Epithelial-Mesenchymal Transition-Related lncRNAs And SNAI2 Are Potential Biomarkers in Coronary Artery Disease

Abstract

BackgroundIncreasing evidence suggests that epithelial-mesenchymal transformation (EMT) is critical in the development of inflammatory response, atherosclerosis, and coronary artery disease (CAD). However, landscapes of EMT-related lncRNAs and their target genes have not been fully established in CAD.MethodsLncRNA and mRNA expression profiles obtained from Gene Expression Omnibus (GEO) database were used to identify the differentially expressed mRNAs (DEGs) and lncRNAs (DElncRNAs) between CAD and normal samples. Based on Pearson correlation analysis to identify the EMT-related lncRNAs, the optimal features were identified by receiver operating characteristic (ROC), the least absolute shrinkage and selection operator (LASSO) regression, Support Vector Machine Reverse Feature Elimination (SVM-RFE) algorithms, and logistic regression models were constructed aiming to distinguish CAD from normal samples. The cis and trans-regulatory networks were constructed based on EMT-related lncRNAs. We further estimated the infiltration of the immune cells in CAD patients with the CIBERSORT algorithm, and the correlation between key genes and infiltrating immune cells was analyzed.ResultsIn this study, a logistic regression model with powerful diagnostic capability was constructed based on a total of eight EMT-related lncRNAs identified by two machine learning methods. Then, results of the immune analysis revealed three significant immune cell subsets (CD8 T cells, monocytes, and NK cells) in CAD patients and found EMT-related lncRNAs were closely correlated with these immune cell subsets. By Pearson correlation analysis we got 34 “cis” and “trans” genes. Among them, SNAI2, an EMT-TF gene, was found in the trans-regulatory network of EMT-related lncRNAs. Further, through logistic regression and analysis of immune cell infiltration, we found SNAI2 was a potential biomarker for the diagnosis of CAD but also a close correlation between highly expressed SNAI2 and these three immune cell subsets in CAD patients.ConclusionIn conclusion, these biomarkers have important significance in the diagnosis of CAD patients. Eight EMT-related lncRNAs and SNAI2 can improve our understanding of the molecular mechanism between EMT and CAD.