48 datasets found
  1. t

    CRISPR SCREEN: Riba A (2017) - 3-PMID28215525 (Explicit Modeling of...

    • orcs.thebiogrid.org
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    Updated Sep 30, 2018
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    BioGRID Project (2018). CRISPR SCREEN: Riba A (2017) - 3-PMID28215525 (Explicit Modeling of siRNA-Dependent On- and Off-Target Repression Improves the Interpretation of Screening Results.) [Dataset]. https://orcs.thebiogrid.org/Screen/174
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    Dataset updated
    Sep 30, 2018
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Riba A (2017) - 3-PMID28215525 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Riba A (2017)] Explicit Modeling of siRNA-Dependent On- and Off-Target Repression Improves the Interpretation of Screening Results.|ABSTRACT: RNAi is broadly used to map gene regulatory networks, but the identification of genes that are responsible for the observed phenotypes is challenging, as small interfering RNAs (siRNAs) simultaneously downregulate the intended on targets and many partially complementary off targets. Additionally, the scarcity of publicly available control datasets hinders the development and comparative evaluation of computational methods for analyzing the data. Here, we introduce PheLiM (https://github.com/andreariba/PheLiM), a method that uses predictions of siRNA on- and off-target downregulation to infer gene-specific contributions to phenotypes. To assess the performance of PheLiM, we carried out siRNA- and CRISPR/Cas9-based genome-wide screening of two well-characterized pathways, bone morphogenetic protein (BMP) and nuclear factor κB (NF-κB), and we reanalyzed publicly available siRNA screens. We demonstrate that PheLiM has the overall highest accuracy and most reproducible results compared to other available methods. PheLiM can accommodate various methods for predicting siRNA off targets and is broadly applicable to the identification of genes underlying complex phenotypes.

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    CRISPR SCREEN: Zhao Y (2020) - 2-PMID33189395 (Applying genome-wide CRISPR...

    • orcs.thebiogrid.org
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    Updated Dec 13, 2021
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    BioGRID Project (2021). CRISPR SCREEN: Zhao Y (2020) - 2-PMID33189395 (Applying genome-wide CRISPR to identify known and novel genes and pathways that modulate formaldehyde toxicity.) [Dataset]. https://orcs.thebiogrid.org/Screen/1397
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    zipAvailable download formats
    Dataset updated
    Dec 13, 2021
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Zhao Y (2020) - 2-PMID33189395 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Zhao Y (2020)] Applying genome-wide CRISPR to identify known and novel genes and pathways that modulate formaldehyde toxicity.|ABSTRACT: Formaldehyde (FA), a ubiquitous environmental pollutant, is classified as a Group I human carcinogen by the International Agency for Research on Cancer. Previously, we reported that FA induced hematotoxicity and chromosomal aneuploidy in exposed workers and toxicity in bone marrow and hematopoietic stem cells of experimental animals. Using functional toxicogenomic profiling in yeast, we identified genes and cellular processes modulating eukaryotic FA cytotoxicity. Although we validated some of these findings in yeast, many specific genes, pathways and mechanisms of action of FA in human cells are not known. In the current study, we applied genome-wide, loss-of-function CRISPR screening to identify modulators of FA toxicity in the human hematopoietic K562 cell line. We assessed the cellular genetic determinants of susceptibility and resistance to FA at 40, 100 and 150 μM (IC10, IC20 and IC60, respectively) at two time points, day 8 and day 20. We identified multiple candidate genes that increase sensitivity (e.g. ADH5, ESD and FANC family) or resistance (e.g. FASN and KDM6A) to FA when disrupted. Pathway analysis revealed a major role for the FA metabolism and Fanconi anemia pathway in FA tolerance, consistent with findings from previous studies. Additional network analyses revealed potential new roles for one-carbon metabolism, fatty acid synthesis and mTOR signaling in modulating FA toxicity. Validation of these novel findings will further enhance our understanding of FA toxicity in human cells. Our findings support the utility of CRISPR-based functional genomics screening of environmental chemicals.

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    CRISPR SCREEN: Jost M (2017) - 1-PMID28985505 (Combined CRISPRi/a-Based...

