坏死性凋亡是一种参与癌症发病机制的程序性细胞死亡。本工作开发了基于坏死性凋亡相关基因的预后胶质母细胞瘤（GBM）模型。RNA-Seq数据来自TCGA数据库。采用“WGCNA”方法鉴定共表达模块，并在此基础上进行GO和KEGG分析。编译了蛋白质-蛋白质相互作用（PPI）网络。应用 COX 回归和最小绝对收缩和选择算子 (LASSO) 分析来构建 RiskScore 模型，减少关键预后基因的数量。使用 CIBERSORT、ESTIMATE、MCP 计数和 TIMER 数据库评估免疫微环境的差异。通过细胞实验验证了关键预后基因对GBM的潜在影响。坏死性凋亡评分较高组的GBM患者免疫评分较高，生存率较差。 Brown模块与坏死性凋亡评分密切相关，被认为是关键基因模块。通过对五个簇进行回归分析得到三个关键基因（GZMB、PLAUR、SOCS3）。 RiskScore 模型与坏死性凋亡评分显着正相关。低风险患者可以从免疫治疗中受益，而高风险患者可能更适合服用多种化疗药物。列线图在生存预测方面表现出很强的性能。 GZMB、PLAUR 和 SOCS3 在 GBM 发展中发挥了关键作用。其中，高表达的GZMB与GBM细胞的侵袭和迁移能力有关。开发了与坏死性凋亡相关的遗传特征，并构建了RiskScore模型，为预测GBM患者的临床结果和免疫治疗反应提供参考。© 2024 年 Wiley 期刊有限责任公司。

Necroptosis is a type of programmed cell death involved in the pathogenesis of cancers. This work developed a prognostic glioblastoma (GBM) model based on necroptosis-related genes.RNA-Seq data were collected from the TCGA database. The "WGCNA" method was used to identify co-expression modules, based on which GO and KEGG analyses were conducted. A protein-protein interaction (PPI) network was compiled. The number of key prognostic genes was reduced applying COX regression and least absolute shrinkage and selection operator (LASSO) analysis to build a RiskScore model. Differences in immune microenvironments were assessed using CIBERSORT, ESTIMATE, MCP-count, and TIMER databases. The potential impact of key prognostic genes on GBM was validated by cellular experiments.GBM patients in the higher necroptosis score group had higher immune scores and worse survival. The Brown module, which was closely related to the necroptosis score, was considered as a key gene module. Three key genes (GZMB, PLAUR, SOCS3) were obtained by performing regression analysis on the five clusters. The RiskScore model was significantly, positively, correlated with necroptosis score. Low-risk patients could benefit from immunotherapy, while high-risk patients may be more suitable to take multiple chemotherapy drugs. The nomogram showed strong performance in survival prediction. GZMB, PLAUR, and SOCS3 played key roles in GBM development. Among them, high-expressed GZMB was related to the invasive and migratory abilities of GBM cells.A genetic signature associated with necroptosis was developed, and we constructed a RiskScore model to provide reference for predicting clinical outcomes and immunotherapy responses of patients with GBM.© 2024 Wiley Periodicals LLC.