises regulatory issues. Ob.Gyn.News Online. 2004;39(7):5. Available at: http://www.imng.com/IMNG/obgyn/. Accessed June 4, 2004.
    47.  U.S. Food and Drug Administration (FDA), Center for Devices and Radiologic Health (CDRH), Office of In Vitro Diagnostic Device Evaluation and Safety (OVID). Letter to Laboratory Corporation of America. Re: Ovacheck - Ovarian Cancer Screen. Rockville, MD: FDA; March 2, 2004. Available at: http://www.fda.gov/cdrh/oivd/letters/030204-labcorp.html. Accessed June 4, 2004.
    48. U.S. Food and Drug Administration (FDA), Center for Devices and Radiologic Health (CDRH), Office of In Vitro Diagnostic Device Evaluation and Safety (OVID). Letter to Quest Diagnostics. Re: Ovacheck - Ovarian Cancer Screen. Rockville, MD: FDA; March 2, 2004. Available at: http://www.fda.gov/cdrh/oivd/letters/030204-labcorp.html. Accessed June 4, 2004.
    49. Petricoin EF, Ardekani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002;359(9306):572-577.
    50. U.S. Preventive Services Task Force (USPSTF). Screening for bladder cancer in adults. In: Guide to Clinical Preventive Services. Report of the U.S. Preventive Services Task Force. 3rd ed. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); June 2004.
    51. American College of Obstetricians and Gynecologists (ACOG). The role of the generalist obstetrician-gynecologist in the early detection of ovarian cancer. ACOG Committee Opinion No. 280. Washington, DC: ACOG; December 2002.
    52. National Cancer Institute (NCI). Ovarian Cancer (PDQ): Screening. Health Professional Version. Bethesda, MD: NCI; updated February 20, 2004. Available at: http://www.cancer.gov/cancertopics/pdq/screening/
      ovarian/healthprofessional. Accessed September 22, 2004.
    53. U.S. Preventive Services Task Force (USPSTF). Screening for ovarian cancer. In: Guide to Clinical Preventive Services. Report of the U.S. Preventive Services Task Force. 3rd ed. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); May 2004.
    54. American College of Obstetricians and Gynecologists (ACOG). Position of the American College of Obstetricians and Gynecologists Committee on Gynecologic Practice Regarding OvaCheck. Washington, DC: ACOG; February 25, 2004.
    55. Andrews E. Ovacheck: Breakthrough or also ran? Nat Rev Med. 2004;1(5).
    56. Check E. Proteomics and cancer: Running before we can walk? Nature. 2004;429(6991):496-497.
    57. Diamandis EP. OvaCheck: Doubts voiced soon after publication. Nature. 2004;430(7000):611.
    58. Gandini O, Luci L, Stigliano A, et al. Is DD3 a new prostate-specific gene? Anticancer Res. 2003;23:305-308.
    59. Schalken JA, Hessels D, Verhaegh G. New targetes for therapy in prostate cancer: Differential display code 3 (DD3/PCA3), a highly prostate cancer specific gene. Urology. 2003;62(suppl 5A):34-43.
    60. Bussemakers MJG, van Bokhoven A, Verheagh GW, et al. DD3: A new prostate-specific gene, highly overexpressed in prostate cancer. Cancer Res. 1999;59:5975-5979.
    61. de Kok JB, Verhaegh GW, Roelofs RW et al. DDS (PCA3), a very sensitive and specific marker to detect prostate tumors. Cancer Res. 2002;62:2695-2698.
    62. Hessels D, Klein Gunnewiek JM, van Oort I, et al. DD3 (PCA3) based molecular urine analysis for the diagnosis of prostate cancer. Eur Urol. 2003;44:8-16.
    63. Abeloff MD, Armitage JO, Niederhuber JE, et al. Clinical Oncology. 3rd ed. Philadelphia, PA. Churchill Livingstone; 2004: 2369.
    64. U.S. Food and Drug Administration (FDA), Center for Devices and Radiologic Health (CDRH). CellSearch™ Epithelial Cell Kit / CellSpotter™ Analyzer. 510(k) no. K031588. Rockville, MD: FDA; January 21, 2004.
    65. Cristofanilli M, Budd GT, Ellis MJ, et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004;351(8):781-791.
    66. Kahn HJ, Presta A, Yang LY, et al. Enumeration of circulating tumor cells in the blood of breast cancer patients after filtration enrichment: Correlation with disease stage. Breast Cancer Res Treat. 2004;86(3):237-247.
    67. Allard WJ, Matera J, Miller MC, et al. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin Cancer Res. 2004;10(20):6897-6904.
    68. Veridex, LLC. CellSearch™ [website]. Warren, NJ: Veridex; 2005. Available at: http://www.veridex.com. Accessed December 17, 2004.
    69. Muller V, Pantel K. Bone marrow micrometastases and circulating tumor cells: Current aspects and future perspectives. Breast Cancer Res. 2004;6(6):258-261.
    70. Gilbey AM, Burnett D, Coleman RE, Holen I. The detection of circulating breast cancer cells in blood. J Clin Pathol. 2004;57(9):903-911.
    71. Ring A, Smith IE, Dowsett M. Circulating tumour cells in breast cancer. Lancet Oncol. 2004 Feb;5(2):79-88.
    72. Pantel K, Muller V, Auer M, et al. Detection and clinical implications of early systemic tumor cell dissemination in breast cancer. Clin Cancer Res. 2003;9(17):6326-6334.
    73. Baker M, Gillanders WE, Mikhitarian K, et al. The molecular detection of micrometastatic breast cancer. Am J Surg. 2003;186(4):351-358.
    74. Weigelt B, Bosma AJ, Hart AA, et al. Marker genes for circulating tumour cells predict survival in metastasized breast cancer patients. Br J Cancer. 2003;88(7):1091-1094.
    75. Glas A S, Roos D, Deutekom M, et al. Tumor markers in the diagnosis of primary bladder cancer: A systematic review. J Urol. 2003;169(6):1975-1982.
    76. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351(27):2817-2826.
    77. Esteva FJ, Sahin AA, Coombes K, et al. Multi-gene RT-PCR assay for predicting recurrence in node negative breast cancer patients -- M.D. Anderson Clinical Validation Study [abstract]. Breast Cancer Res Treat. 2003;82 (Suppl 1):S11.
    78. Bast RC Jr, Hortobagyi GN. Individualized care for patients with cancer - a work in progress. N Engl J Med. 2004;351(27):2865-2867.
    79. Kamisawa T, Fukayama M, Koike M, et al. Carcinoma of the ampulla of Vater: Expression of cancer-associated antigens inversely correlated with prognosis. Am J Gastroenterol. 1988;83(10):1118-1123.
    80. Matorras R, Rodriguez-Escuderoi FJ, Diez J, et al. Monitoring endometrial adenocarcinoma with a four tumor marker combination. CA 125, squamous cell carcinoma antigen, CA 19.9 and CA 15.3. Acta Obstet Gynecol Scand. 1992;71(6):458-464.
    81. Dorandeu A, Raoul JL, Siriser F, et al. Carcinoma of the ampulla of Vater: prognostic factors after curative surgery: A series of 45 cases. Gut. 1997;40:350-355.
    82. Abrams RA, Grochow LB, Chakravarthy A, et al. Intensified adjuvant therapy for pancreatic and periampullary adenocarcinoma: Survival results and observations regarding patterns of failure, radiotherapy dose and CA19-9 levels. Int J Radiat Oncol Biol Phys. 1999;44(5):1039-1046.
    83. Kau SY, Shyr YM, Su CH, et al. Diagnostic and prognostic values of CA 19-9 and CEA in periampullary cancers. J Am Coll Surg. 1999;188(4):415-420.
    84. Cherchi PL, Dessole S, Ruiu GA, et al. The value of serum CA 125 and association CA 125/CA 19-9 in endometrial carcinoma. Eur J Gynaecol Oncol. 1999;20(4):315-317.
    85. Rojas MP, Telaro E, Russo A, et al. Follow-up strategies for women treated for early breast cancer. Cochrane Database Syst Rev. 2000;(4):CD001768.
    86. Grossfeld GD, Litwin MS, Wolf JS Jr, et al. Evaluation of asymptomatic microscopic hematuria in adults: The American Urological Association best practice policy--part II: Patient evaluation, cytology, voided markers, imaging, cystoscopy, nephrology evaluation, and follow-up. Urology. 2001;57(4):604-610.
    87. Segal R, Lukka H, Klotz LH, et al.; Cancer Care Ontario Practice Guidelines Initiative Genitourinary Cancer Disease Site Group. Surveillance programs for early stage non-seminomatous testicular cancer: A practice guideline. Can J Urol. 2001;8(1):1184-1192.
    88. Levine M, Moutquin JM, Walton R, Feightner J. Chemoprevention of breast cancer. A joint guideline from the Canadian Task Force on Preventive Health Care and the Canadian Breast Cancer Initiative's Steering Committee on Clinical Practice Guidelines for the Care and Treatment of Breast Cancer. CMAJ. 2001;164(12):1681-1690.
    89. U.S. Preventive Services Task Force. Chemoprevention of breast cancer: Recommendations and rationale. Ann Intern Med. 2002;137(1):56-58.
    90. Jeffery GM, Hickey BE, Hider P. Follow-up strategies for patients treated for non-metastatic colorectal cancer. Cochrane Database Syst Rev. 2007;(1):CD002200.
    91. Garcia-Barcina M, Martin Bueno AE, de Bujanda Fernandez Pierola L, et al. Tumour markers in certain cancer locations. D-02-03. Vitoria-Gasteiz, Spain: Basque Office for Health Technology Assessment, Health Department Basque Government (OSTEBA); 2002.
    92. Gupta S, Bent S, Kohlwes J. Test characteristics of alpha-fetoprotein for detecting hepatocellular carcinoma in patients with hepatitis C. Ann Intern Med. 2003;139(1):46-50.
    93. Scottish Intercollegiate Guidelines Network (SIGN). Epithelial ovarian cancer. A national clinical guideline. SIGN Pub. No. 75. Edinburgh, Scotland: Scottish Intercollegiate Guidelines Network (SIGN); October 2003.
    94. Baron TH, Mallery JS, Hirota WK, et al. The role of endoscopy in the evaluation and treatment of patients with pancreaticobiliary malignancy. Gastrointest Endosc. 2003;58(5):643-649.
    95. Riley RD, Burchill SA, Abrams KR, et al. A systematic review and evaluation of the use of tumour markers in paediatric oncology: Ewing's sarcoma and neuroblastoma. Health Technol Assess. 2003;7(5):1-162
    96. Society for Surgery of the Alimentary Tract (SSAT). Operative treatment for chronic pancreatitis. Manchester, MA: SSAT; 2004.
    97. Institute for Clinical Systems Improvement (ICSI). Breast cancer treatment. ICSI Healthcare Guidelines. Bloomington, MN: ICSI; September 2004.
    98. Fradet Y, Saad F, Aprikian A, et al. uPM3, a new molecular urine test for the detection of prostate cancer. Urology. 2004;64(2):311-315; discussion 315-316.
    99. Tinzl M, Marberger M, Horvath S, Chypre C. DD3PCA3 RNA analysis in urine--a new perspective for detecting prostate cancer. Eur Urol. 2004;46(2):182-186; discussion 187.
    100. Pfister DG, Johnson DH, Azzoli CG, et al. American Society of Clinical Oncology treatment of unresectable non-small-cell lung cancer guideline: Update 2003. J Clin Oncol. 2004;22(2):330-353.
    101. Otchy D, Hyman NH, Simmang C, et al. Practice parameters for colon cancer. Dis Colon Rectum. 2004;47(8):1269-1284.
    102. Saad F. UPM3: Review of a new molecular diagnostic urine test for prostate cancer. Can J Urol. 2005;12 Suppl 1:40-43; discussion 99-100.
    103. Bast RC Jr, Badgwell D, Lu Z, et al. New tumor markers: CA125 and beyond. Int J Gynecol Cancer. 2005;15 Suppl 3:274-281.
    104. Garner EI. Advances in the early detection of ovarian carcinoma. J Reprod Med. 2005;50(6):447-453.
    105. Fields MM, Chevlen E. Ovarian cancer screening: A look at the evidence. Clin J Oncol Nurs. 2006;10(1):77-81.
    106. Paik et al. Gene Expression and Benefit of Chemotherapy in Women With Node-Negative, Estrogen Receptor-Positive Breast Cancer J. Clin. Oncol. 2006 0 (2006), p. JCO.2005.04.7985v1
    107. Habel LA, Shak S, Jacobs MK, et al. A population-based study of tumor gene expression and risk of breast cancer death among lymph node-negative patients. Breast Cancer Res. 2006; 8:R25 (doi:10.1186/bcr1412).
    108. Burstein HJ, Paik S, Ravdin PM, Albain KS. Adjuvant chemotherapy for patients with estrogen receptor-postitive breast cancer. 2006 ASCO Educational Sessions. 2006:49-55.