    • orcs.thebiogrid.org
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    Updated Jan 1, 2011
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    BioGRID Project (2011). CRISPR SCREEN: Jost M (2017) - 1-PMID28985505 (Combined CRISPRi/a-Based Chemical Genetic Screens Reveal that Rigosertib Is a Microtubule-Destabilizing Agent.) [Dataset]. https://orcs.thebiogrid.org/Screen/1176
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    xlsx, zipAvailable download formats
    Dataset updated
    Jan 1, 2011
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Jost M (2017) - 1-PMID28985505 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Jost M (2017)] Combined CRISPRi/a-Based Chemical Genetic Screens Reveal that Rigosertib Is a Microtubule-Destabilizing Agent.|ABSTRACT: Chemical libraries paired with phenotypic screens can now readily identify compounds with therapeutic potential. A central limitation to exploiting these compounds, however, has been in identifying their relevant cellular targets. Here, we present a two-tiered CRISPR-mediated chemical-genetic strategy for target identification: combined genome-wide knockdown and overexpression screening as well as focused, comparative chemical-genetic profiling. Application of these strategies to rigosertib, a drug in phase 3 clinical trials for high-risk myelodysplastic syndrome whose molecular target had remained controversial, pointed singularly to microtubules as rigosertib's target. We showed that rigosertib indeed directly binds to and destabilizes microtubules using cell biological, in vitro, and structural approaches. Finally, expression of tubulin with a structure-guided mutation in the rigosertib-binding pocket conferred resistance to rigosertib, establishing that rigosertib kills cancer cells by destabilizing microtubules. These results demonstrate the power of our chemical-genetic screening strategies for pinpointing the physiologically relevant targets of chemical agents.

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    CRISPR SCREEN: Schubert OT (2022) - 6-PMID36326816 (Genome-wide base editor...

    • orcs.thebiogrid.org
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    Updated Jun 23, 2024
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    BioGRID Project (2024). CRISPR SCREEN: Schubert OT (2022) - 6-PMID36326816 (Genome-wide base editor screen identifies regulators of protein abundance in yeast.) [Dataset]. https://orcs.thebiogrid.org/Screen/1925
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    xlsx, zipAvailable download formats
    Dataset updated
    Jun 23, 2024
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Schubert OT (2022) - 6-PMID36326816 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Schubert OT (2022)] Genome-wide base editor screen identifies regulators of protein abundance in yeast.|ABSTRACT: Proteins are key molecular players in a cell, and their abundance is extensively regulated not just at the level of gene expression but also post-transcriptionally. Here, we describe a genetic screen in yeast that enables systematic characterization of how protein abundance regulation is encoded in the genome. The screen combines a CRISPR/Cas9 base editor to introduce point mutations with fluorescent tagging of endogenous proteins to facilitate a flow-cytometric readout. We first benchmarked base editor performance in yeast with individual gRNAs as well as in positive and negative selection screens. We then examined the effects of 16,452 genetic perturbations on the abundance of eleven proteins representing a variety of cellular functions. We uncovered hundreds of regulatory relationships, including a novel link between the GAPDH isoenzymes Tdh1/2/3 and the Ras/PKA pathway. Many of the identified regulators are specific to one of the eleven proteins, but we also found genes that, upon perturbation, affected the abundance of most of the tested proteins. While the more specific regulators usually act transcriptionally, broad regulators often have roles in protein translation. Overall, our novel screening approach provides unprecedented insights into the components, scale and connectedness of the protein regulatory network.

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    CRISPR SCREEN: Flynn RA (2021) - 14-PMID33743211 (Discovery and functional...

