Abstract

Cancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and, as a side effect, create new vulnerabilities for potential therapeutic exploitation. To systematically identify genotype-dependent vulnerabilities and synthetic lethal interactions, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework that integrates CRISPR/Cas9 screens originating from many different libraries and laboratories to build genetic interaction maps. It builds on analytical approaches that were established for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cell lines combining functional data with information on genetic variants to explore the relationships of more than 2.1 million gene-background relationships. In addition to known dependencies, our analysis identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities associated with aberrant Wnt/{beta}-catenin signaling identified GANAB and PRKCSH as new positive regulators of Wnt/{beta}-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data is included.