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Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer

PURPOSE: Aim of this study was to identify biomarkers between different grades of bladder cancer (BLCA) and its prognostic value. METHODS: mRNA expression data from GSE32549 and GSE71576 were extracted for further analysis. Differentially expressed genes (DEGs) were identified using GEO2R web tool....

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Autores principales: Jiao, Fangdong, Sun, Hao, Yang, Qingya, Sun, Hui, Wang, Zehua, Liu, Ming, Chen, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489952/
https://www.ncbi.nlm.nih.gov/pubmed/32982427
http://dx.doi.org/10.2147/CMAR.S254316
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author Jiao, Fangdong
Sun, Hao
Yang, Qingya
Sun, Hui
Wang, Zehua
Liu, Ming
Chen, Jun
author_facet Jiao, Fangdong
Sun, Hao
Yang, Qingya
Sun, Hui
Wang, Zehua
Liu, Ming
Chen, Jun
author_sort Jiao, Fangdong
collection PubMed
description PURPOSE: Aim of this study was to identify biomarkers between different grades of bladder cancer (BLCA) and its prognostic value. METHODS: mRNA expression data from GSE32549 and GSE71576 were extracted for further analysis. Differentially expressed genes (DEGs) were identified using GEO2R web tool. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein–protein interaction (PPI) network were conducted to explore the function and relationship of DEGs. The Cancer Genome Atlas (TCGA) database was used for external validation and Gene set enrichment analysis (GSEA) analysis was used to further identify FADS1 pathways. Bladder cancer cells and patient specimens were used to further demonstrate the function of FADS1. RESULTS: Datasets from GEO identified a panel of DEGs. Functional enrichment analysis highlighted that DEGs were associated with nuclear division, spindle, cell cycle and p53 signaling pathway. External validation from TCGA demonstrated that FADS1 was an independent prognostic marker in BLCA patients. In cell lines and tumor specimen analysis, FADS1 was overexpressed in the tumor specimen, compared with adjacent tissues, and positively correlated with tumor grade of BLCA. Moreover, FADS1 could enhance the proliferation ability and influence cell cycle of bladder cancer cells. CONCLUSION: FADS1 was an independent prognostic biomarker for BLCA and could confer the bladder cancer cells increased proliferation ability.
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spelling pubmed-74899522020-09-24 Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer Jiao, Fangdong Sun, Hao Yang, Qingya Sun, Hui Wang, Zehua Liu, Ming Chen, Jun Cancer Manag Res Original Research PURPOSE: Aim of this study was to identify biomarkers between different grades of bladder cancer (BLCA) and its prognostic value. METHODS: mRNA expression data from GSE32549 and GSE71576 were extracted for further analysis. Differentially expressed genes (DEGs) were identified using GEO2R web tool. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein–protein interaction (PPI) network were conducted to explore the function and relationship of DEGs. The Cancer Genome Atlas (TCGA) database was used for external validation and Gene set enrichment analysis (GSEA) analysis was used to further identify FADS1 pathways. Bladder cancer cells and patient specimens were used to further demonstrate the function of FADS1. RESULTS: Datasets from GEO identified a panel of DEGs. Functional enrichment analysis highlighted that DEGs were associated with nuclear division, spindle, cell cycle and p53 signaling pathway. External validation from TCGA demonstrated that FADS1 was an independent prognostic marker in BLCA patients. In cell lines and tumor specimen analysis, FADS1 was overexpressed in the tumor specimen, compared with adjacent tissues, and positively correlated with tumor grade of BLCA. Moreover, FADS1 could enhance the proliferation ability and influence cell cycle of bladder cancer cells. CONCLUSION: FADS1 was an independent prognostic biomarker for BLCA and could confer the bladder cancer cells increased proliferation ability. Dove 2020-09-10 /pmc/articles/PMC7489952/ /pubmed/32982427 http://dx.doi.org/10.2147/CMAR.S254316 Text en © 2020 Jiao et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Jiao, Fangdong
Sun, Hao
Yang, Qingya
Sun, Hui
Wang, Zehua
Liu, Ming
Chen, Jun
Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer
title Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer
title_full Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer
title_fullStr Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer
title_full_unstemmed Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer
title_short Identification of FADS1 Through Common Gene Expression Profiles for Predicting Survival in Patients with Bladder Cancer
title_sort identification of fads1 through common gene expression profiles for predicting survival in patients with bladder cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489952/
https://www.ncbi.nlm.nih.gov/pubmed/32982427
http://dx.doi.org/10.2147/CMAR.S254316
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