    • orcs.thebiogrid.org
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    Updated Dec 16, 2021
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    BioGRID Project (2021). CRISPR SCREEN: Flynn RA (2021) - 14-PMID33743211 (Discovery and functional interrogation of SARS-CoV-2 RNA-host protein interactions.) [Dataset]. https://orcs.thebiogrid.org/Screen/1611
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    zip, csvAvailable download formats
    Dataset updated
    Dec 16, 2021
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Flynn RA (2021) - 14-PMID33743211 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Flynn RA (2021)] Discovery and functional interrogation of SARS-CoV-2 RNA-host protein interactions.|ABSTRACT: SARS-CoV-2 is the cause of a pandemic with growing global mortality. Using comprehensive identification of RNA-binding proteins by mass spectrometry (ChIRP-MS), we identified 309 host proteins that bind the SARS-CoV-2 RNA during active infection. Integration of this data with ChIRP-MS data from three other RNA viruses defined viral specificity of RNA-host protein interactions. Targeted CRISPR screens revealed that the majority of functional RNA-binding proteins protect the host from virus-induced cell death, and comparative CRISPR screens across seven RNA viruses revealed shared and SARS-specific antiviral factors. Finally, by combining the RNA-centric approach and functional CRISPR screens, we demonstrated a physical and functional connection between SARS-CoV-2 and mitochondria, highlighting this organelle as a general platform for antiviral activity. Altogether, these data provide a comprehensive catalog of functional SARS-CoV-2 RNA-host protein interactions, which may inform studies to understand the host-virus interface and nominate host pathways that could be targeted for therapeutic benefit.

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    CRISPR SCREEN: Hart T (2015) - 4-PMID26627737 (High-Resolution CRISPR...

    • orcs.thebiogrid.org
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    Updated Sep 30, 2018
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    BioGRID Project (2018). CRISPR SCREEN: Hart T (2015) - 4-PMID26627737 (High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities.) [Dataset]. https://orcs.thebiogrid.org/Screen/28
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    Dataset updated
    Sep 30, 2018
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Hart T (2015) - 4-PMID26627737 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Hart T (2015)] High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities.|ABSTRACT: The ability to perturb genes in human cells is crucial for elucidating gene function and holds great potential for finding therapeutic targets for diseases such as cancer. To extend the catalog of human core and context-dependent fitness genes, we have developed a high-complexity second-generation genome-scale CRISPR-Cas9 gRNA library and applied it to fitness screens in five human cell lines. Using an improved Bayesian analytical approach, we consistently discover 5-fold more fitness genes than were previously observed. We present a list of 1,580 human core fitness genes and describe their general properties. Moreover, we demonstrate that context-dependent fitness genes accurately recapitulate pathway-specific genetic vulnerabilities induced by known oncogenes and reveal cell-type-specific dependencies for specific receptor tyrosine kinases, even in oncogenic KRAS backgrounds. Thus, rigorous identification of human cell line fitness genes using a high-complexity CRISPR-Cas9 library affords a high-resolution view of the genetic vulnerabilities of a cell.

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    CRISPR SCREEN: Lin K (2024) - 4-PMID38291084 (A scalable platform for...

    • orcs.thebiogrid.org
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    Updated Feb 2, 2025
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    BioGRID Project (2025). CRISPR SCREEN: Lin K (2024) - 4-PMID38291084 (A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds.) [Dataset]. https://orcs.thebiogrid.org/Screen/2327
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    zip, xlsxAvailable download formats
    Dataset updated
    Feb 2, 2025
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Lin K (2024) - 4-PMID38291084 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Lin K (2024)] A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds.|ABSTRACT: Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds' known modes-of-action (MoA) were enriched among the compounds' CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles.

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    CRISPR SCREEN: Feng X (2022) - 14-PMID35559673 (Genome-wide CRISPR screens...

