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 (...
Autores principales: | , , , , , , , , , , , |
---|---|
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 |