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Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma
BACKGROUND: Bladder carcinoma (BC) is one of the most prevalent and malignant tumors. Multiple gene signatures based on BC metabolism, especially regarding glycolysis, remain unclear. Thus, we developed a glycolysis-related gene signature to be used for BC prognosis prediction. METHODS: Transcriptom...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786194/ https://www.ncbi.nlm.nih.gov/pubmed/33424916 http://dx.doi.org/10.3389/fgene.2020.566918 |
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author | Mou, Zezhong Yang, Chen Zhang, Zheyu Wu, Siqi Xu, Chenyang Cheng, Zhang Dai, Xiyu Chen, Xinan Ou, Yuxi Jiang, Haowen |
author_facet | Mou, Zezhong Yang, Chen Zhang, Zheyu Wu, Siqi Xu, Chenyang Cheng, Zhang Dai, Xiyu Chen, Xinan Ou, Yuxi Jiang, Haowen |
author_sort | Mou, Zezhong |
collection | PubMed |
description | BACKGROUND: Bladder carcinoma (BC) is one of the most prevalent and malignant tumors. Multiple gene signatures based on BC metabolism, especially regarding glycolysis, remain unclear. Thus, we developed a glycolysis-related gene signature to be used for BC prognosis prediction. METHODS: Transcriptomic and clinical data were divided into a training set and a validation set after they were downloaded and analyzed from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Gene-set enrichment analysis (GSEA) and differential analysis were used to screen differentially expressed genes (DEGs), while univariate Cox regression and lasso-penalized Cox regression were employed for signature establishment. To evaluate the prognostic power of the signature, receiver operating characteristic (ROC) curve and Kaplan–Meier (KM) survival analysis were also used. Additionally, we developed a nomogram to predict patients’ survival chances using the identified prognostic gene signature. Further, gene mutation and protein expression, as well as the independence of signature genes, were also analyzed. Finally, we also performed qPCR and western blot to detect the expression and potential pathways of signature genes in BC samples. RESULTS: Ten genes were selected for signature construction among 71 DEGs, including nine risk genes and one protection gene. KM survival analysis revealed that the high-risk group had poor survival and the low-risk group had increased survival. ROC curve analysis and the nomogram validated the accurate prediction of survival using a gene signature composed of 10 glycolysis-related genes. Western blot and qPCR analysis demonstrated that the expression trend of signature genes was basically consistent with previous results. These 10 glycolysis-related genes were independent and suitable for a signature. CONCLUSION: Our current study indicated that we successfully built and validated a novel 10-gene glycolysis-related signature for BC prognosis. |
format | Online Article Text |
id | pubmed-7786194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77861942021-01-07 Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma Mou, Zezhong Yang, Chen Zhang, Zheyu Wu, Siqi Xu, Chenyang Cheng, Zhang Dai, Xiyu Chen, Xinan Ou, Yuxi Jiang, Haowen Front Genet Genetics BACKGROUND: Bladder carcinoma (BC) is one of the most prevalent and malignant tumors. Multiple gene signatures based on BC metabolism, especially regarding glycolysis, remain unclear. Thus, we developed a glycolysis-related gene signature to be used for BC prognosis prediction. METHODS: Transcriptomic and clinical data were divided into a training set and a validation set after they were downloaded and analyzed from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Gene-set enrichment analysis (GSEA) and differential analysis were used to screen differentially expressed genes (DEGs), while univariate Cox regression and lasso-penalized Cox regression were employed for signature establishment. To evaluate the prognostic power of the signature, receiver operating characteristic (ROC) curve and Kaplan–Meier (KM) survival analysis were also used. Additionally, we developed a nomogram to predict patients’ survival chances using the identified prognostic gene signature. Further, gene mutation and protein expression, as well as the independence of signature genes, were also analyzed. Finally, we also performed qPCR and western blot to detect the expression and potential pathways of signature genes in BC samples. RESULTS: Ten genes were selected for signature construction among 71 DEGs, including nine risk genes and one protection gene. KM survival analysis revealed that the high-risk group had poor survival and the low-risk group had increased survival. ROC curve analysis and the nomogram validated the accurate prediction of survival using a gene signature composed of 10 glycolysis-related genes. Western blot and qPCR analysis demonstrated that the expression trend of signature genes was basically consistent with previous results. These 10 glycolysis-related genes were independent and suitable for a signature. CONCLUSION: Our current study indicated that we successfully built and validated a novel 10-gene glycolysis-related signature for BC prognosis. Frontiers Media S.A. 2020-12-23 /pmc/articles/PMC7786194/ /pubmed/33424916 http://dx.doi.org/10.3389/fgene.2020.566918 Text en Copyright © 2020 Mou, Yang, Zhang, Wu, Xu, Cheng, Dai, Chen, Ou and Jiang. http://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 | Genetics Mou, Zezhong Yang, Chen Zhang, Zheyu Wu, Siqi Xu, Chenyang Cheng, Zhang Dai, Xiyu Chen, Xinan Ou, Yuxi Jiang, Haowen Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma |
title | Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma |
title_full | Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma |
title_fullStr | Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma |
title_full_unstemmed | Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma |
title_short | Transcriptomic Analysis of Glycolysis-Related Genes Reveals an Independent Signature of Bladder Carcinoma |
title_sort | transcriptomic analysis of glycolysis-related genes reveals an independent signature of bladder carcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786194/ https://www.ncbi.nlm.nih.gov/pubmed/33424916 http://dx.doi.org/10.3389/fgene.2020.566918 |
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