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The prognostic value of six survival-related genes in bladder cancer

This study was conducted to identify genes that are differentially expressed in paracancerous tissue and to determine the potential predictive value of selected gene panel. Gene transcriptome data of bladder tissue was downloaded from UCSC Xena browser and NCBI GEO repository, including GTEx (the Ge...

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Autores principales: Cheng, Shuting, Jiang, Zhou, Xiao, Jing, Guo, Huiling, Wang, Zhengrong, Wang, Yuhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359373/
https://www.ncbi.nlm.nih.gov/pubmed/32695477
http://dx.doi.org/10.1038/s41420-020-00295-x
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author Cheng, Shuting
Jiang, Zhou
Xiao, Jing
Guo, Huiling
Wang, Zhengrong
Wang, Yuhui
author_facet Cheng, Shuting
Jiang, Zhou
Xiao, Jing
Guo, Huiling
Wang, Zhengrong
Wang, Yuhui
author_sort Cheng, Shuting
collection PubMed
description This study was conducted to identify genes that are differentially expressed in paracancerous tissue and to determine the potential predictive value of selected gene panel. Gene transcriptome data of bladder tissue was downloaded from UCSC Xena browser and NCBI GEO repository, including GTEx (the Genotype-Tissue Expression project) data, TCGA (The Cancer Genome Atlas) data, and GEO (Gene Expression Omnibus) data. Differentially Expressed Genes (DEGs) analysis was performed to identify tumor-DEGs candidate genes, using the intersection of tumor-paracancerous DEGs genes and paracancerous-normal DEGs genes. The survival-related genes were screened by Kaplan–Meier (KM) survival analysis and univariable Cox regression with the cutoff criteria of KM < 0.05 and cox p-value < 0.05. The risk model was developed using Lasso regression. The clinical data were analyzed by univariate and multivariate Cox regression analysis. Gene Ontology (GO) and KEGG enrichment analysis were performed in the DEGs genes between the high-risk and low-risk subgroups. We identified six survival-related genes, EMP1, TPM1, NRP2, FGFR1, CAVIN1, and LATS2, found in the DEG analyses of both, tumor-paracancerous and paracancerous-normal differentially expressed data sets. Then, the patients were classified into two clusters, which can be distinguished by specific clinical characteristics. A three-gene risk prediction model (EMP1, FGFR1, and CAVIN1) was constructed in patients within cluster 1. The model was applied to categorize cluster 1 patients into high-risk and low-risk subgroups. The prognostic risk score was considered as an independent prognostic factor. The six identified survival-related genes can be used in molecular characterization of a specific subtype of bladder cancer. This subtype had distinct clinical features of T (topography), N (lymph node), stage, grade, and survival status, compared to the other subtype of bladder cancer. Among the six identified survival-related genes, three-genes, EMP1, FGFR1, and CAVIN1, were identified as potential independent prognostic markers for the specific bladder cancer subtype with clinical features described.
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spelling pubmed-73593732020-07-20 The prognostic value of six survival-related genes in bladder cancer Cheng, Shuting Jiang, Zhou Xiao, Jing Guo, Huiling Wang, Zhengrong Wang, Yuhui Cell Death Discov Article This study was conducted to identify genes that are differentially expressed in paracancerous tissue and to determine the potential predictive value of selected gene panel. Gene transcriptome data of bladder tissue was downloaded from UCSC Xena browser and NCBI GEO repository, including GTEx (the Genotype-Tissue Expression project) data, TCGA (The Cancer Genome Atlas) data, and GEO (Gene Expression Omnibus) data. Differentially Expressed Genes (DEGs) analysis was performed to identify tumor-DEGs candidate genes, using the intersection of tumor-paracancerous DEGs genes and paracancerous-normal DEGs genes. The survival-related genes were screened by Kaplan–Meier (KM) survival analysis and univariable Cox regression with the cutoff criteria of KM < 0.05 and cox p-value < 0.05. The risk model was developed using Lasso regression. The clinical data were analyzed by univariate and multivariate Cox regression analysis. Gene Ontology (GO) and KEGG enrichment analysis were performed in the DEGs genes between the high-risk and low-risk subgroups. We identified six survival-related genes, EMP1, TPM1, NRP2, FGFR1, CAVIN1, and LATS2, found in the DEG analyses of both, tumor-paracancerous and paracancerous-normal differentially expressed data sets. Then, the patients were classified into two clusters, which can be distinguished by specific clinical characteristics. A three-gene risk prediction model (EMP1, FGFR1, and CAVIN1) was constructed in patients within cluster 1. The model was applied to categorize cluster 1 patients into high-risk and low-risk subgroups. The prognostic risk score was considered as an independent prognostic factor. The six identified survival-related genes can be used in molecular characterization of a specific subtype of bladder cancer. This subtype had distinct clinical features of T (topography), N (lymph node), stage, grade, and survival status, compared to the other subtype of bladder cancer. Among the six identified survival-related genes, three-genes, EMP1, FGFR1, and CAVIN1, were identified as potential independent prognostic markers for the specific bladder cancer subtype with clinical features described. Nature Publishing Group UK 2020-07-13 /pmc/articles/PMC7359373/ /pubmed/32695477 http://dx.doi.org/10.1038/s41420-020-00295-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Cheng, Shuting
Jiang, Zhou
Xiao, Jing
Guo, Huiling
Wang, Zhengrong
Wang, Yuhui
The prognostic value of six survival-related genes in bladder cancer
title The prognostic value of six survival-related genes in bladder cancer
title_full The prognostic value of six survival-related genes in bladder cancer
title_fullStr The prognostic value of six survival-related genes in bladder cancer
title_full_unstemmed The prognostic value of six survival-related genes in bladder cancer
title_short The prognostic value of six survival-related genes in bladder cancer
title_sort prognostic value of six survival-related genes in bladder cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359373/
https://www.ncbi.nlm.nih.gov/pubmed/32695477
http://dx.doi.org/10.1038/s41420-020-00295-x
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