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

• DOI: 10.1016/j.molcel.2016.06.022
• Publication Date: 2016-07-21T23:20:41Z
• Authors: Rohith Srivas; John Paul Shen; Chih Cheng Yang; Su Ming Sun; Jianfeng Li; Andrew M. Gross; James Jensen; Katherine Licon; Ana Bojorquez-Gomez; Kristin Klepper; Justin Huang; Daniel Pekin; Jia L. Xu; Huwate Yeerna; Vignesh Sivaganesh; Leonie Kollenstart; Haico van Attikum; Pedro Aza-Blanc; Robert W. Sobol; Trey Ideker
• Keywords: Synthetic Lethality; HeLa; Interaction network; Cancer Therapy

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 ∼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 ∼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.