AUTHOR=Zhang Hengliang , Merkus Daphne , Zhang Pei , Zhang Huifeng , Wang Yanyu , Du Laijing , Kottu Lakshme 

TITLE=Predicting protective gene biomarker of acute coronary syndrome by the circRNA-associated competitive endogenous RNA regulatory network

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1030510

DOI=10.3389/fgene.2022.1030510

ISSN=1664-8021

ABSTRACT=Background: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. We are trying to run a circRNA-associated ceRNA network to screen the biomarker genes that are conducive to the diagnosis or exclusion of ACS, and explore its pathological mechanism through immune cell analysis.
Materials and methods: The expression profiles of circRNAs (GSE197137), miRNAs (GSE31568) and mRNAs (GSE95368) were downloaded from the GEO database, and differentially expressed (DE) RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) were acquired. The circRNA-miRNA and miRNA-mRNA regulatory links were retrieved from the CircInteractome database and TargetScan databases, respectively. Finally, a regulatory network for ceRNA has been developed. On the basis of the ceRNA network, hub mRNAs were verified by quantitative RT-PCR. Another independent mRNA database GSE60993 was used for validation of the hub genes and a ROC curve was used to evaluate the diagnostic value of hub genes. The single sample gene set enrichment analysis (ssGSEA) method was then used to analyze the correlation between hub genes and ACS related immune cells.
Results: A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 2 circRNA (hsa_circ_0082319 and hsa_circ_0005654), 4 miRNA, and 5 mRNA (XPNPEP1, UCHL1, DBNL, GPC6, RAD51). The qRT-PCR analysis result showed that the XPNPEP1, UCHL1, GPC6 and RAD51 genes had a significantly decreased expression in ACS patients. By ROC curve analysis, we found that the XPNPEP1 gene [AUC = 0.777 (95% CI: 0.577–0.934, P<0.05)] has important significance in protecting the occurrence and excluding diagnosis of ACS. The immune infiltration analysis showed that the other three hub genes (UCHL1, GPC6, RAD51) were significantly correlated with immune cells in ACS.
Conclusion: Our study constructed a circRNA-related ceRNA network in ACS. The XPNPEP1 gene could be a protective gene biomarker for ACS. The UCHL1, GPC6 and RAD51 genes were significantly correlated with immune cells in ACS.