Dakun Wang

Distinct Genes Related to Drug Response Identified in ER Positive and ER Negative Breast Cancer Cell Lines

Breast cancer patients have different responses to chemotherapeutic treatments. Genes associated with drug response can provide insight to understand the mechanisms of drug resistance, identify promising therapeutic opportunities, and facilitate personalized treatment. Estrogen receptor (ER) positive and ER negative breast cancer have distinct clinical behavior and molecular properties. However, to date, few studies have rigorously assessed drug response genes in them. In this study, our goal was to systematically identify genes associated with multidrug response in ER positive and ER negative breast cancer cell lines. We tested 27 human breast cell lines for response to seven chemotherapeutic agents (cyclophosphamide, docetaxel, doxorubicin, epirubicin, fluorouracil, gemcitabine, and paclitaxel). We integrated publicly available gene expression profiles of these cell lines with their in vitro drug response patterns, then applied meta-analysis to identify genes related to multidrug response in ER positive and ER negative cells separately. One hundred eighty-eight genes were identified as related to multidrug response in ER positive and 32 genes in ER negative breast cell lines. Of these, only three genes (DBI, TOP2A, and PMVK) were common to both cell types. TOP2A was positively associated with drug response, and DBI was negatively associated with drug response. Interestingly, PMVK was positively associated with drug response in ER positive cells and negatively in ER negative cells. Functional analysis showed that while cell cycle affects drug response in both ER positive and negative cells, most biological processes that are involved in drug response are distinct. A number of signaling pathways that are uniquely enriched in ER positive cells have complex cross talk with ER signaling, while in ER negative cells, enriched pathways are related to metabolic functions. Taken together, our analysis indicates that distinct mechanisms are involved in multidrug response in ER positive and ER negative breast cells.

Chemoresponse assay for evaluating response to sunitinib in primary cultures of breast cancer

Purpose: Not all patient tumors respond equally to the same type of therapy. An in vitro chemoresponse assay that can suggest individualized tumor response to therapies, in this case sunitinib, can be a valuable guide for clinical decision-making. Experimental Design: The ChemoFx® drug response marker (DRM) (Precision Therapeutics, Inc.) was carried out on SK-OV-3 cells treated with sunitinib to establish appropriate dose ranges and assay thresholds, and to evaluate vendor supplies of sunitinib. Once reference values were determined, the assay was applied to eight different renal cell lines treated with sunitinib, each of which was subsequently classified into responsive, intermediate responsive, and non-responsive groups. Next, ex vivo tumor samples from 39 clinically diagnosed breast cancer patients were grown in culture and assayed for their response to sunitinib using ChemoFx. Results: The assay was shown to be sensitive and reproducible while differentiating renal cell lines based on sunitinib sensitivity and evaluating vendors’ supply of the compound. Of the cultured breast cancer tumor specimens treated with sunitinib, ChemoFx classified 7.6% as responsive (R), 20.5% of specimens as intermediate responsive (IR), and 71.7% as non-responsive (NR). Conclusions: Chemoresponse assay assessment is an effective tool for evaluating sunitinib sensitivity in cultured cell lines as well as ex vivo breast cancer samples. An in vitro assay that may indicate an individual patient’s clinical response to a chemotherapeutic agent can be beneficial in time, cost, and clinical outcome when therapeutic options are considered.

Analytical Performance of a 15-Gene Prognostic Assay for Early-Stage Non–Small-Cell Lung Carcinoma Using RNA-Stabilized Tissue

