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Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains.

ABSTRACT: CRISPR-Cas9 genome editing technology holds great promise for discovering therapeutic targets in cancer and other diseases. Current screening strategies target CRISPR-Cas9-induced mutations to the 5' exons of candidate genes, but this approach often produces in-frame variants that retain functionality, which can obscure even strong genetic dependencies. Here we overcome this limitation by targeting CRISPR-Cas9 mutagenesis to exons encoding functional protein domains. This generates a higher proportion of null mutations and substantially increases the potency of negative selection. We also show that the magnitude of negative selection can be used to infer the functional importance of individual protein domains of interest. A screen of 192 chromatin regulatory domains in murine acute myeloid leukemia cells identifies six known drug targets and 19 additional dependencies. A broader application of this approach may allow comprehensive identification of protein domains that sustain cancer cells and are suitable for drug targeting.

SUBMITTER: Shi J

PROVIDER: S-EPMC4529991 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains.

Shi Junwei J Wang Eric E Milazzo Joseph P JP Wang Zihua Z Kinney Justin B JB Vakoc Christopher R CR

Nature biotechnology 20150511 6

CRISPR-Cas9 genome editing technology holds great promise for discovering therapeutic targets in cancer and other diseases. Current screening strategies target CRISPR-Cas9-induced mutations to the 5' exons of candidate genes, but this approach often produces in-frame variants that retain functionality, which can obscure even strong genetic dependencies. Here we overcome this limitation by targeting CRISPR-Cas9 mutagenesis to exons encoding functional protein domains. This generates a higher prop ...[more]

PMID: 25961408

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Project description:BackgroundLarge-scale genetic screening using CRISPR-Cas9 technology has emerged as a powerful approach to uncover and validate gene functions. The ability to control the timing of genetic perturbation during CRISPR screens will facilitate precise dissection of dynamic and complex biological processes. Here, we report the optimization of a drug-inducible CRISPR-Cas9 system that allows high-throughput gene interrogation with a temporal control.ResultsWe designed multiple drug-inducible sgRNA expression vectors and measured their activities using an EGFP gene disruption assay in 11 human and mouse cell lines. The optimal design allows for a tight and inducible control of gene knockout in vitro, and in vivo during a seven-week-long experiment following hematopoietic reconstitution in mice. We next performed parallel genome-wide loss-of-function screens using the inducible and constitutive CRISPR-Cas9 systems. In proliferation-based dropout screens, these two approaches have similar performance in discriminating essential and nonessential genes. In a more challenging phenotypic assay that requires cytokine stimulation and cell staining, we observed similar sensitivity of the constitutive and drug-induced screening approaches in detecting known hits. Importantly, we demonstrate minimal leakiness of our inducible CRISPR screening platforms in the absence of chemical inducers in large-scale settings.ConclusionsIn this study, we have developed a drug-inducible CRISPR-Cas9 system that shows high cleavage efficiency upon induction but low background activity. Using this system, we have achieved inducible gene disruption in a wide range of cell types both in vitro and in vivo. For the first time, we present a systematic side-by-side comparison of constitutive and drug-inducible CRISPR-Cas9 platforms in large-scale functional screens. We demonstrate the tightness and efficiency of our drug-inducible CRISPR-Cas9 system in genome-wide pooled screening. Our design increases the versatility of CRISPR-based genetic screening and represents a significant upgrade on existing functional genomics toolbox.

Project description:The majority of cancers are driven by multiple genetic alterations, but how these changes collaborate during tumorigenesis remains largely unknown. To gain mechanistic insights into tumor-promoting genetic interactions among tumor suppressor genes (TSG), we conducted combinatorial CRISPR screening coupled with single-cell transcriptomic profiling in human mammary epithelial cells. As expected, different driver gene alterations in mammary epithelial cells influenced the repertoire of tumor suppressor alterations capable of inducing tumor formation. More surprisingly, TSG interaction networks were comprised of numerous cliques-sets of three or four genes such that each TSG within the clique showed oncogenic cooperation with all other genes in the clique. Genetic interaction profiling indicated that the predominant cooperating TSGs shared overlapping functions rather than distinct or complementary functions. Single-cell transcriptomic profiling of CRISPR double knockouts revealed that cooperating TSGs that synergized in promoting tumorigenesis and growth factor independence showed transcriptional epistasis, whereas noncooperating TSGs did not. These epistatic transcriptional changes, both buffering and synergistic, affected expression of oncogenic mediators and therapeutic targets, including CDK4, SRPK1, and DNMT1. Importantly, the epistatic expression alterations caused by dual inactivation of TSGs in this system, such as PTEN and TP53, were also observed in patient tumors, establishing the relevance of these findings to human breast cancer. An estimated 50% of differentially expressed genes in breast cancer are controlled by epistatic interactions. Overall, our study indicates that transcriptional epistasis is a central aspect of multigenic breast cancer progression and outlines methodologies to uncover driver gene epistatic networks in other human cancers. SIGNIFICANCE: This study provides a roadmap for moving beyond discovery and development of therapeutic strategies based on single driver gene analysis to discovery based on interactions between multiple driver genes.See related commentary by Fong et al., p. 6078.

Dataset Information

Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains.

Publications

Discovery of cancer drug targets by CRISPR-Cas9 screening of protein domains.

Similar Datasets

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