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      High expression of SMARCA4 or SMARCA2 is frequently associated with an opposite prognosis in cancer

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      Scientific Reports

      Nature Publishing Group UK

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          Abstract

          The gene encoding the ATPase of the chromatin remodeling SWI/SNF complexes SMARCA4 ( BRG1) is often mutated or silenced in tumors, suggesting a role as tumor suppressor. Nonetheless, recent reports show requirement of SMARCA4 for tumor cells growth. Here, we performed a computational meta-analysis using gene expression, prognosis, and clinicopathological data to clarify the role of SMARCA4 and the alternative SWI/SNF ATPase SMARCA2 (BRM) in cancer. We show that while the SMARCA4 gene is mostly overexpressed in tumors, SMARCA2 is almost invariably downexpressed in tumors. High SMARCA4 expression was associated with poor prognosis in many types of tumors, including liver hepatocellular carcinoma (LIHC), and kidney renal clear cell carcinoma (KIRC). In contrast, high SMARCA2 expression was associated with good prognosis. We compared tumors with high versus low expression of SMARCA4 or SMARCA2 in LIHC and KIRC cohorts from The Cancer Genome Atlas. While a high expression of SMARCA4 is associated with aggressive tumors, a high expression of SMARCA2 is associated with benign differentiated tumors, suggesting that SMARCA4 and SMARCA2 play opposite roles in cancer. Our results demonstrate that expression of SMARCA4 and SMARCA2 have a high prognostic value and challenge the broadly accepted general role of SMARCA4 as a tumor suppressor.

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          Most cited references 99

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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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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                Author and article information

                Contributors
                jose.reyes@cabimer.es
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 February 2018
                1 February 2018
                2018
                : 8
                Affiliations
                ISNI 0000 0001 2183 4846, GRID grid.4711.3, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, , Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO). Av. Americo Vespucio 24, ; 41092 Seville, Spain
                20217
                10.1038/s41598-018-20217-3
                5794756
                29391527
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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