A 15-gene prognostic signature for early-stage, completely resected, non-small-cell lung carcinoma, (which distinguishes between patients with good and poor prognoses) was clinically validated in prior studies. To achieve operational efficiencies, this study was designed to evaluate the assays performance in RNA-stabilized tissue as an alternative to the fresh-frozen tissue format originally used to develop the assay. The percent concordance between matched tissue formats was 84% (95% Wilson CI, 70%-92%), a level of agreement comparable to the inherent reproducibility of the assay observed within biological replicates of fresh-frozen tissue. Furthermore, the analytical performance of the assay using the RNA-stabilized tissue format was evaluated. When compared to an accredited reference laboratory, the clinical laboratory achieved a concordance of 94% (95% Wilson CI, 81%-98%), and there was no evidence of bias between the laboratories. The lower limit of quantitation for the target RNA concentration was confirmed to be, at most, 12.5 ng/μL. The assay reportable range defined in terms of risk score units was determined to be -4.295 to 4.210. In a large-scale precision study, the assay showed high reproducibility and repeatability. When subjected to a maximal amount of genomic DNA, a potential contaminant, the assay still produced the expected results. The 15-gene signature was confirmed to produce reliable results and, thus, is suitable for its intended use.

Adaptation of a chemosensitivity assay to accurately assess pemetrexed in ex vivo cultures of lung cancer.

Purpose: Pemetrexed is the only FDA approved treatment for mesothelioma and is a second line agent for treatment of non-small cell lung carcinoma (NSCLC). Pemetrexed is inhibited by folate and its analogs, which are components of many culture media, making it challenging to study pemetrexed in vitro. In order to accurately evaluate pemetrexed’s effects in vitro, the protocol for a standard chemosensitivity assay, the ChemoFx drug response marker, had to be modified. Experimental Design: Novel rinse and media change steps were assessed and then added to the assay protocol in order to observe pemetrexed activity. The intraday and interday stability of pemetrexed were also established under the adapted protocol. Then, the modified protocol was used to examine pemetrexed in 65 ex vivo lung cancer specimens. Results: Substituting 5% RPMI + EGF for BEGM allowed pemetrexed to exert its anticancer activity in the ChemoFx DRM. ChemoFx classified 6.2% of the lung specimens as responsive, 9.2% as intermediate responsive and 84.6% as non-responsive to pemetrexed. Conclusions: Adapting the ChemoFx protocol allowed for the accurate evaluation of pemetrexed anticancer activity in ex vivo lung specimens. ChemoFx evaluation may provide an indication of a patient’s clinical response to the drug prior to pemetrexed treatment. Having this information when treatment options are being considered could avoid wasted time, unnecessary costs and needless side effects that are the result of an inappropriate chemotherapy regimen.

Abstract 118: Analysis of biological pathways associated with epirubicin and/or cyclophosphamide response by pathway enrichment analysis in human breast cancers

Recently, a number of different approaches for improving cancer treatment have been developed. One scientific approach is to understand the biochemical pathways and coding genes involved in cancer causation, while other approaches look to distinguish the biochemical pathways involved in drug response. Many chemotherapeutic drugs have been developed targeting different cellular properties, and even more targeted therapies impacting specific oncogenic pathways are on the horizon. Pathways implicated in drug response have been studied to determine why some tumors might respond to a given chemotherapy while others do not. Understanding these pathways may provide potential for improving therapeutic efficacy. Pathway analysis methods have been proposed to discover pathways of interests using gene expression profiling. In this study, the biological pathways associated with response to Epirubicin (E), Cyclophosphamide (C) or the combination of the two drugs (combo EC) were evaluated in both breast cancer cell lines and patients. Thirty immortalized breast cancer cell lines were evaluated for response to these drugs using ChemoFx®. Area under the dose-response curve (AUC) was calculated to measure the chemosensitivity. We applied pathway enrichment to detect specific biochemical pathways associated with these drugs based on biological pathway databases (Kyoto Encyclopedia of Genes and Biocarta), breast cancer cell lines’ drug responses and public microarray data. Comparison of pathways associated with single drug E, C, and combo EC revealed that there are pathways associated with drug combination but not significantly associated with single drugs. These drug response-associated pathways offer great potential for new biomarker identification and drug targeting discovery. In addition, EC associated pathways in breast cancer patients were identified using public microarray data and the associated patient clinical outcomes. Of importance, four biological pathways related to adherens junction, leukocyte transendothelial migration, regulation of actin cytoskeleton and ribosomal protein were identified as EC response-associated pathways in both breast cancer cell lines and patients. These common EC response-associated pathways indicate the potential possibility to use cell line in vitro drug responses to predict patient chemotherapy outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 118.

