Table_4_Establishment and Analysis of an Individualized Immune-Related Gene Signature for the Prognosis of Gastric Cancer.XLSX

A growing number of studies have shown that immunity plays an important clinical role in the process of gastric cancer (GC). The purpose of this study was to explore the function of differentially expressed immune-related genes (DEIRGs) of GC, and construct a gene signature to predict the overall survival (OS) of patients. Gene expression profiles and clinical data of GC patients were downloaded from TCGA and GEO databases. Combined with immune-related genes (IRGs) downloaded from the ImmPort database, 357 DEIRGs in GC tissues and adjacent tissues were identified. Based on the analysis of Lasso and Cox in the training set, a prognostic risk scoring model consisting of 9 (RBP7, DES, CCR1, PNOC, SPP1, VIP, TNFRSF12A, TUBB3, PRKCG) DEIRGs was obtained. Functional analysis revealed that model genes may participate in the formation and development of tumor cells by affecting the function of cell gap junction intercellular communication (GJJC). According to the model score, the samples were divided into high-risk and low-risk groups. In multivariate Cox regression analysis, the risk score was an independent prognostic factor (HR = 1.674, 95% CI = 1.470–1.907, P < 0.001). Survival analysis showed that the OS of high-risk GC patients was significantly lower than that of low-risk GC patients (P < 0.001). The area under the receiver operating characteristic curve (ROC) of the model was greater than other clinical indicators when verified in various data sets, confirming that the prediction model has a reliable accuracy. In conclusion, this study has explored the biological functions of DEIRGs in GC and discovered novel gene targets for the treatment of GC. The constructed prognostic gene signature is helpful for clinicians to determine the prognosis of GC patients and formulate personalized treatment plans.

众多研究逐渐揭示，免疫机制在胃癌（GC）的进程 中扮演着至关重要的临床角色。本研究旨在深入探讨胃癌中差异表达的免疫相关基因（DEIRGs）的功能，并构建一个基因特征，以预测患者的总生存期（OS）。通过从TCGA和GEO数据库中下载胃癌患者的基因表达谱和临床数据，并结合从ImmPort数据库中下载的免疫相关基因（IRGs），我们确定了胃癌组织和相邻组织中存在的357个DEIRGs。基于训练集中的Lasso和Cox分析，获得了一个包含9个DEIRGs（RBP7、DES、CCR1、PNOC、SPP1、VIP、TNFRSF12A、TUBB3、PRKCG）的预后风险评估模型。功能分析表明，这些模型基因可能通过影响细胞间隙连接的细胞间通讯（GJJC）功能，参与肿瘤细胞的形成与发展。根据模型评分，样本被分为高风险组和低风险组。在多因素Cox回归分析中，风险评分是一个独立的预后因素（HR = 1.674，95% CI = 1.470–1.907，P < 0.001）。生存分析显示，高风险胃癌患者的总生存期显著低于低风险患者（P < 0.001）。模型在多个数据集中的验证结果表明，其受试者工作特征曲线（ROC）下的面积大于其他临床指标，证实了预测模型的可靠准确性。综上所述，本研究深入探讨了胃癌中DEIRGs的生物学功能，并发现了胃癌治疗的新基因靶点。构建的预后基因特征有助于临床医生确定胃癌患者的预后，并制定个性化的治疗方案。