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Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study

Bladder cancer is the 11th most common cancer in the world. Bladder cancer can be roughly divided into muscle invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer (NMIBC). The aim of the present study was to identify the key genes and pathways associated with the progression of NMIB...

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Autores principales: Zhang, Heng, Shan, Gang, Song, Jukun, Tian, Ye, An, Ling-Yue, Ban, Yong, Luo, Guang-Heng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251326/
https://www.ncbi.nlm.nih.gov/pubmed/32391563
http://dx.doi.org/10.1042/BSR20194192
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author Zhang, Heng
Shan, Gang
Song, Jukun
Tian, Ye
An, Ling-Yue
Ban, Yong
Luo, Guang-Heng
author_facet Zhang, Heng
Shan, Gang
Song, Jukun
Tian, Ye
An, Ling-Yue
Ban, Yong
Luo, Guang-Heng
author_sort Zhang, Heng
collection PubMed
description Bladder cancer is the 11th most common cancer in the world. Bladder cancer can be roughly divided into muscle invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer (NMIBC). The aim of the present study was to identify the key genes and pathways associated with the progression of NMIBC to MIBC and to further analyze its molecular mechanism and prognostic significance. We analyzed microarray data of NMIBC and MIBC gene expression datasets (GSE31684) listed in the Gene Expression Omnibus (GEO) database. After the dataset was analyzed using R software, differentially expressed genes (DEGs) of NMIBC and MIBC were identified. These DEGs were analyzed using Gene Ontology (GO) enrichment, KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein–protein interaction (PPI) analysis. The effect of these hub genes on the survival of bladder cancer patients was analyzed in The Cancer Genome Atlas (TCGA) database. A total of 389 DEGs were obtained, of which 270 were up-regulated and 119 down-regulated. GO and KEGG pathway enrichment analysis revealed that DEGs were mainly involved in the pathway of protein digestion and absorption, extracellular matrix (ECM) receiver interaction, phantom, toll-like receptor (TLR) signaling pathway, focal adhesion, NF-κB signaling pathway, PI3K/Akt signaling pathway, and other signaling pathways. Top five hub genes COL1A2, COL3A1, COL5A1, POSTN, and COL12A1 may be involved in the development of MIBC. These results may provide us with a further understanding of the occurrence and development of MIBC, as well as new targets for the diagnosis and treatment of MIBC in the future.
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spelling pubmed-72513262020-06-05 Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study Zhang, Heng Shan, Gang Song, Jukun Tian, Ye An, Ling-Yue Ban, Yong Luo, Guang-Heng Biosci Rep Bioinformatics Bladder cancer is the 11th most common cancer in the world. Bladder cancer can be roughly divided into muscle invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer (NMIBC). The aim of the present study was to identify the key genes and pathways associated with the progression of NMIBC to MIBC and to further analyze its molecular mechanism and prognostic significance. We analyzed microarray data of NMIBC and MIBC gene expression datasets (GSE31684) listed in the Gene Expression Omnibus (GEO) database. After the dataset was analyzed using R software, differentially expressed genes (DEGs) of NMIBC and MIBC were identified. These DEGs were analyzed using Gene Ontology (GO) enrichment, KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein–protein interaction (PPI) analysis. The effect of these hub genes on the survival of bladder cancer patients was analyzed in The Cancer Genome Atlas (TCGA) database. A total of 389 DEGs were obtained, of which 270 were up-regulated and 119 down-regulated. GO and KEGG pathway enrichment analysis revealed that DEGs were mainly involved in the pathway of protein digestion and absorption, extracellular matrix (ECM) receiver interaction, phantom, toll-like receptor (TLR) signaling pathway, focal adhesion, NF-κB signaling pathway, PI3K/Akt signaling pathway, and other signaling pathways. Top five hub genes COL1A2, COL3A1, COL5A1, POSTN, and COL12A1 may be involved in the development of MIBC. These results may provide us with a further understanding of the occurrence and development of MIBC, as well as new targets for the diagnosis and treatment of MIBC in the future. Portland Press Ltd. 2020-05-26 /pmc/articles/PMC7251326/ /pubmed/32391563 http://dx.doi.org/10.1042/BSR20194192 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
spellingShingle Bioinformatics
Zhang, Heng
Shan, Gang
Song, Jukun
Tian, Ye
An, Ling-Yue
Ban, Yong
Luo, Guang-Heng
Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study
title Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study
title_full Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study
title_fullStr Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study
title_full_unstemmed Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study
title_short Extracellular matrix-related genes play an important role in the progression of NMIBC to MIBC: a bioinformatics analysis study
title_sort extracellular matrix-related genes play an important role in the progression of nmibc to mibc: a bioinformatics analysis study
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251326/
https://www.ncbi.nlm.nih.gov/pubmed/32391563
http://dx.doi.org/10.1042/BSR20194192
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