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Supplementary Figure S3. ERG binding to CHK1 promoter.

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Targeting somatically activated oncogenes has revolutionized the treatment of non–small cell lung cancer (NSCLC). Mutations in the gene mesenchymal–epithelial transition (MET) near the exon 14 splice sites are recurrent in lung adenocarcinoma and cause exon skipping (METΔ14). Here, we analyzed 4,422 samples from 12 different malignancies to estimate the rate of said exon skipping. METΔ14 mutation and transcript were most common in lung adenocarcinoma. Endogenously expressed levels of METΔ14 transformed human epithelial lung cells in a hepatocyte growth factor–dependent manner. In addition, overexpression of the orthologous mouse allele induced lung adenocarcinoma in a novel, immunocompetent mouse model. Met inhibition showed clinical benefit in this model. In addition, we observed a clinical response to crizotinib in a patient with METΔ14-driven NSCLC, only to observe new missense mutations in the MET activation loop, critical for binding to crizotinib, upon clinical progression. These findings support genomically selected clinical trials directed toward METΔ14 in a fraction of NSCLC patients, confirm second-site mutations for further therapeutic targeting prior to and beyond acquired resistance, and provide an in vivo system for the study of METΔ14 in an immunocompetent host. Cancer Res; 77(16); 4498–505. ©2017 AACR.

Supplementary Tables 1 and 2

Supplementary Figure 1: A survey of MET mutations and expression across TCGA datasets from diverse cancer types. Supplementary figure 2, MET exon 14 status and trypsin assay Supplementary Figure 3 MET half-life assay results Supplementary Figure 4 tumor grade and size changes Supplementary Figure 5: Acquired resistance alleles are in trans

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Summary Lung cancers in never- and light-smokers often harbor targetable oncogenic mutations in Ras pathway genes. Here, a novel OCLN-RASGRF1 fusion is identified in an otherwise Ras wild-type lung tumor. Studying this and other RASGRF1 fusions, the authors show that these fusions lead to malignant phenotypes that can be reversed by MEK inhibition. See related article by Hunihan et al., p. 3091

CRISPR-based cancer dependency maps are accelerating advances in cancer precision medicine, but adequate functional maps are limited to the most common oncogenes. To identify opportunities for therapeutic intervention in other rarer subsets of cancer, we investigate the oncogene-specific dependencies conferred by the lung cancer oncogene, RIT1. Here, genome-wide CRISPR screening in KRAS, EGFR, and RIT1-mutant isogenic lung cancer cells identifies shared and unique vulnerabilities of each oncogene. Combining this genetic data with small-molecule sensitivity profiling, we identify a unique vulnerability of RIT1-mutant cells to loss of spindle assembly checkpoint regulators. Oncogenic RIT1M90I weakens the spindle assembly checkpoint and perturbs mitotic timing, resulting in sensitivity to Aurora A inhibition. In addition, we observe synergy between mutant RIT1 and activation of YAP1 in multiple models and frequent nuclear overexpression of YAP1 in human primary RIT1-mutant lung tumors. These results provide a genome-wide atlas of oncogenic RIT1 functional interactions and identify components of the RAS pathway, spindle assembly checkpoint, and Hippo/YAP1 network as candidate therapeutic targets in RIT1-mutant lung cancer., RIT1 mutations are mutually exclusive with other lung cancer drivers and lack targeted therapies. Here the authors examine genetic dependencies of mutant RIT1 with genome-wide CRISPR screens, revealing synergy between RIT1 and YAP1, and increased sensitivity to Aurora kinase inhibitors.

Somatic mutations and focal amplifications in the small GTPase RIT1 (Ras-like in all tissues) account for over 13,500 lung cancer diagnoses annually, but treatment options are limited. Of the currently identified mutations, the M90I variant (RIT1M90I) is most prevalent. A targeted therapy for RIT1-mutant and RIT1-amplified tumors would address a major unmet clinical need, but little is known about how RIT1 drives cellular transformation. Recent work suggests that the protein abundance of RIT1 is important for its function. In line with these findings, our lab performed a genome-wide CRISPR screen in RIT1-mutant lung adenocarcinoma cells and identified the deubiquitinase USP9X as a potential regulator of RIT1 abundance. We hypothesize that USP9X positively regulates wild-type and mutant RIT1, and USP9X inhibition could be a tractable means of abrogating RIT1-driven tumor growth. We have explored this hypothesis in numerous different cell line models, including NCI-H2110 cells—a human lung adenocarcinoma cell line that harbors an endogenous RIT1M90I mutation. siRNA-mediated knockdown of USP9X in NCI-H2110 cells resulted in a 56.29% reduction of RIT1 abundance (95% CI = -76.63 to -10.8) via Western Blot analysis. Furthermore, cycloheximide-chase experiments revealed that RIT1 stability was decreased in siUSP9X-treated cells compared to siCtrl-treated cells. We have also explored USP9X-mediated RIT1 regulation of endogenous wild-type RIT1 in PC9 lung adenocarcinoma cells and found that CRISPR knockout of USP9X reduced wild-type RIT1 abundance by 46.83% (95% CI = -73.84 to -32.51). In PC9 cells engineered to express RIT1M90I, siRNA-mediated knockdown of USP9X decreased RIT1M90I abundance by 58.56% (95% CI = -59.3 to -23.59). Furthermore, pharmacological inhibition of USP9X with two different small molecule inhibitors (WP1130 and G9) decreased RIT1 abundance in PC9 cells. Cells treated with 1μΜ of WP1130 showed a 56.21% (95% CI = -131.1 to 43.55) reduction in RIT1 abundance compared to DMSO-treated cells. In addition to assessing protein abundance and stability, we performed co-immunoprecipitation experiments in RIT1-mutant and RIT1-overexpressing HEK293T cells and found that both RIT1WT and RIT1M90I physically interact with USP9X. We also performed ubiquitination experiments in RIT1-overexpressing HEK293T cells and found that co-expression of wild-type USP9X decreased RIT1 ubiquitination, but a catalytically dead USP9X variant did not affect levels of RIT1-Ub. Taken together, these data support the hypothesis that USP9X controls the deubiquitination and stabilization of RIT1WT and RIT1M90I. This work provides more insight on the basic biology of RIT1 regulation and has important therapeutic implications given that USP9X inhibition could reduce RIT1 protein abundance and abrogate RIT1-driven tumor growth, thereby addressing a major unmet clinical need. Citation Format: Amanda K. Riley, Athea Vichas, Aidan Snell, Michael Grant, Lixin Wan, Alice H. Berger. Protein-level regulation of wild-type and mutant RIT1 by the deubiquitinase USP9X [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2628.

