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A prognostic risk model for glioma patients by systematic evaluation of genomic variations

The overall survival rate of gliomas has not significantly improved despite new effective treatments, mainly due to tumor heterogeneity and drug delivery. Here, we perform an integrated clinic-genomic analysis of 1, 477 glioma patients from a Chinese cohort and a TCGA cohort and propose a potential...

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Detalles Bibliográficos
Autores principales: Zhang, Baifeng, Wan, Weiqing, Li, Zibo, Gao, Zhixian, Ji, Nan, Xie, Jian, Wang, Junmei, Wang, Bin, Lai-Wan Kwong, Dora, Guan, Xinyuan, Gao, Shengjie, Zhao, Yuanli, Lu, Youyong, Zhang, Liwei, Rodland, Karin D., Tsang, Shirley X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758519/
https://www.ncbi.nlm.nih.gov/pubmed/36536675
http://dx.doi.org/10.1016/j.isci.2022.105681
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author Zhang, Baifeng
Wan, Weiqing
Li, Zibo
Gao, Zhixian
Ji, Nan
Xie, Jian
Wang, Junmei
Wang, Bin
Lai-Wan Kwong, Dora
Guan, Xinyuan
Gao, Shengjie
Zhao, Yuanli
Lu, Youyong
Zhang, Liwei
Rodland, Karin D.
Tsang, Shirley X.
author_facet Zhang, Baifeng
Wan, Weiqing
Li, Zibo
Gao, Zhixian
Ji, Nan
Xie, Jian
Wang, Junmei
Wang, Bin
Lai-Wan Kwong, Dora
Guan, Xinyuan
Gao, Shengjie
Zhao, Yuanli
Lu, Youyong
Zhang, Liwei
Rodland, Karin D.
Tsang, Shirley X.
author_sort Zhang, Baifeng
collection PubMed
description The overall survival rate of gliomas has not significantly improved despite new effective treatments, mainly due to tumor heterogeneity and drug delivery. Here, we perform an integrated clinic-genomic analysis of 1, 477 glioma patients from a Chinese cohort and a TCGA cohort and propose a potential prognostic model for gliomas. We identify that SBS11 and SBS23 mutational signatures are associated with glioma recurrence and indicate worse prognosis only in low-grade type of gliomas and IDH-Mut subtype. We also identify 42 genomic features associated with distinct clinical outcome and successfully used ten of these to develop a prognostic risk model of gliomas. The high-risk glioma patients with shortened survival were characterized by high level of frequent copy number alterations including PTEN, CDKN2A/B deletion, EGFR amplification, less IDH1 or CIC gene mutations, high infiltration levels of immunosuppressive cells and activation of G2M checkpoint and Oxidative phosphorylation oncogenic pathway.
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spelling pubmed-97585192022-12-18 A prognostic risk model for glioma patients by systematic evaluation of genomic variations Zhang, Baifeng Wan, Weiqing Li, Zibo Gao, Zhixian Ji, Nan Xie, Jian Wang, Junmei Wang, Bin Lai-Wan Kwong, Dora Guan, Xinyuan Gao, Shengjie Zhao, Yuanli Lu, Youyong Zhang, Liwei Rodland, Karin D. Tsang, Shirley X. iScience Article The overall survival rate of gliomas has not significantly improved despite new effective treatments, mainly due to tumor heterogeneity and drug delivery. Here, we perform an integrated clinic-genomic analysis of 1, 477 glioma patients from a Chinese cohort and a TCGA cohort and propose a potential prognostic model for gliomas. We identify that SBS11 and SBS23 mutational signatures are associated with glioma recurrence and indicate worse prognosis only in low-grade type of gliomas and IDH-Mut subtype. We also identify 42 genomic features associated with distinct clinical outcome and successfully used ten of these to develop a prognostic risk model of gliomas. The high-risk glioma patients with shortened survival were characterized by high level of frequent copy number alterations including PTEN, CDKN2A/B deletion, EGFR amplification, less IDH1 or CIC gene mutations, high infiltration levels of immunosuppressive cells and activation of G2M checkpoint and Oxidative phosphorylation oncogenic pathway. Elsevier 2022-11-28 /pmc/articles/PMC9758519/ /pubmed/36536675 http://dx.doi.org/10.1016/j.isci.2022.105681 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Zhang, Baifeng
Wan, Weiqing
Li, Zibo
Gao, Zhixian
Ji, Nan
Xie, Jian
Wang, Junmei
Wang, Bin
Lai-Wan Kwong, Dora
Guan, Xinyuan
Gao, Shengjie
Zhao, Yuanli
Lu, Youyong
Zhang, Liwei
Rodland, Karin D.
Tsang, Shirley X.
A prognostic risk model for glioma patients by systematic evaluation of genomic variations
title A prognostic risk model for glioma patients by systematic evaluation of genomic variations
title_full A prognostic risk model for glioma patients by systematic evaluation of genomic variations
title_fullStr A prognostic risk model for glioma patients by systematic evaluation of genomic variations
title_full_unstemmed A prognostic risk model for glioma patients by systematic evaluation of genomic variations
title_short A prognostic risk model for glioma patients by systematic evaluation of genomic variations
title_sort prognostic risk model for glioma patients by systematic evaluation of genomic variations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758519/
https://www.ncbi.nlm.nih.gov/pubmed/36536675
http://dx.doi.org/10.1016/j.isci.2022.105681
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