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Building a Competing Endogenous RNA Network to Find Potential Long Non-Coding RNA Biomarkers for Pheochromocytoma

Authors
  • Liang, Ying-Chun
  • Wu, Yu-Peng
  • Chen, Dong-Ning
  • Chen, Shao-Hao
  • Li, Xiao-Dong
  • Sun, Xiong-Lin
  • Wei, Yong
  • Ning, Xu
  • Xue, Xue-Yi
Type
Published Article
Journal
Cellular Physiology and Biochemistry
Publisher
S. Karger AG
Publication Date
Dec 14, 2018
Volume
51
Issue
6
Pages
2916–2924
Identifiers
DOI: 10.1159/000496043
PMID: 30562748
Source
Karger
Keywords
License
Green
External links

Abstract

Background/Aims: Accumulating evidence has shown that long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks play crucial roles in tumor survival and patient prognosis; however, studies investigating ceRNA networks in pheochromocytoma (PCC) are lacking. In this study, we investigated the pathogenesis of PCC and whether lncRNAs acting through ceRNAs networks were associated with prognosis. Methods: A total of 183 PCC samples and 3 control samples from The Cancer Genome Atlas database were analyzed. The Empirical Analysis of Digital Gene Expression Data package in R (edgeR) was used to analyze differentially expressed RNAs. Biological processes and pathways functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. LncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.0 software based on the differentially expressed RNAs Survival package in R was used to perform survival analysis. Results: In total, 554 differentially expressed lncRNAs, 1775 mRNAs and 40 miRNAs were selected for further analysis. Subsequently, 23 lncRNAs, 22 mRNAs, and 6 miRNAs were included in the constructed ceRNA network. Meanwhile, two of the 23 lncRNAs (C9orf147 and BSN-AS2) were identified as independent predictors of overall survival in PCC patients (P< 0.05). Conclusion: This study improves the understanding of lncRNA-related ceRNA networks in PCC and suggests that the lncRNAs C9orf147 and BSN-AS2 could be independent prognostic biomarkers and potential therapeutic targets for PCC.

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