RPL22 is a tumor suppressor in MSI-high cancers and a splicing regulator of MDM4.

Microsatellite instability-high (MSI-H) tumors are malignant tumors that, despite harboring a high mutational burden, often have intact TP53. One of the most frequent mutations in MSI-H tumors is a frameshift mutation in RPL22, a ribosomal protein. Here, we identified RPL22 as a modulator of MDM4 splicing through an alternative splicing switch in exon 6. RPL22 loss increases MDM4 exon 6 inclusion and cell proliferation and augments resistance to the MDM inhibitor Nutlin-3a. RPL22 represses the expression of its paralog, RPL22L1, by mediating the splicing of a cryptic exon corresponding to a truncated transcript. Therefore, damaging mutations in RPL22 drive oncogenic MDM4 induction and reveal a common splicing circuit in MSI-H tumors that may inform therapeutic targeting of the MDM4-p53 axis and oncogenic RPL22L1 induction.

A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data.

BACKGROUND: CRISPR-Cas9 dropout screens are formidable tools for investigating biology with unprecedented precision and scale. However, biases in data lead to potential confounding effects on interpretation and compromise overall quality. The activity of Cas9 is influenced by structural features of the target site, including copy number amplifications (CN bias). More worryingly, proximal targeted loci tend to generate similar gene-independent responses to CRISPR-Cas9 targeting (proximity bias), possibly due to Cas9-induced whole chromosome-arm truncations or other genomic structural features and different chromatin accessibility levels. RESULTS: We benchmarked eight computational methods, rigorously evaluating their ability to reduce both CN and proximity bias in the two largest publicly available cell-line-based CRISPR-Cas9 screens to date. We also evaluated the capability of each method to preserve data quality and heterogeneity by assessing the extent to which the processed data allows accurate detection of true positive essential genes, established oncogenetic addictions, and known/novel biomarkers of cancer dependency. Our analysis sheds light on the ability of each method to correct biases under different scenarios. AC-Chronos outperforms other methods in correcting both CN and proximity biases when jointly processing multiple screens of models with available CN information, whereas CRISPRcleanR is the top performing method for individual screens or when CN information is not available. In addition, Chronos and AC-Chronos yield a final dataset better able to recapitulate known sets of essential and non-essential genes. CONCLUSIONS: Overall, our investigation provides guidance for the selection of the most appropriate bias-correction method, based on its strengths, weaknesses and experimental settings.

Generation of a biliary tract cancer cell line atlas reveals molecular subtypes and therapeutic targets.

Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.

CTAT-LR-fusion: accurate fusion transcript identification from long and short read isoform sequencing at bulk or single cell resolution.

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics, prognostics, and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short read sequences. Recent advances in long read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single cell samples. Here we developed a new computational tool CTAT-LR-fusion to detect fusion transcripts from long read RNA-seq with or without companion short reads, with applications to bulk or single cell transcriptomes. We demonstrate that CTAT-LR-fusion exceeds fusion detection accuracy of alternative methods as benchmarked with simulated and real long read RNA-seq. Using short and long read RNA-seq, we further apply CTAT-LR-fusion to bulk transcriptomes of nine tumor cell lines, and to tumor single cells derived from a melanoma sample and three metastatic high grade serous ovarian carcinoma samples. In both bulk and in single cell RNA-seq, long isoform reads yielded higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-fusion, we are able to further maximize detection of fusion splicing isoforms and fusion-expressing tumor cells. CTAT-LR-fusion is available at https://github.com/TrinityCTAT/CTAT-LR-fusion/wiki.

RPL22 is a tumor suppressor in MSI-high cancers and a key splicing regulator of MDM4.

