Cargando…

Identification of immune-related genes as prognostic factors in bladder cancer

Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Jie, Wang, Han, Ma, Ting, He, Yan, Shen, Meng, Song, Wei, Wang, Jing-Jing, Shi, Jian-Ping, Wu, Meng-Yao, Liu, Chao, Wang, Wen-Jie, Huang, Yue-Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661532/
https://www.ncbi.nlm.nih.gov/pubmed/33184436
http://dx.doi.org/10.1038/s41598-020-76688-w
_version_ 1783609227381571584
author Zhu, Jie
Wang, Han
Ma, Ting
He, Yan
Shen, Meng
Song, Wei
Wang, Jing-Jing
Shi, Jian-Ping
Wu, Meng-Yao
Liu, Chao
Wang, Wen-Jie
Huang, Yue-Qing
author_facet Zhu, Jie
Wang, Han
Ma, Ting
He, Yan
Shen, Meng
Song, Wei
Wang, Jing-Jing
Shi, Jian-Ping
Wu, Meng-Yao
Liu, Chao
Wang, Wen-Jie
Huang, Yue-Qing
author_sort Zhu, Jie
collection PubMed
description Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (DEIRGs) were identified by using the edgeR package. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for functional enrichment analysis of DEIRGs. Survival-associated IRGs were identified by univariate Cox regression analysis. A prognostic model was established by univariate COX regression analysis, and verified by a validation prognostic model based on the GEO database. Patients were divided into high-risk and low-risk groups based on the median risk score value for immune cell infiltration and clinicopathological analyses. A regulatory network of survival-associated IRGs and potential transcription factors was constructed to investigate the potential regulatory mechanisms of survival-associated IRGs. Nomogram and ROC curve to verify the accuracy of the model. Quantitative real-time PCR was performed to validate the expression of relevant key genes in the prognostic model. A total of 259 differentially expressed IRGs were identified in the present study. KEGG pathway analysis of IRGs showed that the “cytokine-cytokine receptor interaction” pathway was the most significantly enriched pathway. Thirteen survival-associated IRGs were selected to establish a prognostic index for bladder cancer. In both TCGA prognostic model and GEO validation model, patients with high riskscore had worse prognosis compared to low riskscore group. A high infiltration level of macrophages was observed in high-risk patients. OGN, ELN, ANXA6, ILK and TGFB3 were identified as hub survival-associated IRGs in the network. EBF1, WWTR1, GATA6, MYH11, and MEF2C were involved in the transcriptional regulation of these survival-associated hub IRGs. The present study identified several survival-associated IRGs of clinical significance and established a prognostic index for bladder cancer outcome evaluation for the first time.
format Online
Article
Text
id pubmed-7661532
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-76615322020-11-13 Identification of immune-related genes as prognostic factors in bladder cancer Zhu, Jie Wang, Han Ma, Ting He, Yan Shen, Meng Song, Wei Wang, Jing-Jing Shi, Jian-Ping Wu, Meng-Yao Liu, Chao Wang, Wen-Jie Huang, Yue-Qing Sci Rep Article Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (DEIRGs) were identified by using the edgeR package. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for functional enrichment analysis of DEIRGs. Survival-associated IRGs were identified by univariate Cox regression analysis. A prognostic model was established by univariate COX regression analysis, and verified by a validation prognostic model based on the GEO database. Patients were divided into high-risk and low-risk groups based on the median risk score value for immune cell infiltration and clinicopathological analyses. A regulatory network of survival-associated IRGs and potential transcription factors was constructed to investigate the potential regulatory mechanisms of survival-associated IRGs. Nomogram and ROC curve to verify the accuracy of the model. Quantitative real-time PCR was performed to validate the expression of relevant key genes in the prognostic model. A total of 259 differentially expressed IRGs were identified in the present study. KEGG pathway analysis of IRGs showed that the “cytokine-cytokine receptor interaction” pathway was the most significantly enriched pathway. Thirteen survival-associated IRGs were selected to establish a prognostic index for bladder cancer. In both TCGA prognostic model and GEO validation model, patients with high riskscore had worse prognosis compared to low riskscore group. A high infiltration level of macrophages was observed in high-risk patients. OGN, ELN, ANXA6, ILK and TGFB3 were identified as hub survival-associated IRGs in the network. EBF1, WWTR1, GATA6, MYH11, and MEF2C were involved in the transcriptional regulation of these survival-associated hub IRGs. The present study identified several survival-associated IRGs of clinical significance and established a prognostic index for bladder cancer outcome evaluation for the first time. Nature Publishing Group UK 2020-11-12 /pmc/articles/PMC7661532/ /pubmed/33184436 http://dx.doi.org/10.1038/s41598-020-76688-w 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zhu, Jie
Wang, Han
Ma, Ting
He, Yan
Shen, Meng
Song, Wei
Wang, Jing-Jing
Shi, Jian-Ping
Wu, Meng-Yao
Liu, Chao
Wang, Wen-Jie
Huang, Yue-Qing
Identification of immune-related genes as prognostic factors in bladder cancer
title Identification of immune-related genes as prognostic factors in bladder cancer
title_full Identification of immune-related genes as prognostic factors in bladder cancer
title_fullStr Identification of immune-related genes as prognostic factors in bladder cancer
title_full_unstemmed Identification of immune-related genes as prognostic factors in bladder cancer
title_short Identification of immune-related genes as prognostic factors in bladder cancer
title_sort identification of immune-related genes as prognostic factors in bladder cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661532/
https://www.ncbi.nlm.nih.gov/pubmed/33184436
http://dx.doi.org/10.1038/s41598-020-76688-w
work_keys_str_mv AT zhujie identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT wanghan identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT mating identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT heyan identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT shenmeng identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT songwei identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT wangjingjing identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT shijianping identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT wumengyao identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT liuchao identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT wangwenjie identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer
AT huangyueqing identificationofimmunerelatedgenesasprognosticfactorsinbladdercancer