    109. Aguado J. Identification of circulating tumour cells in metastatic breast cancer with the CellSearch (TM) system [summary]. Technological Report. Seville, Spain: Agencia de Evaluacion de Tecnologias Sanitarias de Andalucia (AETSA); 2006. Available at: http://www.juntadeandalucia.es/salud/contenidos/aetsa/pdf/Ficha%20CTCs%20ENG.pdf. Accessed October 6, 2006.
    110. Hultcrantz R, Olsson R, Danielsson A, et al. A 3-year prospective study on serum tumor markers used for detecting cholangiocarcinoma in patients with primary sclerosing cholangitis. J Hepatol. 1999;30(4):669-673.
    111. Chakravatri A, Zehr EM, Zietman AL, et al. Thymosin beta-15 predicts for distant failure in patients with clinically localized prostate cancer-results from a pilot study. Urology. 2000;55(5):635-638. 
    112. van de Vijver, He YD, van’t Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347(25):1999-2009.
    113. Nehls O, Gregor M, Klump B. Serum and bile markers for cholangiocarcinoma. Semin Liver Dis. 2004;24(2):139-154.
    114. Levy C, Lymp J, Angulo P, et al. The value of serum CA 19-9 in predicting cholangiocarcinomas in patients with primary sclerosing cholangitis. Dig Dis Sci. 2005;50(9):1734-1740.
    115. Hutchinson LM, Chang EL, Becker CM, et al. Development of a sensitive and specific enzyme-linked immunosorbent assay for thymosin beta15, a urinary biomarker of human prostate cancer. Clin Biochem. 2005;38(6):558-571.
    116. Locker GY, Hamilton S, Harris J, et al; ASCO. ASCO 2006 update of recommendations for the use of tumor markers in gastrointestinal cancer. J Clin Oncol. 2006;24(33):5313-5327.
    117. Khatcheressian JL, Wolff AC, Smith TJ, et al; American Society of Clinical Oncology. American Society of Clinical Oncology 2006 update of the breast cancer follow-up and management guidelines in the adjuvant setting. J Clin Oncol. 2006;24(31):5091-5097.
    118. National Horizon Scanning Centre (NHSC). NMP22 BladderChek proteomic assay for the detection of bladder cancer - horizon scanning technology note. Birmingham, UK: NHSC; 2006.
    119. National Horizon Scanning Centre (NHSC). Prostate cancer gene 3 (Progensa PCA3) assay in the diagnosis of prostate cancer: Horizon Scanning Technology Briefing. Birmingham, UK: NHSC; 2006. 
    120. Parrella A, Mundy L, Merlin T, Hiller J. NMP22 BladderChek(TM) point-of-care diagnostic test for bladder cancer. Horizon Scanning Prioritising Summary - Volume 9. Adelaide, SA: Adelaide Health Technology Assessment (AHTA) on behalf of National Horizon Scanning Unit (HealthPACT and MSAC); 2005.
    121. California Technology Assessment Forum (CTAF). Gene expression profiling as a guide for the management of early stage breast cancer. Technology Assessment. San Francisco, CA: CTAF; 2007. Available at: http://ctaf.org/content/general/detail/621. Accessed. April 13, 2007.
    122. Myers ER, Havrilesky LJ, Kulasingam SL, et al. Genomic tests for ovarian cancer detection and management. Evidence Report/Technology Assessment 145. Prepared by the Duke Evidence-Based Practice Center for the Agency for Healthcare Research and Quality (AHRQ). AHRQ Publication No. 07-E0001. Rockville, MD: AHRQ; October 2006. Available at:
      http://www.ahrq.gov/downloads/pub/evidence/pdf/genomicovc/genovc.pdf. Accessed May 27, 2007.
    123. Finkelstein SD, Marsh W, Demetris AJ, et al. Microdissection-based allelotyping discriminates de novo tumor from intrahepatic spread in hepatocellular carcinoma. Hepatology. 2003;37(4):871-879.
    124. Finkelstein SD, Przygodzki R, Pricolo VE, et al. Prediction of biologic aggressiveness in colorectal cancer by p53/K-ras-2 topographic genotyping. Mol Diagn. 1996;1(1):5-28.
    125. Kanbour-shakir A, Kounelis S, Papadaki H, et al. Relationship of p53 genotype to second-look recurrence and survival in ovarian epithelial malignancy. Mol Diagn. 1996;1(2):121-129.
    126. Ribeiro U, Safatle-Ribeiro AV, Posner MC, et al. Comparative p53 mutational analysis of multiple primary cancers of the upper aerodigestive tract. Surgery. 1996;120(1):45-53.
    127. Przygodzki RM, Koss MN, Moran CA, et al. Pleomorphic (giant and spindle cell) carcinoma is genetically distinct from adenocarcinoma and squamous cell carcinoma by K-ras-2 and p53 analysis. Am J Clin Pathol. 1996;106(4):487-492.
    128. Safatle-Ribeiro AV, Ribeiro Junior U, Reynolds JC, et al. Morphologic, histologic, and molecular similarities between adenocarcinomas arising in the gastric stump and the intact stomach. Cancer. 1996;78(11):2288-2299.
    129. Przygodzki RM, Finkelstein SD, Keohavong P, et al. Sporadic and thorotrast-induced angiosarcomas of the liver manifest frequent and multiple point mutations in K-ras-2. Lab Invest. 1997;76(1):153-159.
    130. Pricolo VE, Finkelstein SD, Bland KI.  Topographic genotyping of colorectal carcinoma: From a molecular carcinogenesis model to clinical relevance. Ann Surg Oncol. 1997;4(3):269-278.
    131. Holst VA, Finkelstein S, Colby TV, et al.  p53 and K-ras mutational genotyping in pulmonary carcinosarcoma, spindle cell carcinoma, and pulmonary blastoma: Implications for histogenesis. Am J Surg Pathol. 1997;21(7):801-811.
    132. Jones MW, Kounelis S, Papadaki H, et al. The origin and molecular characterization of adenoid basal carcinoma of the uterine cervix. Int J Gynecol Pathol. 1997;16(4):301-306.
    133. Jones MW, Kounelis S, Hsu C, et al. Prognostic value of p53 and K-ras-2 topographic genotyping in endometrial carcinoma: A clinicopathologic and molecular comparison. Int J Gynecol Pathol. 1997;16(4):354-360.
    134. Kounelis S, Jones MW, Papadaki H, et al. Carcinosarcomas (malignant mixed mullerian tumors) of the female genital tract: Comparative molecular analysis of epithelial and mesenchymal components. Hum Pathol. 1998;29(1):82-87.
    135. Ribeiro U Jr, Finkelstein SD, Safatle-Ribeiro AV, et al. p53 sequence analysis predicts treatment response and outcome of patients with esophageal carcinoma. Cancer. 1998;83(1):7-18.
    136. Finkelstein SD, Tiffee JC, Bakker A, et al. Malignant transformation in sinonasal papillomas is closely associated with aberrant p53 expression. Mol Diagn. 1998;3(1):37-41.
    137. Holst VA, Finkelstein S, Yousem SA. Bronchioloalveolar adenocarcinoma of lung: Monoclonal origin for multifocal disease. Am J Surg Pathol. 1998;22(11):1343-1350.
    138. Pollack IF, Finkelstein SD, Burnham J, et al.; Children's Cancer Group. Age and TP53 mutation frequency in childhood malignant gliomas: Results in a multi-institutional cohort. Cancer Res. 2001;61(20):7404-7407.
    139. Papadaki H, Kounelis S, Kapadia SB, et al. Relationship of p53 gene alterations with tumor progression and recurrence in olfactory neuroblastoma. Am J Surg Pathol. 1996;20(6):715-721.
    140. Przygodzki RM, Finkelstein SD, Langer JC, et al. Analysis of p53, K-ras-2, and C-raf-1 in pulmonary neuroendocrine tumors. Correlation with histological subtype and clinical outcome. Am J Pathol. 1996;148(5):1531-1541.
    141. Pricolo VE, Finkelstein SD, Wu TT, et al. Prognostic value of TP53 and K-ras-2 mutational analysis in stage III carcinoma of the colon. Am J Surg. 1996;171(1):41-46.
    142. Finkelstein SD, Przygodzki R, Pricolo VE, et al. K-ras-2 topographic genotyping of pancreatic adenocarcinoma. Arch Surg. 1994;129(4):367-73.
    143. Lin X, Finkelstein SD, Zhu B, Silverman JF. Molecular analysis of multifocal papillary thyroid carcinoma. J Mol Endocrinol. 2008;41(4):195-203.
    144. Saad RS, Denning KL, Finkelstein SD, et al. Diagnostic and prognostic utility of molecular markers in synchronous bilateral breast carcinoma. Mod Pathol. 2008;21(10):1200-1207.
    145. Krishnamurti U, Sasatomi E, Swalsky PA, et al. Analysis of loss of heterozygosity in atypical and negative bile duct brushing cytology specimens with malignant outcome: Are 'negative' cytologic findings a representation of morphologically subtle molecular alterations? Arch Pathol Lab Med. 2007;131(1):74-80.
    146. Khalid A, Nodit L, Zahid M, et al. Endoscopic ultrasound fine needle aspirate DNA analysis to differentiate malignant and benign pancreatic masses. Am J Gastroenterol. 2006;101(11):2493-2500.
    147. Maheshwari V, Tsung A, Lin Y, et al. Analysis of loss of heterozygosity for tumor-suppressor genes can accurately classify and predict the clinical behavior of mucinous tumors arising from the appendix. Ann Surg Oncol. 2006;13(12):1610-1616. 
    148. Lapkus O, Gologan O, Liu Y, et al. Determination of sequential mutation accumulation in pancreas and bile duct brushing cytology. Mod Pathol. 2006;19(7):907-913. 
    149. Krishnamurti U, Sasatomi E, Swalsky PA, et al. Microdissection-based mutational genotyping of serous borderline tumors of the ovary. Int J Gynecol Pathol. 2005;24(1):56-61.
    150. American Cancer Society (ACS). Ovarian cancer has early symptoms. First national consensus on common warning signs. ACS News Center. Atlanta, GA: ACS; June 14, 2007. Available at: http://www.cancer.org. Accessed July 6, 2007.
    151. Berchuck A; Society for Gynecologic Oncologists. Ovarian cancer symptoms consensus statement. Chicago, IL: Society for Gynecologic Oncologists; 2007. Available at: http://www.sgo.org/publications/OvarianCancerSymptoms.pdf. Accessed July 6, 2007.
    152. Goff BA, Mandel LS, Melancon CH, Muntz HG. Frequency of symptoms of ovarian cancer in women presenting to primary care clinics. JAMA. 2004;291(22):2705-2712.
    153. Daly MB, Ozols RF. Symptoms of ovarian cancer--where to set the bar? JAMA. 2004;291(22):2755-2756.
    154. Groskopf J, Aubin SM, Deras IL, et al. APTIMA PCA3 molecular urine test: Development of a method to aid in the diagnosis of prostate cancer. Clin Chem. 2006;52(6):1089-1095.
    155. Groskopf J, Nakanishi H, Deras IL, et al. The PCA3 score correlates with tumor volume but not prostate size, and can synergize with other patient information for predicting biopsy outcome. Abstrac 1709. Annual Meeting of the American Urological Association. Anaheim, CA; May 19-24, 2007. Available at: http://www.posters2view.com/aua07/view.php?nu=1709. Accessed August 21, 2007.
    156. van Gils MP, Hessels D, van Hooij O, et al The time-resolved fluorescence-based PCA3 test on urinary sediments after digital rectal examination; A Dutch multicenter validation of the diagnostic performance. Clin Cancer Res. 2007;13(3):939-943.
    157. Marks LS, Fradet Y, Deras IL, et al. PCA3 molecular urine assay for prostate cancer in men undergoing repeat biopsy. Urology. 2007;69(3):532-535.
    158. Gene-Probe, Inc. Gen-Probe PCA3 assay. Package Insert. San Diego, CA: Gen-Probe; April 2007. Available at: http://www.tdlpathology.com/images/downloads/500614RevB-PCA3%20Assay%20PI.pdf. Accessed August 19, 2007.
    159. Haese A, Van Poppel H, Marberger M, et al. The value of the PCA3 assay in guiding decision which men with a negative prostate biopsy need immediate repeat biopsy: Preliminary European data. Abstract. 22nd Annual EAU Congress. Berlin, Germany; March 21-24, 2007. European Association of Urology Web site. Available at: http://www.uroweb.org/publications/eau-abstracts-online/?AID=11696. Accessed August 19, 2007.
