Abstract 2034: Personalized chemotherapy regimen selection for breast cancer

Abstract

Despite the rapid progress in personalized cancer therapy (PCT) for breast cancer, no previous studies have used genomic predictors to choose among multiple chemotherapy regimens. It is unclear that given the current regimens how much PCT can improve the response rate for patients who will receive chemotherapy. In this study, we reanalyzed data from published studies of 1111 breast cancer patients who were treated with neoadjuvant chemotherapies. Those patients were divided into three regimen groups: an anthracycline alone, anthracycline plus paclitaxel, and anthracycline plus docetaxel. We developed a new strategy called PRES (Personalized REgimen Selection) to reassign the optimal regimen to each of the patients. First, a variable selection scheme was developed to identify significant genetic predictors for chemotherapy response. The selected genetic variables were then combined with clinical variables to build random forest models to predict the response of a patient to each regimen using pCR (pathological complete response) as the measure of response. The models were used to assign an optimal regimen to each patient to maximize the chance of pCR. We found that the expected rate of pCR was improved from 21.2% to 39.6% (95% CI: 34.6% - 43.0%). We also found that 31.1% of the patients may have been overtreated and 8.2% patients undertreated. A validation study on 21 cell lines showed that our prediction agrees with their paclitaxel-sensitivity profiles. We performed additional analysis on the Cancer Genome Atlas (TCGA) data and found that 18 of the 19 genes identified are significantly differentially expressed between normal and tumor tissues, and 2 of them, TAF6L and METRN (meteorin), are associated with overall survival. In conclusion, PRES could substantially increase response rates for breast cancer patients who will receive one of the widely-accepted chemotherapy regimens at present. Citation Format: Jinfeng Zhang, Kaixian Yu, Qingxiang Amy Sang, Winston Tan, Mayassa B. Dargham, Jun S. Liu, Ty Lively, Cedric Sheffield. Personalized chemotherapy regimen selection for breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2034.