Microsatellite instability high (MSI-H) tumors are malignant tumors that, despite harboring a high mutational burden, often have intact TP53. One of the most frequent mutations in MSI-H tumors is a frameshift mutation in RPL22, a ribosomal protein. Here, we identified RPL22 as a modulator of MDM4 splicing through an alternative splicing switch in exon 6. RPL22 loss increases MDM4 exon 6 inclusion, cell proliferation, and augments resistance to the MDM inhibitor Nutlin-3a. RPL22 represses expression of its paralog, RPL22L1, by mediating the splicing of a cryptic exon corresponding to a truncated transcript. Therefore, damaging mutations in RPL22 drive oncogenic MDM4 induction and reveal a common splicing circuit in MSI-H tumors that may inform therapeutic targeting of the MDM4-p53 axis and oncogenic RPL22L1 induction.

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal.

BACKGROUND: Hundreds of functional genomic screens have been performed across a diverse set of cancer contexts, as part of efforts such as the Cancer Dependency Map, to identify gene dependencies-genes whose loss of function reduces cell viability or fitness. Recently, large-scale screening efforts have shifted from RNAi to CRISPR-Cas9, due to superior efficacy and specificity. However, many effective oncology drugs only partially inhibit their protein targets, leading us to question whether partial suppression of genes using RNAi could reveal cancer vulnerabilities that are missed by complete knockout using CRISPR-Cas9. Here, we compare CRISPR-Cas9 and RNAi dependency profiles of genes across approximately 400 matched cancer cell lines. RESULTS: We find that CRISPR screens accurately identify more gene dependencies per cell line, but the majority of each cell line's dependencies are part of a set of 1867 genes that are shared dependencies across the entire collection (pan-lethals). While RNAi knockdown of about 30% of these genes is also pan-lethal, approximately 50% have selective dependency patterns across cell lines, suggesting they could still be cancer vulnerabilities. The accuracy of the unique RNAi selectivity is supported by associations to multi-omics profiles, drug sensitivity, and other expected co-dependencies. CONCLUSIONS: Incorporating RNAi data for genes that are pan-lethal knockouts facilitates the discovery of a wider range of gene targets than could be detected using the CRISPR dataset alone. This can aid in the interpretation of contrasting results obtained from CRISPR and RNAi screens and reinforce the importance of partial gene suppression methods in building a cancer dependency map.

Clinicopathological Profiles Associated with Discordant RAS Mutational Status between Liquid and Tissue Biopsies in a Real-World Cohort of Metastatic Colorectal Cancer.

We aimed to identify common mCRC profiles associated with a discordant mutational status of RAS between the standard of care (SoC) tumour tissue tests and ctDNA tests to understand ctDNA detection and improve treatment responses. This was a multicentre, retrospective and prospective study. A total of 366 Spanish mCRC patients were independently recruited. BEAMing ddPCR technology was employed to detect ctDNA RAS mutations, and logistic regression analyses were performed to investigate clinicopathological factors associated with discordance. The highest concordance ratios were observed in profiles with multiple metastatic sites when the liver was present (89.7%; 95% CI 84.8-93.2), profiles with synchronous disease without primary tumour resection (90.2%; 95% CI 83.6-94.3) and profiles with mCRC originating in the left colon (91.3%; 95% CI 85.0-95.0). Metachronous disease originating in the right colon (OR = 6.1; 95% CI 1.7-26.5; p-value = 0.006) or rectum (OR = 5.0; 95% CI 1.5-17.8; p-value = 0.009) showed the highest probability of discrepancies. Primary tumour resection and a higher frequency of single metastases in the peritoneum or lungs in these patients were associated with reduced plasmatic mutation allele fractions (MAFs) and an increased probability of showing false-negative genotypes. Additional testing of patients with mCRC originating in the right colon or rectum with a single non-mutated ctDNA test is advised before the choice of therapy.

Highlights from the 1st European cancer dependency map symposium and workshop.

The systematic identification of tumour vulnerabilities through perturbational experiments on cancer models, including genome editing and drug screens, is playing a crucial role in combating cancer. This collective effort is known as the Cancer Dependency Map (DepMap). The 1st European Cancer Dependency Map Symposium (EuroDepMap), held in Milan last May, featured talks, a roundtable discussion, and a poster session, showcasing the latest discoveries and future challenges related to the DepMap. The symposium aimed to facilitate interactions among participants across Europe, encourage idea exchange with leading experts, and present their work and future projects. Importantly, it sparked discussions on future endeavours, such as screening more complex cancer models and accounting for tumour evolution.

