Amy Goodale

Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting

UNLABELLED The CRISPR/Cas9 system enables genome editing and somatic cell genetic screens in mammalian cells. We performed genome-scale loss-of-function screens in 33 cancer cell lines to identify genes essential for proliferation/survival and found a strong correlation between increased gene copy number and decreased cell viability after genome editing. Within regions of copy-number gain, CRISPR/Cas9 targeting of both expressed and unexpressed genes, as well as intergenic loci, led to significantly decreased cell proliferation through induction of a G2 cell-cycle arrest. By examining single-guide RNAs that map to multiple genomic sites, we found that this cell response to CRISPR/Cas9 editing correlated strongly with the number of target loci. These observations indicate that genome targeting by CRISPR/Cas9 elicits a gene-independent antiproliferative cell response. This effect has important practical implications for the interpretation of CRISPR/Cas9 screening data and confounds the use of this technology for the identification of essential genes in amplified regions. SIGNIFICANCE We found that the number of CRISPR/Cas9-induced DNA breaks dictates a gene-independent antiproliferative response in cells. These observations have practical implications for using CRISPR/Cas9 to interrogate cancer gene function and illustrate that cancer cells are highly sensitive to site-specific DNA damage, which may provide a path to novel therapeutic strategies. Cancer Discov; 6(8); 914-29. ©2016 AACR.See related commentary by Sheel and Xue, p. 824See related article by Munoz et al., p. 900This article is highlighted in the In This Issue feature, p. 803.

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

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.

ATXN1L, CIC, and ETS Transcription Factors Modulate Sensitivity to MAPK Pathway Inhibition

Intrinsic resistance and RTK-RAS-MAPK pathway reactivation has limited the effectiveness of MEK and RAF inhibitors (MAPKi) in RAS- and RAF-mutant cancers. To identify genes that modulate sensitivity to MAPKi, we performed genome-scale CRISPR-Cas9 loss-of-function screens in two KRAS mutant pancreatic cancer cell lines treated with the MEK1/2 inhibitor trametinib. Loss of CIC, a transcriptional repressor of ETV1, ETV4, and ETV5, promoted survival in the setting of MAPKi in cancer cells derived from several lineages. ATXN1L deletion, which reduces CIC protein, or ectopic expression of ETV1, ETV4, or ETV5 also modulated sensitivity to trametinib. ATXN1L expression inversely correlates with response to MAPKi inhibition in clinical studies. These observations identify the ATXN1L-CIC-ETS transcription factor axis as a mediator of resistance to MAPKi.

CRISPR-Cas9 screen reveals a MYCN -amplified neuroblastoma dependency on EZH2

Pharmacologically difficult targets, such as MYC transcription factors, represent a major challenge in cancer therapy. For the childhood cancer neuroblastoma, amplification of the oncogene MYCN is associated with high-risk disease and poor prognosis. Here, we deployed genome-scale CRISPR-Cas9 screening of MYCN-amplified neuroblastoma and found a preferential dependency on genes encoding the polycomb repressive complex 2 (PRC2) components EZH2, EED, and SUZ12. Genetic and pharmacological suppression of EZH2 inhibited neuroblastoma growth in vitro and in vivo. Moreover, compared with neuroblastomas without MYCN amplification, MYCN-amplified neuroblastomas expressed higher levels of EZH2. ChIP analysis showed that MYCN binds at the EZH2 promoter, thereby directly driving expression. Transcriptomic and epigenetic analysis, as well as genetic rescue experiments, revealed that EZH2 represses neuronal differentiation in neuroblastoma in a PRC2-dependent manner. Moreover, MYCN-amplified and high-risk primary tumors from patients with neuroblastoma exhibited strong repression of EZH2-regulated genes. Additionally, overexpression of IGFBP3, a direct EZH2 target, suppressed neuroblastoma growth in vitro and in vivo. We further observed strong synergy between histone deacetylase inhibitors and EZH2 inhibitors. Together, these observations demonstrate that MYCN upregulates EZH2, leading to inactivation of a tumor suppressor program in neuroblastoma, and support testing EZH2 inhibitors in patients with MYCN-amplified neuroblastoma.

