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Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma

BACKGROUND: The aim of this study was to investigate the regulatory network of lncRNAs as competing endogenous RNAs (ceRNA) in bladder urothelial carcinoma (BUC) based on gene expression data derived from The Cancer Genome Atlas (TCGA). MATERIALS AND METHODS: RNA sequence profiles and clinical infor...

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Autores principales: Wang, Jiawu, Zhang, Chengyao, Wu, Yan, He, Weiyang, Gou, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892182/
https://www.ncbi.nlm.nih.gov/pubmed/31827401
http://dx.doi.org/10.1186/s12935-019-1052-2
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author Wang, Jiawu
Zhang, Chengyao
Wu, Yan
He, Weiyang
Gou, Xin
author_facet Wang, Jiawu
Zhang, Chengyao
Wu, Yan
He, Weiyang
Gou, Xin
author_sort Wang, Jiawu
collection PubMed
description BACKGROUND: The aim of this study was to investigate the regulatory network of lncRNAs as competing endogenous RNAs (ceRNA) in bladder urothelial carcinoma (BUC) based on gene expression data derived from The Cancer Genome Atlas (TCGA). MATERIALS AND METHODS: RNA sequence profiles and clinical information from 414 BUC tissues and 19 non-tumor adjacent tissues were downloaded from TCGA. Differentially expressed RNAs derived from BUC and non-tumor adjacent samples were identified using the R package “edgeR”. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the “clusterProfiler” package. Gene ontology and protein–protein interaction (PPI) networks were analyzed for the differentially expressed mRNAs using the “STRING” database. The network for the dysregulated lncRNA associated ceRNAs was then constructed for BUC using miRcode, miRTarBase, miRDB, and TargetScan. Cox regression analysis was performed to identify independent prognostic RNAs associated with BUC overall survival (OS). Survival analysis for the independent prognostic RNAs within the ceRNA network was calculated using Kaplan–Meier curves. RESULTS: Based on our analysis, a total of 666, 1819 and 157 differentially expressed lncRNAs, mRNAs and miRNAs were identified respectively. The ceRNA network was then constructed and contained 59 lncRNAs, 23 DEmiRNAs, and 52 DEmRNAs. In total, 5 lncRNAs (HCG22, ADAMTS9-AS1, ADAMTS9-AS2, AC078778.1, and AC112721.1), 2 miRNAs (hsa-mir-145 and hsa-mir-141) and 6 mRNAs (ZEB1, TMEM100, MAP1B, DUSP2, JUN, and AIFM3) were found to be related to OS. Two lncRNAs (ADAMTS9-AS1 and ADAMTS9-AS2) and 4 mRNA (DUSP2, JUN, MAP1B, and TMEM100) were validated using GEPIA. Thirty key hub genes were identified using the ranking method of degree. KEGG analysis demonstrated that the majority of the DEmRNAs were involved in pathways associated with cancer. CONCLUSION: Our findings provide an understanding of the important role of lncRNA–related ceRNAs in BUC. Additional experimental and clinical validations are required to support our findings.
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spelling pubmed-68921822019-12-11 Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma Wang, Jiawu Zhang, Chengyao Wu, Yan He, Weiyang Gou, Xin Cancer Cell Int Primary Research BACKGROUND: The aim of this study was to investigate the regulatory network of lncRNAs as competing endogenous RNAs (ceRNA) in bladder urothelial carcinoma (BUC) based on gene expression data derived from The Cancer Genome Atlas (TCGA). MATERIALS AND METHODS: RNA sequence profiles and clinical information from 414 BUC tissues and 19 non-tumor adjacent tissues were downloaded from TCGA. Differentially expressed RNAs derived from BUC and non-tumor adjacent samples were identified using the R package “edgeR”. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the “clusterProfiler” package. Gene ontology and protein–protein interaction (PPI) networks were analyzed for the differentially expressed mRNAs using the “STRING” database. The network for the dysregulated lncRNA associated ceRNAs was then constructed for BUC using miRcode, miRTarBase, miRDB, and TargetScan. Cox regression analysis was performed to identify independent prognostic RNAs associated with BUC overall survival (OS). Survival analysis for the independent prognostic RNAs within the ceRNA network was calculated using Kaplan–Meier curves. RESULTS: Based on our analysis, a total of 666, 1819 and 157 differentially expressed lncRNAs, mRNAs and miRNAs were identified respectively. The ceRNA network was then constructed and contained 59 lncRNAs, 23 DEmiRNAs, and 52 DEmRNAs. In total, 5 lncRNAs (HCG22, ADAMTS9-AS1, ADAMTS9-AS2, AC078778.1, and AC112721.1), 2 miRNAs (hsa-mir-145 and hsa-mir-141) and 6 mRNAs (ZEB1, TMEM100, MAP1B, DUSP2, JUN, and AIFM3) were found to be related to OS. Two lncRNAs (ADAMTS9-AS1 and ADAMTS9-AS2) and 4 mRNA (DUSP2, JUN, MAP1B, and TMEM100) were validated using GEPIA. Thirty key hub genes were identified using the ranking method of degree. KEGG analysis demonstrated that the majority of the DEmRNAs were involved in pathways associated with cancer. CONCLUSION: Our findings provide an understanding of the important role of lncRNA–related ceRNAs in BUC. Additional experimental and clinical validations are required to support our findings. BioMed Central 2019-12-03 /pmc/articles/PMC6892182/ /pubmed/31827401 http://dx.doi.org/10.1186/s12935-019-1052-2 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Primary Research
Wang, Jiawu
Zhang, Chengyao
Wu, Yan
He, Weiyang
Gou, Xin
Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma
title Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma
title_full Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma
title_fullStr Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma
title_full_unstemmed Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma
title_short Identification and analysis of long non-coding RNA related miRNA sponge regulatory network in bladder urothelial carcinoma
title_sort identification and analysis of long non-coding rna related mirna sponge regulatory network in bladder urothelial carcinoma
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892182/
https://www.ncbi.nlm.nih.gov/pubmed/31827401
http://dx.doi.org/10.1186/s12935-019-1052-2
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