Tumor Chemoresistance Assays

Number: 0758

Policy

Aetna considers tumor chemoresistance assays experimental and investigational because there is insufficient evidence that these assays influence management decisions such that clinical outcomes are improved.

See also CPB 0245 Tumor Chemosensitivity Assays.

Background

A chemoresistance assay is a laboratory test used to identify chemotherapeutic agents that may be ineffective against tumor growth.  A chemosensitivity assay is a laboratory test performed to evaluate tumor growth and its response to a known chemotherapeutic drug or panel of drugs.  Both techniques have been proposed as an aid in the selection of cancer treatments based on responsiveness of individual tumors.

Multiple sensitivity assays, also referred to as in-vitro assays, are available.  These laboratory tests are performed in a test tube and measure the activity of a drug on a sample of tissue.  Although the assays may differ in their technologies and processes in measuring sensitivity, they share 4 basic steps:
  1. isolation of tumor cells,
  2. incubation of cells with anti-cancer drugs,
  3. assessment of cell growth or survival and
  4.  interpretation of results. 

Examples of chemoresistance assays include, but may not be limited to: Extreme drug resistance (EDR) assay, Duke University chemotherapy assessment test.

Molecular profiling (eg, BioSpeciFx, Target Now, MI Profile) is sometimes used in combination with these technologies.  Molecular profiling is a laboratory method of testing a panel of tumor markers, which may include genetic as well as biochemical markers, to establish a molecular profile of a tumor in order to recommend treatment options.  The combination of molecular profiling and in-vitro drug response marker testing is sometimes referred to as comprehensive tumor profiling.

Chemoresistance assay testing is an in-vitro diagnostic technique intended to identify drugs to which a patient's tumor is resistant.  Chemoresistant assays are based on the same principles as the chemosensitivity assay.  Both assays are performed to evaluate whether tumor growth is inhibited by a known chemotherapy drug or, more commonly, a panel of drugs.  However, chemoresistance assays focus on negative predictive accuracy (the ability of the assay to identify ineffective agents) rather than positive predictive accuracy (the ability of the assay to identify agents capable of inducing a clinical response).  Weisenthal and Kern (1991) reported that the negative predictive value (NPV) for in-vitro drug response assays was generally 90 % to 99 % while the positive predictive value (PPV) was 50 % to 70 %.  Thus, in-vitro drug testing is purportedly more reliable for identifying drugs that are more likely to be ineffective (resistant) as opposed to identifying drugs that would be effective (sensitive).  By eliminating ineffective drugs from treatment regimens, it is hoped that chemoresistance assay testing will spare the patient unnecessary toxicity, correlate a patient's response to chemotherapy and/or patient survival and tailor treatment to individual patients. 

Extreme drug resistance (EDR) assays were designed to provide a very high NPV (greater than 99 %), with the intent to deselect ineffective chemotherapies.  After successful culture, tumor cells obtained from fresh biopsy specimens are labeled with tritiated thymidine.  The level of uptake is tracked after exposure to chemotherapy concentrations that approximate the peak level achieved clinically.  Extreme resistance is identified when thymidine incorporation is inhibited in the presence of the drug by less than 1 standard deviation of the median cell inhibition measured for several hundred refence tumor samples.  In this test, a positive resistance to a specific drug should prevent the selection of “ineffective” drugs for the human tumor cells in the individual patient. 

A slightly different form of tumor cell resistance assay testing consists of exposing tumor cells to anti-neoplastic agents and performing at least 1 or more of the following 3 cell death endpoint tests to determine tumor cell survival:
  1. differential cell staining and microscopic counting;
  2. microplating and use of coloring reagent MTT (dimethyl thiazol-diphenyltetrzolium thiazolyl blue); and
  3. measuring ATP content.

Mehta et al (2001) reported the results of EDR testing on breast tumor tissue (n = 103).  Extreme drug resistance assay scores of 2 for low, 1 for intermediate, or 0 for EDR were determined for each agent tested.  In-vitro EDR scores for 4-hydroxycyclophosphamide (4HC) and doxorubicin were summed for patients treated with AC, or for 4HC and 5-FU for patients treated with CMF.  Treatment selection was blinded to assay results.  The authors reported that median time to progression was significantly shorter for patients with extreme or intermediate in-vitro resistance (n = 55, 48 months), compared to patients with low in-vitro resistance, (n = 41, 100 months, p = 0.022).  Patients demonstrating extreme to intermediate drug resistance showed poorer survival than the low resistance group (49.5 months versus not reached, median follow-up 48 months, p = 0.011).  Compared to EDR scores of 4, summed EDR scores of 0 to 1 and summed EDR scores of 2 to 3 were associated with a relative risk of death of 3.09 (95 % confidence interval [CI]: 1.05 to 9.06, Cox proportional hazards model, p = 0.040) and 2.35 (95 % CI: 1.07 to 5.15, Cox proportional hazards model, p = 0.033), respectively.  The authors concluded that EDR testing identified patients with individual patterns of drug resistance prior to therapy and that summed EDR scores were significantly associated with time to tumor progression and overall survival. 

Haroun et al (2002) described a drug resistance profile (extreme, intermediate, or low) based on statistical comparison to a historical database of brain tumor specimens tested against the same panel of chemotherapeutic agents.  The authors stated that through continued analysis and compilation of data from multiple institutions, chemoresistance profiles could assist future investigators with the development of rationale clinical trials and treatment regimens for patients with brain tumors.

In a retrospective study of EDR testing on newly diagnosed advanced ovarian cancer patients, Holloway et al (2002) stated that patients with ovarian tumors demonstrating in- vitro drug resistance to platinum were at significantly increased risk for progression and death when treated with standard platinum-based regimens.  Median progression free survival was 6 months for tumors exhibiting extreme resistance to platinum (n = 17) compared to 24 months for tumors exhibiting low resistance to platinum (n = 62).

In a retrospective study, Loizzi et al (2003) reported that recurrent ovarian cancer patients (n = 50) with EDR directed therapy had an overall response rate of 65 % compared with 35 % in patients who were treated empirically.  The overall and progression-free median survival were 38 and 15 months in the EDR group compared with 21 and 7 months in the control group, respectively. 

