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Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis

Bladder cancer (BC) is one of the most common malignancies in terms of incidence and recurrence worldwide. The aim of this study was to identify novel prognostic biomarkers related to BC progression utilizing weighted gene co-expression network analysis (WGCNA) and further bioinformatic analysis. Fi...

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Autores principales: Wang, Chengyuan, Yang, Yujing, Yin, Lei, Wei, Ningde, Hong, Ting, Sun, Zuyu, Yao, Jiaxi, Li, Zhi, Liu, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338771/
https://www.ncbi.nlm.nih.gov/pubmed/32695668
http://dx.doi.org/10.3389/fonc.2020.00931
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author Wang, Chengyuan
Yang, Yujing
Yin, Lei
Wei, Ningde
Hong, Ting
Sun, Zuyu
Yao, Jiaxi
Li, Zhi
Liu, Tao
author_facet Wang, Chengyuan
Yang, Yujing
Yin, Lei
Wei, Ningde
Hong, Ting
Sun, Zuyu
Yao, Jiaxi
Li, Zhi
Liu, Tao
author_sort Wang, Chengyuan
collection PubMed
description Bladder cancer (BC) is one of the most common malignancies in terms of incidence and recurrence worldwide. The aim of this study was to identify novel prognostic biomarkers related to BC progression utilizing weighted gene co-expression network analysis (WGCNA) and further bioinformatic analysis. First, we constructed a co-expression network by using WGCNA among 274 TCGA-BLCA patients and preliminarily screened out four genes (CORO1C, TMPRSS4, PIK3C2B, and ZNF692) associated with advanced clinical traits. In support, GSE19915 and specimens from 124 patients were used to validate the genes selected by WGCNA; then, CORO1C and TMPRSS4 were confirmed as hub genes with strong prognostic values in BC. Moreover, the result of gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) indicated that CORO1C and TMPRSS4 might be involved in the process of epithelial to mesenchymal transition (EMT) reversely. In addition, high expression of CORO1C was found to be significantly correlated with tumor-infiltrating neutrophils (TINs), a negative regulatory component that facilitates tumor distant progression and induces poor clinical outcome. In conclusion, our study first identified CORO1C and TMPRSS4 as vital regulators in the process of tumor progression through influencing EMT and could be developed to effective prognostic and therapeutic targets in future BC treatment.
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spelling pubmed-73387712020-07-20 Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis Wang, Chengyuan Yang, Yujing Yin, Lei Wei, Ningde Hong, Ting Sun, Zuyu Yao, Jiaxi Li, Zhi Liu, Tao Front Oncol Oncology Bladder cancer (BC) is one of the most common malignancies in terms of incidence and recurrence worldwide. The aim of this study was to identify novel prognostic biomarkers related to BC progression utilizing weighted gene co-expression network analysis (WGCNA) and further bioinformatic analysis. First, we constructed a co-expression network by using WGCNA among 274 TCGA-BLCA patients and preliminarily screened out four genes (CORO1C, TMPRSS4, PIK3C2B, and ZNF692) associated with advanced clinical traits. In support, GSE19915 and specimens from 124 patients were used to validate the genes selected by WGCNA; then, CORO1C and TMPRSS4 were confirmed as hub genes with strong prognostic values in BC. Moreover, the result of gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) indicated that CORO1C and TMPRSS4 might be involved in the process of epithelial to mesenchymal transition (EMT) reversely. In addition, high expression of CORO1C was found to be significantly correlated with tumor-infiltrating neutrophils (TINs), a negative regulatory component that facilitates tumor distant progression and induces poor clinical outcome. In conclusion, our study first identified CORO1C and TMPRSS4 as vital regulators in the process of tumor progression through influencing EMT and could be developed to effective prognostic and therapeutic targets in future BC treatment. Frontiers Media S.A. 2020-06-30 /pmc/articles/PMC7338771/ /pubmed/32695668 http://dx.doi.org/10.3389/fonc.2020.00931 Text en Copyright © 2020 Wang, Yang, Yin, Wei, Hong, Sun, Yao, Li and Liu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Wang, Chengyuan
Yang, Yujing
Yin, Lei
Wei, Ningde
Hong, Ting
Sun, Zuyu
Yao, Jiaxi
Li, Zhi
Liu, Tao
Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis
title Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis
title_full Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis
title_fullStr Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis
title_full_unstemmed Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis
title_short Novel Potential Biomarkers Associated With Epithelial to Mesenchymal Transition and Bladder Cancer Prognosis Identified by Integrated Bioinformatic Analysis
title_sort novel potential biomarkers associated with epithelial to mesenchymal transition and bladder cancer prognosis identified by integrated bioinformatic analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338771/
https://www.ncbi.nlm.nih.gov/pubmed/32695668
http://dx.doi.org/10.3389/fonc.2020.00931
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