基于缺氧相关基因甲状腺癌预后模型的研究

Prognostic model of thyroid cancer based on hypoxia-related genes

目的通过检索肿瘤与癌症基因组图谱(TCGA)及hypoxiaDB数据库中甲状腺癌的相关数据,建立一个基于差异表达的缺氧相关基因模型。方法比较TCGA数据库和hypoxiaDB数据库中的基因,获得与甲状腺癌缺氧相关的差异表达基因。随后进行基因功能富集分析、构建蛋白质-蛋白质相互作用网络、筛选出具有预后价值的缺氧相关基因来建立并验证预后模型。结果共发现326个缺氧相关甲状腺癌基因。功能富集分析表明,这些基因主要参与生物功能调节。单因素Cox回归分析结果显示,共有23个基因与甲状腺癌预后相关,其中,11个基因通过多因素Cox分析构建了新的预后模型。结果显示,高风险评分(P<0.005)的患者总生存期比低风险评分的患者短。对甲状腺癌患者预后价值的单变量分析结果显示,构建的预后模型与患者的总体生存率显著相关。结论本研究的模型对甲状腺癌的预后有很好的预测作用。

Objective To establish a hypoxia-related gene model by comparing the expression of genes in the TCGA and hypoxia databases and identify differentially expressed genes related to hypoxia in thyroid cancer.Methods We compared the genes in the TCGA and hypoxia databases to identify differentially expressed genes related to hypoxia in thyroid cancer.Gene function enrichment analysis was performed,and protein-protein interaction networks were constructed.Results A total of 326 hypoxia-related thyroid cancer genes were identified.Functional enrichment analysis revealed that they were mainly involved in the regulation of biological functions.Univariate Cox regression analysis confirmed that 23 genes were related to the prognosis of thyroid cancer,of which 11 were identified using the multivariate Cox analysis prognostic model.The overall survival time of the patients with a high-risk score(P<0.005)was shorter than that of the patients with a low-risk score.Univariate analysis of the prognostic value of patients with thyroid cancer revealed that the prognostic model was significantly correlated with the overall survival rate of the patients.Conclusion Our model has a good predictive effect in the prognosis of thyroid cancer.