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      WRN Helicase is a Synthetic Lethal Target in Microsatellite Unstable Cancers

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Summary paragraph:

          Synthetic lethality, an interaction whereby the co-occurrence of two genetic events leads to cell death but one event alone does not, can be exploited for cancer therapeutics 1 . DNA repair processes represent attractive synthetic lethal targets since many cancers exhibit an impaired DNA repair pathway, which can lead to dependence on specific repair proteins 2 . The success of poly (ADP-ribose) polymerase 1 (PARP-1) inhibitors in homologous recombination-deficient cancers highlights the potential of this approach 3 . Hypothesizing that other DNA repair defects would give rise to synthetic lethal relationships, we queried dependencies in cancers with microsatellite instability (MSI), which results from deficient DNA mismatch repair (dMMR). Here we analyzed data from large-scale CRISPR/Cas9 knockout and RNA interference (RNAi) silencing screens and found that the RecQ DNA helicase WRN was selectively essential in MSI models in vitro and in vivo, yet dispensable in microsatellite stable (MSS) models. WRN depletion induced double-strand DNA breaks (DSB) and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models required the helicase activity, but not the exonuclease activity of WRN. These findings expose WRN as a synthetic lethal vulnerability and promising drug target for MSI cancers.

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          Most cited references31

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          Is Open Access

          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            The ATM protein kinase: regulating the cellular response to genotoxic stress, and more.

            The protein kinase ataxia-telangiectasia mutated (ATM) is best known for its role as an apical activator of the DNA damage response in the face of DNA double-strand breaks (DSBs). Following induction of DSBs, ATM mobilizes one of the most extensive signalling networks that responds to specific stimuli and modifies directly or indirectly a broad range of targets. Although most ATM research has focused on this function, evidence suggests that ATM-mediated phosphorylation has a role in the response to other types of genotoxic stress. Moreover, it has become apparent that ATM is active in other cell signalling pathways involved in maintaining cellular homeostasis.
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              Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening

              Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.
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                Author and article information

                Contributors
                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                9 March 2019
                10 April 2019
                April 2019
                10 October 2019
                : 568
                : 7753
                : 551-556
                Affiliations
                Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA., Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA., Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Departments of Laboratory Medicine, Pathology, and Molecular Biophysics and Biochemistry Yale University School of Medicine, New Haven, Connecticut, USA
                Department of Environmental Health. Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Massachusetts General Hospital Cancer Center, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Department of Medicine, Division of Gastroenterology, Duke University, Durham, North Carolina, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Environmental Health. Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
                Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Massachusetts General Hospital Cancer Center, Boston, Massachusetts, USA
                Departments of Laboratory Medicine, Pathology, and Molecular Biophysics and Biochemistry Yale University School of Medicine, New Haven, Connecticut, USA
                Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA., Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA., Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
                Author notes

                These authors contributed equally: Edmond M. Chan and Tsukasa Shibue

                Author Contributions

                E.M.C., T.S., F.V., and A.J.B. initiated the project, designed, and supervised the research plan. J.M.M., M.Gh., Y.L., and Y.E.M. performed computational analysis of the CCLE and cancer dependency datasets under the supervision of D.E.R, J.S.B., G.G., T.R.G., A.T., F.V., and A.J.B.. E.M.C., T.S., B.G., and J.S.M. performed the viability experiments to validate the cancer dependency dataset findings with help from M.S., A.A., S.A.O., and L.L.. The rescue experiments with WRN overexpression were performed by E.M.C. and B.G.. The HCT116 viability experiments were performed by T.S. and B.G.. N.D., A.G., T.L., and Y.Z. performed in vivo experiments. The patient derived organoids were established by J.S.B., Y.Y.T., M.Gi., R.D., and P.K.. Organoid experiments were conducted by E.M.C. and T.S. with help from S.R., R.W.S.N, and J.R.. RNA extraction for mRNA-seq was performed by T.S. and analyzed by J.M.M. and M.I.. J.S.M. and T.S. performed and analyzed the cell cycle and apoptosis assays. Immunoblots were performed by T.S., E.M.C., B.G., and J.S.M. Immunofluorescence were performed by T.S., E.M.C., J.B.L., J.L., E.A.R, and E.R. and analyzed by T.S., E.M.C., J.B.L., J.L., M.A., and A.D.A.. S.C. and P.G. performed the telomere PNA-FISH experiment. Z.N. and C.G.P. performed the fluorescence-based flow-cytometric host cell reactivation assay. E.M.C., T.S., J.M.M., F.V., and A.J.B. wrote the manuscript. All the authors edited and approved the manuscript.

                Corresponding authors: Correspondence to Francisca Vazquez ( vazquez@ 123456broadinstitute.org ) or Adam Bass ( adam_bass@ 123456dfci.harvard.edu )
                Article
                NIHMS1522798
                10.1038/s41586-019-1102-x
                6580861
                30971823
                126a4be2-77f9-4d96-acf1-a42e7adcb32f

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