Up, down, and out: next generation libraries for genome-wide CRISPRa, CRISPRi, and CRISPR-Cas9 knockout genetic screens

Advances in CRISPR-Cas9 technology have enabled the flexible modulation of gene expression at large scale. In particular, the creation of genome-wide libraries for CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) has allowed gene function to be systematically interrogated. Here, we evaluate numerous CRISPRko libraries and show that our recently-described CRISPRko library (Brunello) is more effective than previously published libraries at distinguishing essential and non-essential genes, providing approximately the same perturbation-level performance improvement over GeCKO libraries as GeCKO provided over RNAi. Additionally, we developed genome-wide libraries for CRISPRi (Dolcetto) and CRISPRa (Calabrese). Negative selection screens showed that Dolcetto substantially outperforms existing CRISPRi libraries with fewer sgRNAs per gene and achieves comparable performance to CRISPRko in the detection of gold-standard essential genes. We also conducted positive selection CRISPRa screens and show that Calabrese outperforms the SAM library approach at detecting vemurafenib resistance genes. We further compare CRISPRa to genome-scale libraries of open reading frames (ORFs). Together, these libraries represent a suite of genome-wide tools to efficiently interrogate gene function with multiple modalities.tracr

Mutational processes shape the landscape of TP53 mutations in human cancer

Unlike most tumor suppressor genes, the most common genetic alterations in tumor protein p53 (TP53) are missense mutations1,2. Mutant p53 protein is often abundantly expressed in cancers and specific allelic variants exhibit dominant-negative or gain-of-function activities in experimental models3–8. To gain a systematic view of p53 function, we interrogated loss-of-function screens conducted in hundreds of human cancer cell lines and performed TP53 saturation mutagenesis screens in an isogenic pair of TP53 wild-type and null cell lines. We found that loss or dominant-negative inhibition of wild-type p53 function reliably enhanced cellular fitness. By integrating these data with the Catalog of Somatic Mutations in Cancer (COSMIC) mutational signatures database9,10, we developed a statistical model that describes the TP53 mutational spectrum as a function of the baseline probability of acquiring each mutation and the fitness advantage conferred by attenuation of p53 activity. Collectively, these observations show that widely-acting and tissue-specific mutational processes combine with phenotypic selection to dictate the frequencies of recurrent TP53 mutations.Large-scale loss-of-function screens and TP53 saturation mutagenesis screens in human cancer cell lines suggest that mutational processes combine with phenotypic selection to shape the landscape of somatic mutations at the TP53 locus.

Abstract B39: Genomic copy number alterations introduce a gene-independent viability bias in CRISPR-Cas9 knock-out screens of cancer cell lines

Recent studies have demonstrated the power of CRISPR-Cas9 screening methods for identifying genetic vulnerabilities in cancer cells. As part of a larger effort to generate a comprehensive catalog of vulnerabilities, we performed CRISPR-Cas9 genome-scale loss-of-function screens in 33 cancer cell lines to identify genes essential for proliferation and survival. We found a strong correlation between gene copy number and cell viability after Cas9-targeting. Copy number alterations are extremely prevalent in human cancers and frequently lead to overexpression of driver oncogenes and potential vulnerabilities. Therefore, we sought to identify such genes by investigating the relationship of genomic copy number with essentiality from our screening data. As expected, known oncogenes scored as essential in cell lines harboring amplifications of these genes. However, the scores of all other genes in these amplified regions were also strongly enriched for apparent essentiality, even among unexpressed genes. Furthermore, the infection of cells with sgRNAs targeting Cas9 to non-coding intergenic sequences within regions of high copy number gain also induced this negative effect on cell viability. We observed this effect across multiple different chromosomal structural alterations, including tandem duplications, breakage-fusion-bridge structures, and arm-level gains. More broadly, we found a striking global correlation between cell viability in response to Cas9-targeting and the genomic copy number of the targeted site, even among low-level copy number gain and loss. For example, Cas9-targeting of genes with two copies resulted in, on average, decreased viability relative to Cas9-targeting of genes with only one copy. By examining sgRNAs that target multiple genomic sites, but not within any amplified loci, we found that this cell response to Cas9-targeting correlated strongly with the total number of target sites. Together, these observations indicate that genome targeting by CRISPR-Cas9 elicits a gene-independent anti-proliferative cell response with a severity proportional to the total number of discrete genomic loci targeted. This effect has important practical implications for interpretation of CRISPR-Cas9 screening data and confounds the use of this technology for identification of essential genes in amplified regions. This result illustrates the sensitivity of cancer cells to site-specific DNA damage, which may provide a path to novel therapeutic strategies. Targeting non-essential genes or non-coding intergenic sequences within regions of copy number amplification may reveal cancer-specific vulnerabilities. Citation Format: Robin M. Meyers, Andrew J. Aguirre, Barbara A. Weir, Francisca Vazquez, Cheng-Zhong Zhang, Uri Ben-David, April Cook, Gavin Ha, William F. Harrington, Mihir Doshi, Stanley Gill, Han Xu, Levi D. Ali, Guozhi Jiang, Sasha Pantel, Yenarae Lee, Amy Goodale, Andrew D. Cherniack, Coyin Oh, Gregory Kryukov, Glenn S. Cowley, Levi A. Garraway, Kimberly Stegmaier, Charles W. Roberts, Todd R. Golub, Matthew Meyerson, David E. Root, Aviad Tsherniak, William C. Hahn. Genomic copy number alterations introduce a gene-independent viability bias in CRISPR-Cas9 knock-out screens of cancer cell lines. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr B39.