    • orcs.thebiogrid.org
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    Updated Nov 5, 2023
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    BioGRID Project (2023). CRISPR SCREEN: Feng X (2022) - 14-PMID35559673 (Genome-wide CRISPR screens using isogenic cells reveal vulnerabilities conferred by loss of tumor suppressors.) [Dataset]. https://orcs.thebiogrid.org/Screen/1858
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    Dataset updated
    Nov 5, 2023
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Feng X (2022) - 14-PMID35559673 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Feng X (2022)] Genome-wide CRISPR screens using isogenic cells reveal vulnerabilities conferred by loss of tumor suppressors.|ABSTRACT: Exploiting cancer vulnerabilities is critical for the discovery of anticancer drugs. However, tumor suppressors cannot be directly targeted because of their loss of function. To uncover specific vulnerabilities for cells with deficiency in any given tumor suppressor(s), we performed genome-scale CRISPR loss-of-function screens using a panel of isogenic knockout cells we generated for 12 common tumor suppressors. Here, we provide a comprehensive and comparative dataset for genetic interactions between the whole-genome protein-coding genes and a panel of tumor suppressor genes, which allows us to uncover known and new high-confidence synthetic lethal interactions. Mining this dataset, we uncover essential paralog gene pairs, which could be a common mechanism for interpreting synthetic lethality. Moreover, we propose that some tumor suppressors could be targeted to suppress proliferation of cells with deficiency in other tumor suppressors. This dataset provides valuable information that can be further exploited for targeted cancer therapy.

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    CRISPR SCREEN: Wei J (2020) - 7-PMID33147444 (Genome-wide CRISPR Screens...

    • orcs.thebiogrid.org
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    Updated Nov 13, 2021
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    BioGRID Project (2021). CRISPR SCREEN: Wei J (2020) - 7-PMID33147444 (Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection.) [Dataset]. https://orcs.thebiogrid.org/Screen/1416
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    xlsx, zipAvailable download formats
    Dataset updated
    Nov 13, 2021
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Wei J (2020) - 7-PMID33147444 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Wei J (2020)] Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection.|ABSTRACT: Identification of host genes essential for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may reveal novel therapeutic targets and inform our understanding of coronavirus disease 2019 (COVID-19) pathogenesis. Here we performed genome-wide CRISPR screens in Vero-E6 cells with SARS-CoV-2, Middle East respiratory syndrome CoV (MERS-CoV), bat CoV HKU5 expressing the SARS-CoV-1 spike, and vesicular stomatitis virus (VSV) expressing the SARS-CoV-2 spike. We identified known SARS-CoV-2 host factors, including the receptor ACE2 and protease Cathepsin L. We additionally discovered pro-viral genes and pathways, including HMGB1 and the SWI/SNF chromatin remodeling complex, that are SARS lineage and pan-coronavirus specific, respectively. We show that HMGB1 regulates ACE2 expression and is critical for entry of SARS-CoV-2, SARS-CoV-1, and NL63. We also show that small-molecule antagonists of identified gene products inhibited SARS-CoV-2 infection in monkey and human cells, demonstrating the conserved role of these genetic hits across species. This identifies potential therapeutic targets for SARS-CoV-2 and reveals SARS lineage-specific and pan-CoV host factors that regulate susceptibility to highly pathogenic CoVs.

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    CRISPR SCREEN: Lawson KA (2020) - 18-PMID32968282 (Functional genomic...

    • orcs.thebiogrid.org
    zip
    Updated Oct 25, 2021
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    BioGRID Project (2021). CRISPR SCREEN: Lawson KA (2020) - 18-PMID32968282 (Functional genomic landscape of cancer-intrinsic evasion of killing by T cells.) [Dataset]. https://orcs.thebiogrid.org/Screen/1276
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    Dataset updated
    Oct 25, 2021
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Lawson KA (2020) - 18-PMID32968282 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Lawson KA (2020)] Functional genomic landscape of cancer-intrinsic evasion of killing by T cells.|ABSTRACT: The genetic circuits that allow cancer cells to evade destruction by the host immune system remain poorly understood. Here, to identify a phenotypically robust core set of genes and pathways that enable cancer cells to evade killing mediated by cytotoxic T lymphocytes (CTLs), we performed genome-wide CRISPR screens across a panel of genetically diverse mouse cancer cell lines that were cultured in the presence of CTLs. We identify a core set of 182 genes across these mouse cancer models, the individual perturbation of which increases either the sensitivity or the resistance of cancer cells to CTL-mediated toxicity. Systematic exploration of our dataset using genetic co-similarity reveals the hierarchical and coordinated manner in which genes and pathways act in cancer cells to orchestrate their evasion of CTLs, and shows that discrete functional modules that control the interferon response and tumour necrosis factor (TNF)-induced cytotoxicity are dominant sub-phenotypes. Our data establish a central role for genes that were previously identified as negative regulators of the type-II interferon response (for example, Ptpn2, Socs1 and Adar1) in mediating CTL evasion, and show that the lipid-droplet-related gene Fitm2 is required for maintaining cell fitness after exposure to interferon-γ (IFNγ). In addition, we identify the autophagy pathway as a conserved mediator of the evasion of CTLs by cancer cells, and show that this pathway is required to resist cytotoxicity induced by the cytokines IFNγ and TNF. Through the mapping of cytokine- and CTL-based genetic interactions, together with in vivo CRISPR screens, we show how the pleiotropic effects of autophagy control cancer-cell-intrinsic evasion of killing by CTLs and we highlight the importance of these effects within the tumour microenvironment. Collectively, these data expand our knowledge of the genetic circuits that are involved in the evasion of the immune system by cancer cells, and highlight genetic interactions that contribute to phenotypes associated with escape from killing by CTLs.

