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Bioinformatic Identification of Potential Hub Genes in Muscle-Invasive Bladder Urothelial Carcinoma
Despite aggressive treatment approaches, muscle-invasive bladder urothelial carcinoma (MIBC) patients still have a 50% chance of developing general incurable metastases. Therefore, there is an urgent need for candidate markers to enhance diagnosis and generate effective treatments for this disease....
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Published in: | Cell transplantation 2020-01, Vol.29, p.963689720965178 |
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description | Despite aggressive treatment approaches, muscle-invasive bladder urothelial carcinoma (MIBC) patients still have a 50% chance of developing general incurable metastases. Therefore, there is an urgent need for candidate markers to enhance diagnosis and generate effective treatments for this disease. We evaluated four mRNA microarray datasets to find differences between non-MIBC (NMIBC) and MIBC tissues. Through a gene expression profile analysis via the Gene Expression Omnibus database, we identified 56 differentially expressed genes (DEGs). Enrichment analysis of gene ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome pathways revealed the interactions between these DEGs. Next, we established a protein-protein interaction network to determine the interrelationship between the DEGs and selected 10 hub genes accordingly. Bladder urothelial carcinoma (BLCA) patients with COL1A2, COL5A1, and COL5A2 alterations showed poor disease-free survival rates, while BLCA patients with COL1A1 and LUM alterations showed poor overall survival rates. Oncomine analysis of MIBC versus NMIBC tissues showed that COL1A1, COL5A2, COL1A2, and COL3A1 were consistently among the top 20 overexpressed genes in different studies. Using the TCGAportal, we noted that the high expression of each of the four genes led to shorter BLCA patient overall survival. It was evident that BLCA patients with an elevated high combined gene expression had significantly shorter overall survival and relapse-free survival than those with low combined gene expression using PROGgeneV2. Using Gene Expression Profiling Interactive Analysis, we noted that COL1A1, COL1A2, COL3A1, and COL5A2 were positively correlated with each other in BLCA. These genes are considered as clinically relevant genes, suggesting that they may play an important role in the carcinogenesis, development, invasion, and metastasis of MIBC. However, considering we adopted a bioinformatic approach, more research is crucial to confirm our results. Nonetheless, our findings may have important prospective clinical implementations. |
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Therefore, there is an urgent need for candidate markers to enhance diagnosis and generate effective treatments for this disease. We evaluated four mRNA microarray datasets to find differences between non-MIBC (NMIBC) and MIBC tissues. Through a gene expression profile analysis via the Gene Expression Omnibus database, we identified 56 differentially expressed genes (DEGs). Enrichment analysis of gene ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome pathways revealed the interactions between these DEGs. Next, we established a protein-protein interaction network to determine the interrelationship between the DEGs and selected 10 hub genes accordingly. Bladder urothelial carcinoma (BLCA) patients with COL1A2, COL5A1, and COL5A2 alterations showed poor disease-free survival rates, while BLCA patients with COL1A1 and LUM alterations showed poor overall survival rates. Oncomine analysis of MIBC versus NMIBC tissues showed that COL1A1, COL5A2, COL1A2, and COL3A1 were consistently among the top 20 overexpressed genes in different studies. Using the TCGAportal, we noted that the high expression of each of the four genes led to shorter BLCA patient overall survival. It was evident that BLCA patients with an elevated high combined gene expression had significantly shorter overall survival and relapse-free survival than those with low combined gene expression using PROGgeneV2. Using Gene Expression Profiling Interactive Analysis, we noted that COL1A1, COL1A2, COL3A1, and COL5A2 were positively correlated with each other in BLCA. These genes are considered as clinically relevant genes, suggesting that they may play an important role in the carcinogenesis, development, invasion, and metastasis of MIBC. However, considering we adopted a bioinformatic approach, more research is crucial to confirm our results. Nonetheless, our findings may have important prospective clinical implementations.