DataSheet4_A novel prognostic prediction model of cuprotosis-related genes signature in hepatocellular carcinoma.PDF

Background: Cuprotosis is a recently discovered copper-dependent cell death mechanism that relies on mitochondrial respiration. However, the role of cuprotosis-related genes (CRGs) in hepatocellular carcinoma (HCC) and their prognostic significances remain unknown.
Methods: Based on the recently published CRGs, the LASSO Cox regression analysis was applied to construct a CRGs risk model using the gene expression data from the International Cancer Genome Consortium as a training set, followed by validation with datasets from The Cancer Genome Atlas and the Gene Expression Omnibus (GSE14520). Functional enrichment analysis of the CRGs was performed by single-sample gene set enrichment analysis.
Results: Five of the 13 previously published CRGs were identified to be associated with prognosis in HCC. Kaplan-Meier analysis suggested that patients with high-risk scores have a shorter overall survival time than patients with low-risk scores. ROC curves indicated that the average AUC was more than 0.7, even at 4 years, and at least 0.5 at 5 years. Moreover, addition of this CRG risk score can significantly improve the efficiency of predicting overall survival compared to using traditional factors alone. Functional analysis demonstrated increased presence of Treg cells in patients with high-risk scores, suggesting a suppressed immune state in these patients. Finally, we point to the possibility that novel immunotherapies such as inhibitors of PDCD1, TIGIT, IDO1, CD274, CTLA4, and LAG3 may have potential benefits in high-risk patients.
Conclusion: We constructed a better prognostic model for liver cancer by using CRGs. The CRG risk score established in this study can serve as a potentially valuable tool for predicting clinical outcome of patients with HCC.

背景：铜死亡（Cuprotosis）是近年发现的一种依赖铜离子的细胞死亡机制，其发生依赖线粒体呼吸功能。然而，铜死亡相关基因（Cuproptosis-related genes, CRGs）在肝细胞癌（Hepatocellular carcinoma, HCC）中的作用及其预后价值仍未明确。
方法：基于最新发表的铜死亡相关基因集，本研究以国际癌症基因组联盟（International Cancer Genome Consortium, ICGC）的基因表达数据作为训练集，采用LASSO Cox回归分析构建铜死亡相关基因风险模型，并分别使用癌症基因组图谱（The Cancer Genome Atlas, TCGA）及基因表达综合数据库（Gene Expression Omnibus, GEO）的数据集GSE14520进行验证。通过单样本基因集富集分析（single-sample gene set enrichment analysis, ssGSEA）对铜死亡相关基因进行功能富集分析。
结果：在已发表的13个铜死亡相关基因中，筛选出5个与肝细胞癌预后相关的基因。Kaplan-Meier分析显示，高风险评分患者的总生存期显著短于低风险评分患者。ROC曲线结果表明，该模型的平均曲线下面积（AUC）在4年时仍高于0.7，5年时亦不低于0.5。此外，相较于单独使用传统临床预后因素，加入该铜死亡相关基因风险评分可显著提升总生存期的预测效能。功能富集分析结果显示，高风险评分患者体内调节性T细胞（Treg cells）浸润水平升高，提示此类患者存在免疫抑制状态。最后，本研究指出PDCD1、TIGIT、IDO1、CD274、CTLA4及LAG3等新型免疫治疗抑制剂或可对高风险患者产生潜在获益。
结论：本研究通过整合铜死亡相关基因构建了更优的肝细胞癌预后模型。本研究建立的铜死亡相关基因风险评分可作为预测肝细胞癌患者临床结局的潜在有效工具。