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Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis

BACKGROUND: Bladder cancer (BCa) is one of the important tumors that have been proven to be treatable with immunotherapy. This study aims to identify and validate a molecular prognostic index of BCa based on immunogenomic landscape analysis. METHODS: The cancer genome atlas (TCGA) database and immun...

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Autores principales: Xu, Ning, Ke, Zhi-Bin, Lin, Xiao-Dan, Chen, Ye-Hui, Wu, Yu-Peng, Chen, Yu, Dong, Ru-Nan, Chen, Shao-Hao, Li, Xiao-Dong, Wei, Yong, Zheng, Qing-Shui, Lin, Yun-Zhi, Xue, Xue-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7353795/
https://www.ncbi.nlm.nih.gov/pubmed/32675942
http://dx.doi.org/10.1186/s12935-020-01343-3
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author Xu, Ning
Ke, Zhi-Bin
Lin, Xiao-Dan
Chen, Ye-Hui
Wu, Yu-Peng
Chen, Yu
Dong, Ru-Nan
Chen, Shao-Hao
Li, Xiao-Dong
Wei, Yong
Zheng, Qing-Shui
Lin, Yun-Zhi
Xue, Xue-Yi
author_facet Xu, Ning
Ke, Zhi-Bin
Lin, Xiao-Dan
Chen, Ye-Hui
Wu, Yu-Peng
Chen, Yu
Dong, Ru-Nan
Chen, Shao-Hao
Li, Xiao-Dong
Wei, Yong
Zheng, Qing-Shui
Lin, Yun-Zhi
Xue, Xue-Yi
author_sort Xu, Ning
collection PubMed
description BACKGROUND: Bladder cancer (BCa) is one of the important tumors that have been proven to be treatable with immunotherapy. This study aims to identify and validate a molecular prognostic index of BCa based on immunogenomic landscape analysis. METHODS: The cancer genome atlas (TCGA) database and immunology database and analysis portal (ImmPort) database were used to identified differentially expressed immune-related genes (IRGs). Prognostic IRGs were screened and protein–protein interaction (PPI) network was constructed. Multivariate Cox analysis was performed to develop a molecular prognostic index of BCa. Internal and external validation were then performed in TCGA cohort and GEO cohort, respectively. Besides, we also explore the relationship between this index and clinical characteristics, immune cell infiltration and tumor microenvironment. RESULTS: A total of 61 prognostic IRGs were identified and a molecular prognostic index was developed. The top four hub genes included MMP9, IGF1, CXCL12 and PGF. The difference in overall survival between high-risk group and low-risk group was statistically significant. The area under curve of the receiver operating characteristic (ROC) curve was 0.757, suggesting the potential for this index. Besides, Internal validation using TCGA cohort and external validation using GEO cohort indicated that this index was of great performance in predicting outcome. T cells CD8, T cells CD4 memory activated, T cells follicular helper, macrophages M0, macrophages M2 and neutrophils were significantly associated with prognosis of BCa patients. Female, high grade, stage III&IV, N1-3 and T3-4 were associated significantly with higher risk score compared with male, low grade, stage I&II, N0 and T1-2, respectively. High risk score had a positive association with higher stromal score and ESTIMATE score while high risk score had a negative association with tumor purity. CONCLUSIONS: This study identified several prognostic immune-related genes of clinical value. Besides, we developed and validated a molecular index based on immunogenomic landscape analysis, which performed well in predicting prognosis of BCa. Further researches are needed to verify the effectiveness of this index and these vital genes.
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spelling pubmed-73537952020-07-15 Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis Xu, Ning Ke, Zhi-Bin Lin, Xiao-Dan Chen, Ye-Hui Wu, Yu-Peng Chen, Yu Dong, Ru-Nan Chen, Shao-Hao Li, Xiao-Dong Wei, Yong Zheng, Qing-Shui Lin, Yun-Zhi Xue, Xue-Yi Cancer Cell Int Primary Research BACKGROUND: Bladder cancer (BCa) is one of the important tumors that have been proven to be treatable with immunotherapy. This study aims to identify and validate a molecular prognostic index of BCa based on immunogenomic landscape analysis. METHODS: The cancer genome atlas (TCGA) database and immunology database and analysis portal (ImmPort) database were used to identified differentially expressed immune-related genes (IRGs). Prognostic IRGs were screened and protein–protein interaction (PPI) network was constructed. Multivariate Cox analysis was performed to develop a molecular prognostic index of BCa. Internal and external validation were then performed in TCGA cohort and GEO cohort, respectively. Besides, we also explore the relationship between this index and clinical characteristics, immune cell infiltration and tumor microenvironment. RESULTS: A total of 61 prognostic IRGs were identified and a molecular prognostic index was developed. The top four hub genes included MMP9, IGF1, CXCL12 and PGF. The difference in overall survival between high-risk group and low-risk group was statistically significant. The area under curve of the receiver operating characteristic (ROC) curve was 0.757, suggesting the potential for this index. Besides, Internal validation using TCGA cohort and external validation using GEO cohort indicated that this index was of great performance in predicting outcome. T cells CD8, T cells CD4 memory activated, T cells follicular helper, macrophages M0, macrophages M2 and neutrophils were significantly associated with prognosis of BCa patients. Female, high grade, stage III&IV, N1-3 and T3-4 were associated significantly with higher risk score compared with male, low grade, stage I&II, N0 and T1-2, respectively. High risk score had a positive association with higher stromal score and ESTIMATE score while high risk score had a negative association with tumor purity. CONCLUSIONS: This study identified several prognostic immune-related genes of clinical value. Besides, we developed and validated a molecular index based on immunogenomic landscape analysis, which performed well in predicting prognosis of BCa. Further researches are needed to verify the effectiveness of this index and these vital genes. BioMed Central 2020-07-11 /pmc/articles/PMC7353795/ /pubmed/32675942 http://dx.doi.org/10.1186/s12935-020-01343-3 Text en © The Author(s) 2020 Open AccessThis 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
Xu, Ning
Ke, Zhi-Bin
Lin, Xiao-Dan
Chen, Ye-Hui
Wu, Yu-Peng
Chen, Yu
Dong, Ru-Nan
Chen, Shao-Hao
Li, Xiao-Dong
Wei, Yong
Zheng, Qing-Shui
Lin, Yun-Zhi
Xue, Xue-Yi
Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
title Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
title_full Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
title_fullStr Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
title_full_unstemmed Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
title_short Development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
title_sort development and validation of a molecular prognostic index of bladder cancer based on immunogenomic landscape analysis
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7353795/
https://www.ncbi.nlm.nih.gov/pubmed/32675942
http://dx.doi.org/10.1186/s12935-020-01343-3
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