Discovery of genetic interactions in cancer

Division Of Basic Sciences - Nci

Investigators

Linked publications & trials

Abstract

A main focus in cancer research is on studying a few hundred cancer driver genes, to identify 'actionable' mutations that can be targeted therapeutically. Complementing this approach, my lab has focused in recent years on studying the value of genetic interactions (GIs) between genes across the whole genome to advance cancer research and treatment. This approach has been motivated by recent work in our lab and others showing that (i) genetic interactions between genes are critical in tumor development and drug response, and that (ii) such interactions can be computationally identified by analyzing large-scale genomics and patient data. This work encompasses several types of genetic interactions (GI) that are relevant to cancer therapeutics, including Synthetic Lethal (SL) interactions, Synthetic Dosage Lethal (SDL) interactions and Synthetic Rescue (SR) interactions. Based on the tools we have developed for the data-driven identification of all three types of GI networks from large cohorts of tumor samples, we have shown that the cancer GIs identified can be successfully used for a variety of important challenges including: (a) Generating the first clinically-derived pan-cancer SL and SDL networks, we show that these networks can successfully predict the response of cancer patients to many widely used drug treatments, offering a complementary approach to existing mutation-based methods for precision-based cancer therapy. (b) Aiming to fight resistance to cancer therapy, we have identified genome-wide pancancer SR networks, which are predictive of patients' drug response and resistance to the majority of current cancer drugs.