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    CRISPR SCREEN: MacLeod G (2019) - 9-PMID30995489 (Genome-Wide CRISPR-Cas9...

    • orcs.thebiogrid.org
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    Updated May 16, 2022
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    BioGRID Project (2022). CRISPR SCREEN: MacLeod G (2019) - 9-PMID30995489 (Genome-Wide CRISPR-Cas9 Screens Expose Genetic Vulnerabilities and Mechanisms of Temozolomide Sensitivity in Glioblastoma Stem Cells.) [Dataset]. https://orcs.thebiogrid.org/Screen/1028
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    Dataset updated
    May 16, 2022
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results MacLeod G (2019) - 9-PMID30995489 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [MacLeod G (2019)] Genome-Wide CRISPR-Cas9 Screens Expose Genetic Vulnerabilities and Mechanisms of Temozolomide Sensitivity in Glioblastoma Stem Cells.|ABSTRACT: Glioblastoma therapies have remained elusive due to limitations in understanding mechanisms of growth and survival of the tumorigenic population. Using CRISPR-Cas9 approaches in patient-derived GBM stem cells (GSCs) to interrogate function of the coding genome, we identify actionable pathways responsible for growth, which reveal the gene-essential circuitry of GBM stemness and proliferation. In particular, we characterize members of the SOX transcription factor family, SOCS3, USP8, and DOT1L, and protein ufmylation as important for GSC growth. Additionally, we reveal mechanisms of temozolomide resistance that could lead to combination strategies. By reaching beyond static genome analysis of bulk tumors, with a genome-wide functional approach, we reveal genetic dependencies within a broad range of biological processes to provide increased understanding of GBM growth and treatment resistance.

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    BIOGRID CURATED DATA FOR ORC-5 (Caenorhabditis elegans)

    • thebiogrid.org
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    Updated Jul 2, 2024
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    BioGRID Project (2024). BIOGRID CURATED DATA FOR ORC-5 (Caenorhabditis elegans) [Dataset]. https://thebiogrid.org/43065/table/caenorhabditis-elegans/orc-5.html
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    Dataset updated
    Jul 2, 2024
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Protein-Protein, Genetic, and Chemical Interactions for ORC-5 (Caenorhabditis elegans) curated by BioGRID (https://thebiogrid.org); DEFINITION: Protein ORC-5

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    CRISPR SCREEN: Viswanatha R (2018) - 2-PMID30051818 (Pooled genome-wide...

    • orcs.thebiogrid.org
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    Updated Nov 1, 2020
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    BioGRID Project (2020). CRISPR SCREEN: Viswanatha R (2018) - 2-PMID30051818 (Pooled genome-wide CRISPR screening for basal and context-specific fitness gene essentiality in cells.) [Dataset]. https://orcs.thebiogrid.org/Screen/634
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    Dataset updated
    Nov 1, 2020
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Viswanatha R (2018) - 2-PMID30051818 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Viswanatha R (2018)] Pooled genome-wide CRISPR screening for basal and context-specific fitness gene essentiality in cells.|ABSTRACT: Genome-wide screens in cells have offered numerous insights into gene function, yet a major limitation has been the inability to stably deliver large multiplexed DNA libraries to cultured cells allowing barcoded pooled screens. Here, we developed a site-specific integration strategy for library delivery and performed a genome-wide CRISPR knockout screen in S2R+ cells. Under basal growth conditions, 1235 genes were essential for cell fitness at a false-discovery rate of 5%, representing the highest-resolution fitness gene set yet assembled for , including 407 genes which likely duplicated along the vertebrate lineage and whose orthologs were underrepresented in human CRISPR screens. We additionally performed context-specific fitness screens for resistance to or synergy with trametinib, a Ras/ERK/ETS inhibitor, or rapamycin, an mTOR inhibitor, and identified key regulators of each pathway. The results present a novel, scalable, and versatile platform for functional genomic screens in invertebrate cells.

