Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality.
Journal:
Molecular cancer
PMID:
34454516
Abstract
BACKGROUND: Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells. CRISPR viability screens have been widely employed to identify cancer vulnerabilities. However, an approach to systematically infer genetic interactions from viability screens is missing.