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

• Published in: iScience Vol. 25; no. 12; p. 105681
• Main Authors: 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.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 22.12.2022; Elsevier
• Subjects: 60 APPLIED LIFE SCIENCES; Cancer; Genetics; Genomics; Science & Technology - Other Topics; Genetics; Genomics; Cancer
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2022.105681

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. [Display omitted] •Systematical evaluation of prognostic value of genomic features in over 1400 gliomas•SBS11 mutational signature is associated with glioma recurrence•SBS11 mutational signature predicts worse prognosis in low-grade gliomas•Prediction of high-risk gliomas with shortened survival Genetics; Genomics; Cancer