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    BIOGRID CURATED DATA FOR ORC-4 (Caenorhabditis elegans)

    • thebiogrid.org
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    Updated Jul 2, 2024
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    BioGRID Project (2024). BIOGRID CURATED DATA FOR ORC-4 (Caenorhabditis elegans) [Dataset]. https://thebiogrid.org/41676/table/caenorhabditis-elegans/orc-4.html
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    zipAvailable download formats
    Dataset updated
    Jul 2, 2024
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Protein-Protein, Genetic, and Chemical Interactions for ORC-4 (Caenorhabditis elegans) curated by BioGRID (https://thebiogrid.org); DEFINITION: ORC (Origin Recognition Complex) subunit

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    CRISPR SCREEN: Chai AWY (2020) - 13-PMID32990596 (Genome-wide CRISPR screens...

    • orcs.thebiogrid.org
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    Updated Jul 28, 2022
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    BioGRID Project (2022). CRISPR SCREEN: Chai AWY (2020) - 13-PMID32990596 (Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway.) [Dataset]. https://orcs.thebiogrid.org/Screen/1304
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    Dataset updated
    Jul 28, 2022
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Chai AWY (2020) - 13-PMID32990596 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Chai AWY (2020)] Genome-wide CRISPR screens of oral squamous cell carcinoma reveal fitness genes in the Hippo pathway.|ABSTRACT: 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 favourable response towards 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.

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    CRISPR SCREEN: Jiang C (2019) - 1-PMID31365872 (CRISPR/Cas9 Screens Reveal...

    • orcs.thebiogrid.org
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    Updated Dec 19, 2020
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    BioGRID Project (2020). CRISPR SCREEN: Jiang C (2019) - 1-PMID31365872 (CRISPR/Cas9 Screens Reveal Multiple Layers of B cell CD40 Regulation.) [Dataset]. https://orcs.thebiogrid.org/Screen/1041
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    Dataset updated
    Dec 19, 2020
    Dataset authored and provided by
    BioGRID Project
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    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Jiang C (2019) - 1-PMID31365872 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Jiang C (2019)] CRISPR/Cas9 Screens Reveal Multiple Layers of B cell CD40 Regulation.|ABSTRACT: CD40 has major roles in B cell development, activation, and germinal center responses. CD40 hypoactivity causes immunodeficiency whereas its overexpression causes autoimmunity and lymphomagenesis. To systematically identify B cell autonomous CD40 regulators, we use CRISPR/Cas9 genome-scale screens in Daudi B cells stimulated by multimeric CD40 ligand. These highlight known CD40 pathway components and reveal multiple additional mechanisms regulating CD40. The nuclear ubiquitin ligase FBXO11 supports CD40 expression by targeting repressors CTBP1 and BCL6. FBXO11 knockout decreases primary B cell CD40 abundance and impairs class-switch recombination, suggesting that frequent lymphoma monoallelic FBXO11 mutations may balance BCL6 increase with CD40 loss. At the mRNA level, CELF1 controls exon splicing critical for CD40 activity, while the N6-adenosine methyltransferase WTAP negatively regulates CD40 mRNA abundance. At the protein level, ESCRT negatively regulates activated CD40 levels while the negative feedback phosphatase DUSP10 limits downstream MAPK responses. These results serve as a resource for future studies and highlight potential therapeutic targets.

