Identification of circRNA-miRNA-mRNA regulatory network and its role in cardiac hypertrophy

Abstract

Background Hypertrophic cardiomyopathy (HCM) is a grave hazard to human health. Circular RNA (circRNAs) and micro RNA (miRNAs), which are competitive endogenous RNA, have been shown to play a critical role inHCM pathogenicity. However, to a great extent, the biological activities of ceRNA in HCM pathophysiology and prognosis remain to be investigated. Materials and methods By analyzing the expression files in the Gene Expression Comprehensive (GEO) database, differentially expressed (DE) circRNAs, miRNAs, and mRNAs in HCM were identified, and the target molecules of circRNAs and miRNAs were predicted. The intersection of the differentially expressed RNA molecules and the expected target was then calculated, and a ceRNA network was subsequently constructed using RNA molecules. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, the potential etiology was elucidated. qPCR was used to validate a portion of the hub gene using Angiotensin II to generate a cell hypertrophy model. Results Three large-scale HCM sample datasets were extracted from the GEO database. After crossing these molecules with their expected targets, the circRNA-miRNA-mRNA network had two DEcircRNAs, two DEmiRNAs, and thirty DEmRNAs, compared to normal tissues. Functional enrichment analysis of GO and KEGG demonstrated that many of the HCM pathways and mechanisms were associated with calcium channel release, which is also the primary focus of future research. The qPCR results revealed that circRNA, miRNA, and mRNA expression levels were different. They may include novel noninvasive indicators for the early screening and prognostic prediction of HCM. Conclusion In this study, we hypothesized a circRNA-miRNA-mRNA regulation network that is closely related to the progression and clinical outcomes of HCM and may contain promising biomarkers and treatment targets for HCM.

Cirscan: a shiny application to identify differentially active sponge mechanisms and visualize circRNA-miRNA-mRNA networks

“…miRNA and mRNA expression data), and to their predictions databases restricted to interactions between miRNA and mRNA [11, 12]. Moreover, the studies focusing on circRNA-miRNA-mRNA networks have not developed a computational tool that automates the search for large-scale ce-circRNA [13, 14, 15, 16, 17, 18, 19]. Two circRNA functional annotation databases predicting sponge mechanisms involving circRNAs in several tissues have been developed, but they do not allow users to query their own transcriptomic datasets on a large scale, they most often limite queries to circRNA identifiers or sequences [20, 21].…”