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Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma

BACKGROUND: Competing endogenous RNAs (ceRNAs) are a newly identified type of regulatory RNA. Accumulating evidence suggests that ceRNAs play an important role in the pathogenesis of diseases such as cancer. Thus, ceRNA dysregulation may represent an important molecular mechanism underlying cancer p...

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Autores principales: Liu, Yu, Xie, Deyao, He, Zhifeng, Zheng, Liangcheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497041/
https://www.ncbi.nlm.nih.gov/pubmed/31106044
http://dx.doi.org/10.7717/peerj.6694
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author Liu, Yu
Xie, Deyao
He, Zhifeng
Zheng, Liangcheng
author_facet Liu, Yu
Xie, Deyao
He, Zhifeng
Zheng, Liangcheng
author_sort Liu, Yu
collection PubMed
description BACKGROUND: Competing endogenous RNAs (ceRNAs) are a newly identified type of regulatory RNA. Accumulating evidence suggests that ceRNAs play an important role in the pathogenesis of diseases such as cancer. Thus, ceRNA dysregulation may represent an important molecular mechanism underlying cancer progression and poor prognosis. In this study, we aimed to identify ceRNAs that may serve as potential biomarkers for early diagnosis of lung adenocarcinoma (LUAD). METHODS: We performed differential gene expression analysis on TCGA-LUAD datasets to identify differentially expressed (DE) mRNAs, lncRNAs, and miRNAs at different tumor stages. Based on the ceRNA hypothesis and considering the synergistic or feedback regulation of ceRNAs, a lncRNA–miRNA–mRNA network was constructed. Functional analysis was performed using gene ontology term and KEGG pathway enrichment analysis and KOBAS 2.0 software. Transcription factor (TF) analysis was carried out to identify direct targets of the TFs associated with LUAD prognosis. Identified DE genes were validated using gene expression omnibus (GEO) datasets. RESULTS: Based on analysis of TCGA-LUAD datasets, we obtained 2,610 DE mRNAs, 915 lncRNAs, and 125 miRNAs that were common to different tumor stages (|log(2)(Fold change)| ≥ 1, false discovery rate < 0.01), respectively. Functional analysis showed that the aberrantly expressed mRNAs were closely related to tumor development. Survival analyses of the constructed ceRNA network modules demonstrated that five of them exhibit prognostic significance. The five ceRNA interaction modules contained one lncRNA (FENDRR), three mRNAs (EPAS1, FOXF1, and EDNRB), and four miRNAs (hsa-miR-148a, hsa-miR-195, hsa-miR-196b, and hsa-miR-301b). The aberrant expression of one lncRNA and three mRNAs was verified in the LUAD GEO dataset. Transcription factor analysis demonstrated that EPAS1 directly targeted 13 DE mRNAs. CONCLUSION: Our observations indicate that lncRNA-related ceRNAs and TFs play an important role in LUAD. The present study provides novel insights into the molecular mechanisms underlying LUAD pathogenesis. Furthermore, our study facilitates the identification of potential biomarkers for the early diagnosis and prognosis of LUAD and therapeutic targets for its treatment.
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spelling pubmed-64970412019-05-17 Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma Liu, Yu Xie, Deyao He, Zhifeng Zheng, Liangcheng PeerJ Bioinformatics BACKGROUND: Competing endogenous RNAs (ceRNAs) are a newly identified type of regulatory RNA. Accumulating evidence suggests that ceRNAs play an important role in the pathogenesis of diseases such as cancer. Thus, ceRNA dysregulation may represent an important molecular mechanism underlying cancer progression and poor prognosis. In this study, we aimed to identify ceRNAs that may serve as potential biomarkers for early diagnosis of lung adenocarcinoma (LUAD). METHODS: We performed differential gene expression analysis on TCGA-LUAD datasets to identify differentially expressed (DE) mRNAs, lncRNAs, and miRNAs at different tumor stages. Based on the ceRNA hypothesis and considering the synergistic or feedback regulation of ceRNAs, a lncRNA–miRNA–mRNA network was constructed. Functional analysis was performed using gene ontology term and KEGG pathway enrichment analysis and KOBAS 2.0 software. Transcription factor (TF) analysis was carried out to identify direct targets of the TFs associated with LUAD prognosis. Identified DE genes were validated using gene expression omnibus (GEO) datasets. RESULTS: Based on analysis of TCGA-LUAD datasets, we obtained 2,610 DE mRNAs, 915 lncRNAs, and 125 miRNAs that were common to different tumor stages (|log(2)(Fold change)| ≥ 1, false discovery rate < 0.01), respectively. Functional analysis showed that the aberrantly expressed mRNAs were closely related to tumor development. Survival analyses of the constructed ceRNA network modules demonstrated that five of them exhibit prognostic significance. The five ceRNA interaction modules contained one lncRNA (FENDRR), three mRNAs (EPAS1, FOXF1, and EDNRB), and four miRNAs (hsa-miR-148a, hsa-miR-195, hsa-miR-196b, and hsa-miR-301b). The aberrant expression of one lncRNA and three mRNAs was verified in the LUAD GEO dataset. Transcription factor analysis demonstrated that EPAS1 directly targeted 13 DE mRNAs. CONCLUSION: Our observations indicate that lncRNA-related ceRNAs and TFs play an important role in LUAD. The present study provides novel insights into the molecular mechanisms underlying LUAD pathogenesis. Furthermore, our study facilitates the identification of potential biomarkers for the early diagnosis and prognosis of LUAD and therapeutic targets for its treatment. PeerJ Inc. 2019-04-29 /pmc/articles/PMC6497041/ /pubmed/31106044 http://dx.doi.org/10.7717/peerj.6694 Text en © 2019 Liu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Liu, Yu
Xie, Deyao
He, Zhifeng
Zheng, Liangcheng
Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma
title Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma
title_full Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma
title_fullStr Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma
title_full_unstemmed Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma
title_short Integrated analysis reveals five potential ceRNA biomarkers in human lung adenocarcinoma
title_sort integrated analysis reveals five potential cerna biomarkers in human lung adenocarcinoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497041/
https://www.ncbi.nlm.nih.gov/pubmed/31106044
http://dx.doi.org/10.7717/peerj.6694
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