MiRNA-Mediated Subpathway Identification and Network Module Analysis to Reveal Prognostic Markers in Human Pancreatic Cancer - Liu, Yuejuan; Cui, Yuxia; Bai, Xuefeng; Feng, Chenchen; Li, Meng; Han, Xiaole; Ai, Bo; Zhang, Jian; Li, Xuecang; Han, Junwei; Zhu, Jiang; Jiang, Yong; et al. (Frontiers in Genetics, 2020)
BACKGROUND: Pancreatic cancer (PC) remains one of the most lethal cancers. In contrast to the steady increase in survival for most cancers, the five-year survival remains low for PC patients. METHODS: We 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. RESULTS: We identified 105 miRNA-mediated subpathways associated with PC. Two subpathways within the MAPK signalling 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. CONCLUSIONS: Our 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.