In recent work, we performed CRISPR/Cas9 screening in RIT1 (Ras-like in all tissues)-mutant cancer cells. We found that RIT1-mutant cells are vulnerable to loss of mitotic regulators, and mutant RIT1 synergizes with YAP1 (yes-associated protein 1) in oncogenesis. These findings can be leveraged to identify targeted therapies for RIT1-mutant cancer.

While RNA-seq has enabled comprehensive quantification of alternative splicing, no correspondingly high-throughput assay exists for functionally interrogating individual isoforms. We describe pgFARM (paired guide RNAs for alternative exon removal), a CRISPR–Cas9-based method to manipulate isoforms independent of gene inactivation. This approach enabled rapid suppression of exon recognition in polyclonal settings to identify functional roles for individual exons, such as an SMNDC1 cassette exon that regulates pan-cancer intron retention. We generalized this method to a pooled screen to measure the functional relevance of ‘poison’ cassette exons, which disrupt their host genes’ reading frames yet are frequently ultraconserved. Many poison exons were essential for the growth of both cultured cells and lung adenocarcinoma xenografts, while a subset had clinically relevant tumor-suppressor activity. The essentiality and cancer relevance of poison exons are likely to contribute to their unusually high conservation and contrast with the dispensability of other ultraconserved elements for viability. pgFARM (paired guide RNAs for alternative exon removal) is a CRISPR–Cas9-based approach to manipulate alternative splicing and identify functional roles for individual exons, including poison exons with essential and tumor-suppressor roles.

Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding gene is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance (VUS) as impactful vs. neutral in an approach called expression-based variant-impact phenotyping (eVIP). We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cell’s image, we found that cell morphological profiling (cmVIP) can predict variants’ functional impact and, particularly at the single-cell level, reveals biological insights into variants which can be explored in our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene-specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

Aberrant activation of the RAS family of guanosine triphosphatases (GTPases) is prevalent in lung adenocarcinoma, with somatic mutation of KRAS occurring in ~30% of tumors. We previously identified somatic mutations and amplifications of the gene encoding RAS family GTPase RIT1 in lung adenocarcinomas. To explore the biological pathways regulated by RIT1 and how they relate to the oncogenic KRAS network, we performed quantitative proteomic, phosphoproteomic, and transcriptomic profiling of isogenic lung epithelial cells in which we ectopically expressed wild-type or cancer-associated variants of RIT1 and KRAS. We found that both mutant KRAS and mutant RIT1 promoted canonical RAS signaling, and that overexpression of wild-type RIT1 partially phenocopied oncogenic RIT1 and KRAS, including induction of epithelial-to-mesenchymal transition. Our findings suggest that RIT1 protein abundance is a factor in its pathogenic function. Therefore, chromosomal amplification of wild-type RIT1 in lung and other cancers may be tumorigenic.

MGA, a transcription factor and member of the MYC network, is mutated or deleted in a broad spectrum of malignancies. As a critical test of a tumor suppressive role, we inactivated Mga in two mouse models of non-small cell lung cancer using a CRISPR-based approach. MGA loss significantly accelerated tumor growth in both models and led to de-repression of non-canonical Polycomb ncPRC1.6 targets, including genes involved in metastasis and meiosis. Moreover, MGA deletion in human lung adenocarcinoma lines augmented invasive capabilities. We further show that MGA-MAX, E2F6, and L3MBTL2 co-occupy thousands of promoters and that MGA stabilizes these ncPRC1.6 subunits. Lastly, we report that MGA loss also induces a pro-growth effect in human colon organoids. Our studies establish MGA as a bona fide tumor suppressor in vivo and suggest a tumor suppressive mechanism in adenocarcinomas resulting from widespread transcriptional attenuation of MYC and E2F target genes mediated by MGA-MAX associated with a non-canonical Polycomb complex.

Variants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.

Cuella-Martin et al. (2020) and Hanna et al. (2020) showcase CRISPR base editing in large-scale pooled screens in human cells. Base editor screens discover both loss- and gain-of-function variants, enabling protein structure/function insights and clinical variant interpretation.

