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      Mutational processes shape the landscape of TP53 mutations in human cancer

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          Abstract

          Unlike most tumor suppressor genes, the most common genetic alterations in TP53 are missense mutations 1, 2 . Mutant p53 protein is often abundantly expressed in cancers, and specific allelic variants exhibit dominant-negative or gain-of-function activities in experimental models 38 . To gain a systematic view of p53 function, we interrogated loss-of-function screens conducted in hundreds of human cancer cell lines and performed TP53 saturation mutagenesis screens in an isogenic pair of TP53-wild-type and -null cell lines. We found that loss or dominant-negative inhibition of p53 function reliably enhanced cellular fitness. By integrating these data with the COSMIC mutational signatures database 9, 10 , we developed a statistical model that describes the TP53 mutational spectrum as a function of the baseline probability of acquiring each mutation and the fitness advantage conferred by attenuation of p53 activity. Collectively, these observations show that widely-acting and tissue-specific mutational processes combine with phenotypic selection to dictate the frequencies of recurrent TP53 mutations.

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          Most cited references40

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Requirement for p53 and p21 to sustain G2 arrest after DNA damage.

            After DNA damage, many cells appear to enter a sustained arrest in the G2 phase of the cell cycle. It is shown here that this arrest could be sustained only when p53 was present in the cell and capable of transcriptionally activating the cyclin-dependent kinase inhibitor p21. After disruption of either the p53 or the p21 gene, gamma radiated cells progressed into mitosis and exhibited a G2 DNA content only because of a failure of cytokinesis. Thus, p53 and p21 appear to be essential for maintaining the G2 checkpoint in human cells.
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              AACR Project GENIE: Powering Precision Medicine through an International Consortium

              (2017)
              The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine.Significance: The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy. Cancer Discov; 7(8); 818-31. ©2017 AACR.See related commentary by Litchfield et al., p. 796This article is highlighted in the In This Issue feature, p. 783.
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                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nat. Genet.
                Nature genetics
                1061-4036
                1546-1718
                28 July 2018
                17 September 2018
                October 2018
                17 March 2019
                : 50
                : 10
                : 1381-1387
                Affiliations
                [1 ]Dana-Farber Cancer Institute, Boston, Massachusetts, USA
                [2 ]Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
                [3 ]Harvard Medical School, Boston, Massachusetts, USA
                [4 ]Department of Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
                [5 ]Massachusetts General Hospital Center for Cancer Research, Charlestown, Massachusetts, USA
                [6 ]Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA
                [7 ]Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
                Author notes
                Correspondence should be addressed to W.C.H., william_hahn@ 123456dfci.harvard.edu
                Article
                NIHMS1501645
                10.1038/s41588-018-0204-y
                6168352
                30224644
                3047e15e-76e2-4681-9293-6033ef93470a

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                Genetics
                Genetics

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