</description><identifier>ISSN: 0963-6897</identifier><identifier>ISSN: 1555-3892</identifier><identifier>EISSN: 1555-3892</identifier><identifier>DOI: 10.1177/0963689720965178</identifier><identifier>PMID: 33035117</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Bladder ; Bladder cancer ; Carcinogenesis ; Collagen (type I) ; Collagen Type I - genetics ; Collagen Type I - metabolism ; Collagen Type I, alpha 1 Chain ; Collagen Type III - genetics ; Collagen Type III - metabolism ; Computational Biology - methods ; DNA microarrays ; Gene expression ; Genomes ; Humans ; Invasiveness ; Metastases ; Original ; Patients ; Protein Binding ; Protein interaction ; Survival ; Transcriptome ; Urinary Bladder - metabolism ; Urinary Bladder - pathology ; Urothelial carcinoma</subject><ispartof>Cell transplantation, 2020-01, Vol.29, p.963689720965178</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020. This work is licensed under the Creative Commons Attribution – Non-Commercial License https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020 2020 SAGE Publications Inc, unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c528t-5a8ad39698232d60da59696081d72c2caa3289fb687d61dfc23eba3c8ded09323</citedby><cites>FETCH-LOGICAL-c528t-5a8ad39698232d60da59696081d72c2caa3289fb687d61dfc23eba3c8ded09323</cites><orcidid>0000-0001-9982-1391</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7784563/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2473737608?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,21945,25731,27830,27901,27902,36989,36990,44566,44921,45309,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33035117$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guo, Changgang</creatorcontrib><creatorcontrib>Shao, Ting</creatorcontrib><creatorcontrib>Wei, Dadong</creatorcontrib><creatorcontrib>Li, Chunsheng</creatorcontrib><creatorcontrib>Liu, Fengjun</creatorcontrib><creatorcontrib>Li, Minghui</creatorcontrib><creatorcontrib>Gao, Zhiming</creatorcontrib><creatorcontrib>Bao, Guochang</creatorcontrib><title>Bioinformatic Identification of Potential Hub Genes in Muscle-Invasive Bladder Urothelial Carcinoma</title><title>Cell transplantation</title><addtitle>Cell Transplant</addtitle><description>Despite aggressive treatment approaches, muscle-invasive bladder urothelial carcinoma (MIBC) patients still have a 50% chance of developing general incurable metastases. Therefore, there is an urgent need for candidate markers to enhance diagnosis and generate effective treatments for this disease. We evaluated four mRNA microarray datasets to find differences between non-MIBC (NMIBC) and MIBC tissues. Through a gene expression profile analysis via the Gene Expression Omnibus database, we identified 56 differentially expressed genes (DEGs). Enrichment analysis of gene ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome pathways revealed the interactions between these DEGs. Next, we established a protein-protein interaction network to determine the interrelationship between the DEGs and selected 10 hub genes accordingly. Bladder urothelial carcinoma (BLCA) patients with COL1A2, COL5A1, and COL5A2 alterations showed poor disease-free survival rates, while BLCA patients with COL1A1 and LUM alterations showed poor overall survival rates. Oncomine analysis of MIBC versus NMIBC tissues showed that COL1A1, COL5A2, COL1A2, and COL3A1 were consistently among the top 20 overexpressed genes in different studies. Using the TCGAportal, we noted that the