In a prospective phase II blinded study of 48 patients with recurrent malignant glioma, Parker et al (2004) evaluated the predictive reliability of an EDR assay to identify clinical resistance to irinotecan (CPT-11) using tumor biopsies obtained from patients immediately prior to their first dose of CPT-11 therapy.  In-vitro tumor response to SN38 (bioactive species of CPT-11 used in the EDR assay) determined prior to treatment was correlated with objective response, time to tumor progression (TTP) and survival following the administration of CPT-11.  SN38 activity was tested in 19 of 29 tumors, with 15 of 18 assay results evaluable for correlation with clinical outcomes.  In-vitro drug resistance was classified as either extreme, intermediate (IDR), or low (LDR).  Median TTP for IDR/LDR cases was 3 months versus 6 weeks for EDR cases.  A 13-week median survival for EDR cases was significantly shorter compared to 38 weeks for IDR/LDR cases (p = 0.029).  At  follow-up, 2 of 3 survivors were patients who had tumors IDR/LDR to SN38.

Cloven et al (2004) reported the results of EDR testing to epithelial ovarian cancer (n = 5,195) and found EDR to cisplatin (10 %), carboplatin (16 %), cyclophosphamide (16 %), doxorubicin (40 %), gemcitabine (21 %), paclitaxel (22 %), and topotecan (13 %).  The investigators also reported differences of EDR among histologic subtypes of epithelial ovarian cancer.

Fruehauf et al (2006) described in-vitro drug response profiles on biopsy specimens from patients with malignant gliomas (n = 478).  Samples were tested for drug resistance to 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU), cisplatin, dacarbazine, paclitaxel, vincristine, and irinotecan.  Biomarkers associated with drug resistance were detected by imunohistochemistry, including multi-drug resistance gene-1, glutathione S-transferase pi (GSTP1), O(6)-methylguanine-DNA methyltransferase (MGMT), and mutant p53.  In-vitro drug resistance in malignant gliomas was independent of prior therapy.  High-grade glioblastomas showed a lower level of EDR than low-grade astrocytomas to cisplatin (11 % versus 27 %), temozolomide (14 % versus 27 %), irinotecan (33 % versus 53 %), and BCNU (29 % versus 38 %).  A substantial percentage of brain tumors overexpressed biomarkers associated with drug resistance, including MGMT (67 %), GSTP1 (49 %), and mutant p53 (41 %).  MGMT and GSTP1 over-expression was independently associated with in-vitro resistance to BCNU, whereas coexpression of these 2 markers was associated with the greatest degree of BCNU resistance.

d'Amato et al (2006) reported EDR or IDR to non-small cell lung cancer specimens (n = 3,042) to carboplatin (68 %), cisplatin (63 %), doxorubicin (75 %), etoposide (63 %), gemcitabine (72 %), navelbine (42 %), paclitaxel (40 %), taxotere (52 %), and topotecan (31 %).  In a follow-up study, d'Amato et al (2007) reported resistance to multiple-agent chemotherapy to non-small cell lung cancer specimens (n = 4,571) to carboplatin-paclitaxel (30 %), cisplatin-navelbline (24 %), cisplatin-gemcitabine (42 %), and cisplatin-docetaxel (27 %).

In a retrospective analysis comparing the differences of EDR testing between invasive micropapillary/low-grade serous ovarian carcinoma (n = 13) and high-grade serous ovarian carcinoma (n = 31), patients with recurrent invasive micropapillary/low-grade serous ovarian carcinoma were more likely to manifest EDR to standard chemotherapy agents.  Compared to high-grade serous ovarian carcinoma, invasive micropapillary/low-grade serous ovarian carcinoma were more likely to manifest EDR to the drugs paclitaxel (69 % versus 14 %, p < 0.001), carboplatin (50 % versus 17 %, p = 0.05), cyclophosphamide (40 % versus 23 %, p = 0.41), gemcitabine (36 % versus 19 %, p =  0.40), and cisplatin (33 % versus 28 %, p = 0.72) and less likely to be resistant to etoposide (0 % versus 44 %, p = 0.007), doxorubicin (8 % versus 45 %, p = 0.03), and topotecan (8 % versus 21 %, p = 0.65) (Santillan et al, 2007). 

Based on a review of the current literature, the American Society of Clinical Oncology (ASCO) Working Group found insufficient evidence to support the use of any chemotherapy sensitivity and resistance assays (CSRAs) in oncological practice.  Specifically, the ASCO Work Group found limitations in the literature that included small sample sizes and a lack of prospective studies.  For technically challenging CSRAs that require colony formation (e.g., the human tumor cloning assay), and for surgical procedures including the sub-renal capsule assay, the success rate of the CSRAs is modest.  Furthermore, preparation of the assay may involve complex laboratory work, limiting a broad application of the technology to routine clinical practice.  Because the in-vitro analytic strategy has potential importance, participation in clinical trials evaluating these technologies remains a priority (Schrag et al, 2004).

Chemoresistance assays, using measurements of extreme drug resistance, have been shown to have a high negative predictive value for identifying those drugs which are ineffective.  Although advocates of chemoresistance assays may argue that the relevant outcome is avoidance of the toxicity and morbidity of an ineffective drug, it is impossible to separate this limited outcome from the final outcome of improved survival based on the selection of potentially more effective chemotherapy.  For example, when one drug is eliminated on the basis of chemoresistance assays, it is implied that the remaining drugs, which did not show chemoresistance, are potentially more effective.  In this way, by a process of elimination, chemoresistance results dictate the positive selection of potentially effective drugs.  However, even the avoidance of potentially unnecessary toxicity is not a straightforward outcome.  If one drug is eliminated from a regimen on the basis of chemoresistance, in most cases another drug with its associated toxicity will be substituted.

Proponents of the EDR assays believe the ability to predict clinical failure with 99 % accuracy is the compelling feature of the EDR assay (Mehta, 2001; Holloway, 2002; Loizzi, 2003; Parker, 2004) while others (Schrag, 2004) find no convincing evidence that chemoresistant assays should be integrated into routine oncology care until further randomized controlled testing is done. 