Genome-scale functional genomics identify genes preferentially essential for multiple myeloma cells compared to other neoplasias.

Clinical progress in multiple myeloma (MM), an incurable plasma cell (PC) neoplasia, has been driven by therapies that have limited applications beyond MM/PC neoplasias and do not target specific oncogenic mutations in MM. Instead, these agents target pathways critical for PC biology yet largely dispensable for malignant or normal cells of most other lineages. Here we systematically characterized the lineage-preferential molecular dependencies of MM through genome-scale clustered regularly interspaced short palindromic repeats (CRISPR) studies in 19 MM versus hundreds of non-MM lines and identified 116 genes whose disruption more significantly affects MM cell fitness compared with other malignancies. These genes, some known, others not previously linked to MM, encode transcription factors, chromatin modifiers, endoplasmic reticulum components, metabolic regulators or signaling molecules. Most of these genes are not among the top amplified, overexpressed or mutated in MM. Functional genomics approaches thus define new therapeutic targets in MM not readily identifiable by standard genomic, transcriptional or epigenetic profiling analyses.

Mapping the landscape of genetic dependencies in chordoma.

Identifying the spectrum of genes required for cancer cell survival can reveal essential cancer circuitry and therapeutic targets, but such a map remains incomplete for many cancer types. We apply genome-scale CRISPR-Cas9 loss-of-function screens to map the landscape of selectively essential genes in chordoma, a bone cancer with few validated targets. This approach confirms a known chordoma dependency, TBXT (T; brachyury), and identifies a range of additional dependencies, including PTPN11, ADAR, PRKRA, LUC7L2, SRRM2, SLC2A1, SLC7A5, FANCM, and THAP1. CDK6, SOX9, and EGFR, genes previously implicated in chordoma biology, are also recovered. We find genomic and transcriptomic features that predict specific dependencies, including interferon-stimulated gene expression, which correlates with ADAR dependence and is elevated in chordoma. Validating the therapeutic relevance of dependencies, small-molecule inhibitors of SHP2, encoded by PTPN11, have potent preclinical efficacy against chordoma. Our results generate an emerging map of chordoma dependencies to enable biological and therapeutic hypotheses.

A Ubiquitination Cascade Regulating the Integrated Stress Response and Survival in Carcinomas.

Systematic identification of signaling pathways required for the fitness of cancer cells will facilitate the development of new cancer therapies. We used gene essentiality measurements in 1,086 cancer cell lines to identify selective coessentiality modules and found that a ubiquitin ligase complex composed of UBA6, BIRC6, KCMF1, and UBR4 is required for the survival of a subset of epithelial tumors that exhibit a high degree of aneuploidy. Suppressing BIRC6 in cell lines that are dependent on this complex led to a substantial reduction in cell fitness in vitro and potent tumor regression in vivo. Mechanistically, BIRC6 suppression resulted in selective activation of the integrated stress response (ISR) by stabilization of the heme-regulated inhibitor, a direct ubiquitination target of the UBA6/BIRC6/KCMF1/UBR4 complex. These observations uncover a novel ubiquitination cascade that regulates ISR and highlight the potential of ISR activation as a new therapeutic strategy. SIGNIFICANCE: We describe the identification of a heretofore unrecognized ubiquitin ligase complex that prevents the aberrant activation of the ISR in a subset of cancer cells. This provides a novel insight on the regulation of ISR and exposes a therapeutic opportunity to selectively eliminate these cancer cells. See related commentary Leli and Koumenis, p. 535. This article is highlighted in the In This Issue feature, p. 517.

BAF Complex Maintains Glioma Stem Cells in Pediatric H3K27M Glioma.

