Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens.

Functional genomics approaches can overcome limitations-such as the lack of identification of robust targets and poor clinical efficacy-that hamper cancer drug development. Here we performed genome-scale CRISPR-Cas9 screens in 324 human cancer cell lines from 30 cancer types and developed a data-driven framework to prioritize candidates for cancer therapeutics. We integrated cell fitness effects with genomic biomarkers and target tractability for drug development to systematically prioritize new targets in defined tissues and genotypes. We verified one of our most promising dependencies, the Werner syndrome ATP-dependent helicase, as a synthetic lethal target in tumours from multiple cancer types with microsatellite instability. Our analysis provides a resource of cancer dependencies, generates a framework to prioritize cancer drug targets and suggests specific new targets. The principles described in this study can inform the initial stages of drug development by contributing to a new, diverse and more effective portfolio of cancer drug targets.

Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets.

CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR-Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets.

JACKS: joint analysis of CRISPR/Cas9 knockout screens.

Genome-wide CRISPR/Cas9 knockout screens are revolutionizing mammalian functional genomics. However, their range of applications remains limited by signal variability from different guide RNAs that target the same gene, which confounds gene effect estimation and dictates large experiment sizes. To address this problem, we report JACKS, a Bayesian method that jointly analyzes screens performed with the same guide RNA library. Modeling the variable guide efficacies greatly improves hit identification over processing a single screen at a time and outperforms existing methods. This more efficient analysis gives additional hits and allows designing libraries with a 2.5-fold reduction in required cell numbers without sacrificing performance compared to current analysis standards.

Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens.

Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism-of-action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti-cancer drugs with genome-wide CRISPR loss-of-function screens in 484 cell lines to systematically investigate cellular drug mechanism-of-action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein-protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin-protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on-target and off-target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss-of-fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss-of-function screens can elucidate mechanism-of-action to advance drug development.

Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.

BACKGROUND: Genome editing by CRISPR-Cas9 technology allows large-scale screening of gene essentiality in cancer. A confounding factor when interpreting CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes within copy number amplified regions of the genome. We have developed the computational tool CRISPRcleanR which is capable of identifying and correcting gene-independent responses to CRISPR-Cas9 targeting. CRISPRcleanR uses an unsupervised approach based on the segmentation of single-guide RNA fold change values across the genome, without making any assumption about the copy number status of the targeted genes. RESULTS: Applying our method to existing and newly generated genome-wide essentiality profiles from 15 cancer cell lines, we demonstrate that CRISPRcleanR reduces false positives when calling essential genes, correcting biases within and outside of amplified regions, while maintaining true positive rates. Established cancer dependencies and essentiality signals of amplified cancer driver genes are detectable post-correction. CRISPRcleanR reports sgRNA fold changes and normalised read counts, is therefore compatible with downstream analysis tools, and works with multiple sgRNA libraries. CONCLUSIONS: CRISPRcleanR is a versatile open-source tool for the analysis of CRISPR-Cas9 knockout screens to identify essential genes.

Benchmark Software and Data for Evaluating CRISPR-Cas9 Experimental Pipelines Through the Assessment of a Calibration Screen.

Genome-wide genetic screens using CRISPR-guide RNA libraries are widely performed in mammalian cells to functionally characterize individual genes and for the discovery of new anticancer therapeutic targets. As the effectiveness of such powerful and precise tools for cancer pharmacogenomics is emerging, tools and methods for their quality assessment are becoming increasingly necessary. Here, we provide an R package and a high-quality reference data set for the assessment of novel experimental pipelines through which a single calibration experiment has been executed: a screen of the HT-29 human colorectal cancer cell line with a commercially available genome-wide library of single-guide RNAs. This package and data allow experimental researchers to benchmark their screens and produce a quality-control report, encompassing several quality and validation metrics. The R code used for processing the reference data set, for its quality assessment, as well as to evaluate the quality of a user-provided screen, and to reproduce the figures presented in this article is available at https://github.com/DepMap-Analytics/HT29benchmark. The reference data is publicly available on FigShare.

A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization.

Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

Minimal genome-wide human CRISPR-Cas9 library.

CRISPR guide RNA libraries have been iteratively improved to provide increasingly efficient reagents, although their large size is a barrier for many applications. We design an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9) by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other CRISPR-Cas9 libraries while preserving assay sensitivity and specificity. MinLibCas9 provides backward compatibility with existing datasets, increases the dynamic range of CRISPR-Cas9 screens and extends their application to complex models and assays.

Combinatorial CRISPR screen identifies fitness effects of gene paralogues.

Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. Our studies reveal the fitness effects of FAM50A/FAM50B in cancer cells.

An integrative genomic approach in oesophageal cells identifies TRB3 as a bile acid responsive gene, downregulated in Barrett's oesophagus, which regulates NF-kappaB activation and cytokine levels.

Reflux of gastroduodenal contents and consequent inflammatory responses are associated with the development of Barrett's oesophagus (BO) and the promotion of oesophageal adenocarcinoma (OAC). Deregulation of inflammatory processes is a hallmark of oesophageal cancer. In this study, we aimed to investigate (i) the transcriptional responses to deoxycholic acid (DCA) in cell lines representative of either end of the oesophageal cancer sequence, (ii) the expression of DCA-regulated genes in data charting oesophageal carcinogenesis and (iii) the impact of these genes on oesophageal inflammatory signalling. Gene expression microarrays were utilized to demonstrate differential transcriptional responses between squamous (HET-1A) and adenomatous (SKGT4) cell lines exposed to DCA. Differential basal and DCA-inducible expression of cytokines such as interleukin (IL) 8 was observed between both cell types. A cohort of DCA-regulated genes specific to each cell type was identified in microarray experimentation and subsequently validated. Cell type-specific genes included TRB3, CXCL14, GDF15 and LIF in HET-1A cells, with COX2-, ESM1-, URHF1- and IL1alpha-and IL1beta-specific expression in SKGT4 cells. Over 30% of the genes altered in BO and OAC were shown to be regulated by DCA utilizing an integrative genomic approach. One such gene, tribbles-homology-3 (TRB3) was induced specifically in HET-1A cells, absent in SKGT4 cells and decreased in BO samples in silico and in vivo. Inhibition and re-introduction of TRB3 in HET-1A and SKGT4 cells, respectively, demonstrated the ability of TRB3 to regulate inflammatory signalling through nuclear factor-kappaB. This study identifies mechanisms through which bile acids such as DCA, in conjunction with the loss of key signalling molecules, could regulate oesophageal metaplasticity.

Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway.

New therapeutic targets for oral squamous cell carcinoma (OSCC) are urgently needed. We conducted genome-wide CRISPR-Cas9 screens in 21 OSCC cell lines, primarily derived from Asians, to identify genetic vulnerabilities that can be explored as therapeutic targets. We identify known and novel fitness genes and demonstrate that many previously identified OSCC-related cancer genes are non-essential and could have limited therapeutic value, while other fitness genes warrant further investigation for their potential as therapeutic targets. We validate a distinctive dependency on YAP1 and WWTR1 of the Hippo pathway, where the lost-of-fitness effect of one paralog can be compensated only in a subset of lines. We also discover that OSCCs with WWTR1 dependency signature are significantly associated with biomarkers of favorable response toward immunotherapy. In summary, we have delineated the genetic vulnerabilities of OSCC, enabling the prioritization of therapeutic targets for further exploration, including the targeting of YAP1 and WWTR1.

Many types of cancer now have 'targeted treatments', which specifically home in on genes cancer cells rely on for survival. But there are very few of these treatments available for the most common type of mouth cancer, oral squamous cell carcinoma, which around 350,000 people are diagnosed with each year. Designing targeted treatments relies on detailed knowledge of the genetic makeup of the cancer cells. But, little is known about which genes drive oral squamous cell carcinoma, especially among patients living in Asia, which is where over half of yearly cases are diagnosed. One way to resolve this is to use gene editing technology to find the genes that the cancer cells need to survive. Now, Chai et al. have used a gene editing tool known as CRISPR to examine 21 cell lines from patients diagnosed with oral squamous cell carcinoma. Most of these lines were from Asian patients, some of whom had a history of chewing betel quid which increases the risk of mouth cancer. By individually inactivating genes in these cell lines one by one, Chai et al. were able to identify 918 genes linked to the survival of the cancer cells. Some of these genes have already been associated with the spread of other types of cancer, whereas others are completely unique to oral squamous cell carcinoma. The screen also discovered that some cell lines could not survive without genes involved in a signalling pathway called Hippo, which is known to contribute to the progression of many other types of cancer. Uncovering the genes associated with oral squamous cell carcinoma opens the way for the development of new targeted treatments. Targeted therapies already exist for some of the genes identified in this study, and it may be possible to repurpose them as a treatment for this widespread mouth cancer. But, given that different cell lines relied on different genes to survive, the next step will be to identify which genes to inactivate in each patient.

Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

BACKGROUND: CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. RESULTS: Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene-independent manner. In contrast, amplifications caused by whole chromosomal duplication have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. CONCLUSION: Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening.