SUMMARY RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(–) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(–) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(–) cases are required to understand this important LUAD subset., In Brief Carrot-Zhang et al. perform whole-genome characterization of lung adenocarcinomas (LUADs) lacking RTK/RAS/RAF pathway alterations (RPAs) and identify mutations or structural variants in both coding and non-coding spaces that define a unique entity of RPA(–) LUADs and potentially explain the underlying biology of this disease., Graphical Abstract

Objectives Determine the diagnostic accuracy of two antigen-detecting rapid diagnostic tests (Ag-RDT) for SARS-CoV-2 at the point of care and define individuals’ characteristics providing best performance. Methods We performed a prospective, single-center, point of care validation of two Ag-RDT in comparison to RT-PCR on nasopharyngeal swabs. Results Between October 9th and 23rd, 2020, 1064 participants were enrolled. The PanbioTM Covid-19 Ag Rapid Test device (Abbott) was validated in 535 participants, with 106 positive Ag-RDT results out of 124 positive RT-PCR individuals, yielding a sensitivity of 85.5% (95% CI: 78.0–91.2). Specificity was 100.0% (95% CI: 99.1–100) in 411 RT-PCR negative individuals. The Standard Q Ag-RDT (SD Biosensor, Roche) was validated in 529 participants, with 170 positive Ag-RDT results out of 191 positive RT-PCR individuals, yielding a sensitivity of 89.0% (95%CI: 83.7–93.1). One false positive result was obtained in 338 RT-PCR negative individuals, yielding a specificity of 99.7% (95%CI: 98.4–100). For individuals presenting with fever 1–5 days post symptom onset, combined Ag-RDT sensitivity was above 95%. Lower sensitivity of 88.2% was seen on the same day of symptom development (day 0). Conclusions We provide an independent validation of two widely available commercial Ag-RDTs, both meeting WHO criteria of ≥80% sensitivity and ≥97% specificity. Although less sensitive than RT-PCR, these assays could be beneficial due to their rapid results, ease of use, and independence from existing laboratory structures. Testing criteria focusing on patients with typical symptoms in their early symptomatic period onset could further increase diagnostic value.

Standard care of lung cancer treatment has shifted away from non-specific, cytotoxic chemotherapy in favor of targeted therapies based on genetic mutations within tumors. In 2014, somatic mutations in the small GTPase RIT1 (Ras-like in all tissues) were discovered as oncogenic drivers of lung adenocarcinoma. Thousands of patients per year are diagnosed with RIT1-driven cancer, but treatment options are limited. A targeted therapy for RIT1-driven tumors would address a major unmet clinical need. Little is known about how RIT1 drives cellular transformation. To genetically dissect RIT1 function, we performed a genome-wide CRISPR/Cas9 screen in isogenic PC9 lung adenocarcinoma cells. This screen took advantage of the observation that RIT1-mutant cells are resistant to EGFR inhibition. We leveraged this drug resistance phenotype to identify genetic dependencies (gene knockouts that are detrimental to cell growth) and cooperating factors (gene knockouts that are beneficial to cell growth) in RIT1-mutant cells. From this screen, we found that one of the top essential genes was the deubiquitinase USP9X. This is intriguing given that the protein abundance of RIT1 is known to be important for its function. Therefore, we sought out to test the hypothesis that USP9X regulates RIT1 abundance and that inhibition of USP9X could be an effective therapeutic strategy for abrogating RIT1-driven tumor growth. Our model suggests that USP9X promotes proteasome-mediated degradation of RIT1. To test this, we assessed RIT1 abundance in the context of USP9X knockout (KO). We found that RIT1 protein abundance was decreased in USP9X KO PC9 cells compared to parental cells. Furthermore, cycloheximide (CHX)-chase experiments revealed that RIT1 stability was decreased in USP9X KO cells, and RIT1 degraded faster than in parental cells. The average half-life of RIT1 in USP9X KO cells was 3.4 hrs while the average half-life in parental PC9 cells was 12.3 hrs (95% CI = -12.5 to -5.4 hrs). Treatment with the proteasome inhibitor bortezomib (BTZ) rescued RIT1 degradation by 99% in parental cells and 190% in USP9X KO cells (95% CI = 57 to 126%). In addition to assessing protein abundance and stability, we performed co-immunoprecipitation experiments in RIT1-expressing HEK293T cells and found that RIT1 and USP9X physically interact. Taken together, these data support the hypothesis that RIT1 is a substrate of USP9X. In addition to providing better insight on the protein regulation of RIT1, this work has crucial therapeutic implications. The protein abundance of RIT1 is important for its function, and our model suggests that USP9X inhibition could be an effective means of reducing RIT1 protein abundance and abrogating tumor growth. Overall, this work is poised to significantly impact the field of RIT1 biology and address a major unmet clinical need for the treatment of RIT1-driven diseases. Citation Format: Amanda K. Riley, Athea Vichas, Naomi T. Nkinsi, Phoebe C. Parrish, Shriya Kamlapurkar, Alice H. Berger. Identification of USP9X as a novel regulator of RIT1 protein abundance and as a potential therapeutic target in RIT1-driven lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2972.

