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

Authors :
Baifeng Zhang
Weiqing Wan
Zibo Li
Zhixian Gao
Nan Ji
Jian Xie
Junmei Wang
Bin Wang
Dora Lai-Wan Kwong
Xinyuan Guan
Shengjie Gao
Yuanli Zhao
Youyong Lu
Liwei Zhang
Karin D. Rodland
Shirley X. Tsang
Source :
iScience, Vol 25, Iss 12, Pp 105681- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Summary: 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.

Subjects

Subjects :
Genetics
Genomics
Cancer
Science

Details

Language :
English
ISSN :
25890042
Volume :
25
Issue :
12
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.fcd0c9c07b5d44129093145a6b637a17
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2022.105681