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    CRISPR SCREEN: Tsujino T (2023) - 5-PMID36650183 (CRISPR screens reveal...

    • orcs.thebiogrid.org
    xlsx, zip
    Updated May 12, 2024
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    BioGRID Project (2024). CRISPR SCREEN: Tsujino T (2023) - 5-PMID36650183 (CRISPR screens reveal genetic determinants of PARP inhibitor sensitivity and resistance in prostate cancer.) [Dataset]. https://orcs.thebiogrid.org/Screen/2109
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    Dataset updated
    May 12, 2024
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Tsujino T (2023) - 5-PMID36650183 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Tsujino T (2023)] CRISPR screens reveal genetic determinants of PARP inhibitor sensitivity and resistance in prostate cancer.|ABSTRACT: Prostate cancer harboring BRCA1/2 mutations are often exceptionally sensitive to PARP inhibitors. However, genomic alterations in other DNA damage response genes have not been consistently predictive of clinical response to PARP inhibition. Here, we perform genome-wide CRISPR-Cas9 knockout screens in BRCA1/2-proficient prostate cancer cells and identify previously unknown genes whose loss has a profound impact on PARP inhibitor response. Specifically, MMS22L deletion, frequently observed (up to 14%) in prostate cancer, renders cells hypersensitive to PARP inhibitors by disrupting RAD51 loading required for homologous recombination repair, although this response is TP53-dependent. Unexpectedly, loss of CHEK2 confers resistance rather than sensitivity to PARP inhibition through increased expression of BRCA2, a target of CHEK2-TP53-E2F7-mediated transcriptional repression. Combined PARP and ATR inhibition overcomes PARP inhibitor resistance caused by CHEK2 loss. Our findings may inform the use of PARP inhibitors beyond BRCA1/2-deficient tumors and support reevaluation of current biomarkers for PARP inhibition in prostate cancer.

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    CRISPR SCREEN: Chan K (2022) - 4-PMID36597481 (Survival-based CRISPR genetic...

    • orcs.thebiogrid.org
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    Updated Apr 28, 2024
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    BioGRID Project (2024). CRISPR SCREEN: Chan K (2022) - 4-PMID36597481 (Survival-based CRISPR genetic screens across a panel of permissive cell lines identify common and cell-specific SARS-CoV-2 host factors.) [Dataset]. https://orcs.thebiogrid.org/Screen/2064
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    Dataset updated
    Apr 28, 2024
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Chan K (2022) - 4-PMID36597481 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Chan K (2022)] Survival-based CRISPR genetic screens across a panel of permissive cell lines identify common and cell-specific SARS-CoV-2 host factors.|ABSTRACT: SARS-CoV-2 depends on host cell components for infection and replication. Identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection and replication. If druggable, host factor dependencies may present an attractive strategy for anti-viral therapy. In this study, we performed genome wide CRISPR knockout screens in Vero E6 cells and four human cell lines including Calu-3, UM-UC-4, HEK-293 and HuH-7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only , the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while other host genes identified were largely cell line specific, including known factors and . Several of the discovered host-dependency factors converged on pathways involved in cell signalling, immune-related pathways, and chromatin modification. Notably, the chromatin modifier gene in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed.

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    CRISPR SCREEN: Meyers RM (2017) - 302-PMID29083409 (Computational correction...

    • orcs.thebiogrid.org
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    Updated Nov 30, 2018
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    BioGRID Project (2018). CRISPR SCREEN: Meyers RM (2017) - 302-PMID29083409 (Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells.) [Dataset]. https://orcs.thebiogrid.org/Screen/488
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    zip, csvAvailable download formats
    Dataset updated
    Nov 30, 2018
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Meyers RM (2017) - 302-PMID29083409 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Meyers RM (2017)] Computational correction of copy number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells.|ABSTRACT: The CRISPR-Cas9 system has revolutionized gene editing both at single genes and in multiplexed loss-of-function screens, thus enabling precise genome-scale identification of genes essential for proliferation and survival of cancer cells. However, previous studies have reported that a gene-independent antiproliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, thereby leading to false-positive results in copy number-amplified regions. We developed CERES, a computational method to estimate gene-dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy number-specific effect. In our efforts to define a cancer dependency map, we performed genome-scale CRISPR-Cas9 essentiality screens across 342 cancer cell lines and applied CERES to this data set. We found that CERES decreased false-positive results and estimated sgRNA activity for both this data set and previously published screens performed with different sgRNA libraries. We further demonstrate the utility of this collection of screens, after CERES correction, for identifying cancer-type-specific vulnerabilities.

