Glioblastoma（GBM）是一种高度恶性的神经系统肿瘤，预后不良。虽然细胞凋亡影响癌细胞增殖、侵袭和迁移，但与GBM相关的细胞凋亡相关基因（PRGs）的作用以及PRGs的预后意义仍然不明确。通过分析细胞凋亡和GBM之间的关联机制，我们的研究希望为GBM的治疗提供新的见解。在这里，我们确定了52个PRGs中的32个差异表达基因，它们是GBM肿瘤与正常组织之间的差异表达基因。利用综合生物信息学分析，将所有GBM病例按差异表达基因的表达分为两组。最小绝对值收缩与选择算子分析导致了一个9基因标志的建立，并将GBM患者的癌症基因组图谱分为高风险和低风险亚组。与高风险患者相比，低风险患者的生存可能性显著增加。一致地，基因表达杂志队列的低风险患者表现出明显更长的总生存时间，而高风险患者则相反。采用基因标志计算的风险评分被发现是GBM病例生存的独立预测因子。此外，我们观察到高风险GBM患者和低风险GBM患者之间免疫检查点表达水平的显著差异，提供了对GBM免疫治疗的指导建议。总体而言，本研究开发了一种新的多基因标志来预测GBM的预后。本文版权©2023年作者（们）。 Wolters Kluwer Health, Inc.出版。

Glioblastoma (GBM) is a highly malignant neurological tumor that has a poor prognosis. While pyroptosis affects cancer cell proliferation, invasion and migration, function of pyroptosis-related genes (PRGs) in GBM as well as the prognostic significance of PRGs remain obscure. By analyzing the mechanisms involved in the association between pyroptosis and GBM, our study hopes to provide new insights into the treatment of GBM. Here, 32 out of 52 PRGs were identified as the differentially expressed genes between GBM tumor versus normal tissues. And all GBM cases were assigned to 2 groups according to the expression of the differentially expressed genes using comprehensive bioinformatics analysis. The least absolute shrinkage and selection operator analysis led to the construction of a 9-gene signature, and the cancer genome atlas cohort of GBM patients were categorized into high risk and low risk subgroups. A significant increase in the survival possibility was found in low risk patients in comparison with the high risk ones. Consistently, low risk patients of a gene expression omnibus cohort displayed a markedly longer overall survival than the high risk counterparts. The risk score calculated using the gene signature was found to be an independent predictor of survival of GBM cases. Besides, we observed significant differences in the expression levels of immune checkpoints between the high risk versus low risk GBM cases, providing instructive suggestions for immunotherapy of GBM. Overall, the present study developed a new multigene signature for prognostic prediction of GBM.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.