    160. National Horizon Scanning Center (NHSC). Prostate cancer gene 3 (Progensa PCA3) assay in the diagnosis of prostate cancer. Horizon Scanning Technology Briefing. Birmingham, UK: NHSC; December 2006. Available at: http://pcpoh.bham.ac.uk/publichealth/horizon/PDF_files/2006reports/December06
      /PCA3%20for%20diagnosis%20of%20prostate%20cancer.pdf. Accessed August 21, 2007.
    161. George B, Datar RH, Wu L, et al. p53 gene and protein status: The role of p53 alterations in predicting outcome in patients with bladder cancer. J Clin Oncol. 2007;25(34):5352-5358.
    162. Real FX. p53: It has it all, but will it make it to the clinic as a marker in bladder cancer? J Clin Oncol. 2007;25(34):5341-5344.
    163. Parekh DJ, Ankerst DP, Troyer D, et al. Biomarkers for prostate cancer detection. J Urol. 2007;178(6):2252-2259.
    164. Harris L, Fritsche H, Mennel R, et al; American Society of Clinical Oncology. American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol. 2007;25(33):5287-5312.
    165. Svatek RS, Karam J, Karakiewicz PI, et al. Role of urinary cathepsin B and L in the detection of bladder urothelial cell carcinoma. J Urol. 2008;179(2):478-484; discussion 484.
    166. Marchionni L, Wilson RF, Wolff AC, et al. Systematic review: Gene expression profiling assays in early-stage breast cancer. Ann Intern Med. 2008;148(5):358-369.
    167. Wolf I, Ben-Baruch N, Shapira-Frommer R, et al. Association between standard clinical and pathologic characteristics and the 21-gene recurrence score in breast cancer patients: A population-based study. Cancer. 2008;112(4):731-736. 
    168. Australia and New Zealand Horizon Scanning Network (ANZHSN). Genesearch™ breast lymph node (BLN) assay. Horizon Scanning Technology Prioritising Summaries. Canberra, ACT: Australian Government, Department of Health and Ageing; May 2008. Available at:  http://www.health.gov.au/. Accessed August 12, 2008. 
    169. Blumencranz P, Whitworth PW, Deck K, et al. Scientific Impact Recognition Award. Sentinel node staging for breast cancer: intraoperative molecular pathology overcomes conventional histologic sampling errors. Am J Surg. 2007; 194(4):426-432.
    170. Blue Cross Blue Shield Association (BCBSA), Technology Evaluation Center (TEC). Use of genesearch breast lymph node assay to detect sentinel node metastases in early stage breast cancer. TEC Assessment Program. Chicago, IL:BCBSA; 2007; 22(8). Available at: http://www.bcbs.com/blueresources/tec/vols/22/22_08.html. Accessed August 12, 2008.
    171. U. S. Food and Drug Administration.  GeneSearch BLN Testkit. P060017. Rockville, MD: FDA. July 16, 2007. Available at: http://www.fda.gov/cdrh/pdf6/p060017a.pdf. Accessed August 12, 2008.
    172. U.S. Food and Drug Administration CDRH Consumer Information. Genesearch BLN Test Kit - P060017. Rockville, MD: FDA. August 3, 2007. Available at: http://www.fda.gov/cdrh/MDA/DOCS/p060017.html. Accessed August 12, 2008.
    173. Viale G, Bosari S, Maxxarol G, et al. Intra-operative examination of axillary sentinel lymph nodes in breast carcinoma patients. Cancer 1999; 85(11):2433-2438.
    174. Smeets A, Christiaens M. Implications of the sentinel lymph node procedure for local and systemic adjuvant treatment. Current Opinion in Oncology 2005; 17:539-544.
    175. Viale G, Dell'Orto P, Biasi MO, et al. Comparative evaluation of an extensive histopathologic examination and a real-time reverse-transcription-polymerase chain reaction assay for mammaglobin and cytokeratin 19 on axillary sentinel lymph nodes of breast carcinoma patients. Ann Surg. 2008;247(1):136-142.
    176. Julian TB, Blumencranz P, Deck K, et al. Novel intraoperative molecular test for sentinel lymph node metastases in patients with early-stage breast cancer. J Clin Oncol. 2008;26(20):3338-3345.
    177. Visintin I, Feng Z, Longton G, et al. Diagnostic markers for early detection of ovarian cancer. Clin Cancer Res. 2008;14(4):1065-1072.
    178. Society of Gynecologic Oncologists (SGO).. Statement regarding OvaSure. Chicago, IL: SGO; July 2, 2008. Available at: http://blog.targethealth.com/?p=1492. Accessed September 2, 2008.
    179. U.S. Food and Drug Administration (FDA), Center for Devices and Radiologic Health (CDRH), Office of In Vitro Diagnostic Device Evaluation and Safety (OVID). Warning Letter to Laboratory Corporation of America. Rockville, MD: FDA; September 29, 2008. Available at: http://www.fda.gov/foi/warning_letters/s6947c.htm. Accessed October 9, 2008.
    180. Coradini D, Daidone MG. Biomolecular prognostic factors in breast cancer. Curr Opin Obstet Gynecol. 2004;16(1):49-55.
    181. Provista Life Sciences. The BT test and early breast cancer detection [website]. Phoenix, AZ: Provista Life Sciences; 2008. Available at: http://www.provistals.com/BTTestOverview.aspx. Accessed September 8, 2008.
    182. Urban N, McIntosh MW, Andersen M, Karlan BY. Ovarian cancer screening. Hematol Oncol Clin North Am. 2003;17(4):989-1005.
    183. Lu KH, Patterson AP, Wang L, et al. Selection of potential markers for epithelial ovarian cancer with gene expression arrays and recursive descent partition analysis. Clin Cancer Res. 2004;10(10):3291-3300.
    184. Drapkin R, von Horsten HH, Lin Y, et al. Human epididymis protein 4 (HE4) is a secreted glycoprotein that is overexpressed by serous and endometrioid ovarian carcinomas. Cancer Res. 2005;65(6):2162-2169.
    185. Rosenthal AN, Menon U, Jacobs IJ. Screening for ovarian cancer. Clin Obstet Gynecol. 2006;49(3):433-447.
    186. Scholler N, Crawford M, Sato A, et al. Bead-based ELISA for validation of ovarian cancer early detection markers. Clin Cancer Res. 2006;12(7 Pt 1):2117-2124.
    187. Havrilesky LJ, Whitehead CM, Rubatt JM, et al. Evaluation of biomarker panels for early stage ovarian cancer detection and monitoring for disease recurrence. Gynecol Oncol. 2008;110(3):374-382.
    188. Lowe KA, Shah C, Wallace E, et al. Effects of personal characteristics on serum CA125, mesothelin, and HE4 levels in healthy postmenopausal women at high-risk for ovarian cancer. Cancer Epidemiol Biomarkers Prev. 2008;17(9):2480-2487.
    189. Otchy D, Hyman NH, Simmang C, et al. Practice parameters for colon cancer. Dis Colon Rectum. 2004;47(8):1269-1284.
    190. Compton CC. Pathology and prognostic determinants of colorectal cancer. UpToDate [online serial]. Waltham, MA: UpToDate; 2008.
    191. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Special Report: Pharmacogenomics of cancer-candidate genes.TEC Assessment Program. Chicago, IL: BCBSA; November 2007;22(5). Available at: http://www.bcbs.com/blueresources/tec/vols/22/22_05.pdf. Accessed September 9, 2008.
    192. Duffy MJ, van Dalen A, Haglund C, et al. Tumour markers in colorectal cancer: European Group on Tumour Markers (EGTM) guidelines for clinical use. Eur J Cancer. 2007 Jun;43(9):1348-1360.
    193. Shankaran V, Wisinski KB, Mulcahy MF, et al. The role of molecular markers in predicting response to therapy in patients with colorectal cancer. Mol Diagn Ther. 2008;12(2):87-98.
    194. Welch S, Kocha RB, Rumble K, et al., Gastrointestinal Cancer Disease Site Group. Cancer Care Ontario. The role of bevacizumab (avastin) combined with chemotherapy in the treatment of patients with advanced colorectal cancer: Guideline recommendations.  Evidence-based Series #2-25: Section 1. Toronto, ON: Cancer Care Ontario; May 2008.
    195. National Institute for Health and Clinical Excellence (NICE). Bevacizumab and cetuximab for the treatment of metastatic colorectal cancer. Technology Appraisal Guidance 118. London, UK: NICE; January 2007. Available at: http://www.nice.org.uk/guidance/TA118. Accessed July 25, 2007.
    196. Secord AA, Darcy KM, Hutson A, et al; Gynecologic Oncology Group study. Co-expression of angiogenic markers and associations with prognosis in advanced epithelial ovarian cancer: a Gynecologic Oncology Group study. Gynecol Oncol. 2007;106(1):221-232.
    197. Hellstrom I, Raycraft J, Hayden-Ledbetter M, et al. The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma. Cancer Res. 2003;63:3695. 
    198. Hellstrom I, Hellstrom KE. SMRP and HE4 as biomarkers for ovarian carcinoma when used alone and in combination with CA125 and/or each other. Adv Exp Med Biol. 2008;622:15-21
    199. Moore RG, Brown AK, Miller MC, et al. The use of multiple novel tumor biomarkers for the detection of ovarian carcinoma in patients with a pelvic mass. Gynecol Oncol. 2008;108(2):402-408.
    200. Bast RC Jr, Brewer M, Zou C, et al. Prevention and early detection of ovarian cancer: Mission impossible? Recent Results Cancer Res. 2007;174:91-100. 
    201. Scholler N, Crawford M, Sato A, et al. Bead-based ELISA for validation of ovarian cancer early detection markers. Clin Cancer Res. 2006;12(7 Pt 1):2117-2124.
    202. Adams JM, Cory S. The Bcl-2 apoptotic switch in cancer development and therapy. Oncogene. 2007;26:1324-1337.
    203. Salgia R. Molecular markers in non-small cell lung cancer. Waltham, MA; UpToDate [online serial]; 2008.
    204. Reed JC. Bcl-2-family proteins and hematologic malignancies: history and future prospects. Blood. 2008;111(7):3322-3330.
    205. Bos JL. Ras oncogenes in human cancer: A review. Cancer Res. 1989;49(17):4682-4689.
    206. Lièvre A, Bachet JB, Le Corre D, et al. KRAS mutation status is predictive of response to cetuximab therapy in colorectal cancer. Cancer Res. 2006;66(8):3992-3995.
    207. Di Fiore F, Blanchard F, Charbonnier F, et al. Clinical relevance of KRAS mutation detection in metastatic colorectal cancer treated by Cetuximab plus chemotherapy. Br J Cancer. 2007;96(8):1166-1169.
    208. De Roock W, Piessevaux H, De Schutter J, et al. KRAS wild-type state predicts survival and is associated to early radiological response in metastatic colorectal cancer treated with cetuximab. Ann Oncol. 2008;19(3):508-515.
    209. Lièvre A, Bachet JB, Boige V, et al. KRAS mutations as an independent prognostic factor in patients with advanced colorectal cancer treated with cetuximab. J Clin Oncol. 2008;26(3):374-379.
    210. Moroni M, Veronese S, Benvenuti S, et al. Gene copy number for epidermal growth factor receptor (EGFR) and clinical response to antiEGFR treatment in colorectal cancer: a cohort study. Lancet Oncol. 2005;6(5):279-286.
    211. Gonçalves A, Esteyries S, Taylor-Smedra B, et al. A polymorphism of EGFR extracellular domain is associated with progression free-survival in metastatic colorectal cancer patients receiving cetuximab-based treatment. BMC Cancer. 2008;8(169). Available at: http://www.biomedcentral.com/1471-2407/8/169.  Accessed October 16, 2008.
    212. Van Cutsem E, Lang I., D'haens G., et al. KRAS status and efficacy in the first-line treatment of patients with metastatic colorectal cancer (mCRC) treated with FOLFIRI with or without cetuximab: The CRYSTAL experience. J Clin Oncol. 2008;26: Abstr. 2. Available at: http://www.asco.org/ASCO/Abstracts+%26+Virtual+Meeting/Abstracts?&vmview=abst_detail_view&confID=55&abstractID=34491. Accessed October 16, 2008.
    213. Linardou H, Dahabreh IJ, Kanaloupiti D, et al. Assessment of somatic k-RAS mutations as a mechanism associated with resistance to EGFR-targeted agents: A systematic review and meta-analysis of studies in advanced non-small-cell lung cancer and metastatic colorectal cancer. Lancet Oncol. 2008;9(10):962-972.
    214. Bokemeyer C, Bondarenko I, Hartmann J, et al. KRAS status and efficacy of first-line treatment of patients with metastatic colorectal cancer (mCRC) with FOLFOX with or without cetuximab: The OPUS experience. J Clin Oncol. 2008; 26: (May 20 Suppl; Abstr. 4000). Available at: http://www.asco.org/ASCO/Abstracts+%26+Virtual+Meeting/Abstracts?&vmview=abst_detail_view&confID=55&abstractID=35260. Accessed October 16, 2008.