Alternative mRNA splicing is dysregulated in many cancers including lung adenocarcinoma. These aberrant splicing events can sometimes be explained by mutations in splice sites or splicing factors. However, the majority of mis-splicing in cancers remains unexplained. We hypothesize that oncogenic signaling pathways play a role in regulating alternative splicing. In this study, we focus on mRNA splicing activity regulated by the Ras signaling cascade, which is frequently mutated in cancers. These pathways offer avenues for therapeutic modulation through small molecule inhibitors.We took a global proteomic and transcriptomic approach to study the effects of oncogenic Ras signaling on RNA splicing in vitro. Specifically, we performed LC-MS/MS and RNA-seq profiling on normal human lung airway epithelial (AALE) cells overexpressing wild-type or mutant KRAS or RIT1 (N = 3 replicates per allele). Phosphorylation of splicing factors was preferentially downregulated in KRASmut cells compared to KRASWT cells, suggesting that oncogenic KRAS signaling regulates splicing factor activity. Additionally, of the 2227 and 2452 skipped exon (SE) events in KRASG12V and KRASQ61H cells, respectively, compared to KRASWT overexpressing cells, 1013 events were shared between the two mutants. This statistically significant overlap (p < 0.001, hypergeometric test) indicates that KRAS has a role in splicing regulation that is disrupted when the protein is mutated. To determine how KRAS-regulated splicing activity compared to other signaling proteins and oncogenes, we also profiled the whole transcriptomes of isogenic A549 lung adenocarcinoma cell lines overexpressing 86 wild-type or variant alleles across 27 genes implicated in lung cancers (N = 4 to 8 replicates per allele). Of all pairs of mutant and wild-type alleles tested, KRASmut cells compared to KRASWT overexpressing cells exhibited the second highest levels of alternative splicing, behind only RNA binding protein RBM45 and its mutant allele RBM45M126I. In particular, ten SE events were observed to be differentially regulated in a KRAS dependent manner in both AALE and A549 cells. One of these 10 events is the differential splicing of the Myc Associated Zinc Finger (MAZ) protein to increase the expression of its splice variant that acts as a negative regulator of transcription. As MAZ regulates expression of KRAS, this splice variant may be a mechanism for the cell to modulate wild-type KRAS levels in the presence of KRAS mutants. Our proteomic and transcriptomic profiling in lung epithelial and lung adenocarcinoma cells uncovers splicing factor activity and mRNA splicing events regulated by oncogenic KRAS. With further studies of the alternative splicing events described, it will be possible to design or repurpose therapies in order to target aberrant splicing caused by disrupted Ras signaling and its downstream effectors. Citation Format: April Lo, Maria McSharry, Alice H. Berger. Dysregulation of alternative mRNA splicing by oncogenic KRAS in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 778.

Synthetic lethal therapies are a promising approach to expand therapeutic options for cancer patients. Since synthetic lethal therapies target tumor cells specifically, they have fewer off-target effects than oncogene targeted approaches. To identify new cancer drug targets, we focused on paralogs, ancestrally-duplicated genes that frequently retain redundant or overlapping functions. To find synthetic lethal human paralogs, we developed paired guide RNAs for Paralog gENetic interaction mapping (pgPEN), a pooled CRISPR-Cas9 single and double knockout approach targeting over 2,000 paralogs. We applied pgPEN to two cancer cell lines and found that 12% of human paralogs exhibit synthetic lethality in at least one context. To our knowledge, pgPEN represents the largest experimental assessment of human paralog synthetic lethality to date. We next identified paralog pairs to prioritize for follow-up study. A key drawback to synthetic lethal therapies is that many genetic interactions are context-dependent. To identify likely penetrant interactions, we compared our data to other published paralog screens and computational predictions of paralog synthetic lethality. We found that over 75% (n=96) of pgPEN hits were predicted to be broadly synthetic lethal, and nearly 10% (n=10) of pairs were synthetic lethal in multiple paralog screens. Finally, we prioritized paralogs targeted by existing small molecule therapies. Of the 122 synthetic lethal pairs identified by pgPEN, 16% (n=20) are currently druggable. We mined drug repurposing data from DepMap to find pairs where a paralog-targeting drug showed a stronger effect in cell lines with low target gene copy number or expression relative to cell lines with normal target gene copy number or expression. These drugs could selectively target cancer cells in cases where one or both paralogs is lost in tumors but retained in normal tissue. We also leveraged The Cancer Genome Atlas tumor sequencing data to find paralog pairs where one member is recurrently lost in cancer. Taken together, these studies identify druggable, highly penetrant synthetic lethal paralog interactions. In combination with tumor sequencing data, we identify high-priority paralog drug targets that can be further tested and translated to the clinic. Paralog synthetic lethal therapies could provide a relatively low-toxicity therapeutic approach to improve the efficacy of cancer treatments and prevent the emergence of acquired resistance. Citation Format: Phoebe C. Parrish, James D. Thomas, Austin M. Gabel, Shriya Kamlapurkar, Robert K. Bradley, Alice H. Berger. Expanding cancer therapy options by leveraging synthetic lethal interactions between druggable paralogs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2278.

CRISPR knockout screens have accelerated the discovery of important cancer genetic dependencies. However, traditional CRISPR-Cas9 screens are limited in their ability to assay the function of redundant or duplicated genes. Paralogs in multi-gene families constitute two-thirds of the protein-coding genome, so this blind spot is the rule, not the exception. To overcome the limitations of single gene CRISPR knockout screens, we developedpairedguide RNAs forParalog gENetic interaction mapping (pgPEN), a pooled CRISPR/Cas9 approach which targets over a thousand duplicated human paralogs in single knockout and double knockout configurations. We applied pgPEN to two cell lineages and discovered that over 10% of human paralogs exhibit synthetic lethality in at least one cellular context. We recovered known synthetic lethal paralogs such asMAP2K1/MAP2K2, important drug targets such asCDK4/CDK6, and numerous other synthetic lethal pairs such asCCNL1/CCNL2.In addition, we identified ten tumor suppressive paralog pairs whose compound loss promotes cell growth. These findings identify a large number of previously unidentified essential gene families and nominate new druggable targets for oncology drug discovery.HighlightsComprehensive genetic interaction mapping of 1,030 human duplicated paralogs using a dual targeting CRISPR/Cas9 approachDuplicated paralogs are highly enriched for genetic interactionsSynthetic lethal paralogs includeCCNL1/CCNL2, CDK4/CDK6, andGSK3A/GSK3BTumor suppressor paralog pairs includeCDKN2A/CDKN2BandFBXO25/FBXO32

