Shao Ruo-Nan, Bai Kun-Hao, Huang Qian-Qian, Chen Si-Liang, Huang Xin, Dai Yu-Jun
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Department of Hematologic Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Front Cell Dev Biol. 2023 Aug 7;11:1180625. doi: 10.3389/fcell.2023.1180625. eCollection 2023.
Cuprotosis is a recently discovered copper-dependent cell death mechanism that relies on mitochondrial respiration. However, the role of cuprotosis-related genes () in hepatocellular carcinoma () and their prognostic significances remain unknown. Based on the recently published , the LASSO Cox regression analysis was applied to construct a 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 was performed by single-sample gene set enrichment analysis. Five of the 13 previously published 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 was more than 0.7, even at 4 years, and at least 0.5 at 5 years. Moreover, addition of this 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 and may have potential benefits in high-risk patients. We constructed a better prognostic model for liver cancer by using . The risk score established in this study can serve as a potentially valuable tool for predicting clinical outcome of patients with .
铜死亡是一种最近发现的依赖于线粒体呼吸的铜依赖性细胞死亡机制。然而,铜死亡相关基因()在肝细胞癌()中的作用及其预后意义尚不清楚。基于最近发表的,使用国际癌症基因组联盟的基因表达数据作为训练集,应用LASSO Cox回归分析构建风险模型,随后用来自癌症基因组图谱和基因表达综合数据库(GSE14520)的数据集进行验证。通过单样本基因集富集分析对进行功能富集分析。在先前发表的13个中,有5个被确定与肝癌预后相关。Kaplan-Meier分析表明,高风险评分患者的总生存时间比低风险评分患者短。ROC曲线表明,即使在4年时,平均也超过0.7,在5年时至少为0.5。此外,与单独使用传统因素相比,添加该风险评分可显著提高预测总生存的效率。功能分析表明,高风险评分患者中调节性T细胞的存在增加,提示这些患者的免疫状态受到抑制。最后,我们指出,诸如和抑制剂等新型免疫疗法可能对高风险患者有潜在益处。我们通过使用构建了一个更好的肝癌预后模型。本研究建立的风险评分可作为预测患者临床结局的潜在有价值工具。