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Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis

Background: Lymph node metastasis (LNM) is an important pathological characteristic of bladder cancer (BCa). However, the molecular mechanism underlying LNM was not thoroughly elaborated. Identification for LNM-related biomarkers may contribute to making suitable therapies. So, the current study was...

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Autores principales: Luo, Cheng, Huang, Bin, Wu, Yukun, Xu, Yadong, Ou, Wei, Chen, Junxing, Chen, Lingwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339436/
https://www.ncbi.nlm.nih.gov/pubmed/34368222
http://dx.doi.org/10.3389/fmolb.2021.633299
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author Luo, Cheng
Huang, Bin
Wu, Yukun
Xu, Yadong
Ou, Wei
Chen, Junxing
Chen, Lingwu
author_facet Luo, Cheng
Huang, Bin
Wu, Yukun
Xu, Yadong
Ou, Wei
Chen, Junxing
Chen, Lingwu
author_sort Luo, Cheng
collection PubMed
description Background: Lymph node metastasis (LNM) is an important pathological characteristic of bladder cancer (BCa). However, the molecular mechanism underlying LNM was not thoroughly elaborated. Identification for LNM-related biomarkers may contribute to making suitable therapies. So, the current study was aimed to identify key genes and construct a prognostic signature. Methods: Based on the Cancer Genome Atlas (TCGA) database, gene expression and clinical information were obtained. Then, the weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules and hub genes. A function analysis and a gene set enrichment analysis were applied to explore biological functions and pathways of interested genes. Furthermore, a prognostic model based on LNM-related genes was constructed by using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Finally, nine co-expression modules were constructed, and two modules (turquoise and green) were significantly associated with LNM. Three hub genes were identified as DACT3, TNS1, and MSRB3, which were annotated in actin binding, actin cytoskeleton, adaptive immune response, and cell adhesion molecular binding by the GSEA method. Further analysis demonstrated that three hub genes were associated with the overall survival of BCa patients. In addition, we built a prognostic signature based on the genes from LNM-related modules and evaluated the prognostic value of this signature. Conclusion: In general, this study revealed the key genes related to LNM and prognostic signature, which might provide new insights into therapeutic target of BCa.
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spelling pubmed-83394362021-08-06 Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis Luo, Cheng Huang, Bin Wu, Yukun Xu, Yadong Ou, Wei Chen, Junxing Chen, Lingwu Front Mol Biosci Molecular Biosciences Background: Lymph node metastasis (LNM) is an important pathological characteristic of bladder cancer (BCa). However, the molecular mechanism underlying LNM was not thoroughly elaborated. Identification for LNM-related biomarkers may contribute to making suitable therapies. So, the current study was aimed to identify key genes and construct a prognostic signature. Methods: Based on the Cancer Genome Atlas (TCGA) database, gene expression and clinical information were obtained. Then, the weighted gene co-expression network analysis (WGCNA) was performed to identify the key modules and hub genes. A function analysis and a gene set enrichment analysis were applied to explore biological functions and pathways of interested genes. Furthermore, a prognostic model based on LNM-related genes was constructed by using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Finally, nine co-expression modules were constructed, and two modules (turquoise and green) were significantly associated with LNM. Three hub genes were identified as DACT3, TNS1, and MSRB3, which were annotated in actin binding, actin cytoskeleton, adaptive immune response, and cell adhesion molecular binding by the GSEA method. Further analysis demonstrated that three hub genes were associated with the overall survival of BCa patients. In addition, we built a prognostic signature based on the genes from LNM-related modules and evaluated the prognostic value of this signature. Conclusion: In general, this study revealed the key genes related to LNM and prognostic signature, which might provide new insights into therapeutic target of BCa. Frontiers Media S.A. 2021-07-22 /pmc/articles/PMC8339436/ /pubmed/34368222 http://dx.doi.org/10.3389/fmolb.2021.633299 Text en Copyright © 2021 Luo, Huang, Wu, Xu, Ou, Chen and Chen. https://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 Molecular Biosciences
Luo, Cheng
Huang, Bin
Wu, Yukun
Xu, Yadong
Ou, Wei
Chen, Junxing
Chen, Lingwu
Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis
title Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis
title_full Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis
title_fullStr Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis
title_full_unstemmed Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis
title_short Identification of Lymph Node Metastasis–Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis
title_sort identification of lymph node metastasis–related key genes and prognostic risk model in bladder cancer by co-expression analysis
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339436/
https://www.ncbi.nlm.nih.gov/pubmed/34368222
http://dx.doi.org/10.3389/fmolb.2021.633299
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