Objective: This study developed a prognosis-associated miRNA (PAM)-based risk score system to predict overall survival for pancreatic cancer.
Methods: We screened potential PAMs using bioinformatics technology. A risk score system integrating the PAMs was established, and the predictive value was evaluated. The targets of these PAMs were identified and functional enrichment analysis was performed.
Results: Seven PAMs (hsa-mir-188, hsa-mir-1301, hsa-mir-424, hsa-mir-5010, hsa-mir-584, hsa-mir-5091, and hsa-mir-3613) were identified. We also developed a risk score system, which showed a high Harrell concordance index (C-index, 0.723) for overall survival in the Cancer Genome Atlas data sets. The areas under the curve of the receiver operating characteristic curve at the 1-, 2-, and 3-year survival points were 0.718, 0.832, and 0.903, respectively. In addition, both the C-index and the areas under the curve for recurrence-free survival showed a good outcome, indicating that the system had a satisfactory predictive power. Furthermore, 49 target genes of PAMs were identified. Functional enrichment analysis revealed that these targets may be involved in various biological pathways, including the transforming growth factor β signaling pathway, Notch signaling, and downregulation of SMAD2/3.
Conclusions: The findings of this study suggest that the 7-miRNA-based risk score system is a promising prognostic model for pancreatic cancer.