Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis.

Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying ther...

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Published in:BioMed Research International pp. 1 - 17
Main Authors: Zeng, Zhi, Lin, Xia, Xia, Tingting, Liu, Wenxiu, Tian, Xiaohui, Li, Manchao
Format: research tables/charts Journal Article
Published: Wiley-Blackwell 11/6/2020
Online Access:View this record in EBSCOhost
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      issn: 23146133
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      dt: 11/6/2020
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        146869318
        146869318
        146869318
        10.1155/2020/1817094
        146869318
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        atl: Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis.
      aug:
        au:
          Zeng, Zhi
          Lin, Xia
          Xia, Tingting
          Liu, Wenxiu
          Tian, Xiaohui
          Li, Manchao
        affil: Center of Reproductive Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
      sug:
        subj:
          Polyendocrine Metabolic Ovarian Syndrome Drug Therapy
          Bioinformatics Evaluation
          RNA Analysis
          Gene Expression
          Human
          Databases
          Drug Interactions
          Female
          Ontologies
          Signal Transduction
          Drug Monitoring
          Female
      ab: Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs. Methods. RNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS. Results. Three modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree = 21) and TLR1 (degree = 18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS. Conclusion. Our study may provide a novel insight into the mechanisms and therapy for PCOS.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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