Prediction of Functional Genes in Primary Varicose Great Saphenous Veins Using the lncRNA-miRNA-mRNA Network

利用lncRNA-miRNA-mRNA网络预测原发性大隐静脉曲张中的功能基因

阅读:1

Abstract

BACKGROUND: Long noncoding RNAs (lncRNAs) have been widely suggested to bind with the microRNA (miRNA) sites and play roles of competing endogenous RNAs (ceRNAs), which can thus affect and regulate target gene and mRNA expression. Such lncRNA-related ceRNAs are identified to exert vital parts in vascular disease. Nonetheless, it remains unknown about how the lncRNA-miRNA-mRNA network functions in the varicose great saphenous veins. METHODS: This study acquired the lncRNA and mRNA expression patterns from the GEO database and identifies the differentially expressed mRNAs and lncRNAs by adopting the R software "limma" package. Then, miRcode, miRDB, miRTarbase, and TargetScan were used to establish the miRNA-mRNA pairs and lncRNA-miRNA pairs. In addition, the lncRNA-miRNA-mRNA ceRNA network was constructed by using Cytoscape. Protein-protein interaction, Gene Ontology functional annotations, and Kyoto Encyclopedia of Genes and Genomes enrichment were carried out to examine the candidate hub genes, the functions of genes, and the corresponding pathways. RESULTS: In line with the preset theory, we constructed ceRNA network comprising 12 lncRNAs, 38 miRNAs, and 149 mRNAs. Kyoto Encyclopedia of Genes and Genomes analysis indicated that the PI3K/Akt signaling pathway played a vital part in the development of varicose great saphenous veins. AC114730, AC002127, and AC073342 were significant biomarkers. At the same time, we predicted the potential miRNA, which may exert a significant influence on the varicose great saphenous veins, namely, miR-17-5p, miR-129-5p, miR-1297, miR-20b-5p, and miR-33a-3p. CONCLUSION: By performing ceRNA network analysis, our study detects new lncRNAs, miRNAs, and mRNAs, which can be applied as underlying biomarkers of varicose great saphenous veins and as therapeutic targets for the treatment of varicose great saphenous veins.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。