SETDB1 suppresses NK cell-mediated immunosurveillance in acute myeloid leukemia with granulo-monocytic differentiation.

Monocytic acute myeloid leukemia (AML) responds poorly to current treatments, including venetoclax-based therapy. We conducted in vivo and in vitro CRISPR-Cas9 library screenings using a mouse monocytic AML model and identified SETDB1 and its binding partners (ATF7IP and TRIM33) as crucial tumor promoters in vivo. The growth-inhibitory effect of Setdb1 depletion in vivo is dependent mainly on natural killer (NK) cell-mediated cytotoxicity. Mechanistically, SETDB1 depletion upregulates interferon-stimulated genes and NKG2D ligands through the demethylation of histone H3 Lys9 at the enhancer regions, thereby enhancing their immunogenicity to NK cells and intrinsic apoptosis. Importantly, these effects are not observed in non-monocytic leukemia cells. We also identified the expression of myeloid cell nuclear differentiation antigen (MNDA) and its murine counterpart Ifi203 as biomarkers to predict the sensitivity of AML to SETDB1 depletion. Our study highlights the critical and selective role of SETDB1 in AML with granulo-monocytic differentiation and underscores its potential as a therapeutic target for current unmet needs.

The methyltransferase domain of DNMT1 is an essential domain in acute myeloid leukemia independent of DNMT3A mutation.

Aberrant DNA methylation patterns are a prominent feature of cancer. Methylation of DNA is mediated by the DNA methyltransferase (DNMT) protein family, which regulates de novo (DNMT3A and DNMT3B) and maintenance (DNMT1) methylation. Mutations in DNMT3A are observed in approximately 22% of acute myeloid leukemia (AML). We hypothesized that DNMT1 or DNMT3B could function as a synthetic lethal therapeutic strategy for DNMT3A-mutant AML. CRISPR-Cas9 tiling screens were performed to identify functional domains within DNMT1/DNMT3B that exhibited greater dependencies in DNMT3A mutant versus wild-type cell lines. Although increased sensitivity to DNMT1 mutation was observed in some DNMT3A mutant cellular models tested, the subtlety of these results prevents us from basing any conclusions on a synthetic lethal relationship between DNMT1 and DNMT3A. Our data suggests that a therapeutic window for DNMT1 methyltransferase inhibition in DNMT3A-driven AML may exist, but validation in more biologically relevant models is required.

Small-Molecule and CRISPR Screening Converge to Reveal Receptor Tyrosine Kinase Dependencies in Pediatric Rhabdoid Tumors.

Cancer is often seen as a disease of mutations and chromosomal abnormalities. However, some cancers, including pediatric rhabdoid tumors (RTs), lack recurrent alterations targetable by current drugs and need alternative, informed therapeutic options. To nominate potential targets, we performed a high-throughput small-molecule screen complemented by a genome-scale CRISPR-Cas9 gene-knockout screen in a large number of RT and control cell lines. These approaches converged to reveal several receptor tyrosine kinases (RTKs) as therapeutic targets, with RTK inhibition effective in suppressing RT cell growth in vitro and against a xenograft model in vivo. RT cell lines highly express and activate (phosphorylate) different RTKs, creating dependency without mutation or amplification. Downstream of RTK signaling, we identified PTPN11, encoding the pro-growth signaling protein SHP2, as a shared dependency across all RT cell lines. This study demonstrates that large-scale perturbational screening can uncover vulnerabilities in cancers with "quiet" genomes.

Next-generation characterization of the Cancer Cell Line Encyclopedia.

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.

Small-molecule targeting of brachyury transcription factor addiction in chordoma.

Chordoma is a primary bone cancer with no approved therapy1. The identification of therapeutic targets in this disease has been challenging due to the infrequent occurrence of clinically actionable somatic mutations in chordoma tumors2,3. Here we describe the discovery of therapeutically targetable chordoma dependencies via genome-scale CRISPR-Cas9 screening and focused small-molecule sensitivity profiling. These systematic approaches reveal that the developmental transcription factor T (brachyury; TBXT) is the top selectively essential gene in chordoma, and that transcriptional cyclin-dependent kinase (CDK) inhibitors targeting CDK7/12/13 and CDK9 potently suppress chordoma cell proliferation. In other cancer types, transcriptional CDK inhibitors have been observed to downregulate highly expressed, enhancer-associated oncogenic transcription factors4,5. In chordoma, we find that T is associated with a 1.5-Mb region containing 'super-enhancers' and is the most highly expressed super-enhancer-associated transcription factor. Notably, transcriptional CDK inhibition leads to preferential and concentration-dependent downregulation of cellular brachyury protein levels in all models tested. In vivo, CDK7/12/13-inhibitor treatment substantially reduces tumor growth. Together, these data demonstrate small-molecule targeting of brachyury transcription factor addiction in chordoma, identify a mechanism of T gene regulation that underlies this therapeutic strategy, and provide a blueprint for applying systematic genetic and chemical screening approaches to discover vulnerabilities in genomically quiet cancers.

