Integrated Analysis Identifies a Nine-microRNA Signature Biomarker for Diagnosis and Prognosis in Colorectal Cancer - Di, Ziyang; Di, Maojun; Fu, Weihua; Tang, Qiang; Liu, Yanwei; Lei, Peijie; Gu, Xinsheng; Liu, Tong; Sun, Min (Frontiers in Genetics, 2020)
Background: Colorectal cancer (CRC) is the third most lethal and malignant type of cancer in the world. Abnormal expression of human microRNA-200a (hsa-miRNA-200a or miR-200a) has previously been characterized as a clinically noticeable biomarker in several cancers, but its role in CRC is still unclear. Methods: Three CRC miRNAs expression datasets were integratively analyzed by Least Absolute Shrinkage and Selector Operation (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Nine candidate miRNAs were identified and validated for diagnostic and prognostic capability with the prediction model. The potential roles of the tumor suppressor miR-200a-3p in invasion, migration and epithelial-mesenchymal transition of CRC cells were elaborated by in vitro studies. Results: Nine miRNAs (miR-492, miR-200a, miR-338, miR-29c, miR-101, miR-148a, miR-92a, miR-424, and miR-210) were identified as potentially useful diagnostic biomarkers in the clinic. The overall accuracy rate of nine miRNAs in the diagnostic model was 0.94, 0.89 and 0.978 in testing, validation and independent validation dataset, respectively. CRC patients in the GSE29622 were separated by the prognostic model into the low-risk score group and the high-risk score group. The area under receiver operating characteristic (ROC) curve (AUC) was 0.872 and 0.783 for predicting 1- to 10-year survival of CRC patients. The performance of the prognostic model was validated by an independent TCGA-Colon Adenocarcinoma (COAD) dataset with AUC values between 0.911 and 0.796 in predicting 1- to 10-year survival. A nomogram comprising risk scores, tumor stage, and TNM staging were generated for predicting 1-, 3-, and 5-year overall survival (OS) in the GSE29622 and TCGA-COAD dataset. Colony formation, invasion, and migration in DLD1 and SW480 cells were suppressed by overexpression of miR-200a-3p. Inhibition of miR-200a-3p function contributed to abnormal colony formation, migration, invasion, and epithelial mesenchymal transition (EMT). MiR-200a-3p binding sites were located within the 3’-untranslated region (3’-UTR) of the Forkhead box protein A1 (FOXA1) mRNA. Conclusion: We developed and validated a diagnostic and prognostic prediction model for CRC. MiR-200a-3p was determined to be a potential diagnostic and prognostic biomarker for CRC.