Frontiers in Genetics (Dec 2020)

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

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

DOI
https://doi.org/10.3389/fgene.2020.606940
Journal volume & issue
Vol. 11

Abstract

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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.

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