Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology · 2018
Building a Competing Endogenous RNA Network to Find Potential Long Non-Coding RNA Biomarkers for Pheochromocytoma.
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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
Аннотация
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.
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.