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Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer
BACKGROUND: Bladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10470057/ https://www.ncbi.nlm.nih.gov/pubmed/37664033 http://dx.doi.org/10.3389/fonc.2023.1102518 |
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author | Wu, Zixuan Li, Xiaohuan Gu, Zhenchang Xia, Xinhua Yang, Jing |
author_facet | Wu, Zixuan Li, Xiaohuan Gu, Zhenchang Xia, Xinhua Yang, Jing |
author_sort | Wu, Zixuan |
collection | PubMed |
description | BACKGROUND: Bladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine metabolism (PyM) is a complex enzyme network that incorporates nucleoside salvage, de novo nucleotide synthesis, and catalytic pyrimidine degradation. Metabolic reprogramming is linked to clinical prognosis in several types of cancer. However, the role of pyrimidine metabolism Genes (PyMGs) in the BLCA-fighting process remains poorly understood. METHODS: Predictive PyMGs were quantified in BLCA samples from the TCGA and GEO datasets. TCGA and GEO provided information on stemness indices (mRNAsi), gene mutations, CNV, TMB, and corresponding clinical features. The prediction model was built using Lasso regression. Co-expression analysis was conducted to investigate the relationship between gene expression and PyM. RESULTS: PyMGs were overexpressed in the high-risk sample in the absence of other clinical symptoms, demonstrating their predictive potential for BLCA outcome. Immunological and tumor-related pathways were identified in the high-risk group by GSWA. Immune function and m6a gene expression varied significantly between the risk groups. In BLCA patients, DSG1, C6orf15, SOST, SPRR2A, SERPINB7, MYBPH, and KRT1 may participate in the oncology process. Immunological function and m6a gene expression differed significantly between the two groups. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and drug sensitivity all showed significant gene connections. CONCLUSIONS: BLCA-associated PyMGs are available to provide guidance in the prognostic and immunological setting and give evidence for the formulation of PyM-related molecularly targeted treatments. PyMGs and their interactions with immune cells in BLCA may serve as therapeutic targets. |
format | Online Article Text |
id | pubmed-10470057 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104700572023-09-01 Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer Wu, Zixuan Li, Xiaohuan Gu, Zhenchang Xia, Xinhua Yang, Jing Front Oncol Oncology BACKGROUND: Bladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine metabolism (PyM) is a complex enzyme network that incorporates nucleoside salvage, de novo nucleotide synthesis, and catalytic pyrimidine degradation. Metabolic reprogramming is linked to clinical prognosis in several types of cancer. However, the role of pyrimidine metabolism Genes (PyMGs) in the BLCA-fighting process remains poorly understood. METHODS: Predictive PyMGs were quantified in BLCA samples from the TCGA and GEO datasets. TCGA and GEO provided information on stemness indices (mRNAsi), gene mutations, CNV, TMB, and corresponding clinical features. The prediction model was built using Lasso regression. Co-expression analysis was conducted to investigate the relationship between gene expression and PyM. RESULTS: PyMGs were overexpressed in the high-risk sample in the absence of other clinical symptoms, demonstrating their predictive potential for BLCA outcome. Immunological and tumor-related pathways were identified in the high-risk group by GSWA. Immune function and m6a gene expression varied significantly between the risk groups. In BLCA patients, DSG1, C6orf15, SOST, SPRR2A, SERPINB7, MYBPH, and KRT1 may participate in the oncology process. Immunological function and m6a gene expression differed significantly between the two groups. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and drug sensitivity all showed significant gene connections. CONCLUSIONS: BLCA-associated PyMGs are available to provide guidance in the prognostic and immunological setting and give evidence for the formulation of PyM-related molecularly targeted treatments. PyMGs and their interactions with immune cells in BLCA may serve as therapeutic targets. Frontiers Media S.A. 2023-08-17 /pmc/articles/PMC10470057/ /pubmed/37664033 http://dx.doi.org/10.3389/fonc.2023.1102518 Text en Copyright © 2023 Wu, Li, Gu, Xia and Yang 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 Wu, Zixuan Li, Xiaohuan Gu, Zhenchang Xia, Xinhua Yang, Jing Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
title | Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
title_full | Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
title_fullStr | Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
title_full_unstemmed | Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
title_short | Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
title_sort | pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10470057/ https://www.ncbi.nlm.nih.gov/pubmed/37664033 http://dx.doi.org/10.3389/fonc.2023.1102518 |
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