Guidelines from the National Comprehensive Cancer Network (2011) stated that chemosensitivity and chemoresistance assays are used in some centers for decisions related to future chemotherapy in situations where there are multiple equivalent chemotherapy options available; "the current level of evidence is not sufficient to supplant current standard of care chemotherapy."

Burstein et al (2011) updated the ASCO Technology Assessment guidelines on CSRAs published in 2004.  An Update Working Group reviewed data published between December 1, 2003, and May 31, 2010.  Medline and the Cochrane Library were searched yielding 11,313 new articles.  The limits for "human and English" were used, and then standard ASCO search strings for randomized controlled trials (RCTs), meta-analyses, guidelines, and reviews were added, yielding 1,298 articles for abstract review.  Of these, only 21 articles met pre-defined inclusion criteria and underwent full text review, and 5 reports of RCTs were included for data extraction.  Review of the literature does not identify any CSRAs for which the evidence base is sufficient to support use in oncology practice.  The authors concluded that the use of CSRAs to select chemotherapeutic agents for individual patients is not recommended outside of the clinical trial setting.  They noted that oncologists should make chemotherapy treatment recommendations based on published reports of clinical trials and a patient's health status and treatment preferences.  Because the in-vitro analytic strategy has potential importance, participation in clinical trials evaluating these technologies remains a priority.

Wang et al (2012) examined if expression of circulating microRNAs (miRNAs) can predict clinical outcome in breast cancer patients treated with adjuvant chemotherapy.  Circulating miRNAs in blood serum prior to treatment were determined by quantitative real-time polymerase chain reaction (PCR) in 56 breast cancer patients with invasive ductal carcinoma and pre-operative neoadjuvant chemotherapy.  Proliferating cell nuclear antigen (PCNA) immunostaining and TUNEL were performed in surgical samples to determine the effects of chemotherapy on cancer cell proliferation and apoptosis, respectively.  Among the miRNAs tested, only miR-125b was significantly associated with therapeutic response, exhibiting higher expression level in non-responsive patients (n  =  26, 46 %; p  =  0.008).  In addition, breast cancers with high miR-125b expression had higher percentage of proliferating cells and lower percentage of apoptotic cells in the corresponding surgical specimens obtained after neoadjuvant chemotherapy.  Increased resistance to anti-cancer drug was observed in-vitro in breast cancer cells with ectopic miR-125b expression; conversely, reducing miR-125b level sensitized breast cancer cells to chemotherapy.  Moreover, these researchers demonstrated that the E2F3 was a direct target of miR-125b in breast cancer cells.  The authors concluded that these findings suggested that circulating miR-125b expression is associated with chemotherapeutic resistance of breast cancer.  This finding has important implications in the development of targeted therapeutics for overcoming chemotherapeutic resistance in novel anti-cancer strategies.

Lee and colleagues (2012) examined
  1. if immunohistochemistry of multi-drug-resistant (MDR) proteins (MDR1, MRP1, MRP2 and BCRP) in colorectal adenocarcinomas can substitute for histoculture drug resistance assays (HDRA) and
  2. if chemosensitivity as indicated by HDRA and MDR protein expression is related to prognostic parameters in colorectal cancers.  

Chemosensitivity of cancer tissues to 5-FU, irinotecan and oxaliplatin was assessed by HDRA.  Immunohistochemical staining of MDR proteins was quantified by image analysis in 76 colorectal adenocarcinoma patients.  Inhibition rates (IRs) of the anti-cancer drugs by HDRA were not related to MDR protein expression.  However, the IR of 5-FU was significantly decreased with lymph node metastasis (p = 0.03) and advanced clinical stages (p = 0.047).  The IRs of irinotecan and oxaliplatin were not associated with clinicopathological parameters.  Immunohistochemically, positive scores for MRP2 and BCRP protein were paradoxically related to lower clinical stages (p = 0.043) and male gender (p = 0.019), respectively.  The authors concluded that immunohistochemical staining of MDR proteins can not predict tumor responses to anti-cancer drugs in colorectal cancers.  Chemoresistance to 5-FU as indicated by HDRA was highly associated with aggressive prognostic factors.

Ebert and associates (2012) noted that chemotherapy for advanced colorectal cancer (CRC) leads to improved survival; however, predictors of response to systemic treatment are not available.  Genomic and epigenetic alterations of the gene encoding transcription factor AP-2 epsilon (TFAP2E) are common in human cancers.  The gene encoding dickkopf homolog 4 protein (DKK4) is a potential down-stream target of TFAP2E and has been implicated in chemotherapy resistance.  These investigators evaluated the role of TFAP2E and DKK4 as predictors of the response of CRC to chemotherapy.  They analyzed the expression, methylation, and function of TFAP2E in CRC cell lines in-vitro and in patients with CRC.  They examined an initial cohort of 74 patients, followed by 4 cohorts of patients (a total of 220) undergoing chemotherapy or chemoradiation.  TFAP2E was hyper-methylated in 38 of 74 patients (51 %) in the initial cohort.  Hyper-methylation was associated with decreased expression of TFAP2E in primary and metastatic CRC specimens and cell lines.  Colorectal-cancer cell lines over-expressing DKK4 showed increased chemoresistance to fluorouracil but not irinotecan or oxaliplatin.  In the 4 other patient cohorts, TFAP2E hyper-methylation was significantly associated with non-response to chemotherapy (p < 0.001).  Conversely, the probability of response among patients with hypo-methylation was approximately 6 times that in the entire population (overall estimated risk ratio, 5.74; 95 % CI: 3.36 to 9.79).  Epigenetic alterations of TFAP2E were independent of mutations in key regulatory cancer genes, microsatellite instability, and other genes that affect fluorouracil metabolism.  The authors concluded that TFAP2E hyper-methylation is associated with clinical non-responsiveness to chemotherapy in CRC.  Functional assays confirm that TFAP2E-dependent resistance is mediated through DKK4.  In patients who have CRC with TFAP2E hyper-methylation, targeting of DKK4 may be an option to overcome TFAP2E-mediated drug resistance.