Abstract 4114: Evaluation of ERCC1 expression and in vitro drug response to cisplatin based on human NSCLC cell lines and primary cultures of human lung cancers

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Introduction: In vitro experimentation has been suggested as a rapid tool for identifying and evaluating biomarkers associated with drug response. Excision repair cross-complementation 1 (ERCC1) enzyme plays a rate-limiting role in the nucleotide excision repair pathway and its up regulation has been associated with resistance to platinum agents. Recent studies have suggested that low expression levels of ERCC1 are related to a better survival benefit from cisplatin-based chemotherapy among patients with advanced non-small cell lung carcinoma (NSCLC). This study evaluates the relationship between ERCC1 expression and in vitro drug response to cisplatin using an in vitro chemoresponse assay, ChemoFx® Drug Response Marker (DRM), in human NSCLC cell lines and primary cultures of human lung cancers. Methods: The ChemoFx® DRM was performed on 13 immortalized human NSCLC cell lines (NCI-H520, HOP_92, HOP-62, A549, Calu-3, HCC827, OK, NCI-H460, NCI-H596, NCI-H1666, EKVX, NCI-H358, and NCI-H1975) and 30 primary cultures established from de-identified lung cancer surgical specimens. Cells were treated with a 10-dose range of cisplatin for 72 hours before DAPI-nuclear staining and counting. Response Index scores (RI scores), which are derived from an area under the dose-response curve (AUC), were calculated on the resulting dose-response curves. Protein expression of ERCC1 was evaluated with In-Cell Western analysis. Pearson correlation coefficient was used to show the association between ERCC1 expression and in vitro drug response. Result: Increased ERCC1 expression was significantly associated with cisplatin resistance in the 13 immortalized NSCLC cell lines (r=−0.72, p=0.004). A similar trend was observed across 30 primary cultures of human lung cancers, but the association did not reach the level of significance (r=−0.22, p=0.24). Conclusion: Clinical observation of a negative correlation between ERCC1 expression level and improved survival benefit from cisplatin-based chemotherapy was mirrored by in vitro ChemoFx® DRM analysis with strong correlation in immortalized human NSCLC cell lines and in primary cultures from human lung cancers with a correlation trend. This result suggests the value of in vitro chemoresponse assay in identification and evaluation of biomarkers and their association with chemotherapeutic response. The less significant correlation in human lung cancer primary cultures indicated that ERCC1 alone may not be sufficient for clinical prediction of response in human lung cancers across different pathological subtypes and stages, and additional biomarkers may be involved. These results suggest the value of in vitro chemo response assay, in helping to determine cisplatin response in human lung cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4114. doi:10.1158/1538-7445.AM2011-4114

Abstract 2618: Identification of multidrug response genes by meta-analysis based on ChemoFx® in human breast cancer cell lines

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC The success of chemotherapeutic agents to treat various forms of cancer has a long history. Unfortunately, a major cause of treatment failure is drug resistance to currently available chemotherapy agents. Understanding the mechanism of resistance to multiple drugs has been a subject of considerable interest. ChemoFx® holds the promise of not only determining which patient will respond to what therapy but also can be used to learn more about drug resistance while acting as a proxy to clinical outcome. In this study, we used the ChemoFx® to identify response vs. non-response to seven different chemotherapeutic agents (paclitaxel, docetaxel, epirubicin, doxorubicin, gemcitabine, fluorouracil, cyclophosphamide) in 28 human breast cancer cell lines. Based on publically available gene expression profiles of these breast cancer cell lines and the ChemoFx® results, differentially expressed (DE) genes related to multi-drug response were identified through meta-analysis method. Five hundred thirty six DE genes were identified to be related to multidrug response at the false discovery rate of 0.05. To segregate the effect of ER status, we also performed meta-analysis within ER positive or ER negative breast cancer cell lines separately. Thirty seven DE genes were identified related to multiple drug response in ER negative breast cancer cell lines and 20 DE genes in ER positive cell lines. Among all these DE genes, only one is in common between ER positive and ER negative groups. These results suggest that multi-drug resistance is the result of not just one gene but the contribution of multiple genes. In addition, gene set enrichment analysis showed that multidrug response genes are involved in different biological processes in ER positive vs. ER negative cell lines. The dissimilarity of multidrug response genes in ER positive vs. ER negative shows the value of integrating multidrug response gene information with clinical factors to identify patients who are unlikely to benefit from current chemotherapeutic drugs. Moreover, understanding the mechanisms of multidrug response has the potential of identifying new therapeutic targets. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2618.

