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用于预测肾透明细胞癌免疫治疗药物反应和预后的铜死亡相关4基因风险模型

Cuproptosis-Related 4-Gene Risk Model for Predicting Immunotherapy Drug Response and Prognosis of Kidney Renal Clear Cell Carcinoma.

作者信息

Guo Jin-Shuai, Ding Hao, Wu Peng-Yu, Xin Zi-Yi, Li Jian-Xin, Jo Hyon-Su, Ma Zhen-Hai

机构信息

Department of Breast Surgery, Breast Cancer Key Lab of Dalian, the Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116027, China.

Department of General Surgery, the Hospital of Pyongyang Medical University, D.P.R. Korea.

出版信息

Chin Med Sci J. 2023 Sep;38(3):191-205. doi: 10.24920/004223.

Abstract

Background Kidney renal clear cell carcinoma (KIRC) is one of the most common renal malignancies with a high mortality rate. Cuproptosis, a novel form of cell death, is strongly linked to mitochondrial metabolism and is mediated by protein lipoylation, leading to a proteotoxic stress response and cell death. To date, few studies have ellucidated the holistic role of cuproptosis-related genes (CRGs) in the pathogenesis of KIRC.Methods We comprehensively and completely analyzed the RNA sequencing data and corresponding clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We screened for differentially expressed CRGs and constructed a prognostic risk model using univariate and multivariate Cox proportional regression analyses. Kaplan-Meier analysis was performed and receiver operating characteristic (ROC) curves were plotted to predict the prognosis of KIRC patients. Functional enrichment analysis was utilized to explore the internal mechanisms. Immune-related functions were analyzed using single-sample gene set enrichment analysis (ssGSEA), tumour immune dysfunction and exclusion (TIDE) scores, and drug sensitivity analysis.Results We established a concise prognostic risk model consisting of four CRGs (DBT, DLAT, LIAS and PDHB) to predict the overall survival (OS) in KIRC patients. The results of the survival analysis indicated a significantly lower OS in the high-risk group as compared to the patients in the low-risk group. The area under the time-dependent ROC curve (AUC) at 1, 3, and 5 year was 0.691, 0.618, and 0.614 in KIRC. Functional enrichment analysis demonstrated that CRGs were significantly enriched in tricarboxylic acid (TCA) cycle-related processes and metabolism-related pathways. Sorafenib, doxorubicin, embelin, and vinorelbine were more sensitive in the high-risk group.Conclusions We constructed a concise CRGs risk model to evaluate the prognosis of KIRC patients and this may be a new direction for the diagnosis and treatment of KIRC.

摘要

背景 肾透明细胞癌(KIRC)是最常见的肾恶性肿瘤之一,死亡率很高。铜死亡是一种新型细胞死亡形式,与线粒体代谢密切相关,由蛋白质脂酰化介导,导致蛋白毒性应激反应和细胞死亡。迄今为止,很少有研究阐明铜死亡相关基因(CRG)在KIRC发病机制中的整体作用。

方法 我们全面且完整地分析了来自癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)的RNA测序数据及相应临床信息。我们筛选出差异表达的CRG,并使用单因素和多因素Cox比例回归分析构建预后风险模型。进行Kaplan-Meier分析并绘制受试者工作特征(ROC)曲线以预测KIRC患者的预后。利用功能富集分析探索其内在机制。使用单样本基因集富集分析(ssGSEA)、肿瘤免疫功能障碍和排除(TIDE)评分以及药物敏感性分析来分析免疫相关功能。

结果 我们建立了一个由四个CRG(DBT、DLAT、LIAS和PDHB)组成的简明预后风险模型,以预测KIRC患者的总生存期(OS)。生存分析结果表明,高风险组的OS明显低于低风险组患者。KIRC中1年、3年和5年的时间依赖性ROC曲线下面积(AUC)分别为0.691、0.618和0.614。功能富集分析表明,CRG在三羧酸(TCA)循环相关过程和代谢相关途径中显著富集。索拉非尼、阿霉素、紫铆素和长春瑞滨在高风险组中更敏感。

结论 我们构建了一个简明的CRG风险模型来评估KIRC患者的预后,这可能是KIRC诊断和治疗的一个新方向。

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