BackgroundAntigen-detecting rapid diagnostic tests for SARS-CoV-2 offer new opportunities for the quick and laboratory-independent identification of infected individuals for control of the SARS-CoV-2 pandemic.MethodsWe performed a prospective, single-center, point of care validation of two antigen-detecting rapid diagnostic tests (Ag-RDT) in comparison to RT-PCR on nasopharyngeal swabs.FindingsBetween October 9th and 23rd, 2020, 1064 participants were enrolled. The Panbio™Covid-19 Ag Rapid Test device (Abbott) was validated in 535 participants, with 106 positive Ag-RDT results out of 124 positive RT-PCR individuals, yielding a sensitivity of 85.5% (95% CI: 78.0–91.2). Specificity was 100.0% (95% CI: 99.1–100) in 411 RT-PCR negative individuals. The Standard Q Ag-RDT (SD Biosensor, Roche) was validated in 529 participants, with 170 positive Ag-RDT results out of 191 positive RT-PCR individuals, yielding a sensitivity of 89.0% (95%CI: 83.7–93.1). One false positive result was obtained in 338 RT-PCR negative individuals, yielding a specificity of 99.7% (95%CI: 98.4–100). For individuals presenting with fever 1-5 days post symptom onset, combined Ag-RDT sensitivity was above 95%.InterpretationWe provide an independent validation of two widely available commercial Ag-RDTs, both meeting WHO criteria of ≥80% sensitivity and ≥97% specificity. Although less sensitive than RT-PCR, these assays could be beneficial due to their rapid results, ease of use, and independence from existing laboratory structures. Testing criteria focusing on patients with typical symptoms in their early symptomatic period onset could further increase diagnostic value.FundingFoundation of Innovative Diagnostics (FIND), Fondation privée des HUG, Pictet Charitable Foundation.

Genome sequencing studies have identified millions of somatic variants in cancer, but their phenotypic impact remains challenging to predict. Current experimental approaches to distinguish between functionally impactful and neutral variants require customized phenotypic assays that often report on average effects, and are not easily scaled. Here, we develop a generalizable, high-dimensional, and scalable approach to functionally assess variant impact in single cells by pooled Perturb-seq. Specifically, we assessed the impact of 200 TP53 and KRAS variants in >300,000 single lung cancer cells, and used the profiles to categorize variants into phenotypic subsets to distinguish gain-of-function, loss-of-function and dominant negative variants, which we validated by comparison to orthogonal assays. Surprisingly, KRAS variants did not merely fit into discrete functional categories, but rather spanned a continuum of gain-of-function phenotypes driven by quantitative shifts in cell composition at the single cell level. We further discovered novel gain-of-function KRAS variants whose impact could not have been predicted solely by their occurrence in patient samples. Our work provides a scalable, gene-agnostic method for coding variant impact phenotyping, which can be applied in cancer and other diseases driven by somatic or germline coding mutations.

Genome sequencing studies have identified millions of somatic variants in cancer, but it remains challenging to predict the phenotypic impact of most. Experimental approaches to distinguish impactful variants often use phenotypic assays that report on predefined gene-specific functional effects in bulk cell populations. Here, we develop an approach to functionally assess variant impact in single cells by pooled Perturb-seq. We measured the impact of 200 TP53 and KRAS variants on RNA profiles in over 300,000 single lung cancer cells, and used the profiles to categorize variants into phenotypic subsets to distinguish gain-of-function, loss-of-function and dominant negative variants, which we validated by comparison with orthogonal assays. We discovered that KRAS variants did not merely fit into discrete functional categories, but spanned a continuum of gain-of-function phenotypes, and that their functional impact could not have been predicted solely by their frequency in patient cohorts. Our work provides a scalable, gene-agnostic method for coding variant impact phenotyping, with potential applications in multiple disease settings.

Our aim was to develop practical models built with simple clinical-radiological features to facilitate COVID-19 diagnosis. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 03/13/2020 to 04/14/2020 were included (244 [47.6%] with a positive RT-PCR). Chest CTs were immediately and prospectively analysed by on-call teleradiologists (OCTR) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. Multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC=0.92 versus 0.88 for OCTR) while step-LR provided the highest AUC with clinical-radiological variables (0.93 versus 0.86 for OCTR). Hence, these two simple models, depending on the availability of clinical data, could be used by any radiologist to support their conclusion in case of COVID-19 suspicion.

Our aim was to develop practical models built with simple clinical and radiological features to help diagnosing Coronavirus disease 2019 [COVID-19] in a real-life emergency cohort. To do so, 513 consecutive adult patients suspected of having COVID-19 from 15 emergency departments from 2020-03-13 to 2020-04-14 were included as long as chest CT-scans and real-time polymerase chain reaction (RT-PCR) results were available (244 [47.6%] with a positive RT-PCR). Immediately after their acquisition, the chest CTs were prospectively interpreted by on-call teleradiologists (OCTRs) and systematically reviewed within one week by another senior teleradiologist. Each OCTR reading was concluded using a 5-point scale: normal, non-infectious, infectious non-COVID-19, indeterminate and highly suspicious of COVID-19. The senior reading reported the lesions’ semiology, distribution, extent and differential diagnoses. After pre-filtering clinical and radiological features through univariate Chi-2, Fisher or Student t-tests (as appropriate), multivariate stepwise logistic regression (Step-LR) and classification tree (CART) models to predict a positive RT-PCR were trained on 412 patients, validated on an independent cohort of 101 patients and compared with the OCTR performances (295 and 71 with available clinical data, respectively) through area under the receiver operating characteristics curves (AUC). Regarding models elaborated on radiological variables alone, best performances were reached with the CART model (i.e., AUC = 0.92 [versus 0.88 for OCTR], sensitivity = 0.77, specificity = 0.94) while step-LR provided the highest AUC with clinical-radiological variables (AUC = 0.93 [versus 0.86 for OCTR], sensitivity = 0.82, specificity = 0.91). Hence, these two simple models, depending on the availability of clinical data, provided high performances to diagnose positive RT-PCR and could be used by any radiologist to support, modulate and communicate their conclusion in case of COVID-19 suspicion. Practically, using clinical and radiological variables (GGO, fever, presence of fibrotic bands, presence of diffuse lesions, predominant peripheral distribution) can accurately predict RT-PCR status.

