Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

By R. Meyers, Jordan G. Bryan, James M. McFarland, B. Weir, Ann E. Sizemore, Han Xu, N. Dharia, Phillip G Montgomery, G. Cowley, S. Pantel and 20 more. Nature Genetics, 2017

1,706 citations recorded by the source corpus.

The CRISPR–Cas9 system has revolutionized gene editing both at single genes and in multiplexed loss-of-function screens, thus enabling precise genome-scale identification of genes essential for proliferation and survival of cancer cells. However, previous studies have reported that a gene-independent antiproliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, thereby leading to false-positive results in copy number–amplified regions. We developed CERES, a computational method to estimate gene-dependency levels from CRISPR–Cas9 essentiality screens while accounting for the copy number–specific effect. In our efforts to define a cancer dependency map, we performed genome-scale CRISPR–Cas9 essentiality screens across 342 cancer cell lines and applied CERES to this data set. We found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sgRNA libraries. We further demonstrate the utility of this collection of screens, after CERES correction, for identifying cancer-type-specific vulnerabilities.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2913fe39492f177f1a571c79b13abca92a25388f

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Citations in the corpus

Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens (2019, neutral): “…that effectively ranks priority targets, exemplified by WRN. Efforts such as ours, and from others(McDonald et al. 2017; Tsherniak et al. 2017; Meyers et al. 2017; Hart et al. 2015; Wang et al. 2017), to build a compendium of fitness genes, and the identification of context specific…”
Genome-wide Programmable Transcriptional Memory by CRISPR-based Epigenome Editing (2021, methodology): “We then analyzed the phenotypes for common essential genes that are required for cell proliferation or survival in most cancer cell lines (Meyers et al., 2017).”
Quantitative Proteomics of the Cancer Cell Line Encyclopedia (2020, neutral): “Several complexes shared edges with correlation networks built from CRISPR (Meyers et al., 2017) and shRNA sensitivity data (McDonald et al.”
Targeted protein degradation: expanding the toolbox (2019, background): “recommended threshold below which a gene is considered essential is −1 (reF.(61)).”
The BioGRID interaction database: 2019 update (2018, background): “Curators thus capture details on original scoring schemes and analytical methods, which currently include BAGEL (78), CasTLE (79), CERES (80), MAGeCK (81), RANKS (82) and others.”