基于自噬相关基因建立和验证胃癌患者的预后评分模型

Establishment and validation of a prognostic model for patients with gastric cancer based on autophagy-related genes

目的:自噬是溶酶体对自身结构降解的再循环系统,在肿瘤的发展中发挥重要作用。本研究旨在探索胃癌(GC)自噬相关基因(ARGs)的功能以完善现有预后分期制度。方法:利用R语言鉴定GC中差异生存ARGs,结合单因素Cox和Lasso回归分析构建ARGs的风险评分模型,在生存分析和ROC曲线中验证其效能。结果:生存分析表明高风险评分预示预后较差(均P<0.05)。ROC曲线证实了该模型具备可靠的预测性能(AUCmax=0.843)。单因素和多因素独立预后分析表明该评分是GC的独立危险因素(P<0.001)。Pearson相关分析发现该模型能反映多类免疫细胞浸润情况(P<0.001)。结论:本研究构建了一个由5个ARGs(CXCR4、GRID2、HSPB8、IRGM、TSC1)标签搭建的风险评分模型,该模型可与现有的临床病理结合,为GC患者提供更精准的预后判断。

Objective:Autophagy is a recirculation system of lysosomal degradation of its own structure,which plays an important role in the development of tumors.The purpose of this study was to explore the functions of autophagy-related genes(ARGs)in gastric cancer(GC)to improve the current prognostic staging system.Methods:The differential survival ARGs in GC was identified by R language,and the risk scoring model of ARGs was constructed by univariate Cox and Lasso regression analysis,and its efficacy was verified by survival analysis and ROC curve.Results:Survival analysis showed that high risk score predicted poor prognosis(all P<0.05).ROC curve confirmed that the model had reliable predictive performance(AUCmax=0.843).Univariate and multivariate independent prognostic analysis showed that this score was an independent risk factor for GC(P<0.001).Pearson correlation analysis showed that the model could reflect multiple types of immune cell infiltration(P<0.001).Conclusion:This study constructed a risk scoring model based on 5 ARGs labels(CXCR4,GRID2,HSPB8,IRGM,TSC1),which can be combined with existing clinicopathology to provide more accurate prognosis for GC patients.