Novel Multiple miRNA-Based Signatures for Predicting Overall Survival and Recurrence-Free Survival of Colorectal Cancer Patients.

BACKGROUND Colorectal cancer (CRC) has become a heavy health burden around the world, accounting for about 10% of newly diagnosed cancer cases. In the present study, we aimed to establish the miRNA-based prediction signature to assess the prognosis of CRC patients. MATERIAL AND METHODS A total of 451 CRC patients' expression profiles and clinical information were download from the TCGA database. LASSO Cox regression was conducted to construct the overall survival (OS)- and recurrence-free survival (RFS)-associated prediction signatures, by which CRC patients were divided into low- and high-risk groups. Kaplan-Meier (K-M) curve and receiver operating characteristic (ROC) curves were used to explore the discriminatory ability and stability of the signatures. Functional enrichment analyses were performed to identify the probable mechanisms. RESULTS miRNA-216a, miRNA-887, miRNA-376b, and miRNA-891a were used to build the prediction formula associated with OS, while miR-1343, miR-149, miR-181a-1, miR-217, miR-3130-1, miR-378a, miR-542, miR-6716, miR-7-3, miR-7702, miR-677, and miR-891a were obtained to construct the formula related to RFS. K-M curve and ROC curve revealed the good discrimination and efficiency of OS in the training (P<0.001, AUC=0.712) and validation cohorts (P=0.019, AUC=0.657), as well as the results of RFS in the training (P<0.001, AUC=0.714) and validation cohorts (P=0.042, AUC=0.651). The function annotations for the targeted genes of these miRNAs show the potential mechanisms of CRC. CONCLUSIONS We established 2 novel miRNA-based prediction signatures of OS and RFS, which are reliable tools to assess the prognosis of CRC patients.