Construction and investigation of circRNA-associated ceRNA regulatory network in molecular subtypes of breast cancer.

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2022-06-15 DOI:10.2174/1573409918666220615151614
Yinming Zhong, Sicen Pan, Shunji Zhi, Yue Li, Zhiping Xiu, Changran Wei, Jiesi Luo
{"title":"Construction and investigation of circRNA-associated ceRNA regulatory network in molecular subtypes of breast cancer.","authors":"Yinming Zhong, Sicen Pan, Shunji Zhi, Yue Li, Zhiping Xiu, Changran Wei, Jiesi Luo","doi":"10.2174/1573409918666220615151614","DOIUrl":null,"url":null,"abstract":"BACKGROUND\nCircular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) that indirectly regulate gene expression and function by binding microRNAs (miRNAs). A growing body of evidence indicates that the ceRNA networks can be used as an effective method to investigate cancer; however, the construction and analysis of ceRNA networks, especially circRNA-miRNA-mRNA regulatory network, in different subtypes of breast cancer has not been previously performed.\n\n\nOBJECTIVES\nIn the present study, we generated a ceRNA network to explore their roles in two BC subtypes, namely Luminal A and triple negative breast cancer (TNBC).\n\n\nMETHODS\nFirst, the expression profiles of circRNA, miRNA, and mRNA were downloaded from the GEO database, differentially expressed genes were obtained using GEO2R, and a ceRNA network, was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs, which was consisted of 10 circRNAs, 25 miRNAs and 39 mRNAs. Further studies of BC subtypes based on TCGA datasets were also performed to validate the effect of novel ceRNA network.\n\n\nRESULTS AND DISCUSSION\nThen, the related genes in the regulatory network were analyzed by GO functional annotation and KEGG pathway enrichment. The analysis showed that targeted genes were enriched in 97 GO terms and 25 KEGG pathways, respectively, involved in the molecular typing of breast cancer. Meanwhile, Kaplan-Meier analysis revealed that three key genes (MKI67, DEF8, and GFRA1) were significantly associated with BC tumor differentiation and prognosis.\n\n\nCONCLUSION\nThe current study provides a potential application of ceRNA network within BC subtypes, and may offer new targets for their diagnosis, therapy and prognosis.","PeriodicalId":10886,"journal":{"name":"Current computer-aided drug design","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current computer-aided drug design","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1573409918666220615151614","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 2

Abstract

BACKGROUND Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) that indirectly regulate gene expression and function by binding microRNAs (miRNAs). A growing body of evidence indicates that the ceRNA networks can be used as an effective method to investigate cancer; however, the construction and analysis of ceRNA networks, especially circRNA-miRNA-mRNA regulatory network, in different subtypes of breast cancer has not been previously performed. OBJECTIVES In the present study, we generated a ceRNA network to explore their roles in two BC subtypes, namely Luminal A and triple negative breast cancer (TNBC). METHODS First, the expression profiles of circRNA, miRNA, and mRNA were downloaded from the GEO database, differentially expressed genes were obtained using GEO2R, and a ceRNA network, was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs, which was consisted of 10 circRNAs, 25 miRNAs and 39 mRNAs. Further studies of BC subtypes based on TCGA datasets were also performed to validate the effect of novel ceRNA network. RESULTS AND DISCUSSION Then, the related genes in the regulatory network were analyzed by GO functional annotation and KEGG pathway enrichment. The analysis showed that targeted genes were enriched in 97 GO terms and 25 KEGG pathways, respectively, involved in the molecular typing of breast cancer. Meanwhile, Kaplan-Meier analysis revealed that three key genes (MKI67, DEF8, and GFRA1) were significantly associated with BC tumor differentiation and prognosis. CONCLUSION The current study provides a potential application of ceRNA network within BC subtypes, and may offer new targets for their diagnosis, therapy and prognosis.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
乳腺癌分子亚型中circrna相关ceRNA调控网络的构建与研究
环状rna (circRNAs)作为竞争性内源性rna (ceRNAs),通过结合microRNAs (miRNAs)间接调节基因表达和功能。越来越多的证据表明,ceRNA网络可以作为研究癌症的有效方法;然而,ceRNA网络的构建和分析,特别是circRNA-miRNA-mRNA调控网络,在不同亚型乳腺癌中尚未进行。目的:在本研究中,我们建立了一个ceRNA网络,探讨它们在两种BC亚型,即Luminal a和三阴性乳腺癌(TNBC)中的作用。方法首先从GEO数据库中下载circRNA、miRNA和mRNA的表达谱,利用GEO2R获取差异表达基因,构建基于circRNA-miRNA对和miRNA-mRNA对的ceRNA网络,包括10个circRNA、25个miRNA和39个mRNA。基于TCGA数据集的BC亚型进一步研究也验证了新型ceRNA网络的效果。然后,通过GO功能注释和KEGG通路富集分析了调控网络中的相关基因。分析结果显示,靶基因分别富集于97个GO项和25个KEGG通路,参与乳腺癌的分子分型。同时Kaplan-Meier分析显示,三个关键基因(MKI67、DEF8和GFRA1)与BC肿瘤的分化和预后显著相关。结论本研究提供了ceRNA网络在BC亚型中的潜在应用,并可能为其诊断、治疗和预后提供新的靶点。
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 去求助
来源期刊
Current computer-aided drug design
Current computer-aided drug design 医学-计算机:跨学科应用
CiteScore
3.70
自引率
5.90%
发文量
46
审稿时长
>12 weeks
期刊介绍: Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.
期刊最新文献
Detection of Brain Tumor Employing Residual Network-based Optimized Deep Learning Computer-Aided Drug Discovery Approaches in the Identification of Anticancer Drugs from Natural Products: A Review An Enhanced Computational Approach Using Multi-kernel Positive Unlabeled Learning for Predicting Drug-target Interactions Study on the Mechanism of Competing Endogenous Network of 'Scutellaria barbata D.Don-Houttuynia cordata- Radix Scutellariae' in the Treatment of NSCLC based on Bioinformatics, Molecular Dynamics and Experimental Verification Designing a Novel di-epitope Diphtheria Vaccine: A Rational Structural Immunoinformatics Approach
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1