Abstract P2-09-10: Feasibility Assessment of Pharmacogenomic Predictors Developed from Breast Cancer Cell Lines To Predict Breast Cancer Patient Pathological Response in Neoadjuvant Chemotherapy

Background: Studies of developing pharmacogenomic predictors from cancer cell lines to predict cancer patient clinical response and outcome to chemotherapy have yielded both positive and negative results. The variability in these results may arise from the noise inherent of microarray technology as well as the small sample size of in cell line studies. Therefore, it is greatly needed to evaluate the feasibility of using cell lines to develop pharmacogenomic predictors of patient pathological response. Material and Methods: Thirty breast cancer cell lines were exposed to 10 concentrations of paclitaxel-5-fluorouracil-doxorubicin-cyclophosphamide (TFAC) to measure in vitro chemosensitivity. Two independent and publicly available microarray datasets (Hoeflich and Neve) on these breast cancer cell lines together with the chemosensitivity results were used to identify pharmacogenomic predictors from each dataset. Two independent clinical trials (Hess and Popovici) with publically available data, having 130 and 100 patients respectively, were used as test sets to validate the accuracy of the pharmacogenomic predictors. All patients received TFAC as neoadjuvant therapy and the gene expression profiles of patients were assessed before receiving chemotherapy treatment. The patient9s pathological complete response (pCR) was determined after treatment to evaluate the chemotherapy efficacy. The pharmacogenomic predictors developed from each of the cell line studies were evaluated for their ability to predict patient pCR in each of the clinical trials using the supervised principle component regression method. Results: The pharmacogenomic predictors identified from the Hoeflich and Neve cell line data (training sets) predicted pCR of the patients in the two clinical trials (test sets) with 64%-68% accuracy, 70%-87% sensitivity, and 60%-67% specificity when 100 genes were selected as pharmacogenomic predictors (Table 1). Conclusions: The four independent prediction results generated in this study demonstrate the feasibility of using breast cancer cell lines to identify pharmacogenomic predictors of response to chemotherapy treatment for breast cancer patients. Future studies will examine the use of drug responses from primary cultures of patient tumors to develop pharmacogenomic predictors of breast cancer patient responses to chemotherapy treatment. Table 1. Prediction of breast cancer patients’ pCR by pharmacogenomic predictors derived from breast cancer cell lines. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-09-10.

Abstract P3-08-02: Pharmacogenomic Predictors of Patient Response to Chemotherapy Derived from Breast Cancer Cell Lines Combining Knowledge-Based and Data-Driven Methods

