Gene expression profiling of breast tumor cell lines to predict for therapeutic response to microtubule-stabilizing agents

Abstract

Microtubule-targeting agents, including taxanes (Tax) and ixabepilone (Ixa), are important components of modern breast cancer chemotherapy regimens, but no molecular parameter is currently available that can predict for their efficiency. We sought to develop pharmacogenomic predictors of Tax- and Ixa-response from a large panel of human breast tumor cell lines (BTCL), then to evaluate their performance in clinical samples. Thirty-two BTCL, representative of the molecular diversity of breast cancers (BC), were treated in vitro with Tax (paclitaxel (Pac), docetaxel (Doc)), and ixabepilone (Ixa), then classified as drug-sensitive or resistant according to their 50% inhibitory concentrations (IC50s). Baseline gene expression data were obtained using Affymetrix U133 Plus 2.0 human oligonucleotide microarrays. Gene expression set (GES) predictors of response to taxanes were derived, then tested for validation internally and in publicly available gene expression datasets. In vitro IC50s of Pac and Doc were almost identical, whereas some Tax-resistant BTCL retained sensitivity to Ixa. GES predictors for Tax-sensitivity (333 genes) and Ixa-sensitivity (79 genes) were defined. They displayed a limited number of overlapping genes. Both were validated by leave-n-out cross-validation (n = 4; for overall accuracy (OA), P = 0.028 for Tax, and P = 0.0005 for Ixa). The GES predictor of Tax-sensitivity was tested on publicly available external datasets and significantly predicted Pac-sensitivity in 16 BTCL (P = 0.04 for OA), and pathological complete response to Pac-based neoadjuvant chemotherapy in BC patients (P = 0.0045 for OA). Applying Tax and Ixa-GES to a dataset of clinically annotated early BC patients identified subsets of tumors with potentially distinct phenotypes of drug sensitivity: predicted Ixa-sensitive/Tax-resistant BC were significantly (P < 0.05, Fischer's exact test) more frequently ER/PR-positive, Ki67-negative, and luminal subtype than predicted Ixa-resistant/Tax-sensitive BC. Genomic predictors for Tax- and Ixa-sensitivity can be derived from BTCL and may be helpful for better selecting cytotoxic treatment in BC patients.

Ixabepilone Administered Weekly or Every Three Weeks in HER2-Negative Metastatic Breast Cancer Patients; A Randomized Non-Comparative Phase II Trial

“…Sample size and consistency with respect to breast cancer molecular subtypes, as well as treatment setting may have accounted for this discrepancy. In support to the present findings, however, ER positive breast cancer cell lines were ixabepilone sensitive, while MAPT mRNA expression was not included in gene expression sets predictive of ixabepilone response in a very recent study [47]. Evidently, the issue of MAPT expression levels with respect to ixabepilone efficiency needs further clarification.…”

Drug Resistance and the Role of Combination Chemotherapy in Improving Patient Outcomes

“…Large-scale pharmacogenomic analyses are underway to identify additional molecular markers potentially capable of distinguishing tumors with differential sensitivities to taxanes and ixabepilone. A recent study was successful in deriving genomic predictors for taxane and ixabepilone sensitivity from breast tumor cell lines [45]. …”

Paclitaxel Response Can Be Predicted With Interpretable Multi-Variate Classifiers Exploiting DNA-Methylation and miRNA Data

“…Precision oncology requires predictors to guide the optimization of drug therapies for patients (Peck, 2016; Schwartzberg et al, 2017). Indeed, it is now well-established that gene polymorphisms and other genomic alterations play important roles in the observed heterogeneous response to drugs (Wang et al, 2011;Harper and Topol, 2012; Kadra et al, 2012). This has led to the identification of clinical biomarkers of drug response from molecular profiles of the patients’ tumors (Huang et al, 2014).…”