Diffuse midline gliomas are uniformly fatal pediatric central nervous system cancers that are refractory to standard-of-care therapeutic modalities. The primary genetic drivers are a set of recurrent amino acid substitutions in genes encoding histone H3 (H3K27M), which are currently undruggable. These H3K27M oncohistones perturb normal chromatin architecture, resulting in an aberrant epigenetic landscape. To interrogate for epigenetic dependencies, we performed a CRISPR screen and show that patient-derived H3K27M-glioma neurospheres are dependent on core components of the mammalian BAF (SWI/SNF) chromatin remodeling complex. The BAF complex maintains glioma stem cells in a cycling, oligodendrocyte precursor cell-like state, in which genetic perturbation of the BAF catalytic subunit SMARCA4 (BRG1), as well as pharmacologic suppression, opposes proliferation, promotes progression of differentiation along the astrocytic lineage, and improves overall survival of patient-derived xenograft models. In summary, we demonstrate that therapeutic inhibition of the BAF complex has translational potential for children with H3K27M gliomas. SIGNIFICANCE: Epigenetic dysregulation is at the core of H3K27M-glioma tumorigenesis. Here, we identify the BRG1-BAF complex as a critical regulator of enhancer and transcription factor landscapes, which maintain H3K27M glioma in their progenitor state, precluding glial differentiation, and establish pharmacologic targeting of the BAF complex as a novel treatment strategy for pediatric H3K27M glioma. See related commentary by Beytagh and Weiss, p. 2730. See related article by Mo et al., p. 2906.

Systematic profiling of conditional degron tag technologies for target validation studies.

Conditional degron tags (CDTs) are a powerful tool for target validation that combines the kinetics and reversible action of pharmacological agents with the generalizability of genetic manipulation. However, successful design of a CDT fusion protein often requires a prolonged, ad hoc cycle of construct design, failure, and re-design. To address this limitation, we report here a system to rapidly compare the activity of five unique CDTs: AID/AID2, IKZF3d, dTAG, HaloTag, and SMASh. We demonstrate the utility of this system against 16 unique protein targets. We find that expression and degradation are highly dependent on the specific CDT, the construct design, and the target. None of the CDTs leads to efficient expression and/or degradation across all targets; however, our systematic approach enables the identification of at least one optimal CDT fusion for each target. To enable the adoption of CDT strategies more broadly, we have made these reagents, and a detailed protocol, available as a community resource.

Computational estimation of quality and clinical relevance of cancer cell lines.

Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome-wide editing screenings have facilitated the discovery of clinically relevant gene-drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision medicine context requires bridging the existing gaps between tumours and in vitro models. Indeed, intrinsic limitations of CCLs such as misidentification, the absence of tumour microenvironment and genetic drift have highlighted the need to identify the most faithful CCLs for each primary tumour while addressing their heterogeneity, with the development of new models where necessary. Here, we discuss the most significant limitations of CCLs in representing patient features, and we review computational methods aiming at systematically evaluating the suitability of CCLs as tumour proxies and identifying the best patient representative in vitro models. Additionally, we provide an overview of the applications of these methods to more complex models and discuss future machine-learning-based directions that could resolve some of the arising discrepancies.

A Mesenchymal Tumor Cell State Confers Increased Dependency on the BCL-XL Antiapoptotic Protein in Kidney Cancer.

PURPOSE: Advanced/metastatic forms of clear-cell renal cell carcinomas (ccRCC) have limited therapeutic options. Genome-wide genetic screens have identified cellular dependencies in many cancers. Using the Broad Institute/Novartis combined short hairpin RNA (shRNA) dataset, and cross-validation with the CRISPR/Cas9 DepMap (21Q3) dataset, we sought therapeutically actionable dependencies in kidney lineage cancers. EXPERIMENTAL DESIGN: We identified preferential genetic dependencies in kidney cancer cells versus other lineages. BCL2L1, which encodes the BCL-XL antiapoptotic protein, scored as the top actionable dependency. We validated this finding using genetic and pharmacologic tools in a panel of ccRCC cell lines. Select BCL-XL-dependent (versus independent) cell lines were then transcriptionally profiled to identify biomarkers and mechanistic drivers of BCL-XL dependence. Cell-based studies (in vitro and in vivo) and clinical validations were used to address physiologic relevance. RESULTS: Inactivation of BCL-XL, but not BCL-2, led to fitness defects in renal cancer cells, and sensitized them to chemotherapeutics. Transcriptomic profiling identified a "BCL-XL dependency" signature, including an elevated mesenchymal gene signature. A mesenchymal state was both necessary and sufficient to confer increased BCL-XL dependence. The "BCL-XL dependency" signature was observed in approximately 30% of human ccRCCs, which were also associated with worse clinical outcomes. Finally, an orally bioavailable BCL-XL inhibitor, A-1331852, showed antitumor efficacy in vivo. CONCLUSIONS: Our studies uncovered an unexpected link between cell state and BCL-XL dependence in ccRCC. Therapeutic agents that specifically target BCL-XL are available. Our work justifies testing the utility of BCL-XL blockade to target, likely, a clinically aggressive subset of human kidney cancers. See related commentary by Wang et al., p. 4600.

