iScience (Dec 2022)

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

  • 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

Journal volume & issue
Vol. 25, no. 12
p. 105681

Abstract

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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.

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