Table_1_Significance of Tumor Mutation Burden Combined With Immune Infiltrates in the Progression and Prognosis of Advanced Gastric Cancer.XLSX

Gastric cancer (GC) is a serious malignant tumor with high mortality and poor prognosis. The prognosis and survival are much worse for advanced gastric cancer (AGC). Recently, immunotherapy has been widely promoted for AGC patients, and studies have shown that tumor mutation burden (TMB) is closely related to immunotherapy response. Here, RNA-seq data, matched clinical information, and MAF files were downloaded from the cancer genome atlas (TCGA)-STAD project in the TCGA database. The collation and visual analysis of mutation data were implemented by the “maftools” package in R. We calculated the TMB values for AGC patients and divided the patients into high- and low-TMB groups according to the median value of TMB. Then, the correlation between high or low TMB and clinicopathological parameters was calculated. Next, we examined the differences in gene expression patterns between the two groups by using the “limma” R package and identified the immune-related genes among the DEGs. Through univariate Cox regression analysis, 15 genes related to prognosis were obtained. Furthermore, the two hub genes (APOD and SLC22A17) were used to construct a risk model to evaluate the prognosis of AGC patients. ROC and survival curves and GEO data were used as a validation set to verify the reliability of this risk model. In addition, the correlation between TMB and tumor-infiltrating immune cells was examined. In conclusion, our results suggest that AGC patients with high TMB have a better prognosis. By testing the patient’s TMB, we could better guide immunotherapy and understand patient response to immunotherapy.

胃癌（GC）是一种死亡率高、预后不良的严重恶性肿瘤。对于晚期胃癌（AGC），其预后和生存率尤为恶劣。近年来，免疫疗法在AGC患者中得到了广泛推广，研究表明肿瘤突变负荷（TMB）与免疫疗法反应密切相关。在本研究中，我们从TCGA数据库的TCGA-STAD项目中下载了RNA-seq数据、匹配的临床信息和MAF文件。利用R语言的“maftools”包进行了突变数据的整理和可视化分析。我们计算了AGC患者的TMB值，并根据TMB的中位数将患者分为高TMB组和低TMB组。然后，我们计算了高或低TMB与临床病理参数之间的相关性。接下来，我们使用“limma”R包检查了两组间基因表达模式的差异，并在差异表达基因（DEGs）中识别了免疫相关基因。通过单变量Cox回归分析，获得了与预后相关的15个基因。此外，利用两个枢纽基因（APOD和SLC22A17）构建了一个风险模型，以评估AGC患者的预后。ROC曲线、生存曲线和GEO数据作为验证集，以验证该风险模型的可靠性。此外，还考察了TMB与肿瘤浸润免疫细胞之间的相关性。总之，我们的研究结果表明，高TMB的AGC患者预后较好。通过检测患者的TMB，我们可以更好地指导免疫疗法，并理解患者对免疫疗法的反应。