Aberrant activation of RAS oncogenes is prevalent in lung adenocarcinoma, with somatic mutation ofKRASoccurring in ∼30% of tumors. Recently, we identified somatic mutation of the RAS-family GTPaseRIT1in lung adenocarcinoma, but relatively little is known about the biological pathways regulated by RIT1 and how these relate to the oncogenic KRAS network. Here we present quantitative proteomic and transcriptomic profiles fromKRAS-mutant andRIT1-mutant isogenic lung epithelial cells and globally characterize the signaling networks regulated by each oncogene. We find that both mutant KRAS and mutant RIT1 promote S6 kinase, AKT, and RAF/MEK signaling, and promote epithelial-to-mesenchymal transition and immune evasion via HLA protein loss. However, KRAS and RIT1 diverge in regulation of phosphorylation sites on EGFR, USO1, and AHNAK proteins. The majority of the proteome changes are related to altered transcriptional regulation, but a small subset of proteins are differentially regulated by both oncoproteins at the post-transcriptional level, including intermediate filament proteins, metallothioneins, and MHC Class I proteins. These data provide the first global, unbiased characterization of oncogenic RIT1 network and identify the shared and divergent functions of oncogenic RIT1 and KRAS GTPases in lung cancer.

SUMMARY CRISPR screens have accelerated the discovery of important cancer vulnerabilities. However, single-gene knockout phenotypes can be masked by redundancy among related genes. Paralogs constitute two-thirds of the human protein-coding genome, so existing methods are likely inadequate for assaying a large portion of gene function. Here, we develop paired guide RNAs for paralog genetic interaction mapping (pgPEN), a pooled CRISPR-Cas9 single- and double-knockout approach targeting more than 2,000 human paralogs. We apply pgPEN to two cell types and discover that 12% of human paralogs exhibit synthetic lethality in at least one context. We recover known synthetic lethal paralogs MEK1/MEK2, important drug targets CDK4/CDK6, and other synthetic lethal pairs including CCNL1/CCNL2. Additionally, we identify ten tumor suppressor paralog pairs whose compound loss promotes cell proliferation. These findings nominate drug targets and suggest that paralog genetic interactions could shape the landscape of positive and negative selection in cancer., Graphical Abstract, In brief Parrish et al. present pgPEN, a method for identifying paralog genetic interactions, and find that human duplicate genes are enriched for functional redundancy and essentiality. These findings provide a framework for identifying synthetic lethal gene pairs and nominate cancer drug targets.

While advancements in genome sequencing have identified millions of somatic mutations in cancer, their functional impact is poorly understood. We previously developed the expression-based variant impact phenotyping (eVIP) method to use gene expression data to characterize the function of gene variants. The eVIP method uses a decision tree-based algorithm to predict the functional impact of somatic variants by comparing gene expression signatures induced by introduction of wild-type (WT) versus mutant cDNAs in cell lines. The method distinguishes between variants that are gain-of-function, loss-of-function, change-of-function, or neutral. We present eVIP2, software that allows for pathway analysis (eVIP Pathways) and usage with RNA-seq data. To demonstrate the eVIP2 software and approach, we characterized two recurrent frameshift variants in RNF43, a negative regulator of Wnt signaling, frequently mutated in colorectal, gastric, and endometrial cancer. RNF43 WT, RNF43 R117fs, RNF43 G659fs, or GFP control cDNA were overexpressed in HEK293T cells. Analysis with eVIP2 predicted that the frameshift at position 117 was a loss-of-function mutation, as expected. The second frameshift at position 659 has been previously described as a passenger mutation that maintains the RNF43 WT function as a negative regulator of Wnt. Surprisingly, eVIP2 predicted G659fs to be a change-of-function mutation. Additional eVIP Pathways analysis of RNF43 G659fs predicted 10 pathways to be significantly altered, including TNF-α via NFκB signaling, KRAS signaling, and hypoxia, highlighting the benefit of a more comprehensive approach when determining the impact of gene variant function. To validate these predictions, we performed reporter assays and found that each pathway activated by expression of RNF43 G659fs, but not expression of RNF43 WT, was identified as impacted by eVIP2, supporting that RNF43 G659fs is a change-of-function mutation and its effect on the identified pathways. Pathway activation was further validated by Western blot analysis. Lastly, we show primary colon adenocarcinoma patient samples with R117fs and G659fs variants have transcriptional profiles similar to BRAF missense mutations with activated RAS/MAPK signaling, consistent with KRAS signaling pathways being GOF in both variants. The eVIP2 method is an important step towards overcoming the current challenge of variant interpretation in the implementation of precision medicine. eVIP2 is available at https://github.com/BrooksLabUCSC/eVIP2., Author summary Cancer is often caused by a DNA change, called a mutation, that creates an atypical protein variant. Many cancer-associated mutations remain uninvestigated because experimental validation of their effect on gene function is costly, time-consuming, and requires prior knowledge of a gene’s function. We present our computational tool, eVIP2, which advances our previous approach called expression-based variant impact phenotyping (eVIP) and can be used with RNA sequencing data. This method uses gene expression data to characterize a gene variant’s function, requiring no prior knowledge of the wild-type gene’s function. With eVIP2, we can predict if a mutation causes a gain, loss, or change in function, or if it is neutral. Here, we found two recurrent frameshift mutations in RNF43 that have different effects on gene function where one mutation causes multiple cancer pathways to be activated. This study highlights the usefulness of using the eVIP2 tool for profiling a mutation’s impact at the pathway level.