    215. Amado RG, Wolf M, Peeters M, et al. Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J Clin Oncol. 2008;26(10):1626-1634.
    216. Blue Cross Blue Shield Association (BCBSA), Technology Evaluation Center (TEC). KRAS mutations and epidermal growth factor receptor inhibitor therapy in metastatic colorectal cancer. TEC Assessment Program. Chicago, IL: BCBSA; January 2009;25(6). 
    217. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Special report: Recent developments in prostate cancer genetics and genetic testing. TEC Assessments in Press. Chicago, IL: BCBSA; September 2008.
    218. Nielsen KV, Ejlertsen B, Møller S, et al. The value of TOP2A gene copy number variation as a biomarker in breast cancer: Update of DBCG trial 89D. Acta Oncol. 2008;47(4):725-734.
    219. Järvinen TA, Liu ET. Simultaneous amplification of HER-2 (ERBB2) and topoisomerase IIalpha (TOP2A) genes--molecular basis for combination chemotherapy in cancer. Curr Cancer Drug Targets. 2006;6(7):579-602.
    220. Pritchard KI, Messersmith H, Elavathil L, et al. HER-2 and topoisomerase II as predictors of response to chemotherapy. J Clin Oncol. 2008;26(5):736-744.
    221. Järvinen TA, Liu ET. Simultaneous amplification of HER-2 (ERBB2) and topoisomerase IIalpha (TOP2A) genes--molecular basis for combination chemotherapy in cancer. Curr Cancer Drug Targets. 2006;6(7):579-602.
    222. Everhard S, Kaloshi G, Crinière E, et al. MGMT methylation: A marker of response to temozolomide in low-grade gliomas. Ann Neurol. 2006;60(6):740-743.
    223. Palanichamy K, Erkkinen M, Chakravarti A. Predictive and prognostic markers in human glioblastomas. Curr Treat Options Oncol. 2006;7(6):490-504.
    224. van den Bent MJ, Kros JM. Predictive and prognostic markers in neuro-oncology. J Neuropathol Exp Neurol. 2007;66(12):1074-1081.
    225. Stupp R, Hegi ME, Gilbert MR, et al. Chemoradiotherapy in malignant glioma: standard of care and future directions. J Clin Oncol. 2007;25(26):4127-4136.
    226. Murat A, Migliavacca E, Gorlia T, et al. Stem cell-related "self-renewal" signature and high epidermal growth factor receptor expression associated with resistance to concomitant chemoradiotherapy in glioblastoma. J Clin Oncol. 2008;26(18):3015-3024.
    227. Secord AA, Darcy KM, Hutson A, et al. Co-expression of angiogenic markers and associations with prognosis in advanced epithelial ovarian cancer: A Gynecologic Oncology Group study. Gynecol Oncol. 2007;106(1):221-232.
    228. Ghoneim C, Soula-Rothhut M, Rothhut B. Thrombospondin-1 in differentiated thyroid cancer: Dr. Jekyll and Mr. Hyde. Connect Tissue Res. 2008;49(3):257-260.
    229. Brostjan C, Gebhardt K, Gruenberger B, et al. Neoadjuvant treatment of colorectal cancer with bevacizumab: the perioperative angiogenic balance is sensitive to systemic thrombospondin-1 levels. Clin Cancer Res. 2008;14(7):2065-2074.
    230. Garcia AA, Hirte H, Fleming G, et al. Phase II clinical trial of bevacizumab and low-dose metronomic oral cyclophosphamide in recurrent ovarian cancer: A trial of the California, Chicago, and Princess Margaret Hospital phase II consortia. J Clin Oncol. 2008;26(1):76-82.
    231. List AF, Spier CM. Multidrug resistance in acute leukemia: A conserved physiologic function. Leuk Lymphoma. 1992;8(1-2):9-14.
    232. Yuen AR, Sikic BI. Multidrug resistance in lymphomas. J Clin Oncol. 1994;12(11):2453-2459.
    233. Solary E, Drenou B, Campos L, et al; Groupe Ouest Est Leucémies Aiguës Myéloblastiques. Quinine as a multidrug resistance inhibitor: A phase 3 multicentric randomized study in adult de novo acute myelogenous leukemia. Blood. 2003;15;102(4):1202-1210.
    234. Gruber A, Björkholm M, Brinch L, et al. A phase I/II study of the MDR modulator Valspodar (PSC 833) combined with daunorubicin and cytarabine in patients with relapsed and primary refractory acute myeloid leukemia. Leuk Res. 2003;27(4):323-328.
    235. Takara K, Sakaeda T, Okumura K. An update on overcoming MDR1-mediated multidrug resistance in cancer chemotherapy. Curr Pharm Des. 2006;12(3):273-286.
    236. Miyake M, Nakano K, Ieki Y, et al. Motility related protein 1 (MRP-1/CD9) expression: inverse correlation with metastases in breast cancer. Cancer Res. 1995;55(18):4127-4131.
    237. Erovic BM, Pammer J, Hollemann D, et al. Motility-related protein-1/CD9 expression in head and neck squamous cell carcinoma Head Neck. 2003;25(10):848-857.
    238. Mimori K, Kataoka A, Yoshinaga K, et al. Identification of molecular markers for metastasis-related genes in primary breast cancer cells. Clin Exp Metastasis. 2005;22(1):59-67.
    239. Mhawech P, Dulguerov P, Tschanz E, et al. Motility-related protein-1 (MRP-1/CD9) expression can predict disease-free survival in patients with squamous cell carcinoma of the head and neck. Br J Cancer. 2004;90(2):471-475.
    240. Mhawech P, Herrmann F, Coassin M, et al. Motility-related protein 1 (MRP-1/CD9) expression in urothelial bladder carcinoma and its relation to tumor recurrence and progression. Cancer. 2003;98(8):1649-1657.
    241. National Cancer Institute. Carcinoma of unknown primary treatment (PDQ®). Bethesda, MD: NCI; 2008. Available at: http://www.cancer.gov/cancertopics/pdq/treatment/unknownprimary. Accessed October 13, 2008.
    242. U.S. Food and Drug Administration (FDA). FDA clears test that helps identify type of cancer in tumor sample. FDA News. Rockville, MD: FDA; July 31, 2008. Available at: http://www.fda.gov/bbs/topics/NEWS/2008/NEW01870.html. Accessed October 13, 2008.
    243. Dumur CI, Lyons-Weiler M, Sciulli C, et al. Interlaboratory performance of a microarray-based gene expression test to determine tissue of origin in poorly differentiated and undifferentiated cancers. J Mol Diagn. 2008;10(1):67-77.
    244. Pathwork Diagnostics [website]. Announcing the pathwork tissue of origin test [website]; Sunnyvale, CA. Available at: http://www.pathworkdx.com/index.html.  Accessed October 13, 2008.
    245. Monzon FA, Dumur CI, Lyons-Weiler M, et al. Validation of a gene expression-based tissue of origin test applied to poorly differentiated and undifferentiated cancers. Abstract presented at the 13th Annual Meeting of the Association for Molecular Pathology, Los Angeles, CA, November 7-10, 2007.
    246. Flynn K. Bladder cancer surveillance. Brief Overview. Final Report. Boston, MA: Veterans Health Administration, Office of Patient Care Services, Technology Assessment Program; November 2007.
    247. Nauseef WM, Olsson I, Arnljots K. Biosynthesis and processing of myeloperoxidase--a marker for myeloid cell differentiation. Eur J Haematol. 1988;40(2):97-110.
    248. Storr J, Dolan G, Coustan-Smith E, et al. Value of monoclonal anti-myeloperoxidase (MPO7) for diagnosing acute leukaemia. J Clin Pathol. 1990;43(10):847-849.
    249. Dunphy CH, Polski JM, Evans HL, Gardner LJ. Evaluation of bone marrow specimens with acute myelogenous leukemia for CD34,CD15, CD117, and myeloperoxidase. Arch Pathol Lab Med. 2001;125(8):1063-1069.
    250. Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood. 2002;100(7):2292-2302.
    251. Matsuo T, Kuriyama K, Miyazaki Y, et al. The percentage of myeloperoxidase-positive blast cells is a strong independent prognostic factor in acute myeloid leukemia, even in the patients with normal karyotype. Leukemia. 2003;17:1538-1543.
    252. British Committee for Standards in Haematology, Milligan DW, Grimwade D, Cullis JO, et al. Guidelines on the management of acute myeloid leukaemia in adults. Br J Haematol. 2006;135(4):450-474.
    253. Storr J, Dolan G, Coustan-Smith E, et al. Value of monoclonal anti-myeloperoxidase (MPO7) for diagnosing acute leukaemia. J Clin Pathol. 1990;43(10):847-849.
    254. British Committee for Standards in Haematology, Milligan DW, Grimwade D, Cullis JO, et al. Guidelines on the management of acute myeloid leukaemia in adults. Br J Haematol. 2006;135(4):450-474.
    255. National Comprehensive Cancer Network (NCCN). Acute myeloid leukemia. NCCN Clinical Practice Guidelines in Oncology v.1.2009. Fort Washington, PA: NCCN; September 2008. Available at: http://www.nccn.org/professionals/physician_gls/PDF/aml.pdf. Accessed January 26, 2009.
    256. Liebman HA, Furie BC, Tong MJ, et al. Des-gamma-carboxy (abnormal) prothrombin as a serum marker of primary hepatocellular carcinoma. NEJM. 1984;310(22):1427-1431.
    257. Fujiyama S, Izuno K, Gohshi K, et al. Clinical usefulness of des-gamma-carboxy prothrombin assay in early diagnosis of hepatocellular carcinoma. Dig Dis Sci. 1991;36(12):1787-1792.
    258. Weitz IC; Liebman HA. Des-gamma-carboxy (abnormal) prothrombin and hepatocellular carcinoma: A critical review. Hepatology. 1993;18(4):990-997.
    259. Nomura F, Ishijima M, Horikoshi A, et al. Determination of serum des-gamma-carboxy prothrombin levels in patients with small-sized hepatocellular carcinoma: Comparison of the conventional enzyme immunoassay and two modified methods. Am J Gastroenterol. 1996;91(7):1380-1383.
    260. Aoyagi Y, Oguro M, Yanagi M, et al. Clinical significance of simultaneous determinations of alpha-fetoprotein and des-gamma-carboxy prothrombin in monitoring recurrence in patients with hepatocellular carcinoma. Cancer. 1996;77(9):1781-1786.
    261. Hamamura K, Shiratori Y, Shiina S, et al. Unique clinical characteristics of patients with hepatocellular carcinoma who present with high plasma des-gamma-carboxy prothrombin and low serum alpha-fetoprotein. Cancer. 2000;88(7):1557-1564.
    262. Ikoma J, Kaito M, Ishihara T, et al. Early diagnosis of hepatocellular carcinoma using a sensitive assay for serum des-gamma-carboxy prothrombin: A prospective study. Hepatogastroenterology. 2002;49(43):235-238.
    263. Nagaoka S, Yatsuhashi H, Hamada H, et al. The des-gamma-carboxy prothrombin index is a new prognostic indicator for hepatocellular carcinoma. Cancer. 2003;98(12):2671-2677.
    264. Yuan LW, Tang W, Kokudo N, et al. Measurement of des-gamma-carboxy prothrombin levels in cancer and non-cancer tissue in patients with hepatocellular carcinoma. Oncol Rep. 2004;12(2):269-273.
    265. Yuen MF, Lai CL. Serological markers of liver cancer. Best Pract Res Clin Gastroenterol. 2005;19(1):91-99.
    266. Nakamura S, Nouso K, Sakaguchi K, et al. Sensitivity and specificity of des-gamma-carboxy prothrombin for diagnosis of patients with hepatocellular carcinomas varies according to tumor size. Am J Gastroenterol. 2006;101(9):2038-2043.
    267. Toyoda H, Kumada T, Kiriyama S, et al. Prognostic significance of simultaneous measurement of three tumor markers in patients with hepatocellular carcinoma. Clin Gastroenterol Hepatol. 2006;4(1):111-117.
    268. Shirabe K, Itoh S, Yoshizumi T, et al. The predictors of microvascular invasion in candidates for liver transplantation with hepatocellular carcinoma-with special reference to the serum levels of des-gamma-carboxy prothrombin. J Surg Oncol. 2007;95(3):235-340.
    269. Schwartz JM, Carithers RL. Clinical features and diagnosis of primary hepatocellular carcinoma. UpToDate [online serial]. Waltham, MA: UpToDate; 2008.
    270. Sherman M. Surveillance for hepatocellular carcinoma in adults with chronic liver disease. UpToDate [online serial]. Waltham, MA: UpToDate; 2008.
    271. Taylor CR. Cirrhosis. eMedicine Medicine Topic 175. Omaha, NE: eMedicine.com. January 7, 2009. Available at: http://emedicine.medscape.com/article/366426-overview. Accessed January 13, 2009.