Hong and colleagues (2014a) stated that although chemotherapy is an important therapeutic strategy for gastro-intestinal cancer, its clinical effect remains unsatisfied due to drug resistance.  Drug resistance is a complex multi-step process resulting from deregulated expression of many molecules, including tumor suppressor genes, oncogenes and miRNAs.  A better understanding of drug resistance-related miRNAs may eventually lead to optimized therapeutic strategies for cancer patients.  These investigators summarized the recent advances of drug resistance-related miRNAs in esophageal, gastric and colorectal cancer.  Furthermore, this study envisaged future developments toward the clinical applications of these miRNAs to cancer therapy.  The authors concluded that drug resistance-related miRNAs may be potentially predicting biomarkers that help guide individualized chemotherapy.  Specific miRNAs and their target genes can be used as therapeutic targets by reversing drug resistance.  They stated that more investigations should be performed to promote the translational bridging of the latest research into clinical application.

Hong and associates (2014b) stated that hepato-cellular cancer (HCC) is a hyper-vascular cancer characterized by rapid progression as well as resistance to chemotherapy.  Drug resistance arises from the alteration of many molecules, including oncogenes, tumor suppressor genes and miRNAs.  These researchers evaluated the advances of drug resistance-related miRNAs in HCC, and analyzed the value of them as prognostic biomarkers and therapeutic targets.  They also discussed the limitations of miRNA-based therapy, and envisaged future developments toward the clinical applications of drug resistance-related miRNAs.

The ASCO’s clinical practice guideline on “Chemotherapy and targeted therapy for women with human epidermal growth factor receptor 2-negative (or unknown) advanced breast cancer” (Partridge et al, 2014) stated that “Chemotherapy regimens should not be specifically tailored to different breast cancer subtypes (e.g., triple negative, lobular) at the present time due to the absence of evidence proving differential efficacies.  In addition, in-vitro chemoresistance assays should not be used to select treatment”.

The U.S. Food and Drug Administration used the Duke University Chemotherapy Assessment Test, an insufficiently validated test for predicting response to specific chemotherapy regimens, as an example of a laboratory developed test (LDT) that may have caused harm.  "As a consequence of the use of this insufficiently validated LDT, cancer patients were exposed to potentially inappropriate chemotherapy" (FDA, 2015).

Wang and colleagues (2016a) noted that chemoresistance in breast cancer has been of great interest in past studies. However, the development of rational therapeutic strategies targeting chemoresistant cells is still a challenge in clinical oncology.  By integrating data from global differences of gene expression and phospho-receptor tyrosine kinases between sensitive parental cells (MCF-7) and doxorubicin-resistant cells (MCF-7/ADR), these researchers identified Axl as a potential target for chemoresistance and metastasis in multi-drug resistant breast cancer cells.  They analyzed Axl expression in 57 breast cancer cell lines and detected a dramatic increase in its expression level in mesenchymal breast cancer cell lines.  Axl silencing suppressed invasive and metastatic potentials of chemoresistant breast cancer cells as well as increased elimination of cancer cells when combined with doxorubicin.  Furthermore, in pre-clinical assays, an Axl inhibitor R428 showed increased cell death upon doxorubicin treatment.  Additionally, using phospho-kinase array based proteomic analysis, thee investigators identified that Akt/GSK-3β/β-catenin cascade was responsible for Axl-induced cell invasion.  Nuclear translocation of β-catenin then induced transcriptional up-regulation of ZEB1, which in turn regulated DNA damage repair and doxorubicin-resistance in breast cancer cells.  Most importantly, Axl was correlated with its down-stream targets in tumor samples and was associated with poor prognosis in breast cancer patients.  The authors concluded that these results demonstrated that Gas6/Axl axis conferred aggressiveness in breast cancer and may represent a therapeutic target for chemoresistance and metastasis.

Wang and co-workers (2016b) stated that kinesin family member 14 (KIF14) is a member of kinesin family proteins which have been found to be dysregulated in various cancer types. However, the expression of KIF14 and its potential prognostic significance have not been investigated in cervical cancer.  Real-time PCR was performed to assess the expression levels of KIF14 in 47 pairs of cervical cancer tissues and their matched normal tissues from patients who had not been exposed to chemotherapy as well as tissue samples from 57 cervical cancer patients who are sensitive to paclitaxel treatment and 53 patients who are resistant.  The association between KIF14 expression levels in tissue and clinicopathological features or chemosensitivity was examined.  Kaplan-Meier analysis and Cox proportional hazards model were applied to assess the correlation between KIF14 expression levels and overall survival (OS) of cervical cancer patients.  KIF14 expression levels were significantly increased in cervical cancer tissues compared with matched non-cancerous tissues and it was higher in tissues of patients who are chemoresistant compared with those who are chemosensitive.  KIF14 expression was positively associated with high tumor stage (p = 0.0044), lymph node metastasis (p = 0.0034) and chemoresistance (p < 0.0001).  Kaplan-Meier analysis showed that high KIF14 expression levels predicted poor survival in patients with (p = 0.0024) or without (p = 0.0028) paclitaxel treatment.  Multi-variate analysis revealed that KIF14 was an independent prognostic factor for OS.  The authors concluded that the findings of this study suggested that KIF14 may serve as a predictor of poor survival and a novel prognostic biomarker of chemoresistance to paclitaxel treatment in cervical cancer.

