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We constructed a prognostic risk model for colon adenocarcinoma (COAD) using microRNAs (miRNAs) as biomarkers. Clinical data of patients with COADs and miRNA-seq data were from TCGA, and the differential expression of miRNAs (carcinoma  vs.  para-carcinoma tissues) was assessed using R software. COAD data were randomly divided into Training and Testing Sets. A linear prognostic risk model was constructed using Cox regression analysis based on the Training Set. Patients were classified as high-risk or low-risk according to the score of the prognostic model. Survival analysis and receiver operating characteristic (ROC) curves were used to evaluate model performance. The gene targets in the prognostic model were identified and their biological functions were analyzed. Analysis of COAD and normal cell lines using qPCR was used to verify the model. There were 134 up-regulated and 140 down-regulated miRNAs. We used the Training Set to develop a prognostic model based on the expression of seven miRNAs. ROC analysis indicated this model had acceptable prediction accuracy (area under the curve=0.784). Kaplan-Meier survival analysis showed that overall survival was worse in the high-risk group. Cox regression analysis showed that the 7-miRNA Risk Score was an independent prognostic factor. The 2,863 predicted target genes were mainly enriched in the MAPK, PI3K-AKT, proteoglycans in cancer, and mTOR signaling pathways. For unknown reasons, expression of these miRNAs in cancerous and normal cells differed somewhat from model predictions. Regardless, the 7-miRNA Risk Score can be used to predict COAD prognosis and may help to guide clinical treatment.

Screening of miRNAs as Prognostic Biomarkers for Colon Adenocarcinoma and Biological Function Analysis of Their Target Genes