Genome-scale CRISPR-Cas9 screens have enabled the identification of essential genes that can serve as cancer drug targets. However, single-gene knockout screens frequently underestimate the essentiality of paralogs, ancestrally duplicated genes that often functionally compensate for one another's loss; we have observed this directly in single-gene CRISPR screen data from a lung cancer cell line (P < 1E-16). Since the human genome is highly duplicated, our ability to identify novel drug targets is greatly limited. To identify paralog pairs essential for cancer cell survival, we developed a multiplexed CRISPR approach that uses paired guide RNAs to knock out human paralogs individually and in pairs. Our library includes 2,060 paralogs (1,030 pairs); the largest human paralog CRISPR library to date. We screened lung adenocarcinoma (PC9) and cervical carcinoma (HeLa) cell lines to identify synthetic lethal paralogs which have minimal growth effects when targeted individually but whose simultaneous loss leads to severely decreased growth. We found that 128 (16%) of the paralog pairs in our study were synthetic lethal and essential in at least one cell line. Gene set enrichment analysis revealed that our top paralogs are overrepresented in pathways related to cell cycle regulation, protein secretion, DNA repair, and PI3K-AKT signaling (FDR q-value < 2.52E-4). Importantly, 15 (18%) synthetic lethal paralog pairs have at least one member that is currently druggable. We validated our screen results using in vitro competition assays and DepMap CRISPR data analysis. For known synthetic lethal paralogs MAGOH and MAGOHB, competition assay data confirmed significantly reduced growth in the dual gene knockout condition versus single-gene knockouts (P < 0.05) and analysis of DepMap CRISPR score correlation with paralog expression showed that MAGOHB is more essential in cell lines with low MAGOH expression (P < 4.6E-41). For novel synthetic lethal paralogs CCNL1/CCNL2, PSMB5/PSMB8, and OXSR1/STK39, DepMap CRISPR score vs. expression correlation analysis again confirmed our findings as cell lines with low expression of paralog 1 showed lower CRISPR scores when paralog 2 was knocked out (P < 1.2E-8 for each pair), suggesting that our novel synthetic lethal paralogs are essential across a range of cancer cell lines. These interactions are also being validated via competition assay, and CRISPR knockout efficiency will be confirmed via Western blot and genomic DNA sequencing. Our studies point to a number of novel synthetic lethal paralogs that could serve as lung cancer drug targets. These paralogs could be targeted alone or in combination with existing therapies to suppress lung cancer growth and prevent acquired drug resistance. Paralog synthetic lethal therapies could make a major impact on clinical care by improving patient outcomes. Citation Format: Phoebe C. Parrish, James D. Thomas, Shriya Kamlapurkar, Robert K. Bradley, Alice H. Berger. Enabling cancer drug target discovery through genome-scale identification of synthetic lethal paralog pairs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2139.

Standard care of lung cancer is moving away from chemotherapy in favor of personalized approaches based on specific mutations in each tumor. Genome-sequencing studies have identified somatic mutations in the small GTPase RIT1 (Ras-like in all tissues) in lung adenocarcinoma patients. Of the identified mutations, M90I is the most recurrent. Thousands of patients per year are diagnosed with RIT1-driven cancer, but treatment options are limited. A targeted therapy for RIT1-driven disease could greatly improve patient outcomes. Little is known about how RIT1 drives cellular transformation. To genetically dissect signaling pathways downstream of RIT1, we performed a genome-wide CRISPR/Cas9 screen in isogenic PC9 lung adenocarcinoma cells in which cell survival is dependent on expression of RIT1M90I. We found that RIT1-mutant cells were highly dependent on components of the Spindle Assembly Checkpoint (SAC), including the Aurora kinases (A and B). The SAC is a surveillance mechanism that ensures proper chromosome segregation during mitosis. We hypothesized that RIT1M90I weakened the SAC and rendered cells vulnerable to loss of mitotic regulators. To explore this, we performed time-lapse imaging in HeLa H2B-GFP cells stably expressing RIT1M90I. In parental cells, the median duration of mitosis was 70.5 min (95% CI = 63 – 82 min), while in RIT1M90I-mutant cells, this was reduced to 48 min (95% CI = 45 – 51 min). Mitotic index was unaffected, suggesting that RIT1M90I does not regulate mitotic entry. This difference in mitotic timing was eliminated by treatment with reversine, an inhibitor that abolishes the SAC, demonstrating that RIT1M90I perturbs mitotic timing at the level of the SAC. If RIT1M90I weakens the SAC, we would expect higher prevalence of chromosomal abnormalities (such as chromosome bridges) in RIT1M90I-mutant cells. Indeed, analysis of fixed-cell populations indicated that RIT1M90I-mutant cells showed higher prevalence of mitotic abnormalities (79% of RIT1M90I-mutant cells compared to 46% of parental cells, 95% CI= 15 – 53). These data support the hypothesis that RIT1M90I weakens the SAC and imply that further SAC perturbation could be lethal. To explore this, we performed a small molecule screen of 160 clinically-relevant inhibitors in PC9-RIT1M90I and PC9-KRASG12V cells. Intriguingly, RIT1M90I-mutant cells were more sensitive than RAS-mutant cells to alisertib and barasertib, inhibitors of Aurora kinase A and B, respectively. Furthermore, alisertib or barasertib treatment abrogated soft agar colony formation in RIT1M90I-mutant cells but not in RAS-mutant cells. Together with our functional genomic analysis, we propose a model whereby expression of RIT1M90I weakens the SAC, thereby accelerating mitosis, increasing the abundance of mitotic abnormalities, and rendering cells vulnerable to genetic knockdown of SAC genes or small molecule inhibition of Aurora kinases A/B. Citation Format: Amanda Riley, Athea Vichas, Naomi T. Nkinsi, Phoebe C. Parrish, Shriya Kamlapurkar, Alice H. Berger. The spindle assembly checkpoint as a therapeutic vulnerability in RIT1-mutant lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2269.

