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      Analyzing the lncRNA, miRNA, and mRNA-associated ceRNA networks to reveal potential prognostic biomarkers for glioblastoma multiforme

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          Abstract

          Background

          Glioblastoma multiforme (GBM) is the most seriously brain tumor with extremely poor prognosis. Recent research has demonstrated that competitive endogenous RNA (ceRNA) network which long noncoding RNAs (lncRNAs) act as microRNA (miRNA) sponges to regulate mRNA expression were closely related to tumor development. However, the regulatory mechanisms and functional roles of ceRNA network in the pathogenesis of GBM are remaining poorly understood.

          Methods

          In this study, we systematically analyzed the expression profiles of lncRNA and mRNA (GSE51146 dataset) and miRNA (GSE65626 dataset) from GEO database. Then, we constructed a ceRNA network with the dysregulated genes by bioinformatics methods. The TCGA and GSE4290 dataset were used to confirm the expression and prognostic value of candidate mRNAs.

          Results

          In total, 3413 differentially expressed lncRNAs and mRNAs, 305 differentially expressed miRNAs were indentified in GBM samples. Then a ceRNA network containing 3 lncRNAs, 5 miRNAs, and 60 mRNAs was constructed. The overall survival analysis of TCGA databases indicated that two mRNAs (C1s and HSD3B7) were remarkly related with the prognosis of GBM.

          Conclusion

          The ceRNA network may increase our understanding to the pathogenesis of GBM. In general, the candidate mRNAs from the ceRNA network can be predicted as new therapeutic targets and prognostic biomarkers for GBM.

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          Most cited references30

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          Gene Ontology: tool for the unification of biology

          Michael Ashburner, Catherine A. Ball, Judith Blake … (2002)
          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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            miRDB: an online resource for microRNA target prediction and functional annotations

            Nathan C. Wong, Xiaowei Wang (2014)
            MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
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              Long non-coding RNA expression profiles predict clinical phenotypes in glioma.

              Xiaoqin Zhang, Stella Sun, Jenny Kan-Suen Pu … (2012)
              Glioma is the commonest form of primary brain tumor in adults with varying malignancy grades and histological subtypes. Long non-coding RNAs (lncRNAs) are a novel class of non-protein-coding transcripts that have been shown to play important roles in cancer development. To discover novel tumor-related lncRNAs and determine their associations with glioma subtypes, we first applied a lncRNA classification pipeline to identify 1970 lncRNAs that were represented on Affymetrix HG-U133 Plus 2.0 array. We then analyzed the lncRNA expression patterns in a set of previously published glioma gene expression profiles of 268 clinical specimens, and identified sets of lncRNAs that were unique to different histological subtypes (astrocytic versus oligodendroglial tumors) and malignancy grades. These lncRNAs signatures were then subject to validation in another non-overlapping, independent data set that contained 157 glioma samples. This is the first reported study that correlates lncRNA expression profiles with malignancy grade and histological differentiation in human gliomas. Our findings indicate the potential roles of lncRNAs in the biogenesis, development and differentiation of gliomas, and provide an important platform for future studies. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Kun Lv:
                ORCID: http://orcid.org/0000-0002-1895-6700
                lvkun315@126.com
                Journal
                Journal ID (nlm-ta): Cancer Cell Int
                Journal ID (iso-abbrev): Cancer Cell Int
                Title: Cancer Cell International
                Publisher: BioMed Central (London )
                ISSN (Electronic): 1475-2867
                Publication date (Electronic): 15 August 2020
                Publication date PMC-release: 15 August 2020
                Publication date Collection: 2020
                Volume: 20
                Electronic Location Identifier: 393
                Affiliations
                [1 ]GRID grid.443626.1, ISNI 0000 0004 1798 4069, Key Laboratory of Non-coding RNA Transformation Research of Anhui Higher Education Institution, , Wannan Medical College, ; Wuhu, 241001 People’s Republic of China
                [2 ]GRID grid.443626.1, ISNI 0000 0004 1798 4069, Non-coding RNA Research Center of Wannan Medical College, ; Wuhu, 241001 China
                [3 ]GRID grid.443626.1, ISNI 0000 0004 1798 4069, Central Laboratory of Yijishan Hospital, , Wannan Medical College, ; Wuhu, 241001 People’s Republic of China
                Author information
                http://orcid.org/0000-0002-1895-6700
                Article
                Publisher ID: 1488
                DOI: 10.1186/s12935-020-01488-1
                PMC ID: 7429694
                PubMed ID: 32821246
                SO-VID: 83e87ac6-f494-4865-b1a0-ad44c0c0a5e9
                Copyright © © The Author(s) 2020
                License:

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                Date received : 9 March 2020
                Date accepted : 7 August 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81701557
                Award ID: 81802503
                Award ID: 81870017
                Award ID: 81772180
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003995, Natural Science Foundation of Anhui Province;
                Award ID: 1908085QH380
                Award Recipient :
                Funded by: Key Projects of Natural Science Research of Universities in Anhui Province
                Award ID: KJ2018A0265
                Categories
                Subject: Primary Research
                Custom metadata
                issue-copyright-statement © The Author(s) 2020

                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: competing endogenous rna,glioblastoma multiforme,prognosis
                Data availability:
                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: competing endogenous rna, glioblastoma multiforme, prognosis

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