table2_Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden.docx

Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).
Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.
Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4+ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.
Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

引言：胃癌是最常见的恶性肿瘤之一。尽管随着手术方式的改良与免疫治疗的应用，胃癌治疗已取得一定进展，但胃癌患者的预后仍不尽如人意。近年来，越来越多的研究证据表明，肿瘤突变负荷（Tumor mutational load, TMB）与患者的生存结局及免疫治疗响应程度密切相关。鉴于胃癌患者对免疫治疗的响应存在显著异质性，探究TMB的临床意义并挖掘适用于胃癌（GC）患者的预后生物标志物具有重要价值。

材料与方法：本研究所有胃癌患者数据均来源于癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库。根据TMB中位数将样本分为高TMB组与低TMB组。鉴定并进一步分析高、低TMB组间的差异表达基因（Differently expressed genes, DEGs）。通过套索（Lasso）回归、单因素及多因素Cox回归分析筛选与TMB相关的基因，并利用凯普兰-迈耶绘图器（Kaplan-Meier Plotter）验证11个核心基因的生存预后价值。此外，本研究采用"CIBERSORT"工具包估算肿瘤免疫浸润水平。

结果：单核苷酸变异（Single nucleotide variant, SNV）中最常见的变异类型为单核苷酸多态性（Single nucleotide polymorphism, SNP）的C>T转换。高TMB组胃癌患者的生存结局优于低TMB组。此外，本研究利用11个与TMB相关的差异表达基因构建了预后预测模型，该模型可作为独立风险因子用于预测胃癌患者的预后。进一步分析显示，相较于低TMB组，高TMB组中CD4+记忆活化T细胞、M0及M1巨噬细胞的浸润水平显著升高。

结论：本研究发现，高TMB胃癌患者拥有更优的生存结局。此外，更高的TMB水平可能促进肿瘤免疫浸润，这一发现可为胃癌免疫治疗提供全新的研究思路。