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基于生物信息学分析鉴定多囊卵巢综合征的关键长链非编码 RNA、微小 RNA、信使 RNA 和潜在治疗性化合物。

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

机构信息

Center of Reproductive Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China.

Department of Gynecology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China.

出版信息

Biomed Res Int. 2020 Nov 6;2020:1817094. doi: 10.1155/2020/1817094. eCollection 2020.

Abstract

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.

摘要

背景

本研究旨在基于共表达和竞争内源性 RNA (ceRNA) 理论,挖掘与多囊卵巢综合征 (PCOS) 发生发展相关的关键长非编码 RNA (lncRNA)、microRNA (miRNA) 和信使 RNA (mRNA),并探讨可能通过逆转 lncRNA、miRNA 和 mRNA 表达而起作用的潜在治疗药物。

方法

从基因表达综合数据库中下载 PCOS 患者的 RNA(GSE106724、GSE114419、GSE137684 和 GSE138518)或 miRNA(GSE84376 和 GSE138572)表达谱数据集。使用四个 RNA 数据集进行加权基因共表达网络分析 (WGCNA),构建 lncRNA-mRNA 共表达网络,同时使用两个 miRNA 数据集和模块 RNA 中的常见差异表达 miRNA 建立 ceRNA 网络。构建蛋白质-蛋白质相互作用 (PPI) 网络以探索基因之间的潜在相互作用。进行基因本体论和京都基因与基因组百科全书 (KEGG) 通路富集分析,以探索网络中基因的功能。进行连接映射 (CMap) 和比较毒理学基因组数据库 (CTD) 分析,以确定 PCOS 的潜在治疗药物。

结果

WGCNA 分析后,共鉴定出 3 个与 PCOS 相关的模块(黑色、品红色和黄色),其中 KLF3-AS1-PLCG2、MAPKAPK5-AS1-MAP3K14 和 WWC2-AS2-TXNIP 是重要的共表达关系对。ceRNA 网络中的关键 ceRNA 环是 WWC2-AS2-hsa-miR-382-PLCG2。PPI 网络显示 MAP3K14 和 TXNIP 可分别与枢纽基因 PLK1(度=21)和 TLR1(度=18)相互作用。这些基因被富集到有丝分裂(PLK1)、免疫反应(PLCG2 和 TLR1)和细胞周期(TXNIP 和 PLK1)的生物过程中。十种小分子药物(尤其是槲皮素)被认为是治疗 PCOS 的药物。

结论

本研究可能为 PCOS 的发病机制和治疗提供新的思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c76/7666708/f1073a0057fd/BMRI2020-1817094.001.jpg

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