MiRNA-Mediated Subpathway Identification and Network Module Analysis to Reveal Prognostic Markers in Human Pancreatic Cancer

Abstract

BackgroundPancreatic cancer (PC) remains one of the most lethal cancers. In contrast to the steady increase in survival for most cancers, the 5-year survival remains low for PC patients.MethodsWe describe a new pipeline that can be used to identify prognostic molecular biomarkers by identifying miRNA-mediated subpathways associated with PC. These modules were then further extracted from a comprehensive miRNA-gene network (CMGN). An exhaustive survival analysis was performed to estimate the prognostic value of these modules.ResultsWe identified 105 miRNA-mediated subpathways associated with PC. Two subpathways within the MAPK signaling and cell cycle pathways were found to be highly related to PC. Of the miRNA-mRNA modules extracted from CMGN, six modules showed good prognostic performance in both independent validated datasets.ConclusionsOur study provides novel insight into the mechanisms of PC. We inferred that six miRNA-mRNA modules could serve as potential prognostic molecular biomarkers in PC based on the pipeline we proposed.