    272. National Comprehensive Cancer Network (NCCN). Hepatobiliary cancers. NCCN Clinical Practice Guidelines in Oncology v.1.2010. Fort Washington, PA: NCCN; 2010.
    273. Lüftner D, Possinger K. Nuclear matrix proteins as biomarkers for breast cancer. Expert Rev Mol Diagn. 2002;2(1):23-31.
    274. Wright T, McGechan A. Breast cancer: New technologies for risk assessment and diagnosis. Mol Diagn. 2003;7(1):49-55.
    275. Matritech, Inc. [website]. Newton, MA; Matritech; 2009. Available at: http://www.matritech.com/. Accessed on January 27, 2009.
    276. National Comprehensive Cancer Network (NCCN). Occult primary. NCCN Clinical Practice Guidelines in Oncology v.1.2009. Fort Washington, PA: NCCN; July 2008.
    277. Singletary SE, Allred C, Ashley P, et al. Revision of the American Joint Committee on Cancer staging system for breast cancer. J Clin Oncol. 2002;20(17):3628-3636.
    278. National Cancer Institute. Hormone therapy with or without combination chemotherapy in treating women who have undergone surgery for node-negative breast cancer (the TAILORx Trial). ClinicalTrials.gov ID. NCT00310180. Bethesda, MD: National Library of Medicine; updated August 11, 2009.
    279. Karapetis CS, Khambata-Ford S, Jonker DJ, et al. K-ras mutations and benefit from cetuximab in advanced colorectal cancer. N Engl J Med. 2008;359(17):1757-1765.
    280. Allegra CJ, Jessup JM, Somerfield MR, et al. American Society of Clinical Oncology provisional clinical opinion: Testing for KRAS gene mutations in patients with metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor monoclonal antibody therapy. J Clin Oncol. 2009;27(12):2091-2096.
    281. Marchionni L, Wilson RF, Marinopoulos SS, et al. Impact of gene expression profiling on breast cancer outcomes. Evidence Report/Technology Assessment No. 160. Prepared by the Johns Hopkins University Evidence-based Practice Center for the Agency for Healthcare Research and Quality (AHRQ). AHRQ Publication No. 08-E002. Rockville, MD: AHRQ; January 2008.
    282. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: Can tumor gene expression profiling improve outcomes in patients with breast cancer? Genet Med. 2009;11(1):66-73.
    283. de Boer M, van Deurzen CH, van Dijck JA, et al. Micrometastases or isolated tumor cells and the outcome of breast cancer. N Engl J Med. 2009;361(7):653-663.
    284. Goodman S, Dickerson K, Wilson R. Gene expression profile tests for early-stage breast cancer. Effectiveness Guidance Document: Methodological Guidance for the Design of Comparative Effectiveness Studies. Version 1.0. Baltimore, MD: Center for Medical Technology Policy (CMTP); June 2009.
    285. Kawai M, Uchiyama K, Tani M, et al. Clinicopathological features of malignant intraductal papillary mucinous tumors of the pancreas: The differential diagnosis from benign entities. Arch Surg. 2004;139(2):188-192.
    286. Donovan MJ, Hamann S, Clayton M, et al. Systems pathology approach for the prediction of prostate cancer progression after radical prostatectomy. J Clin Oncol. 2008;26(24):3923-3929.
    287. Klein EA, Stephenson AJ, Raghavan D, Dreicer R. Systems pathology and predicting outcome after radical prostatectomy. J Clin Oncol. 2008;26(24):3916-3917.
    288. Shen J, Brugge WR, Dimaio CJ, Pitman MB. Molecular analysis of pancreatic cyst fluid: A comparative analysis with current practice of diagnosis. Cancer Cytopathol. 2009;117(3):217-227.
    289. Leung KK, Ross WA, Evans D, et al. Pancreatic cystic neoplasm: The role of cyst morphology, cyst fluid analysis, and expectant management. Ann Surg Oncol. 2009;16(10):2818-2824.
    290. Sutcliffe P, Hummel S, Simpson E, et al. Use of classical and novel biomarkers as prognostic risk factors for localised prostate cancer: A systematic review. Health Technol Assess. 2009;13(5):iii, xi-xiii 1-219.
    291. Gelmann EP, Henshall SM. Clinically relevant prognostic markers for prostate cancer: The search goes on. Ann Intern Med. 2009;150(9):647-649.
    292. Tosoian JJ, Loeb S, Kettermann A, et al. Accuracy of PCA3 measurement in predicting short-term biopsy progression in an active surveillance program. J Urol. 2010;183(2):534-538.
    293. Noon AP, Vlatković N, Polański R, et al. p53 and MDM2 in renal cell carcinoma: Biomarkers for disease progression and future therapeutic targets? Cancer. 2010;116(4):780-790.
    294. Knauer M, Mook S, Rutgers EJ, et al. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat. 2010;120(3):655-661.
    295. Fung ET. A recipe for proteomics diagnostic test development: the OVA1 test,
      from biomarker discovery to FDA clearance. Clin Chem. 2010;56(2):327-329.
    296. Trikalinos TA, Terasawa T, Raman G, et al. A systematic review of loss-of-heterozygosity based topographic genotyping with PathfinderTG. Technology Assessment Report. Project ID: GEND0308. Prepared by the Tufts Evidence-based Practice Center for the Agency for Healthcare Research and Quality (AHRQ) under Contract No. HHSA 290 2007 10055 I. Rockville, MD: AHRQ; March 1, 2010.
    297. National Institute for Health and Clinical Excellence (NICE). Diagnosis and management of metastatic malignant disease of unknown primary origin. Clinical Guideline. Draft for Consultation. London, UK: NICE; December 2009.
    298. National Comprehensive Cancer Network (NCCN). Occult primary (cancer of unknown primary [CUP]). NCCN Clinical Practice Guidelines in Oncology v.1.2010. Fort Washington, PA: NCCN; 2010.
    299. Ring BZ, Seitz RS, Beck R, et al. Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer. J Clin Oncol. 2006; 24(19):3039-3047.
    300. Ross DT, Kim CY, Tang G, et al. Chemosensitivity and stratification by a five monoclonal antibody immunohistochemistry test in the NSABP B14 and B20 trials. Clin Cancer Res. 2008;14(20):6602-6609.
    301. Cohen SJ, Punt CJ, Iannotti N, et al. Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. J Clin Oncol. 2008;26(19):3213-3221.
    302. De Giorgi U, Valero V, Rohren E, et al. Circulating tumor cells and [18F]fluorodeoxyglucose positron emission tomography/computed tomography for outcome prediction in metastatic breast cancer. J Clin Oncol. 2009;27(20):3303-3311.
    303. Mejia A, Schulz S, Hyslop T, et al. GUCY2C reverse transcriptase PCR to stage pN0 colorectal cancer patients. Expert Rev Mol Diagn. 2009;9(8):777-785.
    304. Pénzváltó Z, Mihály Z, Gyorffy B. Gene expression based multigene prognostic and predictive tests in breast cancer. Magy Onkol. 2009;53(4):351-359.
    305. Bartlett JM, Thomas J, Ross DT, et al. Mammostrat as a tool to stratify breast cancer patients at risk of recurrence during endocrine therapy. Breast Cancer Res. 2010;12(4):R47.
    306. Boyle P, Chapman CJ, Holdenrieder S, et al. Clinical validation of an autoantibody test for lung cancer. Ann Oncol. 2011;22(2):383-389.
    307. Murray A, Chapman CJ, Healey G, et al. Technical validation of an autoantibody test for lung cancer. Ann Oncol. 2010;21(8):1687-1693.
    308. U.S. Preventive Services Task Force. Lung cancer screening: Recommendation statement. Ann Intern Med. 2004;140(9):738-739.
    309. Humphrey LL, Teutsch S, Johnson M; U.S. Preventive Services Task Force. Lung cancer screening with sputum cytologic examination, chest radiography, and computed tomography: An update for the U.S. Preventive Services Task Force. Ann Intern Med. 2004;140(9):740-753.
    310. Gradishar WJ. Male breast cancer. UpToDate [online serial]. Waltham, MA: UpToDate; 2010.
    311. Shak S. Palmer G, Baehner FL, et al; Genomic Health, Redwood City, CA; Indiana University School of Medicine, Indianapolis, IN. Molecular characterization of male breast cancer by standardized quantitative RT-PCR analysis: First large genomic study of 347 male breast cancers compared to 82,434 female breast cancers. J Clin Oncol. 2009;27:15s (suppl; abstr 549).
    312. Monzon FA, Lyons-Weiler M, Buturovic LJ, et al. Multicenter validation of a 1,550-gene expression profile for identification of tumor tissue of origin. J Clin Oncol. 2009;27(15):2503-2508.
    313. Yurkovetsky Z, Skates S, Lomakin A, et al. Development of a multimarker assay for early detection of ovarian cancer. J Clin Oncol. 2010;28(13):2159-2166.
    314. Muller CY. Doctor, should I get this new ovarian cancer test-OVA1? Obstet Gynecol. 2010;116(2 Pt 1):246-247.
    315. Monzon FA, Koen TJ. Diagnosis of metastatic neoplasms: molecular approaches for identification of tissue of origin. Arch Pathol Lab Med. 2010;134(2):216-224.
    316. Anderson GG, Weiss LM. Determining tissue of origin for metastatic cancers: Meta-analysis and literature review of immunohistochemistry performance. Appl Immunohistochem Mol Morphol. 2010;18(1):3-8.
    317. Messick CA, Sanchez J, Dejulius KL, et al. CEACAM-7: A predictive marker for rectal cancer recurrence. Surgery. 2010;147(5):713-719.
    318. Castro MA, Dal-Pizzol F, Zdanov S, et al. CFL1 expression levels as a prognostic and drug resistance marker in nonsmall cell lung cancer. Cancer. 2010;116(15):3645-3655.
    319. Shanmugam C, Jhala NC, Katkoori VR, et al. Prognostic value of mucin 4 expression in colorectal adenocarcinomas. Cancer. 2010;116(15):3577-3586.
    320. Ratner E, Lu L, Boeke M, et al. A KRAS-variant in ovarian cancer acts as a genetic marker of cancer risk. Cancer Res. 2010;70(16):6509-6515.
    321. Hollestelle A, Pelletier C, Hooning M, et al. Prevalence of the variant allele rs61764370 T>G in the 3'UTR of KRAS among Dutch BRCA1, BRCA2 and non-BRCA1/BRCA2 breast cancer families. Breast Cancer Res Treat. 2011;128(1):79-84.
    322. Cocco E, Bellone S, El-Sahwi K, et al. Serum amyloid A: A novel biomarker for endometrial cancer. Cancer. 2010;116(4):843-851.
    323. Park CM, Lee WY, Chun HK, et al. Relationship of polymorphism of the tandem repeat sequence in the thymidylate synthase gene and the survival of stage III colorectal cancer patients receiving adjuvant 5-flurouracil-based chemotherapy. J Surg Oncol. 2010;101(1):22-27.
    324. Sumi T, Katsumata K, Tsuchida A, et al. Correlations of clinicopathological factors with protein expression levels of thymidylate synthase, dihydropyrimidine dehydrogenase and orotate phosphoribosyltransferase in colorectal cancer. Chemotherapy. 2010;56(2):120-126.
    325. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Gene expression profiling for women with lymph-node-positive breast cancer to select adjuvant chemotherapy treatment. TEC Assessment Program. Chicago, IL: BCBSA; November 2010;25(1).
    326. Albain KS, Barlow WE, Shak S, et al; Breast Cancer Intergroup of North America. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: A retrospective analysis of a randomised trial. Lancet Oncol. 2010;11(1):55-65.
    327. No authors listed. Committee opinion no. 477: The role of the obstetrician-gynecologist in the early detection of epithelial ovarian cancer. Obstet Gynecol. 2011;117(3):742-746.
    328. Oratz R, Kim B, Chao C, et al. Physician survey of the effect of the 21-gene recurrence score assay results on treatment recommendations for patients with lymph node-positive, estrogen receptor-positive breast cancer. J Oncol Practice. 2011;7(2):94-99.
    329. Cohen SJ, Punt CJ, Iannotti N, et al. Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. J Clin Oncol. 2008;26(19):3213-3221.
    330. De Giorgi U, Valero V, Rohren E, et al. Circulating tumor cells and [18F]fluorodeoxyglucose positron emission tomography/computed tomography for outcome prediction in metastatic breast cancer. J Clin Oncol. 2009;27(20):3303-3311.
    331. Gunven P, Randén M, Elmberger G, et al. Gene expression profiling guiding diagnosis and therapy of rare mammary-like anogenital gland carcinomas. Med Oncol. 2012;29(1):127-132.
    332. Gevensleben H, Gohring UJ, Buttner R, et al. Comparison of MammaPrint and TargetPrint results with clinical parameters in German patients with early stage breast cancer. Int J Mol Med. 2010;26(6):837-843.
