A Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy

作者：Srivas Rohith; Shen John Paul; Yang Chih Cheng; Sun Su Ming; Li Jianfeng; Gross Andrew M; Jensen James; Licon Katherine; Bojorquez Gomez Ana; Klepper Kristin; Huang Justin; Pekin Daniel; Xu Jia L; Yeerna Huwate; Sivaganesh Vignesh; Kollenstart Leonie; van Attikum Haico; Aza Blanc Pedro; Sobol Robert W; Ideker Trey

来源：Molecular Cell, 2016, 63(3): 514-525.

DOI：10.1016/j.molcel.2016.06.022

An emerging therapeutic strategy for cancer is to induce selective lethality in a tumor by exploiting interactions between its driving mutations and specific drug targets. Here we use a multi-species approach to develop a resource of synthetic lethal interactions relevant to cancer therapy. First, we screen in yeast similar to 169,000 potential interactions among orthologs of human tumor suppressor genes (TSG) and genes encoding drug targets across multiple genotoxic environments. Guided by the strongest signal, we evaluate thousands of TSG-drug combinations in HeLa cells, resulting in networks of conserved synthetic lethal interactions. Analysis of these networks reveals that interaction stability across environments and shared gene function increase the likelihood of observing an interaction in human cancer cells. Using these rules, we prioritize similar to 10(5) human TSG-drug combinations for future follow-up. We validate interactions based on cell and/or patient survival, including topoisomerases with RAD17 and checkpoint kinases with BLM.

• 出版日期2016-8-4