基于铜死亡相关基因的肾透明细胞癌中预后模型的构建与应用

Development and validation of cuproptosis-related genes expression-based signature to predict overall survival of clear cell renal cell carcinoma

目的:研究铜死亡相关基因(cuproposis-related genes,CRGs)在肾透明细胞癌(clear cell renal cell carcinoma,ccRCC)中的表达情况,构建预后模型并探讨其临床意义。方法:从TCGA数据库中获得522例ccRCC患者的转录组数据和临床病理数据。将患者随机分为训练集(262例)和验证集1(260例),并将总体患者作为验证集2(522例)。在训练集中采用差异性分析确定肿瘤组织和癌旁组织差异性表达的CRGs,使用LASSO-Cox回归分析构建ccRCC的CRGs预后模型(OSCRG)。根据OSCRG将患者分为低危组和高危组,使用Kaplan-Meier生存分析研究OSCRG与总体生存期(overall survival,OS)的关系。使用单因素和多因素Cox回归分析构建包含OSCRG和临床病理参数的列线图预测OS,并在验证集中验证该列线图的准确性。最后使用KEGG和GO基因富集分析探索差异性表达的CRGs的生物学功能。结果:在训练集中有9个差异性表达的CRGs,并且均与OS相关。LASSO-Cox回归分析确定了3个CRGs并构建OSCRG。使用OSCRG将患者分为高危组和低危组,生存分析显示在训练集和验证集中低危组OS均高于高危组,并且OSCRG是OS的独立预后因素。使用OSCRG和临床病理参数构建的列线图对OS具有良好的预测作用,且加入VHL表达量后其预测能力增强。此外,在训练集和验证集中,高危组术后接受辅助治疗的患者多于低危组。最后,GO和KEGG分析结果表明,差异性表达的CRGs与代谢相关。结论:3种CRGs可能是ccRCC的预后分子标志物,有望为患者的个体化治疗提供新的参考依据。

Objective To clarify an expression pattern of cuproposis-related genes(CRGs)in individual overall survival(OS)risk evaluation among patients with clear cell renal cell carcinoma(ccRCC).Methods In this study,522 patients with ccRCC from the TCGA database were included.Differentially expressed genes(DEGs)were detected in a training cohort(n=262)to establish a gene classifier by Cox regression model.The accuracy of prognostic prediction of this gene classifier was validated in two validation cohorts(n=260 and n=522,respectively).Additionally,we conducted Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)analyses to assess the biological functions of the differentially expressed CRGs.Results In the training cohort,a total of nine differentially expressed CRGs were associated with OS.An overall survival CRGs signature(OSCRG)consisting of three genes was developed to separate patients into high-risk and low-risk groups in the training cohort.In the training cohort,individuals with low-risk scores had longer OS(P<0.0001)than those with high-risk scores.We validated the prognostic accuracy of OSCRG in the two validation cohorts.Moreover,our results showed that patients with additional therapy in the high-risk group were more than those in the low-risk group.We developed a nomogram on the basis of the OSCRG and other variables that predicted an individual's OS risk,which was enhanced by adding VHL expression.The outcomes of GO and KEGG analyses showed that differentially expressed CRGs were metabolic-related.Conclusion Three CRGs may be molecular markers to predict the prognosis of ccRCC,and useful to guide individualized therapeutic decisions.