Peterse et al (2016) noted that chondrosarcoma is a malignant cartilage forming bone tumor for which no effective systemic treatment is available. Previous studies illustrated the need for a better understanding of the role of the IGF pathway in chondrosarcoma to determine if it can be a target for therapy.  In this study, expression of mediators of IGF1R signaling and phosphorylation status of IRS1 was determined in chondrosarcoma cell lines by qRT-PCR and Western blot.  The effect of activation and inhibition of IGF1R signaling on down-stream targets was evaluated by Western blot.  A total of 10 chondrosarcoma cell lines were treated with OSI-906 (IGF1R and IR dual inhibitor) after which cell proliferation and migration were determined by a viability assay and the xCELLigence system, respectively.  In addition, 4 chondrosarcoma cell lines were treated with a combination of doxorubicin and OSI-906.  By immunohistochemistry, IGF1R expression levels were determined in tissue microarrays of 187 cartilage tumors and 10 paraffin embedded cell lines.  Mediators of IGF1R signaling were heterogeneously expressed and phosphorylated IRS1 was detected in 67 % of the tested chondrosarcoma cell lines, suggesting that IGF1R signaling was active in a subset of chondrosarcoma cell lines.  In the cell lines with phosphorylated IRS1, inhibition of IGF1R signaling decreased phosphorylated Akt levels and increased IGF1R expression, but it did not influence MAPK or S6 activity.  In line with these findings, treatment with IGF1R/IR inhibitors did not impact proliferation or migration in any of the chondrosarcoma cell lines, even upon stimulation with IGF1.  Although synergistic effects of IGF1R/IR inhibition with doxorubicin have been described for other cancers, the present findings demonstrated that this was not the case for chondrosarcoma.  In addition, these investigators found minimal IGF1R expression in primary tumors in contrast to the high expression detected in chondrosarcoma cell lines, even if both were derived from the same tumor, suggesting that in-vitro culturing up-regulated IGF1R expression.  The authors concluded that the results from this study indicated that the IGF pathway is not essential for chondrosarcoma growth, migration or chemoresistance.  Furthermore, IGF1R is only minimally expressed in chondrosarcoma primary tumors.  Therefore, the IGF pathway is not expected to be an effective therapeutic target for chondrosarcoma of bone.

Sumiyoshi and associates (2016) noted that pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies, and there is an urgent need for new therapeutic strategies based on the molecular biology of PDAC. Signal transducers and activators of transcription 5 (STAT5) are known to be activated in a variety of malignancies and involved in tumor proliferation, apoptosis, and invasion, whereas the expression and biological role of STAT5b in PDAC are less clearly defined.  These researchers examined the expression and role of STAT5b in human pancreatic cancer cell lines.  Expressions of STAT5b mRNA and protein were detected in 8 kinds of pancreatic cancer cells.  Confocal microscopy and western blot analysis indicated that STAT5b was localized in both cytoplasm and nuclei.  Immuno-precipitation analysis revealed tyrosine phosphorylation of STAT5b in pancreatic cancer cells.  These results indicated that STAT5b in pancreatic cancer cells is constitutively activated.  STAT5b shRNA clones in PANC-1 cells, which express relatively high levels of STAT5b, exhibited reduced chemoresistance against gemcitabine, adhesion and invasion compared to sham.  On the other hand, AsPC-1 and BxPC3 cells, which express relatively low levels of STAT5b, exhibited reduced chemoresistance compared to PANC-1 cells.  Moreover, STAT5b over-expression clones in AsPC-1 cells exhibited increased chemoresistance compared to sham.  STAT5b shRNA clones in PANC-1 cells were more sensitive to the pro-apoptotic actions of gemcitabine, as evidenced by PARP and cleaved caspase-3 activation.  Gemcitabine also significantly reduced Bcl-xL levels in the STAT5b shRNA-expressing cells.  These investigators also investigated the clinicopathological characteristics of STAT5b expression of PDAC.  Although a significant correlation between STAT5b expression and OS rates was not observed, a significant correlation with main pancreatic duct invasion was observed.  The authors concluded that these findings suggested that STAT5b conferred gemcitabine chemoresistance and promoted cell adherence and invasiveness in pancreatic cancer cells.  They stated that targeting STAT5b may lead to novel therapeutic strategies for PDAC.

Krzystyniak et al (2016) stated that epithelial ovarian cancer (EOC) remains one of the leading causes of cancer-related deaths among women worldwide, despite gains in diagnostics and treatments made over the last 3 decades. Existing markers of OC possess very limited clinical relevance highlighting the emerging need for identification of novel prognostic biomarkers as well as better predictive factors that might allow the stratification of patients who could benefit from a more targeted approach.  Large-scale high-throughput genomic technologies appear to be powerful tools for investigations into the genetic abnormalities in ovarian tumors, including studies on dysregulated genes and aberrantly activated signaling pathways.  Such technologies can complement well-established clinical histopathology analysis and tumor grading and will hope to result in better, more tailored treatments in the future.  Genomic signatures obtained by gene expression profiling of EOC may be able to predict survival outcomes and other important clinical outcomes, such as the success of surgical treatment.  Finally, genomic analyses may allow for the identification of novel predictive biomarkers for purposes of treatment planning.  These data suggested a pathway to progress in the treatment of advanced OC and the promise of fulfilling the objective of providing personalized medicine to women with OC.  The authors concluded that the understanding of basic molecular events in the tumorigenesis and chemoresistance of EOC together with discovery of potential biomarkers may be greatly enhanced through large-scale genomic studies.  In order to maximize the impact of these technologies, however, extensive validation studies are needed.

Zhao and colleagues (2016) stated that the prognostic value and clinicopathological significance of CD44 in OC remain unclear. In a meta-analysis, these researchers evaluated the correlation between CD44 expression and OC.  Studies published until March 2016 were searched in PubMed, Embase, and ISI Web of Knowledge databases.  The odds ratio (OR) and the hazard ratio (HR) with 95 % CI were used to assess the effects.  A total of 24 studies that included 2,267 OC patients were identified for the final analysis; 16 studies investigated the expression difference of CD44 standard (CD44s) in 1,848 patients.  Results showed that high CD44s expression is associated with chemoresistance (OR 5.94, 95 % CI: 1.91 to 18.47) and short disease-free survival (DFS) time (HR 2.57, 95 % CI: 1.34 to 4.91).  In addition, CD44s expression was not associated with tumor differentiation grade, residual mass, lymphoid nodal metastasis, and OS; 10 studies investigated the expression difference of CD44v6 in 724 patients.  Results showed that the CD44v6 expression was not correlated with FIGO stage, tumor differentiation grade, lymphoid nodal metastasis, and OS.  The authors concluded that high CD44s expression possibly indicated poor prognosis in OC patients given that high CD44s expression initiates chemotherapy resistance, although this expression pattern was not an independent predictive factor for OS.  They stated that high CD44s expression may be related to poor DFS of OC, but this relationship must be further confirmed.  In addition, the result in which CD44v6 was not associated with OS of OC patients should be interpreted with caution.

