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Functional genomics approaches can overcome limitations-such as the lack of identification of robust targets and poor clinical efficacy-that hamper cancer drug development. Here we performed genome-scale CRISPR-Cas9 screens in 324 human cancer cell lines from 30 cancer types and developed a data-driven framework to prioritize candidates for cancer therapeutics. We integrated cell fitness effects with genomic biomarkers and target tractability for drug development to systematically prioritize new targets in defined tissues and genotypes. We verified one of our most promising dependencies, the Werner syndrome ATP-dependent helicase, as a synthetic lethal target in tumours from multiple cancer types with microsatellite instability. Our analysis provides a resource of cancer dependencies, generates a framework to prioritize cancer drug targets and suggests specific new targets. The principles described in this study can inform the initial stages of drug development by contributing to a new, diverse and more effective portfolio of cancer drug targets.
The molecular features of a patient's tumour influence clinical responses and can be used to guide therapy, leading to more effective treatments and reduced toxicity1. However, most patients do not benefit from such targeted therapies in part owing to a limited knowledge of candidate targets2. Lack of efficacy is a leading cause of the 90% attrition rate in the development of cancer drugs, and fewer molecular entities to new targets are being developed3. Unbiased strategies that effectively identify and prioritize targets in tumours could expand the range of targets, improve success rates and accelerate the development of new cancer therapies.
CRISPR-Cas9 screens that use libraries of single-guide RNAs (sgRNAs) have been used to study gene function and their role in cellular fitness4,5. CRISPR-Cas9-based genome editing provides high specificity and produces penetrant phenotypes as null alleles can be generated. Here we present genome-scale CRISPR-Cas9 fitness screens in 324 cancer cell lines and an integrative analysis that enables the prioritization of candidate cancer therapeutic targets (Fig. 1a), which we illustrate through the identification of Werner syndrome ATPdependent helicase (WRN) as a target for tumours with microsatellite instability (MSI).
Genome-scale CRISPR-Cas9 screens in cancer cell lines
To comprehensively catalogue genes that are required for cancer cell fitness (defined as genes required for cell growth or viability), we performed 941 CRISPR-Cas9 fitness screens in 339 cancer cell lines, targeting...