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Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer

INTRODUCTION: Bladder cancer (BC) is one of the most prevalent urinary cancers, and its management is still a problem causing recurrence and progression, elevating mortality. MATERIALS AND METHODS: We aimed at the nuclear mitochondria-related genes (MTRGs), collected from the MITOMAP: A Human Mitoch...

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Autores principales: Jiang, Xuewen, Xia, Yangyang, Meng, Hui, Liu, Yaxiao, Cui, Jianfeng, Huang, Huangwei, Yin, Gang, Shi, Benkang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8528313/
https://www.ncbi.nlm.nih.gov/pubmed/34692528
http://dx.doi.org/10.3389/fonc.2021.746029
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author Jiang, Xuewen
Xia, Yangyang
Meng, Hui
Liu, Yaxiao
Cui, Jianfeng
Huang, Huangwei
Yin, Gang
Shi, Benkang
author_facet Jiang, Xuewen
Xia, Yangyang
Meng, Hui
Liu, Yaxiao
Cui, Jianfeng
Huang, Huangwei
Yin, Gang
Shi, Benkang
author_sort Jiang, Xuewen
collection PubMed
description INTRODUCTION: Bladder cancer (BC) is one of the most prevalent urinary cancers, and its management is still a problem causing recurrence and progression, elevating mortality. MATERIALS AND METHODS: We aimed at the nuclear mitochondria-related genes (MTRGs), collected from the MITOMAP: A Human Mitochondrial Genome Database. Meanwhile, the expression profiles and clinical information of BC were downloaded from the Cancer Genome Atlas (TCGA) as a training group. The univariate, multivariate, and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a nuclear mitochondrial-related multi-genes signature and the prognostic nomogram. RESULTS: A total of 17 nuclear MTRGs were identified to be correlated with the overall survival (OS) of BC patients, and a nuclear MTRGs signature based on 16 genes expression was further determined by the LASSO Cox regression analysis. Based on a nuclear MTRGs scoring system, BC patients from the TCGA cohort were divided into high- and low- nuclear MTRGs score groups. Patients with a high nuclear MTRGs score exhibited a significantly poorer outcome (median OS: 92.90 vs 20.20 months, p<0.0001). The nuclear MTRGs signature was further verified in three independent datasets, namely, GSE13507, GSE31684, and GSE32548, from the Gene Expression Omnibus (GEO). The BC patients with a high nuclear MTRGs score had significantly worse survival (median OS in GSE13507: 31.52 vs 98.00 months, p<0.05; GSE31684: 32.85 months vs unreached, p<0.05; GSE32548: unreached vs unreached, p<0.05). Furthermore, muscle-invasive bladder cancer (MIBC) patients had a significantly higher nuclear MTRGs score (p<0.05) than non-muscle-invasive bladder cancer (NMIBC) patients. The integrated signature outperformed each involved MTRG. In addition, a nuclear MTRGs-based nomogram was constructed as a novel prediction prognosis model, whose AUC values for OS at 1, 3, 5 years were 0.76, 0.75, and 0.75, respectively, showing the prognostic nomogram had good and stable predicting ability. Enrichment analyses of the hallmark gene set and KEGG pathway revealed that the E2F targets, G2M checkpoint pathways, and cell cycle had influences on the survival of BC patients. Furthermore, the analysis of tumor microenvironment indicated more CD8+ T cells and higher immune score in patients with high nuclear MTRGs score, which might confer sensitivity to immune checkpoint inhibitors. CONCLUSIONS: Not only could the signature and prognostic nomogram predict the prognosis of BC, but it also had potential therapeutic guidance.
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spelling pubmed-85283132021-10-21 Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer Jiang, Xuewen Xia, Yangyang Meng, Hui Liu, Yaxiao Cui, Jianfeng Huang, Huangwei Yin, Gang Shi, Benkang Front Oncol Oncology INTRODUCTION: Bladder cancer (BC) is one of the most prevalent urinary cancers, and its management is still a problem causing recurrence and progression, elevating mortality. MATERIALS AND METHODS: We aimed at the nuclear mitochondria-related genes (MTRGs), collected from the MITOMAP: A Human Mitochondrial Genome Database. Meanwhile, the expression profiles and clinical information of BC were downloaded from the Cancer Genome Atlas (TCGA) as a training group. The univariate, multivariate, and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a nuclear mitochondrial-related multi-genes signature and the prognostic nomogram. RESULTS: A total of 17 nuclear MTRGs were identified to be correlated with the overall survival (OS) of BC patients, and a nuclear MTRGs signature based on 16 genes expression was further determined by the LASSO Cox regression analysis. Based on a nuclear MTRGs scoring system, BC patients from the TCGA cohort were divided into high- and low- nuclear MTRGs score groups. Patients with a high nuclear MTRGs score exhibited a significantly poorer outcome (median OS: 92.90 vs 20.20 months, p<0.0001). The nuclear MTRGs signature was further verified in three independent datasets, namely, GSE13507, GSE31684, and GSE32548, from the Gene Expression Omnibus (GEO). The BC patients with a high nuclear MTRGs score had significantly worse survival (median OS in GSE13507: 31.52 vs 98.00 months, p<0.05; GSE31684: 32.85 months vs unreached, p<0.05; GSE32548: unreached vs unreached, p<0.05). Furthermore, muscle-invasive bladder cancer (MIBC) patients had a significantly higher nuclear MTRGs score (p<0.05) than non-muscle-invasive bladder cancer (NMIBC) patients. The integrated signature outperformed each involved MTRG. In addition, a nuclear MTRGs-based nomogram was constructed as a novel prediction prognosis model, whose AUC values for OS at 1, 3, 5 years were 0.76, 0.75, and 0.75, respectively, showing the prognostic nomogram had good and stable predicting ability. Enrichment analyses of the hallmark gene set and KEGG pathway revealed that the E2F targets, G2M checkpoint pathways, and cell cycle had influences on the survival of BC patients. Furthermore, the analysis of tumor microenvironment indicated more CD8+ T cells and higher immune score in patients with high nuclear MTRGs score, which might confer sensitivity to immune checkpoint inhibitors. CONCLUSIONS: Not only could the signature and prognostic nomogram predict the prognosis of BC, but it also had potential therapeutic guidance. Frontiers Media S.A. 2021-10-06 /pmc/articles/PMC8528313/ /pubmed/34692528 http://dx.doi.org/10.3389/fonc.2021.746029 Text en Copyright © 2021 Jiang, Xia, Meng, Liu, Cui, Huang, Yin and Shi https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Jiang, Xuewen
Xia, Yangyang
Meng, Hui
Liu, Yaxiao
Cui, Jianfeng
Huang, Huangwei
Yin, Gang
Shi, Benkang
Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer
title Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer
title_full Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer
title_fullStr Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer
title_full_unstemmed Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer
title_short Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer
title_sort identification of a nuclear mitochondrial-related multi-genes signature to predict the prognosis of bladder cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8528313/
https://www.ncbi.nlm.nih.gov/pubmed/34692528
http://dx.doi.org/10.3389/fonc.2021.746029
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