    333. Roepman P, Horlings HM, Krijgsman O, et al. Microarray-based determination of estrogen receptor, progesterone receptor, and HER2 receptor status in breast cancer. Clin Cancer Res. 2009;15(22):7003-7011.
    334. Von Hoff DD, Stephenson JJ Jr, Rosen P, et al. Pilot study using molecular profiling of patients' tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol. 2010;28(33):4877-4883.
    335. Doroshow JH. Selecting systemic cancer therapy one patient at a time: Is there a role for molecular profiling of individual patients with advanced solid tumors? J Clin Oncol. 2010;28(33):4869-4876.
    336. Dutch College of Health Insurances (CvZ). Genexpressietest Mammaprint bij de behandeling van het mammacarcinoom. Amsterdam, The Netherlands: CvZ; October 29, 2010.
    337. Borg A, Bergh J, Kirstoffersson U. Genprofiltest vid bröstcancer. [Gene expression profiling for breast cancer.] SBU Kommenterar. Publicerad 2010-10-26. Stockholm, Sweden: Swedish Office of Health Technology Assessment (SBU); 2010.
    338. Romeo MJA, Méndez AL. Gene expression test for breast cancer. Oncotype®. Executive abstract. Informes de Evaluación de Tecnologías Sanitarias AETSA 2007/2-20. Sevilla, Spain: Agencia de Evaluación de Tecnologías Sanitarias de Andalucía (AETSA); 2010.
    339. Smartt P. A comparison of gene expression profiling tests for breast cancer. A systematic review update. HSAC Report. Christchurch, New Zealand; Health Services Assessment Collaboration (HSAC); November 2009;3 (16).
    340. Mundy L, Hiller J. NMP22 BladderChek Diagnostic test for bladder cancer. Horizon Scanning Prioritising Summary Update. Canberra, ACT: Department of Health and Ageing; November 2009.
    341. Tice JA. The 70-gene signature (MammaPrint) as a guide for the management of early stage breast cancer. Technology Assessment. San Francisco, CA: California Technology Assessment Forum (CTAF); June 2, 2010.
    342. Sarbia M, Borchard F, Hengels KJ. Histogenetical investigations on adenocarcinomas of the esophagogastric junction. An immunohistochemical study. Pathol Res Pract. 1993;189(5):530-535.
    343. Deeb G, Wang J, Ramnath N, et al. Altered E-cadherin and epidermal growth factor receptor expressions are associated with patient survival in lung cancer: A study utilizing high-density tissue microarray and immunohistochemistry. Mod Pathol. 2004;17(4):430-439.
    344. Murray NP, Calaf GM, Badinez L, et al. P504S expressing circulating prostate cells as a marker for prostate cancer. Oncol Rep. 2010;24(3):687-692.
    345. Aureon Laboratories, Inc. Aureon Laboratories announces name change for existing post-surgical prostate cancer recurrence test commercially available since February 2006, Post-Op Px(TM) is the first diagnostic test to predict prostate cancer recurrence. March 5, 2010, GlobeNewswire. Nasdaz Omx. Available at: http://www.globenewswire.com/newsroom/news.html?d=185946. Accessed December 9, 2011.
    346. Ellis PM, Blais N, Soulieres D, et al. A systematic review and Canadian consensus recommendations on the use of biomarkers in the treatment of non-small cell lung cancer. J Thorac Oncol. 2011;6(8):1379-1391.
    347. Gray RG, Quirke P, Handley K, et al. Validation study of a quantitative multigene reverse transcriptase-polynmerase chain reaction assay for assessment of recurrence risk in patients with stage II colon cancer.  J Clin Oncol. 2011;29:1-13.
    348. Juntermanns B, Kaiser GM, Reis H, et al. Klatskin-mimicking lesions: Still a diagnostical and therapeutical dilemma? Hepatogastroenterology. 2011;58(106):265-269.
    349. Kumaresan K, Kakkar N, Verma A, et al. Diagnostic utility of α-methylacyl CoA racemase (P504S) & HMWCK in morphologically difficult prostate cancer. Diagn Pathol. 2010;22(5):83.
    350. Lopez SE, Velasco DC, Amaro JAB., A systematic review on efficacy and economic impact of genetic tests in breast cancer and depression treatments. Madrid, Spain: Plan de Calidad para el SNS del MSPSI, Unidad de Evaluación de Tecnologías Sanitarias, Agencia Laín Entralgo; 2010.
    351. National Comprehensive Cancer Network (NCCN). Esophageal and Esophagogastric Junction Cancers. NCCN Clinical Practice Guidelines in Oncology v.2.2011. Fort Washington, PA: NCCN; May, 2011. Available at: http://www.nccn.org/professionals/physician_gls/f_guidelines.asp#site.  Accessed: December 2, 2011.
    352. Sinakos E, Saenger AK, Keach J, et al. Many patients with primary sclerosing cholangitis and increased serum levels of carbohydrate antigen 19-9 do not have cholangiocarcinoma. Clin Gastroenterol Hepatol. 2011;9(5):434-439.
    353. Yoshida A, Tsuta K, Nitta H, et al. Bright-field dual-color chromogenic in situ hybridization for diagnosing echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase-positive lung adenocarcinomas. Am J Surg Pathol. 2011;35(8):1226-1234.
    354. Ueland, FR, Desimone, CP, Seamon LG, et al. Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors. Obstet Gynecol. 2011;117(6):1289-1297.
    355. Ware, MR, Smith, A, DeSimone CP, et al. Performance of the American College of Obstetricians and Gynecologists' ovarian tumor referral guidelines with a multivariate index assay. Obstet Gynecol. 2011;117(6):1298-1306.
    356. Febbo, PG, Ladanyi, M, Aldape, KD, et al.  NCCN Task Force Report: Evaluating the Clinical Utility of Tumor Markers in Oncology. J Natl Compre Canc Netw. 2011;9:S1-S31.
    357. National Comprehensive Cancer Network (NCCN). Breast cancer. NCCN Clinical Practice Guidelines in Oncology. Version 2.2011. Fort Washington, PA: NCCN; 2011.
    358. Adelstein BA, Dobbins TA, Harris CA, et al. A systematic review and meta-analysis of KRAS status as the determinant of response to anti-EGFR antibodies and the impact of partner chemotherapy in metastatic colorectal cancer. Eur J Cancer. 2011;47(9):1343-1354.
    359. Ellis PM, Blais N, Soulieres D, et al. A systematic review and Canadian consensus recommendations on the use of biomarkers in the treatment of
      non-small cell lung cancer. J Thorac Oncol. 2011;6(8):1379-1391.
    360. Nair VS, Maeda LS, Ioannidis JP. Clinical outcome prediction by microRNAs in human cancer: A systematic review. J Natl Cancer Inst. 2012;104(7):528-540.
    361. Raman G, Wallace B, Patel K, et al. Update on horizon scans of genetic tests currently available for clinical use in cancers. Technology Assessment Report. Final Report. Prepared by the Tufts Evidence-based Practice Center for the Agency for Healthcare Research and Quality (AHRQ) under contract no. HHSA 290-2007-10055-I. Project ID: GEND0508. Rockville, MD: AHRQ; April 15, 2011.
    362. Sanz-Pamplona R, Berenguer A, Cordero D, et al. Clinical value of prognosis gene expression signatures in colorectal cancer: A systematic review. PLoS One. 2012;7(11):e48877.
    363. Siddiqui AA, Kowalski TE, Kedika R, et al. EUS-guided pancreatic fluid aspiration for DNA analysis of KRAS and GNAS mutations for the evaluation of pancreatic cystic neoplasia: A pilot study. Gastrointest Endosc. 2013;77(4):669-670.
    364. Finkelstein SD, Bibbo M, Loren DE, et al. Molecular analysis of centrifugation supernatant fluid from
      pancreaticobiliary duct samples can improve cancer detection. Acta Cytol. 2012;56(4):439-447.
    365. Lin X, Zhu B, Finkelstein SD, et al. Significance of loss of heterozygosity in predicting axillary lymph node metastasis of invasive ductal carcinoma of the breast. Appl Immunohistochem Mol Morphol. 2012;20(2):116-123.
    366. Ellsworth EM, Palma JF, Spence WC, et al. Mutational profiling of sporadic versus toxin-associated brain cancer formation: Initial findings using loss of heterozygosity profiling. Int J Hyg Environ
      Health. 2012;215(3):427-433.
    367. Hainsworth JD, Rubin MS, Spigel DR, et al. Molecular gene expression profiling to predict the tissue of origin and direct site-specific therapy in patients With carcinoma of unknown primary site: A prospective trial of the Sarah Cannon Research Institute. J Clin Oncol. 2013;31(2):217-223.
    368. Drukker CA, Bueno-de-Mesquita JM, Retèl VP, et al. A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study. Int J Cancer. 2013 Jan 31.[Epub ahead of print]
    369. Bradley LA, Palomaki G, Gutman S, et al. PCA3 testing for the diagnosis and management of prostate cancer. Comparative Effectiveness Review No. 98. Prepared by the Blue Cross and Blue Shield Technology Evaluation Center Evidence-based Practice Center under Contract No. 290-2007-10058-I). AHRQ Publication No. 13-EHC030-EF. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); April 2013.
    370. Little J, Wilson B, Carter R, et al. Multigene panels in prostate cancer risk assessment. Evidence Report/Technology Assessment No. 209. Prepared by the McMaster University Evidence-based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), Contract No. 290-2007-10060-1. AHRQ Publication No. 12-E020-EF. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); 2012.
    371. Alberts SR, Yu T, Behrens RJ, et al. Real-world comparative economics of a 12-gene assay for prognosis in stage II colon cancer [abstract]. J Clin Oncol. 2012;30(suppl 34):Abstract 391.
    372. Srivastava G, Renfro LA, Behrens RJ, et al. Prospective evaluation of a 12-gene assay on treatment recommendations in patients with stage II colon cancer [abstract]. J Clin Oncol. 2012;30(suppl 34):Abstract 453.
    373. Venook AP, Niedzwiecki D, Lopatin M, et al. Biologic determinants of tumor recurrence in stage II colon cancer: Validation study of the 12-gene recurrence score in cancer and leukemia group B (CALGB) 9581. J Clin Oncol. 2013 Mar 25. [Epub ahead of print]
    374. National Horizon Scanning Centre (NHSC). UPDATED: OVA1™ test for the assessment of suspected ovarian cancer. Horizon Scanning Review. Birmingham, UK: National Horizon Scanning Centre (NHSC); 2012.
    375. National Horizon Scanning Centre (NHSC). UPDATED: RealTime mS9 Colorectal Cancer (CRC) Assay for the early detection of colorectal cancer. Horizon Scanning Review. Birmingham, UK: National Horizon Scanning Centre (NHSC); 2012.
    376. National Collaborating Centre for Cancer. Diagnosis and management of metastatic malignant disease of unknown primary origin. Developed for NICE. July 2010. Available at: http://www.nice.org.uk/nicemedia/live/13044/49864/49864.pdf. Accessed March 29, 2013.
    377. Alberta Provincial Thoracic Tumour Team. Non-small cell lung cancer stage IV. Clinical Practice Guideline No. LU-004. Edmonton, AB: Alberta Health Services, Cancer Care; June 2011. 
    378. Gao G, Ren S, Li A, et al. Epidermal growth factor receptor-tyrosine kinase inhibitor therapy is effective as first-line treatment of advanced non-small-cell lung cancer with mutated EGFR: A meta-analysis from six phase III randomized controlled trials. Int J Cancer. 2012;131(5):E822-E829.
    379. Krijgsman O, Roepman P, Zwart W, et al. A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res Treat. 2012;133(1):37-47.
    380. Trock BJ, Brotzman MJ, Mangold LA, et al. Evaluation of GSTP1 and APC methylation as indicators for repeat biopsy in a high-risk cohort of men with negative initial prostate biopsies. BJU Int. 2012;110(1):56-62.
    381. BlueCross BluShield Association (BCBSA). Technology Evaluation Center (TEC). Multi-analyte testing for the evaluation of adnexal masses. TEC Assessment Program. Chicago, IL: BCBSA; 2013. Available at: http://www.bcbs.com/blueresources/tec/press/multi-analyte-testing-for-the.html. Accessed March 29, 2013.
    382. Yu D, Shi J, Sun T, et al. Pharmacogenetic role of ERCC1 genetic variants in treatment response of platinum-based chemotherapy among advanced non-small cell lung cancer patients. Tumour Biol. 2012;33(3):877-884.
    383. Wang Z, Chen JQ, Liu JL, et al. Polymorphisms in ERCC1, GSTs, TS and MTHFR predict clinical outcomes of gastric cancer patients treated with platinum/5-Fu-based chemotherapy: A systematic review. BMC Gastroenterol. 2012;12:137.
