目的 綜合運用生物信息學(xué)方法進行膠質(zhì)母細胞瘤銅死亡相關(guān)免疫檢查點基因（ICGs）特征分析及潛在候選藥物預(yù)測。方法 從癌癥基因組圖譜（TCGA）數(shù)據(jù)庫下載膠質(zhì)母細胞瘤患者mRNA表達和臨床信息。采用Cox回歸、Lasso回歸及交叉驗證篩選預(yù)后相關(guān)的ICGs，構(gòu)建風(fēng)險模型并對膠質(zhì)母細胞瘤患者進行風(fēng)險評分。利用風(fēng)險評分及臨床特征構(gòu)建列線圖預(yù)測模型，通過校準(zhǔn)曲線及受試者特征曲線（ROC）曲線進行驗證。利用Kaplan-Meier曲線對高、低風(fēng)險組進行預(yù)后分析。利用DSigDB數(shù)據(jù)庫篩選ICGs相關(guān)的潛在候選藥物，并對高、低風(fēng)險組藥物敏感性進行分析。結(jié)果 共得到36個銅死亡相關(guān)的ICGs。通過Cox回歸、Lasso回歸篩選出4個預(yù)后相關(guān)ICGs，分別是CD276、TNFSF14、CD40、TNFSF9。多因素Cox回歸結(jié)果示，風(fēng)險評分是膠質(zhì)母細胞瘤患者的獨立預(yù)后因子。ROC曲線圖預(yù)測1、3年生存率的ROC曲線下面積分別為0.726（95% CI：0.637～0.816）、0.731（95% CI：0.593～0.870）。GSEA分析結(jié)果顯示，DNA復(fù)制、間隙連接、糖胺聚糖生物合成等癌癥通路主要富集在高風(fēng)險組。高風(fēng)險組患者中CD4⁺ T細胞、中性粒細胞、巨噬細胞、髓樣樹突狀細胞免疫浸潤水平較低風(fēng)險組升高，達沙替尼、二甲基乙二酰氨基乙酸的半數(shù)抑制濃度（IC₅₀）較低風(fēng)險組減小。從DSigDB數(shù)據(jù)庫得到8種可能對膠質(zhì)母細胞瘤患者有益的小分子藥物。結(jié)論 篩選出4個預(yù)后有關(guān)的銅死亡相關(guān)ICGs，以此構(gòu)建的風(fēng)險模型具有較好的預(yù)后價值，并確定了8種ICGs相關(guān)治療膠質(zhì)母細胞瘤患者的潛在候選藥物。

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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