Development of a polygenic score predicting drug resistance and patient outcome in breast cancer

Abstract

Gene expression profiles of hundreds of cancer cell-lines and the cell-lines’ response to drug treatment were analyzed to identify genes whose expression correlated with drug resistance. In the GDSC dataset of 809 cancer cell lines, expression of 36 genes were associated with drug resistance (increased IC50) to many anti-cancer drugs. This was validated in the CTRP dataset of 860 cell lines. A polygenic score derived from the correlation coefficients of the 36 genes in cancer cell lines, UAB36, predicted resistance of cell lines to Tamoxifen. Although the 36 genes were selected from cell line behaviors, UAB36 successfully predicted survival of breast cancer patients in three different cohorts of patients treated with Tamoxifen. UAB36 outperforms two existing predictive gene signatures and is a predictor of outcome of breast cancer patients independent of the known clinical co-variates that affect outcome. This approach should provide promising polygenic biomarkers for resistance in many cancer types against specific drugs.