While advancements in genome sequencing have identified millions of somatic mutations in cancer, their functional impact is poorly understood. We previously developed the expression-based variant impact phenotyping (eVIP) method to use gene expression data to characterize the function of gene variants. The eVIP method uses a decision tree-based algorithm to predict the functional impact of somatic variants by comparing gene expression signatures induced by introduction of wild-type versus mutant cDNAs in cell lines. The method distinguishes between variants that are gain-of-function, loss-of-function, change-of-function, or neutral. We present eVIP2, software that allows for pathway analysis (eVIP Pathways) and usage with RNA-seq data. To demonstrate the eVIP2 software and approach, we characterized two recurrent frameshift variants in RNF43, a negative regulator of Wnt signaling, frequently mutated in colorectal, gastric and endometrial cancer. RNF43 WT, RNF43 R117fs, RNF43 G659fs, or GFP control cDNA were overexpressed in HEK293T cells. Analysis with eVIP2 predicted that the frameshift at position 117 was a loss-of-function mutation, as expected. The second frameshift at position 659, was, surprisingly, predicted to be a gain-of-function mutation. Additional eVIP Pathways analysis of RNF43 G659fs predicted 10 pathways to be significantly altered, including TNF alpha via NFKB signaling, KRAS signaling, and hypoxia. To validate these predictions, we performed reporter assays and found that all eVIP2 impactful pathways tested in the assay were activated by expression of RNF43 G659fs, but not by expression of RNF43 WT, supporting that RNF43 G659fs is a gain-of-function mutation and its effect on the identified pathways. The eVIP2 method is an important step towards overcoming the current challenge of variant interpretation in the implementation of precision medicine. eVIP2 is available at https://github.com/BrooksLabUCSC/eVIP2.

Hematopoietic stem cell (HSC) gene therapy has the potential to cure many genetic, malignant and infectious diseases. We have shown in a nonhuman primate (NHP) HSC gene therapy and transplantation model that the CD34+CD90+ cell fraction was exclusively responsible for multilineage engraftment and hematopoietic reconstitution. Here we show the translational potential of this HSC-enriched CD34 subset for lentivirus-mediated gene therapy. Alternative HSC-enrichment strategies include the purification of CD133+ cells or CD38low/- subsets of CD34+ cells from human blood products. We directly compared these strategies to the isolation of CD90+ cells using a GMP-grade flow-sorting protocol with clinical applicability. We show that CD90+ cell selection results in 40-fold fewer target cells in comparison to CD133+ or CD38low/- CD34 subsets without compromising the engraftment potential in vivo. Single cell RNA sequencing confirmed nearly complete depletion of lineage committed progenitor cells in CD90+ fractions compared to alternative selections. Importantly, lentiviral transduction efficiency in purified CD90+ cells resulted in up to 3-fold higher levels of engrafted gene-modified blood cells. These studies should have important implications for the manufacturing of patient-specific HSC gene therapy and genome editing products.

Background Antigen-detecting rapid diagnostic tests (Ag-RDTs) for the detection of SARS-CoV-2 offer new opportunities for testing in the context of the COVID-19 pandemic. Nasopharyngeal swabs (NPS) are the reference sample type, but oropharyngeal swabs (OPS) may be a more acceptable sample type in some patients. Methods We conducted a prospective study in a single screening center to assess the diagnostic performance of the Panbio™ COVID-19 Ag Rapid Test (Abbott) on OPS compared with reverse-transcription quantitative PCR (RT-qPCR) using NPS during the second pandemic wave in Switzerland. Results 402 outpatients were enrolled in a COVID-19 screening center, of whom 168 (41.8%) had a positive RT-qPCR test. The oropharyngeal Ag-RDT clinical sensitivity compared to nasopharyngeal RT-qPCR was 81% (95%CI: 74.2–86.6). Two false positives were noted out of the 234 RT-qPCR negative individuals, which resulted in a clinical specificity of 99.1% (95%CI: 96.9–99.9) for the Ag-RDT. For cycle threshold values ≤ 26.7 (≥ 1E6 SARS-CoV-2 genomes copies/mL, a presumed cut-off for infectious virus), 96.3% sensitivity (95%CI: 90.7–99.0%) was obtained with the Ag-RDT using OPS. Interpretation Based on our findings, the diagnostic performance of the Panbio™ Covid-19 RDT with OPS samples, if taken by a trained person and high requirements regarding quality of the specimen, meet the criteria required by the WHO for Ag-RDTs (sensitivity ≥80% and specificity ≥97%) in a high incidence setting in symptomatic individuals.

To compare lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SqCC) and to identify new drivers of lung carcinogenesis, we examined the exome sequences and copy number profiles of 660 lung ADC and 484 lung SqCC tumor-normal pairs. Recurrent alterations in lung SqCCs were more similar to those of other squamous carcinomas than to alterations in lung ADCs. New significantly mutated genes included PPP3CA, DOT1L, and FTSJD1 in lung ADC, RASA1 in lung SqCC, and KLF5, EP300, and CREBBP in both tumor types. New amplification peaks encompassed MIR21 in lung ADC, MIR205 in lung SqCC, and MAPK1 in both. Lung ADCs lacking receptor tyrosine kinase-Ras-Raf pathway alterations had mutations in SOS1, VAV1, RASA1, and ARHGAP35. Regarding neoantigens, 47% of the lung ADC and 53% of the lung SqCC tumors had at least five predicted neoepitopes. Although targeted therapies for lung ADC and SqCC are largely distinct, immunotherapies may aid in treatment for both subtypes.