背景 免疫检查点抑制剂（ICI）疗法在恶性肿瘤的治疗中引起了广泛关注。本研究旨在基于免疫相关基因构建一种食管腺癌（EAC）的预后模型。 材料和方法 对癌症基因组图谱数据库中EAC与正常样本之间的免疫相关差异表达基因（IRDEGs）进行了分析。使用单变量和多变量Cox回归分析法确定预后性IRDEGs，并构建一个与免疫相关的基因签名（IRGS）以预测EAC患者的总体生存（OS）。然后，综合分析了分子机制和免疫特征。 结果 从加权基因共表达网络分析中获得了111个IRDEGs。单变量Cox回归分析显示12个IRDEGs（对所有P<0.05）与EAC患者的OS相关。根据多变量Cox回归分析，选取4个基因构建了IRGS。高风险组患者的OS较低风险组患者差（P<0.001）。高风险评分与DNA复制相关途径、突变率增加以及活化肥大细胞浸润增加相关。高风险评分患者的肿瘤免疫功能障碍和排除评分较低（P<0.001）。 结论 IRDEGs可能参与了EAC的进展。高风险组更适合免疫治疗，这可能为临床EAC患者的治疗提供参考。因此，可能可以确定更适合ICI治疗的患者。

BACKGROUND Immune checkpoint inhibitor (ICI) therapy has attracted wide attention in the treatment of malignant tumors. This study was designed to build a prognostic model based on immune-related genes for esophageal adenocarcinoma (EAC). MATERIAL AND METHODS The expression of immune-related differentially-expressed genes (IRDEGs) between EAC and normal samples from The Cancer Genome Atlas database was analyzed. Univariate and multivariate Cox regressions were used to identify the prognostic IRDEGs and construct an immune-related gene signature (IRGS) to predict the overall survival (OS) of EAC patients. Then, the molecular mechanisms and immune characteristics were comprehensively analyzed. RESULTS A total of 111 IRDEGs were obtained from the weighted gene co-expression network analysis. Univariate Cox regression analysis showed that 12 IRDEGs (P<0.05 for all) were linked with OS in the EAC patients. Four genes were used to construct the IRGS based on the multivariate Cox regression analysis. Patients in the high-risk group showed worse OS than those in the low-risk group (P<0.001). A high-risk score was related to DNA replication relevant pathways, an increase in mutation rate, and an increase in activated mast cell infiltration. Patients with high-risk scores had lower tumor immune dysfunction and exclusion scores (P<0.001). CONCLUSIONS IRDEGs may be involved in the progression of EAC. The high-risk group is more suitable for immunotherapy, which may provide a reference value for the treatment of clinical EAC patients. Therefore, it is possible to identify the patients who are better suited for ICI therapy.