Author/Authors :
Qin, Da Department of Gastroenterology - Beijing Friendship Hospital - Capital Medical University - National Clinical Research Center forDigestive Disease, Beijing Digestive Disease Center - Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China , Wei, Rui Department of Gastroenterology - Beijing Friendship Hospital - Capital Medical University - National Clinical Research Center forDigestive Disease, Beijing Digestive Disease Center - Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China , Liu, Si Department of Gastroenterology - Beijing Friendship Hospital - Capital Medical University - National Clinical Research Center forDigestive Disease, Beijing Digestive Disease Center - Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China , Zhu, Shengtao Department of Gastroenterology - Beijing Friendship Hospital - Capital Medical University - National Clinical Research Center forDigestive Disease, Beijing Digestive Disease Center - Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China , Zhang, Shutian Department of Gastroenterology - Beijing Friendship Hospital - Capital Medical University - National Clinical Research Center forDigestive Disease, Beijing Digestive Disease Center - Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China , Min, Li Department of Gastroenterology - Beijing Friendship Hospital - Capital Medical University - National Clinical Research Center forDigestive Disease, Beijing Digestive Disease Center - Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China
Abstract :
Introduction. Circulation microRNAs (miRNAs) perform as potential diagnostic biomarkers of many kinds of cancers. This studyis aimed at identifying circulation miRNAs as diagnostic biomarkers in colon cancer.Methods. We conducted a weighted genecoexpression network analysis (WGCNA) in miRNAs tofind out the expression pattern among circulation miRNAs by using a“WGCNA”package in R. Correlation analysis was performed tofind cancer-related modules. Differentially expressed miRNAs(DEmiRs) in colon cancer were identified by a“limma”package in R. Hub gene analysis was conducted for these DEmiRs in thecancer-related modules by the“closeness”method in cytoscape software. Then, logistic regression was performed to identify theindependent risk factors, and a scoring system was constructed based on these independent risk factors. Then, we use data fromthe GEO database to confirm the reliability of this scoring system.Results. A total of 9 independent coexpression moduleswere constructed based on the expression levels of 848 miRNAs by WGCNA. After correlation analysis, green (cor = 0:77,p=3×10‐25) and yellow (cor = 0:65,p=6×10‐16) modules were strongly correlated with cancer development. 20 hub geneswere found after hub gene analysis in these DEmiRs by cytoscape. Among all these hub genes, hsa-miR-23a-3p(OR = 2:6391,p=6:23 × 10‐5) and hsa-miR-663a (OR = 1:4220,p=0:0069) were identified as an independent risk factor ofcolon cancer by multivariate regression. Furthermore, a scoring system was built to predict the probability of colon cancerbased on both of these miRNAs, the area under the curve (AUC) of which was 0.828. Data from GSE106817 andGSE112264 was used to confirm this scoring system. and the AUC of them was 0.980 and 0.917, respectively.Conclusion.We built a scoring system based on circulation hub miRNAs found by WGCNA to predict the development of colon cancer.
