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

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• CRISPR-Cas9 gene editing enables genome-scale screens to identify essential genes in cancer cells.
• Cas9-mediated DNA cleavage can cause gene-independent antiproliferative effects, leading to false positives in essentiality screens, especially in copy number-amplified regions.

Purpose of the Study:

• To develop a computational method, CERES, to accurately estimate gene dependency from CRISPR-Cas9 screens by accounting for copy number effects.
• To create a comprehensive cancer dependency map using genome-scale CRISPR-Cas9 essentiality screens.

Main Methods:

• Development of the CERES computational method to correct for copy number-specific effects in CRISPR-Cas9 essentiality screens.
• Performance of genome-scale CRISPR-Cas9 essentiality screens across 342 cancer cell lines.
• Application of CERES to analyze both new and existing CRISPR-Cas9 screen datasets.

Main Results:

• CERES effectively reduced false-positive results in CRISPR-Cas9 essentiality screens.
• The method accurately estimated single-guide RNA (sgRNA) activity across different sgRNA libraries and datasets.
• The corrected dataset facilitated the identification of cancer-type-specific vulnerabilities.

Conclusions:

• CERES provides a more accurate assessment of gene essentiality in cancer cells by mitigating Cas9-induced artifacts.
• The cancer dependency map generated using CERES offers a valuable resource for discovering novel cancer-specific therapeutic targets.