Table: CPT Codes / HCPCS Codes / ICD-10 Codes
Code Code Description

Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+":

CPT codes not covered for indications listed in the CPB:

87230 Toxin or antitoxin assay, tissue culture (e.g., Clostridium difficile toxin)
88104 Cytopathology, fluids, washings or brushing, except cervical or vaginal; smears with interpretation
88305 Level IV surgical pathology, gross and microscopic examination
+ 88313 Special stain including intrepretation and report; Group II, all other (e.g., iron, trichrome), except stain for microorganisms, stains for enzyme constituents, or immunocytochemistry and immunohistochemistry
88358 Morphometric analysis; tumor (e.g., DNA ploidy)
89050 Cell count, miscellaneous body fluids (e.g., cerebrospinal fluid, joint fluid), except blood

Other CPT codes related to the CPB:

88230 Tissue culture for non-neoplastic disorders; lymphocyte
88233     skin or other solid tissue biopsy
88235     amniotic fluid or chorionic villus cells
88237 Tissue culture for neoplastic disorders; bone marrow, blood cells
88239     solid tumor

Other HCPCS codes related to the CPB:

J9000 - J9999 Chemotherapy drugs

ICD-10 codes not covered for indications listed in the CPB:

C00.0 - D49.9 Neoplasms
Z51.11 - Z51.12 Encounter for antineoplastic chemotherapy and immunotherapy

The above policy is based on the following references:

