基于铜死亡相关基因和多组学分析的新型预后模型预测膀胱尿路上皮癌患者的预后
A Novel Prognostic Model Based on Cuproptosis-Related Genes and Multi-Omics Analysis for Predicting the Prognosis of Patients with Bladder Urothelial Carcinoma
摘要: 铜死亡是一种特殊的细胞死亡形式。膀胱癌，特别是膀胱尿路上皮癌(BLCA)，是全球十大最常见癌症之一。迄今为止，铜死亡在BLCA中的潜在作用尚不明确。在本研究中，我们基于从癌症基因组图谱(TCGA)和基因表达综合(GEO)数据库下载的数据，系统评估了509个BLCA样本中19个经过验证的与铜中毒相关基因(CRGs)介导的铜中毒模式。使用Kaplan-Meier方法分析不同风险组的总体生存率(OS)。使用基因集变异分析(GSVA)研究不同铜死亡簇(CR簇)之间的差异。使用单样本基因集富集分析(ssGSEA)讨CRG簇与免疫状态之间的潜在关系。我们使用GO (基因本体)和KEGG (京都基因与基因组百科全书)富集分析研究各种细胞生化过程。最后，我们建立了一个预后模型，以预测患者的生存结果，并进一步分析BLCA患者的预测特征与各种治疗反应之间的相关性。在本研究中，我们得出了两个CRG簇和基因簇，并建立了一个模型来量化个体BLCA患者的风险评分，发现其与多种临床特征密切相关，并能够准确预测BLCA患者的预后。我们相信，通过本研究，对单个样本中铜死亡介导模式的定量分析可能有助于提高我们对BLCA多组学特征的理解，并指导未来的治疗方案。
Abstract: Cuproptosis is a special form of cell death. Bladder cancer, especially Bladder Urothelial Carcinoma (BLCA), is one of the ten most common cancer types in the world. So far, the potential role of cuproptosis in BLCA is unclear. In the present study, we systematically evaluated the copper poisoning-mediated patterns of 509 BLCA samples based on 19 validated copper poisoning-related genes (CRGs) using data downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Kaplan Meier method was used to analyze the overall survival rate (OS) of different risk groups. Gene Set Variation Analysis (GSVA) was used to study the functional differences between different cuproptosis clusters (CRG clusters). Single sample gene set enrichment analysis (ssGSEA) was used to explore the potential relationship between CRG clusters and immune status. We used GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis to study various cellular biochemical processes. Finally, we established a prognostic model to predict patients’ survival outcomes and to further analyze the correlation between the predictive characteristics of BLCA patients and various treatment responses. In this study, we derived two CRG clusters and gene clusters and also established a model to quantify the risk score of individual BLCA patients, which was found to be closely associated with various clinical characteristics and could precisely predict the prognosis of BLCA patients. We believe that through our study, quantitative analysis of cuproptosis-mediated patterns in a single sample may help to improve our understanding of the multi-omics characteristics of BLCA and guide future treatment regimens.
文章引用：张东升, 于圣杰. 基于铜死亡相关基因和多组学分析的新型预后模型预测膀胱尿路上皮癌患者的预后[J]. 临床医学进展, 2025, 15(3): 903-920. https://doi.org/10.12677/acm.2025.153694

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