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states.

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.

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.

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.

We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens. This study also demonstrates the value of releasing pre-publication data publicly to engage the community in an open research collaboration.

Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States.

The systematic sequencing of the cancer genome has led to the identification of numerous genetic alterations in cancer. However, a deeper understanding of the functional consequences of these alterations is necessary to guide appropriate therapeutic strategies. Here, we describe Onco-GPS (OncoGenic Positioning System), a data-driven analysis framework to organize individual tumor samples with shared oncogenic alterations onto a reference map defined by their underlying cellular states. We applied the methodology to the RAS pathway and identified nine distinct components that reflect transcriptional activities downstream of RAS and defined several functional states associated with patterns of transcriptional component activation that associates with genomic hallmarks and response to genetic and pharmacological perturbations. These results show that the Onco-GPS is an effective approach to explore the complex landscape of oncogenic cellular states across cancers, and an analytic framework to summarize knowledge, establish relationships, and generate more effective disease models for research or as part of individualized precision medicine paradigms.

Defining a Cancer Dependency Map.

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.

PRMT1-Mediated Translation Regulation Is a Crucial Vulnerability of Cancer.

Through an shRNA screen, we identified the protein arginine methyltransferase Prmt1 as a vulnerable intervention point in murine p53/Rb-null osteosarcomas, the human counterpart of which lacks effective therapeutic options. Depletion of Prmt1 in p53-deficient cells impaired tumor initiation and maintenance in vitro and in vivo Mechanistic studies reveal that translation-associated pathways were enriched for Prmt1 downstream targets, implicating Prmt1 in translation control. In particular, loss of Prmt1 led to a decrease in arginine methylation of the translation initiation complex, thereby disrupting its assembly and inhibiting translation. p53/Rb-null cells were sensitive to p53-induced translation stress, and analysis of human cancer cell line data from Project Achilles further revealed that Prmt1 and translation-associated pathways converged on the same functional networks. We propose that targeted therapy against Prmt1 and its associated translation-related pathways offer a mechanistic rationale for treatment of osteosarcomas and other cancers that exhibit dependencies on translation stress response. Cancer Res; 77(17); 4613-25. ©2017 AACR.

PIK3CA mutant tumors depend on oxoglutarate dehydrogenase.

Oncogenic PIK3CA mutations are found in a significant fraction of human cancers, but therapeutic inhibition of PI3K has only shown limited success in clinical trials. To understand how mutant PIK3CA contributes to cancer cell proliferation, we used genome scale loss-of-function screening in a large number of genomically annotated cancer cell lines. As expected, we found that PIK3CA mutant cancer cells require PIK3CA but also require the expression of the TCA cycle enzyme 2-oxoglutarate dehydrogenase (OGDH). To understand the relationship between oncogenic PIK3CA and OGDH function, we interrogated metabolic requirements and found an increased reliance on glucose metabolism to sustain PIK3CA mutant cell proliferation. Functional metabolic studies revealed that OGDH suppression increased levels of the metabolite 2-oxoglutarate (2OG). We found that this increase in 2OG levels, either by OGDH suppression or exogenous 2OG treatment, resulted in aspartate depletion that was specifically manifested as auxotrophy within PIK3CA mutant cells. Reduced levels of aspartate deregulated the malate-aspartate shuttle, which is important for cytoplasmic NAD+ regeneration that sustains rapid glucose breakdown through glycolysis. Consequently, because PIK3CA mutant cells exhibit a profound reliance on glucose metabolism, malate-aspartate shuttle deregulation leads to a specific proliferative block due to the inability to maintain NAD+/NADH homeostasis. Together these observations define a precise metabolic vulnerability imposed by a recurrently mutated oncogene.

Copy-number and gene dependency analysis reveals partial copy loss of wild-type SF3B1 as a novel cancer vulnerability.

Genomic instability is a hallmark of human cancer, and results in widespread somatic copy number alterations. We used a genome-scale shRNA viability screen in human cancer cell lines to systematically identify genes that are essential in the context of particular copy-number alterations (copy-number associated gene dependencies). The most enriched class of copy-number associated gene dependencies was CYCLOPS (Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS) genes, and spliceosome components were the most prevalent. One of these, the pre-mRNA splicing factor SF3B1, is also frequently mutated in cancer. We validated SF3B1 as a CYCLOPS gene and found that human cancer cells harboring partial SF3B1 copy-loss lack a reservoir of SF3b complex that protects cells with normal SF3B1 copy number from cell death upon partial SF3B1 suppression. These data provide a catalog of copy-number associated gene dependencies and identify partial copy-loss of wild-type SF3B1 as a novel, non-driver cancer gene dependency.

The EMT regulator ZEB2 is a novel dependency of human and murine acute myeloid leukemia.

