Journal Article

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

Boehm, Jesse S., Hahn, William C., McFarland, James M., Vazquez, Francisca, Tsherniak, Aviad, Root, David E., Golub, Todd R., Krill-Burger, J. Michael, Borah, Ashir A., Paolella, Brenton R., Dempster, Joshua M.

2023

Overview

Background Hundreds of functional genomic screens have been performed across a diverse set of cancer contexts, as part of efforts such as the Cancer Dependency Map, to identify gene dependencies—genes whose loss of function reduces cell viability or fitness. Recently, large-scale screening efforts have shifted from RNAi to CRISPR-Cas9, due to superior efficacy and specificity. However, many effective oncology drugs only partially inhibit their protein targets, leading us to question whether partial suppression of genes using RNAi could reveal cancer vulnerabilities that are missed by complete knockout using CRISPR-Cas9. Here, we compare CRISPR-Cas9 and RNAi dependency profiles of genes across approximately 400 matched cancer cell lines. Results We find that CRISPR screens accurately identify more gene dependencies per cell line, but the majority of each cell line’s dependencies are part of a set of 1867 genes that are shared dependencies across the entire collection (pan-lethals). While RNAi knockdown of about 30% of these genes is also pan-lethal, approximately 50% have selective dependency patterns across cell lines, suggesting they could still be cancer vulnerabilities. The accuracy of the unique RNAi selectivity is supported by associations to multi-omics profiles, drug sensitivity, and other expected co-dependencies. Conclusions Incorporating RNAi data for genes that are pan-lethal knockouts facilitates the discovery of a wider range of gene targets than could be detected using the CRISPR dataset alone. This can aid in the interpretation of contrasting results obtained from CRISPR and RNAi screens and reinforce the importance of partial gene suppression methods in building a cancer dependency map.

• Publisher: BioMed Central,Springer Nature B.V,BMC
• Subject: Animal Genetics and Genomics / Bioinformatics / Biomedical and Life Sciences / Cancer / Cancer genomics / cell lines / Cell viability / CRISPR / CRISPR-Cas systems / CRISPR-Cas9 genome editing / data collection / Datasets / drugs / Evolutionary Biology / Experiments / Functional genomics / Genes / Genomes / genomics / Human Genetics / Life Sciences / Microbial Genetics and Genomics / multiomics / Mutation / neoplasm cells / Plant Genetics and Genomics / Reagents / RNA-mediated interference / RNAi / Target identification / Tumor cell lines