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      Investigating MicroRNA and transcription factor co-regulatory networks in colorectal cancer

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          Abstract

          Background

          Colorectal cancer (CRC) is one of the most common malignancies worldwide with poor prognosis. Studies have showed that abnormal microRNA (miRNA) expression can affect CRC pathogenesis and development through targeting critical genes in cellular system. However, it is unclear about which miRNAs play central roles in CRC’s pathogenesis and how they interact with transcription factors (TFs) to regulate the cancer-related genes.

          Results

          To address this issue, we systematically explored the major regulation motifs, namely feed-forward loops (FFLs), that consist of miRNAs, TFs and CRC-related genes through the construction of a miRNA-TF regulatory network in CRC. First, we compiled CRC-related miRNAs, CRC-related genes, and human TFs from multiple data sources. Second, we identified 13,123 3-node FFLs including 25 miRNA-FFLs, 13,005 TF-FFLs and 93 composite-FFLs, and merged the 3-node FFLs to construct a CRC-related regulatory network. The network consists of three types of regulatory subnetworks (SNWs): miRNA-SNW, TF-SNW, and composite-SNW. To enhance the accuracy of the network, the results were filtered by using The Cancer Genome Atlas (TCGA) expression data in CRC, whereby we generated a core regulatory network consisting of 58 significant FFLs. We then applied a hub identification strategy to the significant FFLs and found 5 significant components, including two miRNAs (hsa-miR-25 and hsa-miR-31), two genes ( ADAMTSL3 and AXIN1) and one TF (BRCA1). The follow up prognosis analysis indicated all of the 5 significant components having good prediction of overall survival of CRC patients.

          Conclusions

          In summary, we generated a CRC-specific miRNA-TF regulatory network, which is helpful to understand the complex CRC regulatory mechanisms and guide clinical treatment. The discovered 5 regulators might have critical roles in CRC pathogenesis and warrant future investigation.

          Electronic supplementary material

          The online version of this article (10.1186/s12859-017-1796-4) contains supplementary material, which is available to authorized users.

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          Most cited references32

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          Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes.

          MicroRNAs (miRNAs) are short endogenous RNAs known to post-transcriptionally repress gene expression in animals and plants. A microarray profiling survey revealed the expression patterns of 175 human miRNAs across 24 different human organs. Our results show that proximal pairs of miRNAs are generally coexpressed. In addition, an abrupt transition in the correlation between pairs of expressed miRNAs occurs at a distance of 50 kb, implying that miRNAs separated by <50 kb typically derive from a common transcript. Some microRNAs are within the introns of host genes. Intronic miRNAs are usually coordinately expressed with their host gene mRNA, implying that they also generally derive from a common transcript, and that in situ analyses of host gene expression can be used to probe the spatial and temporal localization of intronic miRNAs.
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            Micromanagers of gene expression: the potentially widespread influence of metazoan microRNAs.

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              MicroRNA-mediated feedback and feedforward loops are recurrent network motifs in mammals.

              MicroRNAs (miRNAs) are regulatory molecules that participate in diverse biological processes in animals and plants. While thousands of mammalian genes are potentially targeted by miRNAs, the functions of miRNAs in the context of gene networks are not well understood. Specifically, it is unknown whether miRNA-containing networks have recurrent circuit motifs, as has been observed in regulatory networks of bacteria and yeast. Here we develop a computational method that utilizes gene expression data to show that two classes of circuits-corresponding to positive and negative transcriptional coregulation of a miRNA and its targets-are prevalent in the human and mouse genomes. Additionally, we find that neuronal-enriched miRNAs tend to be coexpressed with their target genes, suggesting that these miRNAs could be involved in neuronal homeostasis. Our results strongly suggest that coordinated transcriptional and miRNA-mediated regulation is a recurrent motif to enhance the robustness of gene regulation in mammalian genomes.
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                Author and article information

                Contributors
                wanghao_smu@163.com
                1016822199@qq.com
                975529339@qq.com
                578549348@qq.com
                jing.wang@vanderbilt.edu
                qi.liu@vanderbilt.edu
                zhongming.zhao@uth.tmc.edu
                hua.xu@uth.tmc.edu
                dyq@fimmu.com
                jingchun.sun@uth.tmc.edu
                zqllc8@fimmu.com
                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                2 September 2017
                2 September 2017
                2017
                : 18
                : 388
                Affiliations
                [1 ]Department of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515 China
                [2 ]ISNI 0000 0000 8877 7471, GRID grid.284723.8, Department of Pathology, College of Basic Medicine, , Southern Medical University, ; Guangzhou, 510515 China
                [3 ]ISNI 0000 0001 2264 7217, GRID grid.152326.1, Center for Quantitative Sciences, , Vanderbilt University School of Medicine, ; Nashville, TN 37232 USA
                [4 ]ISNI 0000 0000 9206 2401, GRID grid.267308.8, School of Biomedical Informatics, , The University of Texas Health Science Center at Houston, ; Houston, TX 77030 USA
                [5 ]ISNI 0000 0000 9206 2401, GRID grid.267308.8, Center for Precision Health, School of Biomedical Informatics, , The University of Texas Health Science Center at Houston, ; Houston, TX 77030 USA
                Article
                1796
                10.1186/s12859-017-1796-4
                5581471
                28865443
                b2650020-44c3-4077-b73f-96474b58f152
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 October 2016
                : 21 August 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81472712
                Award ID: 81071989
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100007162, Guangdong Science and Technology Department;
                Award ID: c1221020700008
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: R21CA196508
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Bioinformatics & Computational biology
                colorectal cancer (crc),microrna,transcription factor,feed-forward loops (ffls),regulatory network

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