  1. Kern DH, Weisenthal LM. Highly specific prediction of antineoplastic drug resistance with an in vitro assay using suprapharmacologic drug exposures. J Natl Cancer Inst. 1990;82(7):582-588.
  2. Fruehauf JP, Manetta A. Use of the extreme drug resistance assay to evaluate mechanisms of resistance in ovarian cancer: Taxol resistance and MDR-1 expression.Contrib Gynecol Obstet. 1994;19:39-52.
  3. Centers for Medicare and Medicaid Services (CMS). National Coverage Determination (NCD) for human tumor stem cell drug sensitivity assays (190.7). Baltimore, MD: CMS; July 1996.
  4. Markman M. Chemosensitivity and chemoresistance assays: Are they clinically relevant? J Cancer Res Clin Oncol. 1995;121(8):441-442.
  5. Brown E, Markman M. Tumor chemosensitivity and chemoresistance assays. Cancer. 1996;77:1020-1025.
  6. Kern DH. Heterogeneity of drug resistance in human breast and ovarian cancers. Cancer J Sci Am. 1998;4(1):41-45.
  7. Eltabbakh GH, Piver MS, Hempling RE, et al. Correlation between extreme drug resistance assay and response to primary paclitaxel and cisplatin in patients with epithelial ovarian cancer. Gynecol Oncol. 1998;70(3):392-397.
  8. Cortazar P, Johnson BE. Review of the efficacy of individualized chemotherapy selected by in vitro drug sensitivity testing for patients with cancer. J Clin Oncol. 1999;17(5):1625-1631.
  9. Orr JW Jr, Orr P, Kern DH. Cost-effective treatment of women with advanced ovarian cancer by cytoreductive surgery and chemotherapy directed by an in vitro assay for drug resistance. Cancer J Sci Am. 1999;5(3):174-178.
  10. Agiostratidou G, Demertzis N, Gonos ES. Evaluation of cytotoxic treatment of patients with osteosarcoma by an in vitro chemoresistance assay. Anticancer Res. 2000;20(5B):3603-3608.
  11. Center for Medicare and Medicaid Services. Human tumor assay systems (#CAG-00044N). National Coverage Analysis (NCA). Baltimore, MD: CMS; April 13, 2000.
  12. Mehta RS, Bornstein R, Yu IR, et al. Breast cancer survival and in vitro tumor response in the extreme drug resistance assay. Breast Cancer Res Treat. 2001;66(3):225-237.
  13. Agiostratidou G, Sgouros I, Galani E, et al. Correlation of in vitro cytotoxicity and clinical response to chemotherapy in ovarian and breast cancer patients. Anticancer Res. 2001;21(1A):455-459.
  14. Haroun RI, Clatterbuck RE, Gibbons MC, et al. Extreme drug resistance in primary brain tumors: In vitro analysis of 64 resection specimens. J Neurooncol. 2002;58(2):115-123.
  15. Holloway RW, Mehta RS, Finkler NJ, et al. Association between in vitro platinum resistance in the EDR assay and clinical outcomes for ovarian cancer patients. Gynecol Oncol. 2002;87(1):8-16.
  16. Monk BJ, Burger RA, Parker R, et al. Development of an in vitro chemo-radiation response assay for cervical carcinoma. Gynecol Oncol. 2002;87(2):193-199.
  17. Ellis RJ, Fabian CJ, Kimler BF, et al. Factors associated with success of the extreme drug resistance assay in primary breast cancer specimens. Breast Cancer Res Treat. 2002;71(2):95-102.
  18. BlueCross BlueShield Association (BCBSA), Technology Evaluation Center (TEC). Chemotherapy sensitivity and resistance assays. TEC Assessment Program. Chicago, IL: BCBSA; October 2002;17(12).
  19. O'Toole SA, Sheppard BL, McGuinness EP, et al. The MTS assay as an indicator of chemosensitivity/resistance in malignant gynaecological tumours. Cancer Detect Prev. 2003;27(1):47-54.
  20. Loizzi V, Chan JK, Osann K, et al. Survival outcomes in patients with recurrent ovarian cancer who were treated with chemoresistance assay-guided chemotherapy. Am J Obstet Gynecol. 2003;189(5):1301-1317.
  21. Cloven NG, Kyshtoobayeva A, Burger RA, et al. In vitro chemoresistance and biomarker profiles are unique for histologic subtypes of epithelial ovarian cancer.Gynecol Oncol. 2004;92(1):160-166.
  22. Fan CW, Fan HA, Hsu SH, et al. An in vitro short time-high dose drug exposure assay for predicting 5FU-resistance of colorectal cancer. Cancer Lett. 2004;214(2):181-188.
  23. Parker RJ, Fruehauf JP, Mehta R, et al. A prospective blinded study of the predictive value of an extreme drug resistance assay in patients receiving CPT-11 for recurrent glioma. J Neurooncol. 2004;66(3):365-375.
  24. Schrag D, Garewal HS, Burstein HJ, Samson et al. American Society of Clinical Oncology Technology Assessment: Chemotherapy sensitivity and resistance assays. J Clin Oncol. 2004;22(17):3631-3638.
  25. Samson D J, Seidenfeld J, Ziegler K, Aronson N. Chemotherapy sensitivity and resistance assays: A systematic review. J Clin Oncol. 2004;22(17):3618-3630.
  26. Tewari D, Monk BJ, Al-Ghazi MS, et al. Gene expression profiling of in vitro radiation resistance in cervical carcinoma: A feasibility study.Gynecol Oncol. 2005;99(1):84-91.
  27. Tewari KS, Mehta RS, Burger RA, et al. Conservation of in vitro drug resistance patterns in epithelial ovarian carcinoma. Gynecol Oncol. 2005;98(3):360-368.
  28. Huang J, Tan PH, Li KB, et al. Y-box binding protein, YB-1, as a marker of tumor aggressiveness and response to adjuvant chemotherapy in breast cancer. Int J Oncol. 2005;26(3):607-613.
  29. Chuthapisith S, Eremin JM, El-Sheemy M, Eremin O. Neoadjuvant chemotherapy in women with large and locally advanced breast cancer: Chemoresistance and prediction of response to drug therapy. Surgeon. 2006;4(4):211-219.  
  30. d'Amato TA, Landreneau RJ, McKenna RJ, et al. Prevalence of in vitro extreme chemotherapy resistance in resected nonsmall-cell lung cancer. Ann Thorac Surg. 2006;81(2):440-447.
  31. Fruehauf JP, Brem H, Brem S, et al. In vitro drug response and molecular markers associated with drug resistance in malignant gliomas. Clin Cancer Res. 2006;12(15):4523-4532.
  32. Quintieri L, Fantin Kubota T, Weisenthal L. Chemotherapy sensitivity and resistance testing: To be 'standard' or to be individualized, that is the question. Gastric Cancer. 2006;9(2):82-87.
  33. Kubota T, Weisenthal L. Chemotherapy sensitivity and resistance testing: To be 'standard' or to be individualized, that is the question. Gastric Cancer. 2006;9(2):82-87.
  34. Quintieri L, Fantin M, Vizler C. Identification of molecular determinants of tumor sensitivity and resistance to anticancer drugs. Adv Exp Med Biol. 2007;593:95-104.
  35. Santillan A, Kim YW, Zahurak ML, et al. Differences of chemoresistance assay between invasive micropapillary/low-grade serous ovarian carcinoma and high-grade serous ovarian carcinoma. Int J Gynecol Cancer. 2007;17(3):601-606.
  36. d'Amato TA, Landreneau RJ, Ricketts W, et al. Chemotherapy resistance and oncogene expression in non-small cell lung cancer. J Thorac Cardiovasc Surg. 2007;133(2):352-363.  
  37. Brower SL, Fensterer JE, Bush JE.  The ChemoFx assay: An ex vivo chemosensitivity and resistance assay for predicting patient response to cancer chemotherapy. Methods Mol Biol. 2008;414:57-78.
  38. Gallion H, Christopherson WA, Coleman RL, et al. Progression-free interval in ovarian cancer and predictive value of an ex vivo chemoresponse assay. Int J Gynecol Cancer. 2006;16(1):194-201.