    384. Gong W, Zhang X, Wu J, et al. RRM1 expression and clinical outcome of gemcitabine-containing chemotherapy for advanced non-small-cell lung cancer: A meta-analysis. Lung Cancer. 2012;75(3):374-380.
    385. Friboulet L, Olaussen KA, Pignon JP, et al. ERCC1 isoform expression and DNA repair in non-small-cell lung cancer. N Engl J Med. 2013;368(12):1101-1110.
    386. Besse B, Olaussen KA, Soria JC. ERCC1 and RRM1: Ready for prime time? J Clin Oncol. 2013;31(8):1050-1060.
    387. Fletcher SW. Screening for breast cancer. Last reviewed February 2013. UpToDate Inc. Waltham, MA.
    388. Collins LC, Laronga C, Wong JS. Ductal carcinoma in situ: Treatment and prognosis. Last reviewed February 2013. UpToDate Inc. Waltham, MA.
    389. National Comprehensive Cancer Network. Clinical Practice Guidelines in Oncology. Breast cancer (Version 2.2013). NCCN: Fort Washington: PA.
    390. National Comprehensive Cancer Network. Clinical Practice Guidelines in Oncology. Multiple myeloma (Version 2.2013). NCCN: Fort Washington: PA.
    391. Oxnard GR, Binder A, Jänne PA. New targetable oncogenes in non-small-cell lung cancer. J Clin Oncol. 2013;31(8):1097-1104.
    392. Shin SJ, Hwang JW, Ahn JB, et al. Circulating vascular endothelial growth factor receptor 2/pAkt-positive cells as a functional pharmacodynamic marker in metastatic colorectal cancers treated with antiangiogenic agent. Invest New Drugs. 2013;31(1):1-13.
    393. Yu Z, Li Z, Cai B, et al. Association between the GSTP1 Ile105Val polymorphism and prostate cancer risk: A systematic review and meta-analysis. Tumour Biol. 2013 34(3):1855-1863.
    394. Janku F, Wheler JJ, Hong DS, Kurzrock R. Bevacizumab-based treatment in colorectal cancer with a NRAS Q61K mutation. Target Oncol. 2013 Feb 12. [Epub ahead of print]
    395. Khatcheressian JL, Hurley P, Bantug E, et al.; American Society of Clinical Oncology. Breast cancer follow-up and management after primary treatment: American Society of Clinical Oncology clinical practice guideline update. J Clin Oncol. 2013;31(7):961-965.
    396. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Special report: Multiple molecular testing of cancers to identify targeted therapies. TEC Assessments in Press. Chicago, IL: BCBSA; February 2013.
    397. Meleth S, Whitehead N, Swinson T, Lux L. Technology assessment on genetic testing or molecular pathology testing of cancers with unknown primary site to determine origin. Technology Assessment Report. Final. Prepared by RTI International-University of North Carolina at Chapel Hill Evidence-based Practice Center for the Agency for Healthcare Research and Quality (AHRQ) under contract no. HHSA290200710057I #8. Project ID: CANU5011. Rockville, MD: AHRQ; February 20, 2013. 
    398. Deverka P, Messner D, Dutta T. Evaluation of clinical validity and clinical utility of actionable molecular diagnostic tests in adult oncology. Effectiveness Guidance Document. Baltimore, MD: Center for Medical Technology Policy (CMTP); 2013.
    399. Andreopoulou E, Yee H, Warycha MA, et al. Mucinous cancer of the appendix: challenges in diagnosis and treatment. J Chemother. 2007;19(4):451-454.
    400. Carmignani CP, Sugarbaker PH. Synchronous extraperitoneal and intraperitoneal dissemination of appendix cancer. Eur J Surg Oncol. 2004a;30(8):864-868.
    401. Carmignani CP, Hampton R, Sugarbaker CE, et al. Utility of CEA and CA 19-9 tumor markers in diagnosis and prognostic assessment of mucinous epithelial cancers of the appendix. J Surg Oncol. 2004b;87(4):162-166.
    402. Rasamny JJ, Allak A, Krook KA, et al. Cyclin D1 and FADD as biomarkers in head and neck squamous cell carcinoma. Otolaryngol Head Neck Surg. 2012;146(6):923-31.
    403. O'Sullivan P, Sharples K, Dalphin M, et al. A multigene urine test for the detection and stratification of bladder cancer in patients presenting with hematuria. J Urol. 2012;188(3):741-747.
    404. NIHR HSC. Caris Target Now™ molecular profiling service for solid malignant tumours. Horizon Scanning Review. Birmingham, UK: NIHR Horizon Scanning Centre (NIHR HSC); 2013
    405. National Institute for Health and Care Excellence. DG10 gene expression profiling and expanded immunohistochemistry tests for guiding adjuvant chemotherapy decisions in early breast cancer management: MammaPrint, Oncotype DX, IHC4 and Mammostrat: Guidance. NICE: London, UK. September 2013. Available at: http://guidance.nice.org.uk/DG10/Guidance/pdf/English. Accessed January 7, 2014.
    406. Lotan Y, Choueiri TK. Clinical presentation, diagnosis, and staging of bladder cancer. Last reviewed December 2013. UpToDate Inc., Waltham, MA.
    407. National Comprehensive Cancer Network. Clinical practice guideline: Bladder cancer. Version 1.2014. NCCN: Fort Washington, PA.
    408. Delahaye LJM, Wehkamp D, Floore AN, et al. Performance characteristics of the MammaPrint breast cancer diagnostic gene signature. Personalized Medicine. 2013;10(8):801.
    409. Sapino A, Roepman P, Linn SC, et al.  MammaPrint molecular diagnostics on formalin-fixed, paraffin-embedded tissue. J Mol Diagn. 2014;16(2):190-197.
    410. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Actions Taken by the BlueCross BlueShield Association Medical Advisory Panel (MAP). Chicago, IL: BCBSA; February 19, 2014.
    411. Cheng S, Qu K, Abdool A, et al. A molecular diagnostic panel for thyroid cancer disease management. J Clin Oncol 30, 2012 (suppl; abstr 5510). Available at: http://meetinglibrary.asco.org/content/94089-114. Accessed April 1, 2014.
    412. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Gene expression analysis for prostate cancer management. TEC Assessment Program. Chicago, IL: BCBSA; April 2014;28(11).
    413. Gerami P, Cook RW, Wilkinson J, et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res. 2015;21(1):175-183.
    414. Canadian Agency for Drugs and Technologies in Health (CADTH). The “CellSearch” System for Detecting Circulating Tumour Cells in Advanced Ovarian Cancer: Clinical Benefit and Cost-Effectiveness. Rapid Response Report. Ottawa, ON: CADTH; November 16, 2012.
    415. National Horizon Scanning Centre (NHSC). Update: OVA1™ test for the assessment of suspected ovarian cancer. Horizon Scanning Report. Birmingham, UK: National Horizon Scanning Centre, University of Birmingham; 2012.
    416. Ellery B, Hiller J. CellSearch®: Detection of circulating tumour cells for the prognosis and improved management of cancer patients. Horizon Scanning Technology Prioritising Summary. Canberra, ACT: Department of Health and Ageing; November 2010.
    417. Mundy L, Merlin T, Hiller J. Diagnostic tests for ovarian cancer. Horizon Scanning Technology Prioritising Summary. Canberra, ACT: Department of Health and Ageing; 2010.
    418. Davis R, Jones JS, Barocas DA, et al. Diagnosis, evaluation and follow-up of asymptomatic microhematuria (AMH) in adults: AUA guideline. Linthicum, MD: American Urological Association Education and Research, Inc. (AUA); May 2012.
    419. Tanaka  M, Fernandez-del Castillo C, Adsay V, et al; International Association of Pancreatology. International consensus guidelines 2012 for the management of IPMN and MCN of the pancreas. Pancreatology. 2012;12(3):183-197.
    420. Ministerio de Salud y Protección Social, Departamento Administrativo de Ciencia Tecnología e Innovación en Salud (Colciencias), Instituto Nacional de Cancerología Empresa Social del Estado-Fedesalud; Instituto de Evaluación Technológica en Salud (IETS), Guía de Práctica Clínica para la detección temprana, tratamiento integral, seguimiento y rehabilitación del cáncer de mama. Guía No. GPC-2013-19. Bogotá, Colombia: Instituto Nacional de Cancerología ESE; 2013.
    421. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: can testing of tumor tissue for mutations in EGFR pathway downstream effector genes in patients with metastatic colorectal cancer improve health outcomes by guiding decisions regarding anti-EGFR therapy? Genet Med. 2013;15(7):517-527.
    422. Maugeri-Sacca M, Coppola V, De Maria R, Bonci D. Functional role of microRNAs in prostate cancer and therapeutic opportunities. Crit Rev Oncog. 2013;18(4):303-315.
    423. Yu JJ, Xia SJ. Novel role of microRNAs in prostate cancer. Chin Med J (Engl). 2013;126(15):2960-2964.
    424. Tiwana SK, Smith A, Leggett L, et al. Use of Oncotype DX for guiding adjuvant chemotherapy decisions in early stage invasive breast cancer patients in Alberta. A Health Technology Assessment. Calgary, AB: Health Technology Assessment Unit, Institute for Public Health, University of Calgary; August 7, 2013.
    425. Ward S, Scope A, Rafia R, et al. Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in breast cancer management: A systematic review and cost-effectiveness analysis. Health Technol Assess. 2013;17(44):1-302.
    426. Chiam K, Ricciardelli C, Bianco-Miotto T. Epigenetic biomarkers in prostate cancer: Current and future uses. Cancer Lett. 2014;342(2):248-256.
    427. Metcalf AM, Spurdle AB. Endometrial tumour BRAF mutations and MLH1 promoter methylation as predictors of germline mismatch repair gene mutation status: A literature review. Fam Cancer. 2014;13(1):1-12.
    428. Den RB, Yousefi K, Trabulsi EJ, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. 2015;33(8):944-951.
    429. Cooperberg MR, Davicioni E, Crisan A, et al. Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort. Eur Urol. 2015;67(2):326-333.
    430. Klein EA, Yousefi K, Haddad Z, . A genomic classifier improves prediction of metastatic disease within 5 years after surgery in node-negative high-risk prostate cancer patients managed by radical prostatectomy without adjuvant therapy. Eur Urol. 2015;67(4):778-786.
    431. Den RB, Feng FY, Showalter TN, et al. Genomic prostate cancer classifier predicts biochemical failure and metastases in patients after postoperative radiation therapy. Int J Radiat Oncol Biol Phys. 2014;89(5):1038-1046.
    432. Ross AE, Feng FY, Ghadessi M, et al. A genomic classifier predicting metastatic disease progression in men with biochemical recurrence after prostatectomy. Prostate Cancer Prostatic Dis. 2014;17(1):64-69.
    433. Karnes RJ, Bergstralh EJ, Davicioni E, et al. Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population. J Urol. 2013;190(6):2047-2053.
    434. Lobo JM, Dicker AP, Buerki C, et al. Evaluating the clinical impact of a genomic classifier in prostate cancer using individualized decision analysis. PLoS One. 2015;10(3):e0116866.
    435. Badani K, Thompson DJ, Buerki C, et al. Impact of a genomic classifier of metastatic risk on postoperative treatment recommendations for prostate cancer patients: A report from the DECIDE study group. Oncotarget. 2013;4(4):600-609.
    436. Michalopoulos SN, Kella N, Payne R, et al.; PRO-ACT Study Group. Influence of a genomic classifier on post-operative treatment decisions in high-risk prostate cancer patients: Results from the PRO-ACT study. Curr Med Res Opin. 2014;30(8):1547-1556.
    437. Badani KK, Thompson DJ, Brown G, et al. Effect of a genomic classifier test on clinical practice decisions for patients with high-risk prostate cancer after surgery. BJU Int. 2015;115(3):419-429.
    438. Nguyen HG, Welty CJ, Cooperberg MR. Diagnostic associations of gene expression signatures in prostate cancer tissue. Curr Opin Urol. 2015;25(1):65-70.
    439. Boström PJ, Bjartell AS, Catto JW, et al. Genomic predictors of outcome in prostate cancer. Eur Urol. 2015 Apr 23. Epub ahead of print]
    440. Chung CH, Zhang Q, Kong CS, et al. p16 protein expression and human papillomavirus status as prognostic biomarkers of nonoropharyngeal head and neck squamous cell carcinoma. J Clin Oncol. 2014;32(35):3930-3938.
    441. Erickson BK, Kinde I, Dobbin ZC, et al. Detection of somatic TP53 mutations in tampons of patients with high-grade serous ovarian cancer. Obstet Gynecol. 2014;124(5):881-885.
    442. Mutch DG. Can molecular diagnostics usher in a new era for screening, diagnosis, and treatment of ovarian cancer? Obstet Gynecol. 2014;124(5):870-872.
    443. National Comprehensive Cancer Network. Clinical practice guideline: Ovarian cancers. Version 3.2014. NCCN: Fort Washington, PA.
