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.

Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean. We found predictive models for 426 dependencies (55%) by nonlinear regression modeling considering 66,646 molecular features. Many dependencies fall into a limited number of classes, and unexpectedly, in 82% of models, the top biomarkers were expression based. We demonstrated the basis behind one such predictive model linking hypermethylation of the UBB ubiquitin gene to a dependency on UBC. Together, these observations provide a foundation for a cancer dependency map that facilitates the prioritization of therapeutic targets.

Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas. We present an expression-based variant-impact phenotyping (eVIP) method that uses gene expression changes to distinguish impactful from neutral somatic mutations. eVIP identified 69% of mutations analyzed as impactful and 31% as functionally neutral. A subset of the impactful mutations induces xenograft tumor formation in mice and/or confers resistance to cellular EGFR inhibition. Among these impactful variants are rare somatic, clinically actionable variants including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and multiple BRAF variants, demonstrating that rare mutations can be functionally important in cancer.

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyze data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger Institutes. Despite significant differences in experimental protocols and reagents, we find that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one data set are recovered in the other. Through further analysis and replication experiments at each institute, we show that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.

Drug resistance represents a major challenge to achieving durable responses to cancer therapeutics. Resistance mechanisms to epigenetically targeted drugs remain largely unexplored. We used bromodomain and extra-terminal domain (BET) inhibition in neuroblastoma as a prototype to model resistance to chromatin modulatory therapeutics. Genome-scale, pooled lentiviral open reading frame (ORF) and CRISPR knockout rescue screens nominated the phosphatidylinositol 3-kinase (PI3K) pathway as promoting resistance to BET inhibition. Transcriptomic and chromatin profiling of resistant cells revealed that global enhancer remodeling is associated with upregulation of receptor tyrosine kinases (RTKs), activation of PI3K signaling, and vulnerability to RTK/PI3K inhibition. Large-scale combinatorial screening with BET inhibitors identified PI3K inhibitors among the most synergistic upfront combinations. These studies provide a roadmap to elucidate resistance to epigenetic-targeted therapeutics and inform efficacious combination therapies.

Cas9 is commonly introduced into cell lines to enable CRISPR-Cas9-mediated genome editing. Here, we studied the genetic and transcriptional consequences of Cas9 expression itself. Gene expression profiling of 165 pairs of human cancer cell lines and their Cas9-expressing derivatives revealed upregulation of the p53 pathway upon introduction of Cas9, specifically in wild-type TP53 (TP53-WT) cell lines. This was confirmed at the messenger RNA and protein levels. Moreover, elevated levels of DNA repair were observed in Cas9-expressing cell lines. Genetic characterization of 42 cell line pairs showed that introduction of Cas9 can lead to the emergence and expansion of p53-inactivating mutations. This was confirmed by competition experiments in isogenic TP53-WT and TP53-null (TP53-/-) cell lines. Lastly, Cas9 was less active in TP53-WT than in TP53-mutant cell lines, and Cas9-induced p53 pathway activation affected cellular sensitivity to both genetic and chemical perturbations. These findings may have broad implications for the proper use of CRISPR-Cas9-mediated genome editing.