• Guizhi Xu, Yuhui Deng, and Huaizhang Shi.
• Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China; Department of Neurosurgery, The Second Hospital of Heilongjiang Province, Harbin, China.
• World Neurosurg. 2023 Aug 1; 176: e598e609e598-e609.

BackgroundThe efficacy of treatment of glioblastoma multiforme (GBM) is limited. The effect of DNA damage repair is an important factor.MethodsExpression data were downloaded from The Cancer Genome Atlas (training dataset) and the Gene Expression Omnibus (validation dataset) databases. Univariate Cox regression analysis and the least absolute shrinkage and selection operator were used to construct a DNA damage response (DDR) gene signature. Receiver operating characteristic curve analysis and Kaplan-Meier curve analysis were used to estimate the prognostic value of the risk signature. Moreover, consensus clustering analysis was used to investigate the potential subtypes of GBM according to DDR expression.ResultsWe constructed a 3-DDR-related gene signature through the survival analysis. The Kaplan-Meier curve analysis suggested that patients in the low-risk group have significantly better survival outcomes compared with the high-risk group in the training and external validation datasets. The results from the receiver operating characteristic curve analysis indicated that the risk model has high prognostic value in the training and external validation datasets. Moreover, 3 stable molecular subtypes were identified and validated in the Gene Expression Omnibus and The Cancer Genome Atlas databases according to the expression of the DNA repair gene. The microenvironment and immunity of GBM were further investigated and showed that cluster 2 had higher immunity and a higher immune score compared with clusters 1 and 3.ConclusionsThe DNA damage repair-related gene signature was an independent and powerful prognostic biomarker in GBM. Knowledge of the GBM subtypes could have important implications in the subclassification of GBM.Copyright © 2023 Elsevier Inc. All rights reserved.

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