    444. Ruzzenente A, Iacono C, Conci S, et al. A novel serum marker for biliary tract cancer: Diagnostic and prognostic values of quantitative evaluation of serum mucin 5AC (MUC5AC). Surgery. 2014;155(4):633-639.
    445. Chen L-M, Berek JS. Endometrial carcinoma: Clinical features and diagnosis. UpToDate Inc., Waltham, MA. Last reviewed January 2015.
    446. Plaxe SC, Mundt AJ. Overview of endometrial carcinoma. UpToDate Inc., Waltham, MA. Last reviewed January 2015.
    447. National Comprehensive Cancer Network. Clinical practice guideline: Colon cancer. Version 2.2015. NCCN: Fort Washington, PA.
    448. National Comprehensive Cancer Network. Clinical practice guideline: Uterine neoplasms. Version 2.2015. NCCN: Fort Washington, PA.
    449. National Comprehensive Cancer Network. Clinical practice guideline: Prostate cancer. Version 1.2015. NCCN: Fort Washington, PA.
    450. National Comprehensive Cancer Network. Clinical practice guideline: Hepatobiliary cancers. Version 2.2015. NCCN: Fort Washington, PA.
    451. Zhang J, Zhu Z, Liu Y, et al. Diagnostic value of multiple tumor markers for patients with esophageal carcinoma. PLoS One. 2015;10(2):e0116951.
    452. BlueCross BlueShield Association (BCBSA). Gene expression analysis for prostate cancer management. TEC Assessment. Chicago, IL: BCBSA; January 2015; 29(9).
    453. BlueCross BlueShield Association (BCBSA). Gene expression profiling in women with lymph node-negative breast cancer to select adjuvant chemotherapy. TEC Assessment. Chicago, IL: BCBSA; October 2014;29(3).
    454. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Mutianalyte testing for evaluation of adnexal masses. TEC Assessment Program. Chicago, IL: BCBSA; April 2013;27(8).
    455. National Institute for Health and Care Excellence (NICE). Gene expression profiling and expanded immunohistochemistry tests for guiding adjuvant chemotherapy decisions in early breast cancer management: MammaPrint, Oncotype DX, IHC4 and Mammostrat. London, UK: National Institute for Health and Care Excellence (NICE); 2013 Sep. 57 p. (Diagnostics guidance; no. 10).
    456. Chang M, Ismaila N, Kamel-Reid S, et al. Comparison of Oncotype DX with Multi-gene Profiling Assays, (e.g., MammaPrint, PAM50) and Other Tests (e.g., Adjuvant! Online, Ki-67 and IHC4) in Early-stage Breast Cancer. Recommendation Report MOAC-2. Edmonton, ON: Program in Evidence-Based Care, Cancer Care Ontario; November 20, 2013.
    457. Martínez-Férez IM, Márquez-Peláez S, Isabel-Gómez R, Beltrán-Calvo C.. Pruebas genómicas para el pronóstico de pacientes con cáncer de mama. MammaPrint® y Oncotype DX®.. [Prognostic genomic tests in early breast cancer: MammaPrint® and Oncotype DX®] Seville: Andalusian Agency for Health Technology Assessment (AETSA). AETSA 2013/3. 2014.
    458. Meleth S, Reeder-Hayes K, Ashok M, et al. Technology assessment of molecular pathology testing for the estimation of prognosis for common cancers. Technology Assessment Report. Prepared for the RTI International-University of North Carolina at Chapel Hill Evidence Based Practice Center (RTI-UNC EPC) for the Agency for Healthcare Research and Quality (AHRQ), Contract No. HHSA2902007100561.Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); 2014.
    459. Van den Bulcke, M, San Miguel L, Salgado R,, et al. Next generation sequencing panels for target therapy in oncology and haematology-oncology. KCE Report 240. Brussels, Belgium: Belgian Healthcare Knowledge Centre (KCE); March 19, 2015.
    460. Nikiforov YE, Ohori NP, Hodak SP, et al. Impact of mutational testing on the diagnosis and management of patients with cytologically indeterminate thyroid nodules: A prospective analysis of 1056 FNA samples. J Clin Endocrinol Metab. 2011;96(11):3390-3397.
    461. Ohori NP, Nikiforova MN, Schoedel KE, et al. Contribution of molecular testing to thyroid fine-needle aspiration cytology of "follicular lesion of undetermined significance/atypia of undetermined significance". Cancer Cytopathol. 2010;118(1):17-23.
    462. Nikiforov YE, Steward DL, Robinson-Smith TM, et al. Molecular testing for mutations in improving the fine-needle aspiration diagnosis of thyroid nodules. J Clin Endocrinol Metab. 2009;94(6):2092-2098.
    463. Scheiman JM, Hwang JH, Moayyedi P. American Gastroenterological Association technical review on the diagnosis and management of asymptomatic neoplastic pancreatic cysts. Gastroenterology. 2015;148(4):824-848.
    464. Vege SS, Ziring B, Jain R, Moayyedi P; Clinical Guidelines Committee. American Gastroenterological Association Institute guideline on the diagnosis and
      management of asymptomatic neoplastic pancreatic cysts. Gastroenterology. 2015;148(4):819-822.
    465. Gregorc V, Novello S, Lazzari C, et al. Predictive value of a proteomic signature in patients with non-small-cell lung cancer treated with second-line erlotinib or chemotherapy (PROSE): A biomarker-stratified, randomised phase 3 trial. Lancet Oncol. 2014;15(7):713-721.
    466. Butts CA. VeriStrat validated in patients with non-small-cell lung cancer. Lancet Oncol. 2014;15(7):671-672.
    467. Valent P, Horny HP, Bennett JM, et al. Definitions and standards in the diagnosis and treatment of the myelodysplastic syndromes: Consensus statements and report from a working conference. Leuk Res. 2007 Jun;31(6):727-736.
    468. San Miguel L, Vlayen J, De Laet C. Gene expression profiling and immunohistochemistry tests for personalized management of adjuvant chemotherapy decisions in early breast cancer – a Rapid Assessment. Health Technology Assessment (HTA). KCE Reports 237.  D/2015/10.273/13. Brussels, Belgium: Belgian Health Care Knowledge Centre (KCE); 2015.
    469. Kisser A, Zechmeister-Koss I. A systematic review of p16/Ki-67 immuno-testing for triage of low grade cervical cytology. BJOG 2014.
    470. Ellery B, Parsons J, Merlin T. Molecular testing for prostate cancer prognosis. Technology Brief. Herston, QLD: Department of Health, Queensland; November 2014.
    471. Shore N, Concepcion R, Saltzstein D, et al. Clinical utility of a biopsy-based cell cycle gene expression assay in localized prostate cancer. Curr Med Res Opin. 2014;30(4):547-553.
    472. Sestak I, Cuzick J, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: A combined analysis of patients from the Austrian Breast and Colorectal Cancer Study Group 8 and Arimidex, Tamoxifen Alone or in Combination Randomized Trials using the PAM50 Risk of Recurrence Score. J Clin Oncol. 2014, epub ahead of print.
    473. Gnant M, Filipits M, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: Using the PAM50 Risk of Recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol. 2014;25(2):339-345.
    474. Dowsett M, Sestak I, et al. Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol. 2014;31(22): 2783-2790.
    475. National Institute for Health and Care Excellence (NICE). The Prosigna gene expression profiling assay for assessing long-term risk of breast cancer recurrence. Medtech Innovation Briefing. London, UK: NICE; March 25, 2015. 
    476. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: Does PCA3 testing for the diagnosis and management of prostate cancer improve patient health outcomes? Genet Med. 2014;16(4):338-346.
    477. Mundy L. Gene expression profiling of breast cancer. Technology Brief. Health Policy Advisory Committee on Technology (HealthPACT) Emerging Health Techology. Brisbane, QLD; Queensland Health; May 2012. 
    478. Sgroi DC, Sestak I, Cuzick J, et al. Prediction of late distant recurrence in patients with oestrogen-receptor-positive breast cancer: A prospective comparison of the breast-cancer index (BCI) assay, 21-gene recurrence score, and IHC4 in the TransATAC study population. Lancet Oncol. 2013;14(11):1067-1076.
    479. Zhang Y, Schnabel CA, Schroeder BE, et al. Breast cancer index identifies early-stage estrogen receptor-positive breast cancer patients at risk for early- and late-distant recurrence. Clin Cancer Res. 2013;19(15):4196-4205.
    480. Sgroi DC, Carney E, Zarrella E, et al. Prediction of late disease recurrence and extended adjuvant letrozole benefit by the HOXB13/IL17BR biomarker. J Natl Cancer Inst. 2013;105(14):1036-1042.
    481. Gustavsen G, Schroeder B, Kennedy P, et al. Health economic analysis of Breast Cancer Index in patients with ER+, LN-breast cancer. Am J Manag Care. 2014;20(8):e302-e310.
    482. Habel LA, Sakoda LC, Achacoso N, et al. HOXB13:IL17BR and molecular grade index and risk of breast cancer death among patients with lymph node-negative invasive disease. Breast Cancer Res. 201315(2):R24.
    483. Mathieu MC, Mazouni C, Kesty NC, et al. Breast Cancer Index predicts pathological complete response and eligibility for breast conserving surgery in breast cancer patients treated with neoadjuvant chemotherapy. Ann Oncol. 2012;23(8):2046-2052.
    484. Jankowitz RC, Cooper K, Erlander MG, et al. Prognostic utility of the breast cancer index and comparison to Adjuvant! Online in a clinical case series of early breast cancer. Breast Cancer Res. 2011;13(5):R98.
    485. Jerevall PL, Ma XJ, Li H, Salunga R, et al. Prognostic utility of HOXB13:IL17BR and molecular grade index in early-stage breast cancer patients from the Stockholm trial. Br J Cancer. 2011;104(11):1762-1769.
    486. Ma XJ, Wang Z, Ryan PD, et al. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell. 2004;5(6):607-616.
    487. Ma XJ, Salunga R, Dahiya S, et al. A five-gene molecular grade index and HOXB13:IL17BR are complementary prognostic factors in early stage breast cancer. Clin Cancer Res. 2008;14(9):2601-2608.
    488. Azim HA Jr, Michiels S, Zagouri F, et al. Utility of prognostic genomic tests in breast cancer practice: The IMPAKT 2012 Working Group Consensus Statement. Ann Oncol. 2013;24(3):647-654.
    489. Smith IE, Yeo B, Schiavon, G. The optimal duration and selection of adjuvant endocrine therapy for breast cancer: How long is enough? ASCO Educational Book 2014. ASCO University. Alexandria, VA: American Society for Clinical Oncology (ASCO); 2014.
    490. National Comprehensive Cancer Network (NCCN). Breast cancer. NCCN Clinical Practice Guidelines in Oncology, version 2.2015. Fort Washington, PA: NCCN; 2015.
    491. Coates AS, Winer EP, Goldhirsch A, et al.; Panel Members. Tailoring therapies-improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol. 2015 May 4. [Epub ahead of print].
    492. Burstein HJ, Temin S, Anderson H, et al. Adjuvant endocrine therapy for women with hormone receptor-positive breast cancer: American Society of Clinical Oncology clinical practice guideline focused update. J Clin Oncol. 2014;32(21):2255-2269
    493. Centers for Medicare & Medicare Services (CMS). Local Coverage Determination (LCD): MolDX: Breast Cancer Index℠ Genetic Assay (L35294). Palmetto GBA – MAC Part B. Medicare Coverage Database. Baltimore, MD: CMS; effective November 3, 2014.
    494. Sestak I, Dowsett M, Sgroi D. Comparison of fibe different scores for the prediction of late recurrence for oestrogen receptor-positive breast cancer. Ann Oncol. 2013; 24 (suppl 3): iii29.
    495. Sestak I, Cuzick J. Markers for the identification of late breast cancer recurrence. Breast Cancer Res. 2015;17:10.
    496. Bianchini G, Gianni L. An unmet need: Tailoring extended adjuvant endocrine therapy. Br J Cancer. 2013;109(12):2951-2953.
    497. Ignatiadis M. Multigene assays for late recurrence of breast cancer. Lancet Oncol. 2013;14(11):1029-1030.
    498. Mehta A, Carpenter JT. How do I recommend extended adjuvant hormonal therapy? Curr Treat Options Oncol. 2014;15(1):55-62.
    499. Ignatiadis M, Sotiriou C. Luminal breast cancer: From biology to treatment. Nat Rev Clin Oncol. 2013;10(9):494-506.
    500. Foukakis T, Bergh J. Prognostic and predictive factors in early, non-metastatic breast cancer. UpToDate [online serial]. Waltham, MA: UpToDate; June 2015.
    501. Senkus E, Kyriakides S, Penault-Llorca F, et al.; ESMO Guidelines Working Group. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2013;24 Suppl 6:vi7-23.


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