Identification of predictive markers to differentiate ixabepilone from paclitaxel activity in ER-negative breast cancer patients

Song Wu, Scott D. Chasalow, H. Lee, Lei Xu, Betsy Paul, O. Mokliatchouk, W. Fraser Symmans, Kim E. Zerba, Lajos Pusztai, Ed Clark

Journal of Clinical Oncology · 2007 · 11 citations · 0 references

Concepts

Abstract

2525 Background: Ixabepilone (BMS-247550) is a microtubule stabilizing agent with demonstrable therapeutic value in taxane- refractory breast cancer (BC) patients. Biomarkers to predict either ixabepilone or paclitaxel activity in BC patients have previously been reported. However, markers that differentiate response to the two agents have yet to be identified. This study sought to discover predictive markers that will enable patient selection to differentially enhance response to ixabepilone or paclitaxel in ER-negative (ER-) patients. Materials and Methodologies: Pre-treatment gene expression profiles were generated for 62 ER- patients treated with ixabepilone in clinical study CA163080, and 51 ER- patients treated with T/FAC (paclitaxel and fluorouracil-doxorubicin-cyclophosphamide) in clinical study MDA133. Biomarkers differentially predictive of complete pathological response in breast were identified through gene set enrichment analysis (GSEA) or classification by threshold gradient descent (TGD). Gene knockdown by siRNA was used to study some of these candidate markers. Results: Four candidate models that differentiate response to ixabepilone treatment and taxane-containing therapy were identified. Two of the models, found by GSEA, are based on expression levels for single microtubule-related genes: transforming, acidic coiled-coil containing protein 3 (TACC3) and chromosome condensation protein G (HCAP-G). The potential of HCAP-G as a differential marker was supported by siRNA studies. Two of the models, found by TGD, are based on expression levels for 26 and 20 genes. Areas under the ROC curves for the models applied to each study separately are given in the table . Conclusions: We have identified four predictive models that differentiate response in a clinical trial of ixabepilone from that in a trial of T/FAC. A clinical trial is under way to further evaluate their utility for differentiating response to ixabepilone- and taxane-containing regimens. [Table: see text] [Table: see text]