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      Tissue-specific Co-expression of Long Non-coding and Coding RNAs Associated with Breast Cancer

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          Abstract

          Inference of the biological roles of lncRNAs in breast cancer development remains a challenge. Here, we analyzed RNA-seq data in tumor and normal breast tissue samples from 18 breast cancer patients and 18 healthy controls and constructed a functional lncRNA-mRNA co-expression network. We revealed two distinctive co-expression patterns associated with breast cancer, reflecting different underlying regulatory mechanisms: (1) 516 pairs of lncRNA-mRNAs have differential co-expression pattern, in which the correlation between lncRNA and mRNA expression differs in tumor and normal breast tissue; (2) 291 pairs have dose-response co-expression pattern, in which the correlation is similar, but the expression level of lncRNA or mRNA differs in the two tissue types. We further validated our findings in TCGA dataset and annotated lncRNAs using TANRIC. One novel lncRNA, AC145110.1 on 8p12, was found differentially co-expressed with 127 mRNAs (including TOX4 and MAEL) in tumor and normal breast tissue and also highly correlated with breast cancer clinical outcomes. Functional enrichment and pathway analyses identified distinct biological functions for different patterns of co-expression regulations. Our data suggested that lncRNAs might be involved in breast tumorigenesis through the modulation of gene expression in multiple pathologic pathways.

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          Most cited references 28

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          The transcriptional landscape of the mammalian genome.

          This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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            Controlling the false discovery rate - a practical and powerful approach to multiple testing.

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              ConsensusPathDB—a database for integrating human functional interaction networks

              ConsensusPathDB is a database system for the integration of human functional interactions. Current knowledge of these interactions is dispersed in more than 200 databases, each having a specific focus and data format. ConsensusPathDB currently integrates the content of 12 different interaction databases with heterogeneous foci comprising a total of 26 133 distinct physical entities and 74 289 distinct functional interactions (protein–protein interactions, biochemical reactions, gene regulatory interactions), and covering 1738 pathways. We describe the database schema and the methods used for data integration. Furthermore, we describe the functionality of the ConsensusPathDB web interface, where users can search and visualize interaction networks, upload, modify and expand networks in BioPAX, SBML or PSI-MI format, or carry out over-representation analysis with uploaded identifier lists with respect to substructures derived from the integrated interaction network. The ConsensusPathDB database is available at: http://cpdb.molgen.mpg.de
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                06 September 2016
                2016
                : 6
                Affiliations
                [1 ]Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University , Indianapolis, IN, USA
                [2 ]Department of Medical and Molecular Genetics, Indiana University School of Medicine , Indianapolis, IN, USA
                [3 ]Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Hospital and Institute, National Clinical Research Center for Cancer, Tianjin & Key Laboratory of Cancer Prevention and Therapy , Tianjin, China
                [4 ]Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School , Boston, MA, USA
                [5 ]Indiana University Melvin and Bren Simon Cancer Center , Indianapolis, IN, USA
                [6 ]Spinal Cord and Brain Injury Research Group, Department of Neurosurgery, Stark Neuroscience Research Institute, Indiana University , Indianapolis, IN, USA
                [7 ]Susan G. Komen Tissue Bank at the Indiana University Melvin and Bren Simon Cancer Center , Indianapolis, IN, USA
                [8 ]Center for Computational Biology and Bioinformatics, Indiana University , Indianapolis, IN 46202, USA
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep32731
                10.1038/srep32731
                5011741
                27597120
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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