Acute myeloid leukemia (AML) is a heterogeneous disease with complex molecular pathophysiology. To systematically characterize AML's genetic dependencies, we conducted genome-scale short hairpin RNA screens in 17 AML cell lines and analyzed dependencies relative to parallel screens in 199 cell lines of other cancer types. We identified 353 genes specifically required for AML cell proliferation. To validate the in vivo relevance of genetic dependencies observed in human cell lines, we performed a secondary screen in a syngeneic murine AML model driven by the MLL-AF9 oncogenic fusion protein. Integrating the results of these interference RNA screens and additional gene expression data, we identified the transcription factor ZEB2 as a novel AML dependency. ZEB2 depletion impaired the proliferation of both human and mouse AML cells and resulted in aberrant differentiation of human AML cells. Mechanistically, we showed that ZEB2 transcriptionally represses genes that regulate myeloid differentiation, including genes involved in cell adhesion and migration. In addition, we found that epigenetic silencing of the miR-200 family microRNAs affects ZEB2 expression. Our results extend the role of ZEB2 beyond regulating epithelial-mesenchymal transition (EMT) and establish ZEB2 as a novel regulator of AML proliferation and differentiation.

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.

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of ß-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.

High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines.

Hundreds of genetically characterized cell lines are available for the discovery of genotype-specific cancer vulnerabilities. However, screening large numbers of compounds against large numbers of cell lines is currently impractical, and such experiments are often difficult to control. Here we report a method called PRISM that allows pooled screening of mixtures of cancer cell lines by labeling each cell line with 24-nucleotide barcodes. PRISM revealed the expected patterns of cell killing seen in conventional (unpooled) assays. In a screen of 102 cell lines across 8,400 compounds, PRISM led to the identification of BRD-7880 as a potent and highly specific inhibitor of aurora kinases B and C. Cell line pools also efficiently formed tumors as xenografts, and PRISM recapitulated the expected pattern of erlotinib sensitivity in vivo.

MTAP deletion confers enhanced dependency on the PRMT5 arginine methyltransferase in cancer cells.

The discovery of cancer dependencies has the potential to inform therapeutic strategies and to identify putative drug targets. Integrating data from comprehensive genomic profiling of cancer cell lines and from functional characterization of cancer cell dependencies, we discovered that loss of the enzyme methylthioadenosine phosphorylase (MTAP) confers a selective dependence on protein arginine methyltransferase 5 (PRMT5) and its binding partner WDR77. MTAP is frequently lost due to its proximity to the commonly deleted tumor suppressor gene, CDKN2A. We observed increased intracellular concentrations of methylthioadenosine (MTA, the metabolite cleaved by MTAP) in cells harboring MTAP deletions. Furthermore, MTA specifically inhibited PRMT5 enzymatic activity. Administration of either MTA or a small-molecule PRMT5 inhibitor showed a modest preferential impairment of cell viability for MTAP-null cancer cell lines compared with isogenic MTAP-expressing counterparts. Together, our findings reveal PRMT5 as a potential vulnerability across multiple cancer lineages augmented by a common "passenger" genomic alteration.

Identification of an "Exceptional Responder" Cell Line to MEK1 Inhibition: Clinical Implications for MEK-Targeted Therapy.

UNLABELLED: The identification of somatic genetic alterations that confer sensitivity to pharmacologic inhibitors has led to new cancer therapies. To identify mutations that confer an exceptional dependency, shRNA-based loss-of-function data were analyzed from a dataset of numerous cell lines to reveal genes that are essential in a small subset of cancer cell lines. Once these cell lines were determined, detailed genomic characterization from these cell lines was utilized to ascertain the genomic aberrations that led to this extreme dependency. This method, in a large subset of lung cancer cell lines, yielded a single lung adenocarcinoma cell line, NCI-H1437, which is sensitive to RNA interference of MAP2K1 expression. Notably, NCI-H1437 is the only lung cancer cell line included in the dataset with a known activating mutation in MAP2K1 (Q56P). Subsequent validation using shRNA and CRISPR-Cas9 confirmed MAP2K1 dependency. In vitro and in vivo inhibitor studies established that NCI-H1437 cells are sensitive to MEK1 inhibitors, including the FDA-approved drug trametinib. Like NCI-H1437 cells, the MAP2K1-mutant cell lines SNU-C1 (colon) and OCUM-1 (gastric) showed decreased viability after MAP2K1 depletion via Cas9-mediated gene editing. Similarly, these cell lines were particularly sensitive to trametinib treatment compared with control cell lines. On the basis of these data, cancers that harbor driver mutations in MAP2K1 could benefit from treatment with MEK1 inhibitors. Furthermore, this functional data mining approach provides a general method to experimentally test genomic features that confer dependence in tumors. IMPLICATIONS: Cancers with an activated RAS/MAPK pathway driven by oncogenic MAP2K1 mutations may be particularly sensitive to MEK1 inhibitor treatments.