Abstract PR02: Towards a Cancer Dependency Map

The mapping of cancer genomes is rapidly approaching completion. The genomic information encoded by individual patients9 tumors should, in principle, provide a guide for predicting acquired cancer dependencies. Unfortunately, while the success of precision cancer genomics hinges on the decoding of such dependencies, we lack the ability to predict dependencies for most individual tumors. The challenge stems from the absence of clinical data relating genotypes with dependencies since most cancer mutations are rare and our arsenal of cancer drugs is incomplete. A comprehensive Cancer Dependency Map comprised of a catalog of genetic and small molecule vulnerabilities across a diverse set of cancers, along with robust statistical models able to predict these vulnerabilities from molecular and genomic features, would provide a roadmap of targets ripe for therapeutic development and would help reveal the mechanisms underlying the emergence of these vulnerabilities. Here, we report progress in creating a Cancer Dependency Map consisting of the following components: 1) Systematic genetic perturbation (RNAi/CRISPR) of over 600 cancer cell models representing a wide range of human cancers and cell lineages using massively parallel genome scale loss-of-function screens. 2) Computational segregation of on- from off-target effects of RNAi enabling the discovery of outlier dependencies. 3) Predictive modeling to discover biomarkers for each dependency. Our results demonstrate that our analytical approach (DEMETER) that models both gene and miRNA-based seed sequence effects effectively segregates on- from off-target effects of shRNAs. We discover 768 preferential dependencies whose suppression decreases viability at a level greater than six standard deviations in at least one of 503 cancer models and 105 such dependencies each present in at least 15 models. We find that 95% of the cancer models screened are strongly sensitive to the suppression of at least one of these dependencies, and that many models have common dependencies so that all models harbor at least one six-sigma dependency out of a set of only 76. Using a custom random forest based predictive modeling framework (ATLANTIS), we discover predictive biomarkers for hundreds of dependencies. These include known and novel vulnerabilities specified by somatic oncogenic alterations, overexpression of genes that specify lineage and differentiation, copy-number driven essentiality, and loss of functionally redundant paralogs. These observations provide a rigorous computational and experimental foundation for the creation of a comprehensive Cancer Dependency Map. Subsampling and projection analyses suggest that over 10,000 genomically characterized cancer cell models will be needed to achieve this important goal. This abstract is also being presented as Poster B43. Citation Format: Aviad Tsherniak, Francisca Vazquez, Barbara Weir, Philip Montgomery, Glenn Cowley, Stanley Gill, Gregory Kryukov, Sasha Pantel, Will Harrington, Mike Burger, Robin Meyers, Levi Ali, Amy Goodale, Yenarae Lee, Levi Garraway, Jesse Boehm, David Root, Todd Golub, William Hahn. Towards a Cancer Dependency Map. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr PR02.