基于TCGA数据库分析代谢限速酶相关基因对胃癌患者预后的影响及生存模型预测

Analysis of effect of metabolic rate limiting enzyme related genes on prognosis of patients with gastric cancer and prediction of survival model based on TCGA database

目的采用生物信息学方法,构建胃癌(Gastric Cancer,GC)患者代谢限速酶表达的预后评估模型,并判断对GC患者预后情况。方法从肿瘤基因组图谱(the cancer genome atlas program,TCGA)数据库中下载375例GC和32例正常组织标本的RNA测序数据,使用R语言筛选得到差异表达的代谢限速酶。采用Lasso回归模型分析并构建差异代谢限速酶预后模型并对该预后模型的有效性进行验证。此外,使用单因素和多因素COX分析评估临床特征、风险评分是否可以作为GC预后的独立风险因素。结果筛选得到5个差异表达的代谢限速酶(DCK、GAD1、UCK2、GNE和SOAT1),并建立GC代谢限速酶相关的预后模型,该模型的ROC曲线下面积为0.777,证实该模型具有较好的预后预测价值。多因素COX回归分析表明构建的风险评分是影响GC患者总体生存时间的独立因素(HR=8.889,P<0.001)。结论采用TCGA数据库成功构建了GC代谢限速酶相关基因的预后模型,并为判断GC患者的生存预后情况提供帮助。

ObjectiveTo construct a prognostic model of metabolic rate limiting enzymes in patients with gastric cancer(GC)by bioinformatics method.Methods downloaded from the Cancer Genome Atlas(TCGA)program database,and differentially expressed metabolic rate limiting enzymes were screened by R language.Lasso regression model was used to analyze and construct the prognosis model of differential metabolic rate limiting enzymes,and the effectiveness of the prognosis model was verified.In addition,the univariate and multivariate Cox analyses were used to evaluate whether clinical characteristics and risk score could be used as independent risk factors for GC prognosis.Results UCK2,GNE and SOAT1)were screened to establish the prognostic model related to GC metabolic rate limiting enzymes.The area under the receiver operator characteristic(ROC)curve of the model was 0.777,which confirmed that the model had a good prognostic value.The multivariate Cox regression analysis showed that the risk score we constructed was an independent factor affecting the overall survival of GC patients(HR=8.889,P<0.001).ConclusionThe prognosis model of GC metabolic rate limiting enzymes is successfully constructed by TCGA database,which can help to judge the survival and prognosis of GC patients.