目的 综合运用生物信息学方法进行胶质母细胞瘤铜死亡相关免疫检查点基因（ICGs）特征分析及潜在候选药物预测。方法 从癌症基因组图谱（TCGA）数据库下载胶质母细胞瘤患者mRNA表达和临床信息。采用Cox回归、Lasso回归及交叉验证筛选预后相关的ICGs，构建风险模型并对胶质母细胞瘤患者进行风险评分。利用风险评分及临床特征构建列线图预测模型，通过校准曲线及受试者特征曲线（ROC）曲线进行验证。利用Kaplan-Meier曲线对高、低风险组进行预后分析。利用DSigDB数据库筛选ICGs相关的潜在候选药物，并对高、低风险组药物敏感性进行分析。结果 共得到36个铜死亡相关的ICGs。通过Cox回归、Lasso回归筛选出4个预后相关ICGs，分别是CD276、TNFSF14、CD40、TNFSF9。多因素Cox回归结果示，风险评分是胶质母细胞瘤患者的独立预后因子。ROC曲线图预测1、3年生存率的ROC曲线下面积分别为0.726（95% CI：0.637～0.816）、0.731（95% CI：0.593～0.870）。GSEA分析结果显示，DNA复制、间隙连接、糖胺聚糖生物合成等癌症通路主要富集在高风险组。高风险组患者中CD4⁺ T细胞、中性粒细胞、巨噬细胞、髓样树突状细胞免疫浸润水平较低风险组升高，达沙替尼、二甲基乙二酰氨基乙酸的半数抑制浓度（IC₅₀）较低风险组减小。从DSigDB数据库得到8种可能对胶质母细胞瘤患者有益的小分子药物。结论 筛选出4个预后有关的铜死亡相关ICGs，以此构建的风险模型具有较好的预后价值，并确定了8种ICGs相关治疗胶质母细胞瘤患者的潜在候选药物。

Objective To comprehensively use bioinformatics methods to analyze the characteristics of copper death-related immune checkpoint genes (ICGs) and predict potential drug candidates in glioblastoma. Methods The mRNA expression and clinical information of glioblastoma patients were obtained from The Cancer Genome Atlas (TCGA) database. The Cox regression, Lasso regression and cross-validation were used to screen out the ICGs related to prognosis, then construct a risk model and score the risk of glioblastoma patients. A nomogram prediction model was constructed using risk scores and clinical characteristics, and verified by calibration curve and ROC curve. Prognostic analysis of high and low risk groups was performed using Kaplan-Meier curves. The DSigDB database was used to screen potential drug candidates related to ICGs, and the drug sensitivity of high and low risk groups was analyzed. Results A total of 36 copper death-related ICGs were obtained. Four prognosis-related ICGs were screened by Cox regression and Lasso regression, namely CD276, TNFSF14, CD40, and TNFSF9. Multivariate Cox regression results showed that risk score was an independent prognostic factor for glioblastoma patients. The results of the ROC curve showed that the area under the ROC curve of the nomogram to predict the 1-year and 3-year survival rates was 0.726 (95% CI: 0.637-0.816) and 0.731 (95% CI: 0.593-0.870), respectively. The results of GSEA analysis showed that cancer pathways such as DNA replication, gap junctions, and glycosaminoglycan biosynthesis were mainly enriched in high-risk groups. The immune infiltration levels of CD4⁺ T cells, neutrophils, macrophages, and myeloid dendritic cells in the high-risk group were significantly increased, while the IC₅₀s of dasatinib and dimethyloxalylglycine were significantly decreased. Eight small-molecule drugs that may benefit glioblastoma patients were obtained from the DSigDB database. Conclusion In this study, 4 prognostic copper death-related ICGs were screened, and the risk model constructed by these ICGs had good prognostic value, and 8 potential drug candidates related to ICGs were identified for the treatment of glioblastoma patients.

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