Literature DB >> 33362865

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

Yuejuan Liu1, Yuxia Cui2, Xuefeng Bai1, Chenchen Feng1, Meng Li1, Xiaole Han1, Bo Ai1, Jian Zhang1, Xuecang Li1, Junwei Han3, Jiang Zhu1, Yong Jiang1, Qi Pan1, Fan Wang1, Mingcong Xu1, Chunquan Li1, Qiuyu Wang1.   

Abstract

BACKGROUND: 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.
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 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.
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.
Copyright © 2020 Liu, Cui, Bai, Feng, Li, Han, Ai, Zhang, Li, Han, Zhu, Jiang, Pan, Wang, Xu, Li and Wang.

Entities:  

Keywords:  gene; miRNA; pancreatic cancer; pathway; survival

Year:  2020        PMID: 33362865      PMCID: PMC7756031          DOI: 10.3389/fgene.2020.606940

Source DB:  PubMed          Journal:  Front Genet        ISSN: 1664-8021            Impact factor:   4.599


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