Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension

Xiao Jin, Ling Jin, Li Han, Shiping Zhu
{"title":"Bioinformatics Analysis of the Regulatory lncRNA–miRNA–mRNA Network and Drug Prediction in Patients with Pulmonary Arterial Hypertension","authors":"Xiao Jin, Ling Jin, Li Han, Shiping Zhu","doi":"10.1097/CD9.0000000000000091","DOIUrl":null,"url":null,"abstract":"Objective: Pulmonary arterial hypertension (PAH) is a cardiovascular disease caused by primary proliferative lesions in pulmonary arterioles. Competing endogenous RNAs (ceRNAs) have been reported to act as sponges for microRNAs (miRNAs). To date, however, the mechanisms underlying ceRNA involvement in PAH have not been investigated. This study aimed to construct a PAH-related ceRNA network to further explore the mechanisms of PAH. Methods: A probe reannotation was conducted to identify the long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in PAH. Based on the reannotation results, the “limma” package was used to identify the differentially expressed genes (DEGs) and lncRNAs. The miRcode database was used to predict the lncRNA–miRNA interactions. Then, the mRNAs targeted by the miRNAs were predicted by using TargetScan, miRTarBase, and miRDB. Based on the above interactions, a ceRNA network was constructed, which was mapped and visualized with Cytoscape 3.6.1 software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the database. To predict possible drugs or molecules that may mitigate PAH, C-Map analysis was applied to find relevant molecular compounds that can reverse the expression of DEGs in cell lines. Results: The ceRNA network consisted of 174 nodes and 304 links, which included 10 lncRNAs, 23 miRNAs, and 53 mRNAs. The hub genes of the ceRNA network for PAH included hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p. Calprotectin, irinotecan, and medrysone were found to be the 3 significant compounds. Conclusion: This study found that hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p maybe the underlying biomarkers and targets for diagnosis and treatment of PAH.","PeriodicalId":72524,"journal":{"name":"Cardiology discovery","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cardiology discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/CD9.0000000000000091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: Pulmonary arterial hypertension (PAH) is a cardiovascular disease caused by primary proliferative lesions in pulmonary arterioles. Competing endogenous RNAs (ceRNAs) have been reported to act as sponges for microRNAs (miRNAs). To date, however, the mechanisms underlying ceRNA involvement in PAH have not been investigated. This study aimed to construct a PAH-related ceRNA network to further explore the mechanisms of PAH. Methods: A probe reannotation was conducted to identify the long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in PAH. Based on the reannotation results, the “limma” package was used to identify the differentially expressed genes (DEGs) and lncRNAs. The miRcode database was used to predict the lncRNA–miRNA interactions. Then, the mRNAs targeted by the miRNAs were predicted by using TargetScan, miRTarBase, and miRDB. Based on the above interactions, a ceRNA network was constructed, which was mapped and visualized with Cytoscape 3.6.1 software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the database. To predict possible drugs or molecules that may mitigate PAH, C-Map analysis was applied to find relevant molecular compounds that can reverse the expression of DEGs in cell lines. Results: The ceRNA network consisted of 174 nodes and 304 links, which included 10 lncRNAs, 23 miRNAs, and 53 mRNAs. The hub genes of the ceRNA network for PAH included hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p. Calprotectin, irinotecan, and medrysone were found to be the 3 significant compounds. Conclusion: This study found that hsa-miR-17-5p, hsa-miR-20b-5p, MEG3, HCP5, hsa-miR-27a-3p, hsa-miR-107, hsa-miR-142-3p, hsa-miR-363-3p, hsa-miR-301b-3p, and hsa-miR-23b-3p maybe the underlying biomarkers and targets for diagnosis and treatment of PAH.
肺动脉高压患者lncRNA-miRNA-mRNA调控网络的生物信息学分析及药物预测
目的:肺动脉高压(PAH)是由原发性肺动脉增生性病变引起的心血管疾病。竞争性内源性RNA(ceRNA)已被报道为微小RNA(miRNA)的海绵。然而,迄今为止,ceRNA参与PAH的机制尚未得到研究。本研究旨在构建PAH相关的ceRNA网络,以进一步探讨PAH的发病机制。方法:对PAH相关的长链非编码RNA(lncRNA)和信使RNA(mRNA)进行探针再标记。基于再标记结果,使用“limma”软件包来鉴定差异表达基因(DEG)和lncRNA。miRcode数据库用于预测lncRNA-miRNA的相互作用。然后,通过使用TargetScan、miRTarBase和miRDB来预测miRNA靶向的mRNA。基于上述相互作用,构建了一个ceRNA网络,并用Cytoscape 3.6.1软件对其进行了映射和可视化。使用该数据库进行基因本体论和京都基因和基因组百科全书途径富集分析。为了预测可能减轻PAH的药物或分子,应用C-Map分析来寻找可以逆转细胞系中DEG表达的相关分子化合物。结果:ceRNA网络由174个节点和304个链接组成,其中包括10个lncRNA、23个miRNA和53个mRNA。PAH的ceRNA网络的枢纽基因包括hsa-miR-17-5p、hsa-miR-20b-5p、MEG3、HCP5、hsa-iR-27a-3p、hsa-miR-107、hsa--miR-142-3p、hsa-miR-363-3p、hsa-miR-301b-3p和hsa-miR-23b-3p。钙卫蛋白、伊立替康和药物是三个重要的化合物。结论:本研究发现hsa-miR-17-5p、hsa-miR-20b-5p、MEG3、HCP5、hsa-iR-27a-3p、hsa-miR-107、hsa-micro-142-3p、hsa-miR-363-3p、hsa miR-301b-3p和hsa-miR-23b-3p可能是PAH诊断和治疗的潜在生物标志物和靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信