Background: Responses of breast cancer patients to chemotherapy treatments vary considerably, and population treatment response rates remain low. To improve patient outcomes, genomic profiles have been used to identify patients who would benefit from specific treatments. Several studies have used cancer cell lines to develop pharmacogenomic predictors by identifying genes associated with drug response. However, pharmacogenomic predictors derived by this data-driven approach may not readily elucidate the underlying mechanisms associated with drug responses, because the identified predictors by computational methods may not directly associate with drug responses considering the complex genetic regulatory network. To overcome this issue, we proposed a strategy to integrate data-driven methods with biological knowledge-based approaches to identify genomic predictors. We then applied this approach to breast cancer cell lines to identify genomic predictors of paclitaxel-5-fluorouracil-doxorubicin-cyclophosphamide (TFAC), the identified predictors are then evaluated by their ability to predict the clinical outcome of the breast cancer patients who are treated by TFAC. Material: Thirty immortalized breast cancer cell lines were exposed to various concentrations of TFAC using a chemosensitivity assay. Area under the dose-response curves was calculated to measure chemoresponses. Gene expression profiles of the 30 cell lines, the expression profiles as well as the pathologic complete response (pCR) information of 133 breast cancer patients treated by TFAC were publicly available. Methods: We performed pathway enrichment analysis in breast cancer cell lines to assess the association between drug response and curated gene sets predefined by molecular signature database. Pathways with p-value less than 0.01 were considered enriched. The genes from the enriched pathways whose expression values were highly correlated with drug sensitivity were selected as the pharmacogenomic predictors. To validate these predictors, the performances of their prediction for patients’ pCR were evaluated using principle component regression method. Results: Using pathway enrichment analysis, 17 pathways were identified to be related to TFAC drug response. These pathways are related to different biological functions, including breast cancer ER status and BRCA type, immune response, differentiation, and drug response. Using supervised principal component regression, 59 genes involved in at least one of these 17 pathways were selected as genomic predictors. The prediction accuracy of patient pCR was 0.70, sensitivity was 0.71, and specificity was 0.70. Conclusion: By combining knowledge-based and data-driven methods, we have identified 59 genes from breast cancer cell lines as pharmacogenomic predictors of drug response to TFAC. These results support the viability of using breast cancer cell lines to predict breast cancer patient response to chemotherapy. Further functional study of these pharmacogenomic predictors will extend our understanding of individual drug response and facilitate personalized treatment. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P3-08-02.

Prediction of Response to Paclitaxel by ChemoFx assay Correlates with Estrogen Receptor Status and Changes in Apoptosis Pathway in Human Breast Cancers.

Background: Paclitaxel belongs to the taxane family of therapeutics, which have emerged as critically important drugs for breast cancer treatment. In addition to inhibiting cell growth by interfering with microtubule disassembly, its mechanism of action also includes induction of apoptosis. Recent studies suggest that besides being a key predictor for endocrine therapy response, Estrogen Receptor (ER) status also influences sensitivity of breast cancer to paclitaxel, with ER negative tumors being more responsive to the drug. Methods: The ChemoFx live cell chemoresponse assay was performed on 25 breast cancer cell lines (10 ER+ and 15 ER-). These cells were treated with a range of 10 doses of paclitaxel for 72 hours before DAPI staining of nuclei and counting. AUC (Area Under Curve) values were calculated and additional statistical analysis was performed on the resulting dose-response curves. Differential gene expression analysis was conducted to compare ER+ (n=82) and ER- (n=51) breast cancer patients using a public Microarray database. In addition, 2 of the 25 breast cancer cell lines, T47D (ER+) and SKBR3 (ER-), were treated with paclitaxel, lysed, and analyzed with Western blotting to detect cleaved caspase-3 and cleaved PARP expression, with beta-actin employed as a normal control. Results : The ChemoFx assay results revealed that none of the ER+ cells were categorized as R (responsive) to paclitaxel, with seven NR (non-responsive) and one IR (intermediate responsive). On the contrary, of the 15 ER- cell lines, three were categorized as R, only four were categorized as NR, and eight were categorized as IR. Statistical analysis suggested that paclitaxel responsiveness based on ChemoFx assay correlates with ER status (Chi-square test, p Conclusions: ER status appears to predict in part, the response of breast cancer cells to paclitaxel as determined by the ChemoFx assay. ER-negative breast cancer cells are more likely to be responsive, which is consistent with established clinical findings. Our assay also distinguishes between NR/IR and R to paclitaxel within the ER- population. Similar ChemoFx assays are being performed on primary cultures from ER+ and ER- breast cancer patient specimens. Results from RNA microarray and Western blot analyses indicate that differences in gene expression in the apoptosis pathway, and in activation of apoptosis pathway, namely changes in expressions of cleaved PARP and cleaved caspase-3 in response to paclitaxel, may explain differences in the responsiveness of ER+ and ER- breast cancers to paclitaxel. This also suggests a potential role of cleaved PARP and cleaved caspase-3 as biomarkers in addition to ER for prediction of paclitaxel responsiveness in breast cancer. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 2028.