【摘要】 目的 通过分析肿瘤突变负荷(TMB)相关基因，开发并验证TMB相关的预后模型，寻找预测胃癌预后和免疫治疗反应的生物标志物。方法 使用limma包筛选胃癌和正常组织中的差异表达基因，结合LASSO回归和多因素Cox回归方法构建胃癌的预后模型，使用CIBERSORT算法分析肿瘤免疫浸润的情况，以评估免疫治疗的反应性。结果 所构建的TMB相关预后模型表现出较好的预测准确性，在TCGA总队列中1、3、5年的曲线下面积分别为0.641、0.665和0.720。低风险组患者的总体生存率要优于高风险组，且与免疫激活细胞的较高浸润程度相关。结论 该研究构建的预后模型具有良好的预测准确性，并能够评估免疫治疗反应性，为胃癌的临床诊治与免疫治疗提供有效支持。更多还原

【Abstract】 Objective To develop and validate a tumor mutational burden(TMB) related prognostic model and identify biomarkers for predicting gastric cancer prognosis and immunotherapy response by analyzing genes associated with tumor mutation burden.Methods Limma package was used to screen differentially expressed genes in gastric cancer and normal tissues, and the prognostic model of gastric cancer was constructed by LASSO regression and multivariate Cox regression.The CIBERSORT algorithm was used to analyze the immune invasion of the tumor to assess the response to immunotherapy.Results The established tumor mutation load-related prognostic model showed good prediction accuracy, and the AUC values of 1,3 and 5 years in the TCGA fleet were 0.641,0.665 and 0.720,respectively.Overall survival was better in the low-risk group than in the high-risk group and was associated with a higher degree of infiltration of immune-activated cells.Conclusion The prognostic model constructed in this study has good prediction accuracy and can evaluate immunotherapy reactivity, providing effective support for clinical diagnosis, treatment and immunotherapy of gastric cancer.更多还原