Identifying chemogenetic interactions from CRISPR screens with drugZ

• Published in: Genome medicine Vol. 11; no. 1; pp. 52 - 12
• Main Authors: Colic, Medina, Wang, Gang, Zimmermann, Michal, Mascall, Keith, McLaughlin, Megan, Bertolet, Lori, Lenoir, W. Frank, Moffat, Jason, Angers, Stephane, Durocher, Daniel, Hart, Traver
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 22.08.2019; BioMed Central; BMC
• Subjects: Algorithms; Analysis; Anopheles; Cells (Biology); Chemogenetic interactions; Clustered Regularly Interspaced Short Palindromic Repeats; Computer programs; Criminal investigation; CRISPR; CRISPR screens; CRISPR-Cas Systems; Deoxyribonucleic acid; DNA; DNA damage; DNA repair; Drug Discovery - methods; Drug efficacy; Drug interactions; Drug resistance; Gene mutation; Genes; Genetic Predisposition to Disease; Genomes; Genomics; Humans; Hypothesis testing; Mutation; Novels; Open source software; Pharmacogenetics - methods; Pharmacogenomic Variants; Poly(ADP-ribose) polymerase; Software; Standard deviation; Synthetic lethality; Temozolomide; Tumor suppressor genes; Tumors; Canada; CRISPR screens; Synthetic lethality; Drug resistance; Chemogenetic interactions
• ISSN: 1756-994X; 1756-994X
• DOI: 10.1186/s13073-019-0665-3

Chemogenetic profiling enables the identification of gene mutations that enhance or suppress the activity of chemical compounds. This knowledge provides insights into drug mechanism of action, genetic vulnerabilities, and resistance mechanisms, all of which may help stratify patient populations and improve drug efficacy. CRISPR-based screening enables sensitive detection of drug-gene interactions directly in human cells, but until recently has primarily been used to screen only for resistance mechanisms. We present drugZ, an algorithm for identifying both synergistic and suppressor chemogenetic interactions from CRISPR screens. DrugZ identifies synthetic lethal interactions between PARP inhibitors and both known and novel members of the DNA damage repair pathway, confirms KEAP1 loss as a resistance factor for ERK inhibitors in oncogenic KRAS backgrounds, and defines the genetic context for temozolomide activity. DrugZ is an open-source Python software for the analysis of genome-scale drug modifier screens. The software accurately identifies genetic perturbations that enhance or suppress drug activity. Interestingly, analysis of new and previously published data reveals tumor suppressor genes are drug-agnostic resistance genes in drug modifier screens. The software is available at github.com/hart-lab/drugz .