Phosphate dysregulation via the XPR1-KIDINS220 protein complex is a therapeutic vulnerability in ovarian cancer.

Despite advances in precision medicine, the clinical prospects for patients with ovarian and uterine cancers have not substantially improved. Here, we analyzed genome-scale CRISPR-Cas9 loss-of-function screens across 851 human cancer cell lines and found that frequent overexpression of SLC34A2-encoding a phosphate importer-is correlated with sensitivity to loss of the phosphate exporter XPR1, both in vitro and in vivo. In patient-derived tumor samples, we observed frequent PAX8-dependent overexpression of SLC34A2, XPR1 copy number amplifications and XPR1 messenger RNA overexpression. Mechanistically, in SLC34A2-high cancer cell lines, genetic or pharmacologic inhibition of XPR1-dependent phosphate efflux leads to the toxic accumulation of intracellular phosphate. Finally, we show that XPR1 requires the novel partner protein KIDINS220 for proper cellular localization and activity, and that disruption of this protein complex results in acidic "vacuolar" structures preceding cell death. These data point to the XPR1-KIDINS220 complex and phosphate dysregulation as a therapeutic vulnerability in ovarian cancer.

Sparse dictionary learning recovers pleiotropy from human cell fitness screens.

In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach (Webster) recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and predicted the stoichiometry of an unknown protein complex subunit from fitness data alone. Modeling compound sensitivity profiles in terms of genetic functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts.

Are CRISPR Screens Providing the Next Generation of Therapeutic Targets?

CRISPR screens combined with molecular and genetic profiling of large panels of cell lines are helping to systematically identify cancer vulnerabilities. These large-scale screens, together with focused in vivo and isogenic cell line screens, have identified a growing number of promising targets and led directly to numerous target-specific drug discovery programs, several of which have reached clinical testing. However, systematic loss-of-function studies are still in their early stages. Genetic redundancy, the limitation of cell line models for many cancer types, and the difficulty of conducting complex in vitro and in vivo screens remain opportunities for discovery. We expect that over the next few years, efforts like the Cancer Dependency Map along with more focused screens will play a significant role in the creation of a roadmap of oncology therapeutic targets.

Paralog knockout profiling identifies DUSP4 and DUSP6 as a digenic dependence in MAPK pathway-driven cancers.

Although single-gene perturbation screens have revealed a number of new targets, vulnerabilities specific to frequently altered drivers have not been uncovered. An important question is whether the compensatory relationship between functionally redundant genes masks potential therapeutic targets in single-gene perturbation studies. To identify digenic dependencies, we developed a CRISPR paralog targeting library to investigate the viability effects of disrupting 3,284 genes, 5,065 paralog pairs and 815 paralog families. We identified that dual inactivation of DUSP4 and DUSP6 selectively impairs growth in NRAS and BRAF mutant cells through the hyperactivation of MAPK signaling. Furthermore, cells resistant to MAPK pathway therapeutics become cross-sensitized to DUSP4 and DUSP6 perturbations such that the mechanisms of resistance to the inhibitors reinforce this mechanism of vulnerability. Together, multigene perturbation technologies unveil previously unrecognized digenic vulnerabilities that may be leveraged as new therapeutic targets in cancer.