AUTHOR=Liu Yuejuan , Cui Yuxia , Bai Xuefeng , Feng Chenchen , Li Meng , Han Xiaole , Ai Bo , Zhang Jian , Li Xuecang , Han Junwei , Zhu Jiang , Jiang Yong , Pan Qi , Wang Fan , Xu Mingcong , Li Chunquan , Wang Qiuyu 

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

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.606940

DOI=10.3389/fgene.2020.606940

ISSN=1664-8021

ABSTRACT=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.