基于糖代谢相关基因的肾透明细胞癌预后模型的构建与评价  

Construction and evaluation of a prognostic model for clear cell renal cell carcinoma based on carbohydrate metabolism-related genes

作　　者：段霜霜 古丽乃再尔·阿卜杜赛麦提 孙淼 柳惠斌 Shuangshuang Duan;Abudusaimaiti Gulinaizaier;Miao Sun;Huibin Liu(College of Pharmacy,Xinjiang Medical University,Xinjiang 830000,China;Clinical Operation,Xinjiang Medical University Affiliated Cancer Hospital,Xinjiang 830000,China)

机构地区：[1]新疆医科大学药学院,乌鲁木齐市830000 [2]新疆医科大学附属肿瘤医院药物临床试验机构

出　　处：《中国肿瘤临床》2024年第10期493-499,共7页Chinese Journal of Clinical Oncology

基　　金：新疆维吾尔自治区科技支疆项目(编号:2022E02131)资助。

摘　　要：目的:构建肾透明细胞癌(clear cell renal cell carcinoma,ccRCC)的糖代谢相关基因(carbohydrate metabolism-related genes,CRGs)预后模型并探索其临床意义。方法:选取TCGA数据库中ccRCC的mRNA表达数据,从MSigDB和KEGG数据库获取CRGs。通过LASSO回归建立CRGs预后模型并计算风险评分(RS)。按照RS中位数将患者分为高、低风险组,利用Kaplan-Meier曲线和生物信息学方法分析两组间的生存、免疫浸润、突变和免疫应答之间的差异。依据RS与临床特征构建诺模图,验证其预后预测效能。利用RT-qPCR检测ccRCC样本中CRGs表达量。结果:8个CRGs用于构建ccRCC预后风险模型,生存分析显示低风险组的患者预后较好(P<0.001)。生物信息学分析表明RS与免疫浸润、突变和免疫应答相关。根据RS与临床特征构建的诺模图具有良好的预后预测性能。体外实验证实上述8个CRGs在ccRCC组织和癌旁组织之间的表达存在显著的差异。结论:基于CRGs的预后模型可以用于ccRCC患者的预后预测。Objective:To establish a carbohydrate metabolism-related genes(CRGs)prognostic model for clear cell renal cell carcinoma(ccRCC)and investigate its clinical value.Methods:ccRCC mRNA expression data were sourced from The Cancer Genome Atlas(TCGA)data-base.CRGs were retrieved from the MSigDB and KEGG databases.A prognostic model based on CRGs was constructed using the LASSO lin-ear regression model,and the risk score(RS)was calculated.Patients were assigned into high-and low-risk groups according to the median RS.Differences in survival,immune infiltration,mutation,and immune response between the two groups were analyzed using Kaplan-Meier curves and bioinformatics methods.Constructing a nomogram based on the RS and clinical features and validating its accuracy of prognostic predictions.The expression of CRGs in the ccRCC samples was detected using RT-qPCR.Results:A total of eight key genes were utilized to construct a prognostic risk model for ccRCC.Survival analysis revealed that patients in the low-risk group had a better prognosis(P<0.001).Bioinformatics analysis showed that the RS correlated with immune cell infiltration,mutation,and immune responses.The nomogram based on the RS and clinical features demonstrated a strong predictive ability for prognosis.In vitro experiments confirmed notable differences in the expression of the eight CRGs between ccRCC and adjacent non-malignant tissues.Conclusions:A prognostic model based on CRGs can effectively predict the prognosis of patients with ccRCC.

关 键 词：肾透明细胞癌 糖代谢 预后模型 

分 类 号：R737.11[医药卫生—肿瘤]