Yi Sun1, Jie Lin2, Shuna Huang3, Xingyan Xu4, Yingying Cai4, Le Yang4, Huangyuan Li5, Siying Wu6. 1. Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, China; School of Public Health, Fujian Medical University, Minhou County, Fuzhou, China. 2. The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China. 3. Department of Clinical research and translation center office, the First Affiliated Hospital of Fujian Medical University, Fuzhou, China. 4. School of Public Health, Fujian Medical University, Minhou County, Fuzhou, China. 5. Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, China; School of Public Health, Fujian Medical University, Minhou County, Fuzhou, China. Electronic address: fmulhy@163.com. 6. Fujian Key Lab of Environmental Factors and Cancer, School of Public Health, Fujian Medical University, China; Key Lab of Environment and Health, School of Public Health, Fujian Medical University, China. Electronic address: fmuwsy@163.com.
Abstract
BACKGROUND: This study aims to explore the possible ceRNA regulatory network of lncRNA ENST00000609755.1 in CHD patients based on the population; reveal the possible regulatory mechanism of lncRNA ENST00000609755.1. METHOD: Microarray analysis were used to identify differentially expressed miRNA, and mRNA profiles between 5 CHD and 5 healthy controls. The lncRNA ENST00000609755.1-miRNA-mRNA ceRNA regulatory network was constructed with lncRNA ENST00000609755.1 as the core based on microarray data and related prediction software (RNAhybird, miRanda, miRWalk 2.0). Furthermore, qRT-PCR was used to verify the expression levels of miRNA and mRNA. t-test and pearson correlation analysis were used to compare the expression differences and correlations of lncRNA, miRNA and mRNA. The receiver operating characteristic (ROC) curve was used to determine the discriminative ability of lncRNA ENST00000609755.1 and its downstream targets. RESULTS: Totally 25 miRNAs and 953 mRNAs were differentially expressed between CHD and healthy control. The lncRNA ENST00000609755.1- miRNA- mRNA ceRNA regulatory network was constructed (5 miRNA and 58 mRNA). qRT-PCR results suggest that the expression of lncRNA ENST00000609755.1 and ELK1 were up-regulated in CHD group and positively correlated, the expression of miR-150 was down-regulated in CHD, which was negatively correlated with lncRNA ENST00000609755.1 and ELK1. The AUC was 0.777(95%CI, 0.659-0.895) when miRNA-150 and ELK1 was added, which was higher than that of lncRNA ENST00000609755.1 single indicator. CONCLUSION: LncRNA ENST00000609755.1, miR-150 and ELK1 may have a potential ceRNA regulatory network relationship which could be considered to have a good combined diagnostic value for CHD. Also, preliminarily reveal the possible mechanism of lncRNA ENST00000609755.1 involved in CHD.
BACKGROUND: This study aims to explore the possible ceRNA regulatory network of lncRNA ENST00000609755.1 in CHD patients based on the population; reveal the possible regulatory mechanism of lncRNA ENST00000609755.1. METHOD: Microarray analysis were used to identify differentially expressed miRNA, and mRNA profiles between 5 CHD and 5 healthy controls. The lncRNA ENST00000609755.1-miRNA-mRNA ceRNA regulatory network was constructed with lncRNA ENST00000609755.1 as the core based on microarray data and related prediction software (RNAhybird, miRanda, miRWalk 2.0). Furthermore, qRT-PCR was used to verify the expression levels of miRNA and mRNA. t-test and pearson correlation analysis were used to compare the expression differences and correlations of lncRNA, miRNA and mRNA. The receiver operating characteristic (ROC) curve was used to determine the discriminative ability of lncRNA ENST00000609755.1 and its downstream targets. RESULTS: Totally 25 miRNAs and 953 mRNAs were differentially expressed between CHD and healthy control. The lncRNA ENST00000609755.1- miRNA- mRNA ceRNA regulatory network was constructed (5 miRNA and 58 mRNA). qRT-PCR results suggest that the expression of lncRNA ENST00000609755.1 and ELK1 were up-regulated in CHD group and positively correlated, the expression of miR-150 was down-regulated in CHD, which was negatively correlated with lncRNA ENST00000609755.1 and ELK1. The AUC was 0.777(95%CI, 0.659-0.895) when miRNA-150 and ELK1 was added, which was higher than that of lncRNA ENST00000609755.1 single indicator. CONCLUSION: LncRNA ENST00000609755.1, miR-150 and ELK1 may have a potential ceRNA regulatory network relationship which could be considered to have a good combined diagnostic value for CHD. Also, preliminarily reveal the possible mechanism of lncRNA ENST00000609755.1 involved in CHD.