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=11

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=<sec><title>Background</title><p>Pancreatic 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.</p></sec><sec><title>Methods</title><p>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.</p></sec><sec><title>Results</title><p>We 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.</p></sec><sec><title>Conclusions</title><p>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.</p></sec>