Integrated cross-study datasets of genetic dependencies in cancer

Clare Pacini,Andrew Barthorpe,James M Mcfarland,Dieudonne Van Der Meer,Aviad Tsherniak,Patricia Jaaks,Mathew J Garnett,Emanuel Gonçalves,Isabella Boyle,Howard Lightfoot,Francesco Iorio,Hanna Najgebauer,Joshua M Dempster,Emre Karakoc

doi:10.1038/s41467-021-21898-7

Abstract

CRISPR-Cas9 viability screens are increasingly performed at a genome-wide scale across large panels of cell lines to identify new therapeutic targets for precision cancer therapy. Integrating the datasets resulting from these studies is necessary to adequately represent the heterogeneity of human cancers and to assemble a comprehensive map of cancer genetic vulnerabilities. Here, we integrated the two largest public independent CRISPR-Cas9 screens performed to date (at the Broad and Sanger institutes) by assessing, comparing, and selecting methods for correcting biases due to heterogeneous single-guide RNA efficiency, gene-independent responses to CRISPR-Cas9 targeting originated from copy number alterations, and experimental batch effects. Our integrated datasets recapitulate findings from the individual datasets, provide greater statistical power to cancer- and subtype-specific analyses, unveil additional biomarkers of gene dependency, and improve the detection of common essential genes. We provide the largest integrated resources of CRISPR-Cas9 screens to date and the basis for harmonizing existing and future functional genetics datasets.

Highlights

CRISPR-Cas[9] viability screens are increasingly performed at a genome-wide scale across large panels of cell lines to identify new therapeutic targets for precision cancer therapy
We have previously shown that the pan-cancer CRISPR-Cas[9] datasets independently generated at the Broad and Sanger institutes are consistent on the domain of 147 commonly screened cell lines[16]
We evaluated the ability of the CERES processed integrated dataset to predict common essential genes and its performance when compared to the individual datasets and two existing sets of common essential genes from recent publications: Behan[2] and Hart[35]

Summary

Introduction

CRISPR-Cas[9] viability screens are increasingly performed at a genome-wide scale across large panels of cell lines to identify new therapeutic targets for precision cancer therapy. In order to identify and prioritize new potential therapeutic targets for precision cancer therapy, analyses of cancer vulnerabilities are increasingly performed at a genome-wide scale and across large panels of in vitro cancer models[2,3,4,5,6,7,8,9,10,11] This has been facilitated by recent advances in genome editing technologies allowing unprecedented precision and scale via CRISPR-Cas[9] screens. The integration of these two datasets will be key for the DepMap and other projects aiming at systematically probing cancer dependencies These integrated datasets will provide a more comprehensive representation of heterogeneous cancer types and form the basis for the development of effective new therapies with associated biomarkers for patient stratification[15]. We estimate the minimal size (in terms of the number of screened cell lines) required in order to effectively correct batch effects when integrating a new dataset

Methods

Results

Conclusion