Many gene fusions are reported in tumours and for most their role remains unknown. As fusions are used for diagnostic and prognostic purposes, and are targets for treatment, it is crucial to assess their function in cancer. To systematically investigate the role of fusions in tumour cell fitness, we utilized RNA-sequencing data from 1011 human cancer cell lines to functionally link 8354 fusion events with genomic data, sensitivity to >350 anti-cancer drugs and CRISPR-Cas9 loss-of-fitness effects. Established clinically-relevant fusions were identified. Overall, detection of functional fusions was rare, including those involving cancer driver genes, suggesting that many fusions are dispensable for tumour fitness. Therapeutically actionable fusions involving RAF1, BRD4 and ROS1 were verified in new histologies. In addition, recurrent YAP1-MAML2 fusions were identified as activators of Hippo-pathway signaling in multiple cancer types. Our approach discriminates functional fusions, identifying new drivers of carcinogenesis and fusions that could have clinical implications.

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets.

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.

siRNA Library Screening Identifies a Druggable Immune-Signature Driving Esophageal Adenocarcinoma Cell Growth.

BACKGROUND & AIMS: Effective therapeutic approaches are urgently required to tackle the alarmingly poor survival outcomes in esophageal adenocarcinoma (EAC) patients. EAC originates from within the intestinal-type metaplasia, Barrett's esophagus, a condition arising on a background of gastroesophageal reflux disease and associated inflammation. METHODS: This study used a druggable genome small interfering RNA (siRNA) screening library of 6022 siRNAs in conjunction with bioinformatics platforms, genomic studies of EAC tissues, somatic variation data of EAC from The Cancer Genome Atlas data of EAC, and pathologic and functional studies to define novel EAC-associated, and targetable, immune factors. RESULTS: By using a druggable genome library we defined genes that sustain EAC cell growth, which included an unexpected immunologic signature. Integrating Cancer Genome Atlas data with druggable siRNA targets showed a striking concordance and an EAC-specific gene amplification event associated with 7 druggable targets co-encoded at Chr6p21.1. Over-representation of immune pathway-associated genes supporting EAC cell growth included leukemia inhibitory factor, complement component 1, q subcomponent A chain (C1QA), and triggering receptor expressed on myeloid cells 2 (TREM2), which were validated further as targets sharing downstream signaling pathways through genomic and pathologic studies. Finally, targeting the triggering receptor expressed on myeloid cells 2-, C1q-, and leukemia inhibitory factor-activated signaling pathways (TYROBP-spleen tyrosine kinase and JAK-STAT3) with spleen tyrosine kinase and Janus-activated kinase inhibitor fostamatinib R788 triggered EAC cell death, growth arrest, and reduced tumor burden in NOD scid gamma mice. CONCLUSIONS: These data highlight a subset of genes co-identified through siRNA targeting and genomic studies of expression and somatic variation, specifically highlighting the contribution that immune-related factors play in support of EAC development and suggesting their suitability as targets in the treatment of EAC.

The characterization of an intestine-like genomic signature maintained during Barrett's-associated adenocarcinogenesis reveals an NR5A2-mediated promotion of cancer cell survival.

Barrett's oesophagus (BO), an intestinal-type metaplasia (IM), typically arising in conjunction with gastro-oesophageal reflux disease, is a prominent risk factor for the development of oesophageal adenocarcinoma (OAC). The molecular similarities between IM and normal intestinal tissues are ill-defined. Consequently, the contribution of intestine-enriched factors expressed within BO to oncogenesis is unclear. Herein, using transcriptomics we define the intestine-enriched genes expressed in meta-profiles of BO and OAC. Interestingly, 77% of the genes differentially expressed in a meta-profile of BO were similarly expressed in intestinal tissues. Furthermore, 85% of this intestine-like signature was maintained upon transition to OAC. Gene networking analysis of transcription factors within this signature revealed a network centred upon NR5A2, GATA6 and FOXA2, whose over-expression was determined in a cohort of BO and OAC patients. Simulated acid reflux was observed to induce the expression of both NR5A2 and GATA6. Using siRNA-mediated silencing and an NR5A2 antagonist we demonstrate that NR5A2-mediated cancer cell survival is facilitated through augmentation of GATA6 and anti-apoptotic factor BCL-XL levels. Abrogation of NR5A2-GATA6 expression in conjunction with BCL-XL co-silencing resulted in synergistically increased sensitivity to chemotherapeutics and photo-dynamic therapeutics. These findings characterize the intestine-like signature associated with IM which may have important consequences to adenocarcinogenesis.