  39. Peters D, Freund J, Ochs RL. Genome-wide transcriptional analysis of carboplatin response in chemosensitive and chemoresistant ovarian cancer cells. Mol Cancer Ther. 2005;4(10):1605-1616.
  40. Ochs RL, Burholt D, Kornblith P. The ChemoFx assay: An ex vivo cell culture assay for predicting anticancer drug responses. Methods Mol Med. 2005;110:155-172.
  41. Ness RB, Wisniewski SR, Eng H, et al.  Cell viability assay for drug testing in ovarian cancer: In vitro kill versus clinical response. Anticancer Res. 2002;22(2B):1145-1149.
  42. Cree IA. Chemosensitivity and chemoresistance testing in ovarian cancer. Curr Opin Obstet Gynecol. 2009;21(1):39-43.
  43. Rass K, Hassel JC. Chemotherapeutics, chemoresistance and the management of melanoma. G Ital Dermatol Venereol. 2009;144(1):61-78.
  44. Lyons JM 3rd, Abergel J, Thomson JL, et al. In vitro chemoresistance testing in well-differentiated carcinoid tumors. Ann Surg Oncol. 2009;16(3):649-655.
  45. National Comprehensive Cancer Network (NCCN). Ovarian cancer including fallopian tube cancer and primary peritoneal cancer. NCCN Clinical Practice Guidelines in Oncology v.2.2011. Fort Washington, PA: NCCN; 2011.
  46. Burstein HJ, Mangu PB, Somerfield MR, et al. American society of clinical oncology clinical practice guideline update on the use of chemotherapy sensitivity and resistance assays. J Clin Oncol. 2011;29(24):3328-3330.
  47. Chao SY, Chiang JH, Huang AM, Chang WS. An integrative approach to identifying cancer chemoresistance-associated pathways. BMC Med Genomics. 2011;4:23.
  48. Wang H, Tan G, Dong L, et al. Circulating MiR-125b as a marker predicting chemoresistance in breast cancer. PLoS One. 2012;7(4):e34210.
  49. Lee JH, Um JW, Lee JH, et al. Can immunohistochemistry of multidrug-resistant proteins replace the histoculture drug response assay in colorectal adenocarcinomas? Hepatogastroenterology. 2012;59(116):1075-1078.
  50. Ebert MP, Tänzer M, Balluff B, et al. TFAP2E-DKK4 and chemoresistance in colorectal cancer. N Engl J Med. 2012;366(1):44-53.
  51. Hu H, Li S, Cui X, et al. The overexpression of hypomethylated miR-663 induces chemotherapy resistance in human breast cancer cells by targeting heparin sulfate proteoglycan 2 (HSPG2). J Biol Chem. 2013;288(16):10973-10985.
  52. Hong L, Han Y, Zhang Y, et al. MicroRNA-21: A therapeutic target for reversing drug resistance in cancer. Expert Opin Ther Targets. 2013;17(9):1073-1080.
  53. Jiang L, He D, Yang D, et al. MiR-489 regulates chemoresistance in breast cancer via epithelial mesenchymal transition pathway. FEBS Lett. 2014;588(11):2009-2015.
  54. Ma X, Chen Z, Hua D, et al. Essential role for TrpC5-containing extracellular vesicles in breast cancer with chemotherapeutic resistance. Proc Natl Acad Sci U S A. 2014;111(17):6389-6394.
  55. Chen Y, Ke G, Han D, et al. MicroRNA-181a enhances the chemoresistance of human cervical squamous cell carcinoma to cisplatin by targeting PRKCD. Exp Cell Res. 2014;320(1):12-20.
  56. Li B, Tsao SW, Chan KW, et al. Id1-induced IGF-II and its autocrine/endocrine promotion of esophageal cancer progression and chemoresistance -- implications for IGF-II and IGF-IR-targeted therapy. Clin Cancer Res. 2014;20(10):2651-2662.
  57. Germani A, Matrone A, Grossi V, et al. Targeted therapy against chemoresistant colorectal cancers: Inhibition of p38α modulates the effect of cisplatin in vitro and in vivo through the tumor suppressor FoxO3A. Cancer Lett. 2014;344(1):110-118.
  58. Yang YI, Ahn JH, Lee KT, et al. RSF1 is a positive regulator of NF-κB-induced gene expression required for ovarian cancer chemoresistance. Cancer Res. 2014;74(8):2258-2269.
  59. Shin DH, Choi YJ, Park JW. SIRT1 and AMPK mediate hypoxia-induced resistance of non-small cell lung cancers to cisplatin and doxorubicin. Cancer Res. 2014;74(1):298-308.
  60. Xiao F, Bai Y, Chen Z, et al. Downregulation of HOXA1 gene affects small cell lung cancer cell survival and chemoresistance under the regulation of miR-100. Eur J Cancer. 2014;50(8):1541-1554.
  61. Hong L, Han Y, Yang J, et al. MicroRNAs in gastrointestinal cancer: Prognostic significance and potential role in chemoresistance. Expert Opin Biol Ther. 2014(a);14(8):1103-1111.
  62. Hong L, Han Y, Zhang H, et al. Drug resistance-related miRNAs in hepatocellular cancer. Expert Rev Gastroenterol Hepatol. 2014(b);8(3):283-288.
  63. National Comprehensive Cancer Network (NCCN).Ovarian cancer including fallopian tube cancer and primary peritoneal cancer. NCCN Clinical Practice Guidelines in Oncology. Fort Washington, PA: NCCN; 2015.
  64. U.S, Food & Drug Administration (FDA). The public health evidence for FDA oversight of laboratory developed tests: 20 case studies. Silver Spring, MD: FDA; November 16, 2015.
  65. Partridge AH, Rumble RB, Carey LA, et al. Chemotherapy and targeted therapy for women with human epidermal growth factor receptor 2-negative (or unknown) advanced breast cancer: American Society of Clinical Oncology clinical practice guideline. J Clin Oncol. 2014;32(29):3307-3329.
  66. Potti A, Dressman HK, Bild A, et al. Genomic signatures to guide the use of chemotherapeutics. Nature Med. 2006;12:1294-1300. (Retracted January 2011)
  67. Kolata G. How bright promise in cancer testing fell apart. The New York Times. July 7, 2011. 
  68. Coombes KR, Wang J, Baggerly KA. Supplementary Reports 0-9. Nature Med. 2007;13:1276-1277.
  69. Coombes KR, Wang J, Baggerly KA. Microarrays: Retracing steps. Nat Med. 2007;13:1276-1277.
  70. Baggerly K, Coombes K. Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology. Ann Applied Statistics. 2009;3(4):1309-1334.
  71. Institute of Medicine. Evolution of Translational Omics: Lessons Learned and the Path Forward. The National Academies Press (US). 2012. 
  72. Wang C, Jin H, Wang N, et al. Gas6/Axl axis contributes to chemoresistance and metastasis in breast cancer through Akt/GSK-3β/β-catenin signaling. Theranostics. 2016a;6(8):1205-1219.
  73. Wang W, Shi Y, Li J, et al. Up-regulation of KIF14 is a predictor of poor survival and a novel prognostic biomarker of chemoresistance to paclitaxel treatment in cervical cancer. Biosci Rep. 2016b;36(2).
  74. Peterse EF, Cleven AH, De Jong Y, et al. No preclinical rationale for IGF1R directed therapy in chondrosarcoma of bone. BMC Cancer. 2016;16(1):475.
  75. Sumiyoshi H, Matsushita A, Nakamura Y, et al. Suppression of STAT5b in pancreatic cancer cells leads to attenuated gemcitabine chemoresistance, adhesion and invasion. Oncol Rep. 2016;35(6):3216-3226.
  76. Krzystyniak J, Ceppi L, Dizon DS, Birrer MJ. Epithelial ovarian cancer: The molecular genetics of epithelial ovarian cancer. Ann Oncol. 2016;27 Suppl 1:i4-i10.
  77. Zhao L, Gu C, Huang K, et al. The prognostic value and clinicopathological significance of CD44 expression in ovarian cancer: A meta-analysis. Arch Gynecol Obstet. 2016;294(5):1019-1029.