high expression of each of the four genes led to shorter BLCA patient overall survival. It was evident that BLCA patients with an elevated high combined gene expression had significantly shorter overall survival and relapse-free survival than those with low combined gene expression using PROGgeneV2. Using Gene Expression Profiling Interactive Analysis, we noted that COL1A1, COL1A2, COL3A1, and COL5A2 were positively correlated with each other in BLCA. These genes are considered as clinically relevant genes, suggesting that they may play an important role in the carcinogenesis, development, invasion, and metastasis of MIBC. However, considering we adopted a bioinformatic approach, more research is crucial to confirm our results. Nonetheless, our findings may have important prospective clinical implementations.</description><subject>Bladder</subject><subject>Bladder cancer</subject><subject>Carcinogenesis</subject><subject>Collagen (type I)</subject><subject>Collagen Type I - genetics</subject><subject>Collagen Type I - metabolism</subject><subject>Collagen Type I, alpha 1 Chain</subject><subject>Collagen Type III - genetics</subject><subject>Collagen Type III - metabolism</subject><subject>Computational Biology - methods</subject><subject>DNA microarrays</subject><subject>Gene expression</subject><subject>Genomes</subject><subject>Humans</subject><subject>Invasiveness</subject><subject>Metastases</subject><subject>Original</subject><subject>Patients</subject><subject>Protein Binding</subject><subject>Protein interaction</subject><subject>Survival</subject><subject>Transcriptome</subject><subject>Urinary Bladder - metabolism</subject><subject>Urinary Bladder - pathology</subject><subject>Urothelial carcinoma</subject><issn>0963-6897</issn><issn>1555-3892</issn><issn>1555-3892</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp1kk1v1DAQhi1ERZfCnROKxIVLqD_i2L4g0RW0K7UqB3q2Jraz9Sqxi52s1H-Pw5ZCKyEf7Jl557FnPAi9I_gTIUKcYtWyVipBy4ETIV-gFeGc10wq-hKtlnC9xI_R65x3GGPBKH-FjhnDjBfCCpkzH33oYxph8qbaWBcm33tTrBiq2Fff47S4YKgu5q46d8Hlyofqas5mcPUm7CH7vavOBrDWpeomxenWDYt-Dcn4EEd4g456GLJ7-7CfoJtvX3-sL-rL6_PN-stlbTiVU81BgmWqVZIyaltsgRejxZJYQQ01AIxK1XetFLYltjeUuQ6YkdZZrBhlJ2hz4NoIO32X_AjpXkfw-rcjpq2GVKocnG5LloDSwo6LRnaNsk2Bcsp6hgnjXWF9PrDu5m501pQeJBieQJ9Ggr_V27jXQsiGt6wAPj4AUvw5uzzp0WfjhgGCi3PWtGmU4pIrUqQfnkl3cU6htKqoBCurNKGo8EFlUsw5uf7xMQTrZRr082koKe__LeIx4c_3F0F9EGTYur-3_hf4C3OlvIU</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Guo, Changgang</creator><creator>Shao, Ting</creator><creator>Wei, Dadong</creator><creator>Li, Chunsheng</creator><creator>Liu, Fengjun</creator><creator>Li, Minghui</creator><creator>Gao, Zhiming</creator><creator>Bao, Guochang</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><general>SAGE Publishing</general><scope>AFRWT</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9982-1391</orcidid></search><sort><creationdate>20200101</creationdate><title>Bioinformatic Identification of Potential Hub Genes in Muscle-Invasive Bladder Urothelial Carcinoma</title><author>Guo, Changgang ; Shao, Ting ; Wei, Dadong ; Li, Chunsheng ; Liu, Fengjun ; Li, Minghui ; Gao, Zhiming ; Bao, Guochang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c528t-5a8ad39698232d60da59696081d72c2caa3289fb687d61dfc23eba3c8ded09323</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Bladder</topic><topic>Bladder cancer</topic><topic>Carcinogenesis</topic><topic>Collagen (type I)</topic><topic>Collagen Type I - genetics</topic><topic>Collagen Type I - metabolism</topic><topic>Collagen Type I, alpha 1 Chain</topic><topic>Collagen Type III - genetics</topic><topic>Collagen Type III - metabolism</topic><topic>Computational Biology - methods</topic><topic>DNA microarrays</topic><topic>Gene expression</topic><topic>Genomes</topic><topic>Humans</topic><topic>Invasiveness</topic><topic>Metastases</topic><topic>Original</topic><topic>Patients</topic><topic>Protein Binding</topic><topic>Protein interaction</topic><topic>Survival</topic><topic>Transcriptome</topic><topic>Urinary Bladder - metabolism</topic><topic>Urinary Bladder - pathology</topic><topic>Urothelial