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Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer
BACKGROUNDS: Glucose metabolism is associated with the development of cancers, and m6A RNA methylation regulator-related genes play vital roles in bladder urothelial carcinoma (BLCA). However, the role of m6A-related glucose metabolism genes in BLCA occurrence and development has not yet been report...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10683108/ https://www.ncbi.nlm.nih.gov/pubmed/38017469 http://dx.doi.org/10.1186/s12935-023-03160-w |
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author | Zhou, Guanwen Li, Yi Ren, Xiangguo Qin, Guoliang Zhang, Zhaocun Zhao, Haifeng Gao, Lijian Jiang, Xianzhou |
author_facet | Zhou, Guanwen Li, Yi Ren, Xiangguo Qin, Guoliang Zhang, Zhaocun Zhao, Haifeng Gao, Lijian Jiang, Xianzhou |
author_sort | Zhou, Guanwen |
collection | PubMed |
description | BACKGROUNDS: Glucose metabolism is associated with the development of cancers, and m6A RNA methylation regulator-related genes play vital roles in bladder urothelial carcinoma (BLCA). However, the role of m6A-related glucose metabolism genes in BLCA occurrence and development has not yet been reported. Our study aims to integrate m6A- and glycolysis-related genes and find potential gene targets for clinical diagnosis and prognosis of BLCA patients. METHODS: Sequencing data and clinical information on BLCA were extracted from common databases. Univariate Cox analysis was used to screen prognosis-related m6A glucose metabolism genes; BLCA subtypes were distinguished using consensus clustering analysis. Subsequently, genes associated with BLCA occurrence and development were identified using the “limma” R package. The risk score was then calculated, and a nomogram was constructed to predict survival rate of BLCA patients. Functional and immune microenvironment analyses were performed to explore potential functions and mechanisms of the different risk groups. RESULTS: Based on 70 prognosis-related m6A glucose metabolism genes, BLCA was classified into two subtypes, and 34 genes associated with its occurrence and development were identified. Enrichment analysis revealed an association of genes in high-risk groups with tricarboxylic acid cycle function and glycolysis. Moreover, significantly higher levels of seven immune checkpoints, 14 immune checkpoint inhibitors, and 32 immune factors were found in high-risk score groups. CONCLUSIONS: This study identified two biomarkers associated with BLCA prognosis; these findings may deepen our understanding of the role of m6A-related glucose metabolism genes in BLCA development. We constructed a m6A-related glucose metabolism- and immune-related gene risk model, which could effectively predict patient prognosis and immunotherapy response and guide individualized immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-023-03160-w. |
format | Online Article Text |
id | pubmed-10683108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106831082023-11-30 Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer Zhou, Guanwen Li, Yi Ren, Xiangguo Qin, Guoliang Zhang, Zhaocun Zhao, Haifeng Gao, Lijian Jiang, Xianzhou Cancer Cell Int Research BACKGROUNDS: Glucose metabolism is associated with the development of cancers, and m6A RNA methylation regulator-related genes play vital roles in bladder urothelial carcinoma (BLCA). However, the role of m6A-related glucose metabolism genes in BLCA occurrence and development has not yet been reported. Our study aims to integrate m6A- and glycolysis-related genes and find potential gene targets for clinical diagnosis and prognosis of BLCA patients. METHODS: Sequencing data and clinical information on BLCA were extracted from common databases. Univariate Cox analysis was used to screen prognosis-related m6A glucose metabolism genes; BLCA subtypes were distinguished using consensus clustering analysis. Subsequently, genes associated with BLCA occurrence and development were identified using the “limma” R package. The risk score was then calculated, and a nomogram was constructed to predict survival rate of BLCA patients. Functional and immune microenvironment analyses were performed to explore potential functions and mechanisms of the different risk groups. RESULTS: Based on 70 prognosis-related m6A glucose metabolism genes, BLCA was classified into two subtypes, and 34 genes associated with its occurrence and development were identified. Enrichment analysis revealed an association of genes in high-risk groups with tricarboxylic acid cycle function and glycolysis. Moreover, significantly higher levels of seven immune checkpoints, 14 immune checkpoint inhibitors, and 32 immune factors were found in high-risk score groups. CONCLUSIONS: This study identified two biomarkers associated with BLCA prognosis; these findings may deepen our understanding of the role of m6A-related glucose metabolism genes in BLCA development. We constructed a m6A-related glucose metabolism- and immune-related gene risk model, which could effectively predict patient prognosis and immunotherapy response and guide individualized immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-023-03160-w. BioMed Central 2023-11-28 /pmc/articles/PMC10683108/ /pubmed/38017469 http://dx.doi.org/10.1186/s12935-023-03160-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 | Research Zhou, Guanwen Li, Yi Ren, Xiangguo Qin, Guoliang Zhang, Zhaocun Zhao, Haifeng Gao, Lijian Jiang, Xianzhou Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
title | Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
title_full | Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
title_fullStr | Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
title_full_unstemmed | Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
title_short | Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
title_sort | identifying prognostic characteristics of m6a-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10683108/ https://www.ncbi.nlm.nih.gov/pubmed/38017469 http://dx.doi.org/10.1186/s12935-023-03160-w |
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