Cargando…
Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer
BACKGROUND: Muscle-invasive bladder cancer (MIBC) is originated in the muscle wall of the bladder, and is the ninth most common malignancy worldwide. However, there are no reliable, accurate and robust gene signatures for MIBC prognosis prediction, which is of the importance in assisting oncologists...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916460/ https://www.ncbi.nlm.nih.gov/pubmed/31866765 http://dx.doi.org/10.1186/s12935-019-1056-y |
_version_ | 1783480245746139136 |
---|---|
author | Zhang, Ping-Bao Huang, Zi-Li Xu, Yong-Hua Huang, Jin Huang, Xin-Yu Huang, Xiu-Yan |
author_facet | Zhang, Ping-Bao Huang, Zi-Li Xu, Yong-Hua Huang, Jin Huang, Xin-Yu Huang, Xiu-Yan |
author_sort | Zhang, Ping-Bao |
collection | PubMed |
description | BACKGROUND: Muscle-invasive bladder cancer (MIBC) is originated in the muscle wall of the bladder, and is the ninth most common malignancy worldwide. However, there are no reliable, accurate and robust gene signatures for MIBC prognosis prediction, which is of the importance in assisting oncologists to make a more accurate evaluation in clinical practice. METHODS: This study used univariable and multivariable Cox regression models to select gene signatures and build risk prediction model, respectively. The t-test and fold change methods were used to perform the differential expression analysis. The hypergeometric test was used to test the enrichment of the differentially expressed genes in GO terms or KEGG pathways. RESULTS: In the present study, we identified three prognostic genes, KLK6, TNS1, and TRIM56, as the best subset of genes for muscle-invasive bladder cancer (MIBC) risk prediction. The validation of this stratification method on two datasets demonstrated that the stratified patients exhibited significant difference in overall survival, and our stratification was superior to three other stratifications. Consistently, the high-risk group exhibited worse prognosis than low-risk group in samples with and without lymph node metastasis, distant metastasis, and radiation treatment. Moreover, the upregulated genes in high-risk MIBC were significantly enriched in several cancer-related pathways. Notably, PDGFRB, a receptor for platelet-derived growth factor of PI3K-Akt signaling pathway, and TUBA1A were identified as two targets of multiple drugs. In addition, the angiogenesis-related genes, as well as two marker genes of M2 macrophage, CD163 and MRC1, were highly upregulated in high-risk MIBC. CONCLUSIONS: In summary, this study investigated the underlying molecular mechanism and potential therapeutic targets associated with worse prognosis of high-risk MIBC, which could improve our understanding of progression of MIBC and provide new therapeutic strategies for the MIBC patients. |
format | Online Article Text |
id | pubmed-6916460 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69164602019-12-20 Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer Zhang, Ping-Bao Huang, Zi-Li Xu, Yong-Hua Huang, Jin Huang, Xin-Yu Huang, Xiu-Yan Cancer Cell Int Primary Research BACKGROUND: Muscle-invasive bladder cancer (MIBC) is originated in the muscle wall of the bladder, and is the ninth most common malignancy worldwide. However, there are no reliable, accurate and robust gene signatures for MIBC prognosis prediction, which is of the importance in assisting oncologists to make a more accurate evaluation in clinical practice. METHODS: This study used univariable and multivariable Cox regression models to select gene signatures and build risk prediction model, respectively. The t-test and fold change methods were used to perform the differential expression analysis. The hypergeometric test was used to test the enrichment of the differentially expressed genes in GO terms or KEGG pathways. RESULTS: In the present study, we identified three prognostic genes, KLK6, TNS1, and TRIM56, as the best subset of genes for muscle-invasive bladder cancer (MIBC) risk prediction. The validation of this stratification method on two datasets demonstrated that the stratified patients exhibited significant difference in overall survival, and our stratification was superior to three other stratifications. Consistently, the high-risk group exhibited worse prognosis than low-risk group in samples with and without lymph node metastasis, distant metastasis, and radiation treatment. Moreover, the upregulated genes in high-risk MIBC were significantly enriched in several cancer-related pathways. Notably, PDGFRB, a receptor for platelet-derived growth factor of PI3K-Akt signaling pathway, and TUBA1A were identified as two targets of multiple drugs. In addition, the angiogenesis-related genes, as well as two marker genes of M2 macrophage, CD163 and MRC1, were highly upregulated in high-risk MIBC. CONCLUSIONS: In summary, this study investigated the underlying molecular mechanism and potential therapeutic targets associated with worse prognosis of high-risk MIBC, which could improve our understanding of progression of MIBC and provide new therapeutic strategies for the MIBC patients. BioMed Central 2019-12-16 /pmc/articles/PMC6916460/ /pubmed/31866765 http://dx.doi.org/10.1186/s12935-019-1056-y Text en © The Author(s) 2019 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Primary Research Zhang, Ping-Bao Huang, Zi-Li Xu, Yong-Hua Huang, Jin Huang, Xin-Yu Huang, Xiu-Yan Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
title | Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
title_full | Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
title_fullStr | Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
title_full_unstemmed | Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
title_short | Systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
title_sort | systematic analysis of gene expression profiles reveals prognostic stratification and underlying mechanisms for muscle-invasive bladder cancer |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916460/ https://www.ncbi.nlm.nih.gov/pubmed/31866765 http://dx.doi.org/10.1186/s12935-019-1056-y |
work_keys_str_mv | AT zhangpingbao systematicanalysisofgeneexpressionprofilesrevealsprognosticstratificationandunderlyingmechanismsformuscleinvasivebladdercancer AT huangzili systematicanalysisofgeneexpressionprofilesrevealsprognosticstratificationandunderlyingmechanismsformuscleinvasivebladdercancer AT xuyonghua systematicanalysisofgeneexpressionprofilesrevealsprognosticstratificationandunderlyingmechanismsformuscleinvasivebladdercancer AT huangjin systematicanalysisofgeneexpressionprofilesrevealsprognosticstratificationandunderlyingmechanismsformuscleinvasivebladdercancer AT huangxinyu systematicanalysisofgeneexpressionprofilesrevealsprognosticstratificationandunderlyingmechanismsformuscleinvasivebladdercancer AT huangxiuyan systematicanalysisofgeneexpressionprofilesrevealsprognosticstratificationandunderlyingmechanismsformuscleinvasivebladdercancer |