A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization
Clare Pacini, Emma L. Duncan, Emanuel Gonçalves, James Gilbert, Shriram G. Bhosle, Stuart Horswell, Emre Karakoç, Howard Lightfoot, Edward Curry, Francesc Muyas, Monsif Bouaboula, Chandra Sekhar Pedamallu, Isidro Cortés‐Ciriano, Fiona M. Behan, Lykourgos‐Panagiotis Zalmas, Andrew Barthorpe, Hayley E. Francies, Steve Rowley, Jack Pollard, Pedro Beltrão, Leopold Parts, Francesco Iorio, Mathew J. Garnett
Abstract
Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.