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      Distinct co-expression networks using multi-omic data reveal novel interventional targets in HPV-positive and negative head-and-neck squamous cell cancer

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      Scientific Reports
      Nature Publishing Group UK

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          Abstract

          The human papillomavirus (HPV) is present in a significant fraction of head-and-neck squamous cell cancer (HNSCC). The main goal of this study was to identify distinct co-expression patterns between HPV+ and HPV− HNSCC and to provide insights into potential regulatory mechanisms/effects within the analyzed networks. We selected cases deposited in The Cancer Genome Atlas database comprising data of gene expression, methylation profiles and mutational patterns, in addition to clinical information. The intersection among differentially expressed and differentially methylated genes showed the negative correlations between the levels of methylation and expression, suggesting that these genes have their expression levels regulated by methylation alteration patterns in their promoter. Weighted correlation network analysis was used to identify co-expression modules and a systematic approach was applied to refine them and identify key regulatory elements integrating results from the other omics. Three distinct co-expression modules were associated with HPV status and molecular signatures. Validation using independent studies reporting biological experimental data converged for the most significant genes in all modules. This study provides insights into complex genetic and epigenetic particularities in the development and progression of HNSCC according to HPV status, and contribute to unveiling specific genes/pathways as novel therapeutic targets in HNSCC.

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          Most cited references33

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Gene Ontology: tool for the unification of biology

            Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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              Emergence of scaling in random networks

              Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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                Author and article information

                Contributors
                quelopes@lncc.br
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 October 2018
                15 October 2018
                2018
                : 8
                : 15254
                Affiliations
                [1 ]GRID grid.419166.d, Programa de Oncovirologia, , Instituto Nacional de Câncer, ; Rio de Janeiro, Brazil
                [2 ]GRID grid.419166.d, Bioinformatics and Computational Biology Lab, , Instituto Nacional de Câncer, ; Rio de Janeiro, Brazil
                [3 ]ISNI 0000 0001 2294 473X, GRID grid.8536.8, Department of Genetics, , Universidade Federal do Rio de Janeiro, ; Rio de Janeiro, Brazil
                Author information
                http://orcid.org/0000-0002-7139-0865
                http://orcid.org/0000-0002-9013-2570
                Article
                33498
                10.1038/s41598-018-33498-5
                6189122
                30323202
                f5094d79-5bb8-44d9-a97f-e51ac49f294d
                © 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/.

                History
                : 16 April 2018
                : 19 September 2018
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