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    CRISPR SCREEN: Zhu Y (2021) - 1-PMID33574281 (A genome-wide CRISPR screen...

    • orcs.thebiogrid.org
    xlsx, zip
    Updated Dec 6, 2021
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    BioGRID Project (2021). CRISPR SCREEN: Zhu Y (2021) - 1-PMID33574281 (A genome-wide CRISPR screen identifies host factors that regulate SARS-CoV-2 entry.) [Dataset]. https://orcs.thebiogrid.org/Screen/1622
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    Dataset updated
    Dec 6, 2021
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    CRISPR Screen results Zhu Y (2021) - 1-PMID33574281 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Zhu Y (2021)] A genome-wide CRISPR screen identifies host factors that regulate SARS-CoV-2 entry.|ABSTRACT: The global spread of SARS-CoV-2 is posing major public health challenges. One feature of SARS-CoV-2 spike protein is the insertion of multi-basic residues at the S1/S2 subunit cleavage site. Here, we find that the virus with intact spike (Sfull) preferentially enters cells via fusion at the plasma membrane, whereas a clone (Sdel) with deletion disrupting the multi-basic S1/S2 site utilizes an endosomal entry pathway. Using Sdel as model, we perform a genome-wide CRISPR screen and identify several endosomal entry-specific regulators. Experimental validation of hits from the CRISPR screen shows that host factors regulating the surface expression of angiotensin-converting enzyme 2 (ACE2) affect entry of Sfull virus. Animal-to-animal transmission with the Sdel virus is reduced compared to Sfull in the hamster model. These findings highlight the critical role of the S1/S2 boundary of SARS-CoV-2 spike protein in modulating virus entry and transmission and provide insights into entry of coronaviruses.

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BioGRID Project (2018). CRISPR SCREEN: Riba A (2017) - 3-PMID28215525 (Explicit Modeling of siRNA-Dependent On- and Off-Target Repression Improves the Interpretation of Screening Results.) [Dataset]. https://orcs.thebiogrid.org/Screen/174

CRISPR SCREEN: Riba A (2017) - 3-PMID28215525 (Explicit Modeling of siRNA-Dependent On- and Off-Target Repression Improves the Interpretation of Screening Results.)

Related Article
Explore at:
zipAvailable download formats
Dataset updated
Sep 30, 2018
Dataset authored and provided by
BioGRID Project
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Description

CRISPR Screen results Riba A (2017) - 3-PMID28215525 curated by BioGRID-ORCS (https://orcs.thebiogrid.org) from publication : [Riba A (2017)] Explicit Modeling of siRNA-Dependent On- and Off-Target Repression Improves the Interpretation of Screening Results.|ABSTRACT: RNAi is broadly used to map gene regulatory networks, but the identification of genes that are responsible for the observed phenotypes is challenging, as small interfering RNAs (siRNAs) simultaneously downregulate the intended on targets and many partially complementary off targets. Additionally, the scarcity of publicly available control datasets hinders the development and comparative evaluation of computational methods for analyzing the data. Here, we introduce PheLiM (https://github.com/andreariba/PheLiM), a method that uses predictions of siRNA on- and off-target downregulation to infer gene-specific contributions to phenotypes. To assess the performance of PheLiM, we carried out siRNA- and CRISPR/Cas9-based genome-wide screening of two well-characterized pathways, bone morphogenetic protein (BMP) and nuclear factor κB (NF-κB), and we reanalyzed publicly available siRNA screens. We demonstrate that PheLiM has the overall highest accuracy and most reproducible results compared to other available methods. PheLiM can accommodate various methods for predicting siRNA off targets and is broadly applicable to the identification of genes underlying complex phenotypes.

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