carcinoma</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guo, Changgang</creatorcontrib><creatorcontrib>Shao, Ting</creatorcontrib><creatorcontrib>Wei, Dadong</creatorcontrib><creatorcontrib>Li, Chunsheng</creatorcontrib><creatorcontrib>Liu, Fengjun</creatorcontrib><creatorcontrib>Li, Minghui</creatorcontrib><creatorcontrib>Gao, Zhiming</creatorcontrib><creatorcontrib>Bao, Guochang</creatorcontrib><collection>Sage Journals GOLD Open Access 2024</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Cell transplantation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guo, Changgang</au><au>Shao, Ting</au><au>Wei, Dadong</au><au>Li, Chunsheng</au><au>Liu, Fengjun</au><au>Li, Minghui</au><au>Gao, Zhiming</au><au>Bao, Guochang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bioinformatic Identification of Potential Hub Genes in Muscle-Invasive Bladder Urothelial Carcinoma</atitle><jtitle>Cell transplantation</jtitle><addtitle>Cell Transplant</addtitle><date>2020-01-01</date><risdate>2020</risdate><volume>29</volume><spage>963689720965178</spage><pages>963689720965178-</pages><issn>0963-6897</issn><issn>1555-3892</issn><eissn>1555-3892</eissn><abstract>Despite aggressive treatment approaches, muscle-invasive bladder urothelial carcinoma (MIBC) patients still have a 50% chance of developing general incurable metastases. Therefore, there is an urgent need for candidate markers to enhance diagnosis and generate effective treatments for this disease. We evaluated four mRNA microarray datasets to find differences between non-MIBC (NMIBC) and MIBC tissues. Through a gene expression profile analysis via the Gene Expression Omnibus database, we identified 56 differentially expressed genes (DEGs). Enrichment analysis of gene ontology, Kyoto Encyclopedia of Genes and Genomes, and Reactome pathways revealed the interactions between these DEGs. Next, we established a protein-protein interaction network to determine the interrelationship between the DEGs and selected 10 hub genes accordingly. Bladder urothelial carcinoma (BLCA) patients with COL1A2, COL5A1, and COL5A2 alterations showed poor disease-free survival rates, while BLCA patients with COL1A1 and LUM alterations showed poor overall survival rates. Oncomine analysis of MIBC versus NMIBC tissues showed that COL1A1, COL5A2, COL1A2, and COL3A1 were consistently among the top 20 overexpressed genes in different studies. Using the TCGAportal, we noted that the high expression of each of the four genes led to shorter BLCA patient overall survival. It was evident that BLCA patients with an elevated high combined gene expression had significantly shorter overall survival and relapse-free survival than those with low combined gene expression using PROGgeneV2. Using Gene Expression Profiling Interactive Analysis, we noted that COL1A1, COL1A2, COL3A1, and COL5A2 were positively correlated with each other in BLCA. These genes are considered as clinically relevant genes, suggesting that they may play an important role in the carcinogenesis, development, invasion, and metastasis of MIBC. However, considering we adopted a bioinformatic approach, more research is crucial to confirm our results. Nonetheless, our findings may have important prospective clinical implementations.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>33035117</pmid><doi>10.1177/0963689720965178</doi><orcidid>https://orcid.org/0000-0001-9982-1391</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Bladder Bladder cancer Carcinogenesis Collagen (type I) Collagen Type I - genetics Collagen Type I - metabolism Collagen Type I, alpha 1 Chain Collagen Type III - genetics Collagen Type III - metabolism Computational Biology - methods DNA microarrays Gene expression Genomes Humans Invasiveness Metastases Original Patients Protein Binding Protein interaction Survival Transcriptome Urinary Bladder - metabolism Urinary Bladder - pathology Urothelial carcinoma |
title | Bioinformatic Identification of Potential Hub Genes in Muscle-Invasive Bladder Urothelial Carcinoma |
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