Molecular features that predict the response to antimetabolite chemotherapies

Abstract

Antimetabolite chemotherapeutic agents that target cellular metabolism are widely used in the clinic and are thought to exert their anti-cancer effects mainly through non-specific cytotoxic effects. However, patients vary dramatically with respect to treatment outcome, and the sources of heterogeneity remain largely unknown. Here, we introduce a computational method for identifying gene expression signatures of response to chemotherapies and apply it to human tumors and cancer cell lines. Furthermore, we characterize a set of 17 antimetabolite agents in various contexts to investigate determinants of sensitivity to these agents. We identify distinct favorable and unfavorable metabolic expression signatures for 5-FU and Gemcitabine. Importantly, we find that metabolic pathways targeted by each of these antimetabolites are specifically enriched in its expression signatures. We provide evidence against the common notion about non-specific cytotoxic functions of antimetabolite drugs. This study demonstrates through unbiased analyses that the activities of metabolic pathways likely contribute to therapeutic response.