RESUMO
Although single-gene perturbation screens have revealed a number of new targets, vulnerabilities specific to frequently altered drivers have not been uncovered. An important question is whether the compensatory relationship between functionally redundant genes masks potential therapeutic targets in single-gene perturbation studies. To identify digenic dependencies, we developed a CRISPR paralog targeting library to investigate the viability effects of disrupting 3,284 genes, 5,065 paralog pairs and 815 paralog families. We identified that dual inactivation of DUSP4 and DUSP6 selectively impairs growth in NRAS and BRAF mutant cells through the hyperactivation of MAPK signaling. Furthermore, cells resistant to MAPK pathway therapeutics become cross-sensitized to DUSP4 and DUSP6 perturbations such that the mechanisms of resistance to the inhibitors reinforce this mechanism of vulnerability. Together, multigene perturbation technologies unveil previously unrecognized digenic vulnerabilities that may be leveraged as new therapeutic targets in cancer.
Assuntos
Fosfatase 6 de Especificidade Dupla/genética , Fosfatases de Especificidade Dupla/genética , Sistema de Sinalização das MAP Quinases , Fosfatases da Proteína Quinase Ativada por Mitógeno/genética , Neoplasias/genética , Linhagem Celular Tumoral , Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Ativação Enzimática , GTP Fosfo-Hidrolases/genética , Técnicas de Inativação de Genes , Humanos , Melanoma Experimental/genética , Melanoma Experimental/terapia , Proteínas de Membrana/genética , Neoplasias/enzimologia , Neoplasias/metabolismo , Neoplasias/terapia , Proteínas Proto-Oncogênicas B-raf/genéticaRESUMO
Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.