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A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization.

Created on 13 Jan 2024

Authors

Clare Pacini, Emma Duncan, Emanuel Gonçalves, James Gilbert, Shriram Bhosle, Stuart Horswell, Emre Karakoc, Howard Lightfoot, Ed Curry, Francesc Muyas, Monsif Bouaboula, Chandra Sekhar Pedamallu, Isidro Cortes-Ciriano, Fiona M Behan, Lykourgos-Panagiotis Zalmas, Andrew Barthorpe, Hayley Francies, Steve Rowley, Jack Pollard, Pedro Beltrao, Leopold Parts, Francesco Iorio, Mathew J Garnett

Published in

Cancer cell. Jan 03, 2024. Epub Jan 03, 2024.

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.

PMID:
38215750
Bibliographic data and abstract were imported from PubMed on 13 Jan 2024.

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