8 research outputs found

    Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions.

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    We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies

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

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    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 among genes mutated in cancer, including tumor suppressor genes (TSG) and druggable genes. First, we screen in yeast ~169,000 potential interactions amongst TSG orthologs 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
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