Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zeng, Zhi, Lin, Xia, Xia, Tingting, Liu, Wenxiu, Tian, Xiaohui, Li, Manchao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666708/
https://www.ncbi.nlm.nih.gov/pubmed/33224973
http://dx.doi.org/10.1155/2020/1817094
_version_ 1783610182231654400
author Zeng, Zhi
Lin, Xia
Xia, Tingting
Liu, Wenxiu
Tian, Xiaohui
Li, Manchao
author_facet Zeng, Zhi
Lin, Xia
Xia, Tingting
Liu, Wenxiu
Tian, Xiaohui
Li, Manchao
author_sort Zeng, Zhi
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7666708
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-76667082020-11-19 Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis Zeng, Zhi Lin, Xia Xia, Tingting Liu, Wenxiu Tian, Xiaohui Li, Manchao Biomed Res Int Research Article 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. Hindawi 2020-11-06 /pmc/articles/PMC7666708/ /pubmed/33224973 http://dx.doi.org/10.1155/2020/1817094 Text en Copyright © 2020 Zhi Zeng et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zeng, Zhi
Lin, Xia
Xia, Tingting
Liu, Wenxiu
Tian, Xiaohui
Li, Manchao
Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
title Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
title_full Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
title_fullStr Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
title_full_unstemmed Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
title_short Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
title_sort identification of crucial lncrnas, mirnas, mrnas, and potential therapeutic compounds for polycystic ovary syndrome by bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666708/
https://www.ncbi.nlm.nih.gov/pubmed/33224973
http://dx.doi.org/10.1155/2020/1817094
work_keys_str_mv AT zengzhi identificationofcruciallncrnasmirnasmrnasandpotentialtherapeuticcompoundsforpolycysticovarysyndromebybioinformaticsanalysis
AT linxia identificationofcruciallncrnasmirnasmrnasandpotentialtherapeuticcompoundsforpolycysticovarysyndromebybioinformaticsanalysis
AT xiatingting identificationofcruciallncrnasmirnasmrnasandpotentialtherapeuticcompoundsforpolycysticovarysyndromebybioinformaticsanalysis
AT liuwenxiu identificationofcruciallncrnasmirnasmrnasandpotentialtherapeuticcompoundsforpolycysticovarysyndromebybioinformaticsanalysis
AT tianxiaohui identificationofcruciallncrnasmirnasmrnasandpotentialtherapeuticcompoundsforpolycysticovarysyndromebybioinformaticsanalysis
AT limanchao identificationofcruciallncrnasmirnasmrnasandpotentialtherapeuticcompoundsforpolycysticovarysyndromebybioinformaticsanalysis