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Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma

Background: Copper and copper-binding proteins are key components of tumor progression as they play important roles in tumor invasion and migration, but their associations in gliomas remain unclear. Methods: Transcriptomic datasets of glioblastoma, low-grade glioma, and normal brain cortex were deri...

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Autores principales: Zeng, Hao-Long, Li, Huijun, Yang, Qing, Li, Chao-Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605646/
https://www.ncbi.nlm.nih.gov/pubmed/37891828
http://dx.doi.org/10.3390/brainsci13101460
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author Zeng, Hao-Long
Li, Huijun
Yang, Qing
Li, Chao-Xi
author_facet Zeng, Hao-Long
Li, Huijun
Yang, Qing
Li, Chao-Xi
author_sort Zeng, Hao-Long
collection PubMed
description Background: Copper and copper-binding proteins are key components of tumor progression as they play important roles in tumor invasion and migration, but their associations in gliomas remain unclear. Methods: Transcriptomic datasets of glioblastoma, low-grade glioma, and normal brain cortex were derived from the TCGA and GTEX databases. Differentially expressed genes (DEGs) of copper-binding proteins were screened and used to construct a prognostic model based on COX and LASSO regression, which was further validated by the CGGA datasets. The expressions of risk-model genes were selectively confirmed via anatomic feature-based expression analysis and immunohistochemistry. The risk score was stratified by age, gender, WHO grade, IDH1 mutation, MGMT promoter methylation, and 1p/19q codeletion status, and a nomogram was constructed and validated. Results: A total of 21 DEGs of copper-binding proteins were identified and a six-gene risk-score model was constructed, consisting of ANG, F5, IL1A, LOXL1, LOXL2, and STEAP3, which accurately predicted 1-, 3-, and 5-year overall survival rates, with the AUC values of 0.87, 0.88, and 0.82, respectively. The high-risk group had a significantly shorter OS (p < 0.0001) and was associated with old age, wild-type IDH1, a high WHO grade, an unmethylated MGMT promoter, and 1p/19q non-codeletion and had higher levels of immune cell infiltration, cancer-immunity suppressor, and immune checkpoint gene expression as well as a higher TMB. Conclusions: The model based on the genes of copper-binding proteins could contribute to prognosis prediction and provide potential targets against gliomas.
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spelling pubmed-106056462023-10-28 Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma Zeng, Hao-Long Li, Huijun Yang, Qing Li, Chao-Xi Brain Sci Article Background: Copper and copper-binding proteins are key components of tumor progression as they play important roles in tumor invasion and migration, but their associations in gliomas remain unclear. Methods: Transcriptomic datasets of glioblastoma, low-grade glioma, and normal brain cortex were derived from the TCGA and GTEX databases. Differentially expressed genes (DEGs) of copper-binding proteins were screened and used to construct a prognostic model based on COX and LASSO regression, which was further validated by the CGGA datasets. The expressions of risk-model genes were selectively confirmed via anatomic feature-based expression analysis and immunohistochemistry. The risk score was stratified by age, gender, WHO grade, IDH1 mutation, MGMT promoter methylation, and 1p/19q codeletion status, and a nomogram was constructed and validated. Results: A total of 21 DEGs of copper-binding proteins were identified and a six-gene risk-score model was constructed, consisting of ANG, F5, IL1A, LOXL1, LOXL2, and STEAP3, which accurately predicted 1-, 3-, and 5-year overall survival rates, with the AUC values of 0.87, 0.88, and 0.82, respectively. The high-risk group had a significantly shorter OS (p < 0.0001) and was associated with old age, wild-type IDH1, a high WHO grade, an unmethylated MGMT promoter, and 1p/19q non-codeletion and had higher levels of immune cell infiltration, cancer-immunity suppressor, and immune checkpoint gene expression as well as a higher TMB. Conclusions: The model based on the genes of copper-binding proteins could contribute to prognosis prediction and provide potential targets against gliomas. MDPI 2023-10-14 /pmc/articles/PMC10605646/ /pubmed/37891828 http://dx.doi.org/10.3390/brainsci13101460 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zeng, Hao-Long
Li, Huijun
Yang, Qing
Li, Chao-Xi
Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma
title Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma
title_full Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma
title_fullStr Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma
title_full_unstemmed Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma
title_short Transcriptomic Characterization of Copper-Binding Proteins for Predicting Prognosis in Glioma
title_sort transcriptomic characterization of copper-binding proteins for predicting prognosis in glioma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605646/
https://www.ncbi.nlm.nih.gov/pubmed/37891828
http://dx.doi.org/10.3390/brainsci13101460
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