免疫原性细胞死亡（ICD）可诱导抗肿瘤免疫反应，有助于瓦解免疫压抑型肿瘤微环境（TME），属于一种规管的细胞死亡方式。由于胃癌（GC）是一种高度异质性且具有侵袭性的疾病，因此胃癌亚型的分化和预后生物标志物的发现对其治疗至关重要。但是，尽管诱导肿瘤细胞的ICD与良好的预后相关，但其在GC中的作用机制仍不清楚。我们从癌症基因组图谱（TCGA）数据库中检索了GC患者的转录组分析数据和临床数据。在此基础上，采用一致性聚类算法对患者进行分类，并根据ICD相关基因的表达探索相关生物学功能和免疫微环境浸润。通过最小绝对收缩和选择算子回归（LASSO）方法建立了由11个ICD相关基因组成的风险评分签名。我们检索了近年来的类似研究，并使用时间相关的接收者操作特征曲线（ROC）进行比较。通过基因集变异分析（GSVA）和单样本基因集富集分析（ssGSEA），探究了该签名与肿瘤微环境（TME）之间的关联。在GC中鉴定了与ICD相关的两个不同亚型，每个亚型具有不同的预后。ICD高表达亚型与更高的免疫细胞浸润和更好的预后相关。包含11个基因（CGB5、Z84468.1、APOA5、EPHA8、CLEC18C、TLR7、MUC7、MUC15、CTLA4、CALB2和UGT2B28）的ICD相关基因签名可以独立且准确地预测GC的预后。本研究进行了基于ICD的分类以辅助GC的诊断和个体化治疗，并建立了ICD相关基因风险评分模型来预测预后。 © 2023作者，独家授权Springer Science+Business Media，LLC，属于Springer Nature。

Immunogenic cell death (ICD) induces anti-tumor immunity and aids in dismantling the immunosuppressive immune microenvironment (TME), which belongs to a type of regulated cell death. The differentiation of gastric cancer (GC) subtypes and the discovery of prognostic biomarkers are crucial for its treatment because GC is a disease that is both highly heterogeneous and aggressive. However, although the induction of ICD in tumor cells is associated with a favorable prognosis, the exact mechanism of its role in GC remains unclear. Transcriptome profiling data and clinical data of GC patients were retrieved from The Cancer Genome Atlas (TCGA) database. Herein, patients were classified with the consensus clustering algorithm, and the associated biological functions and immune microenvironment infiltration were explored based on the expression of ICD-associated genes. A risk score signature consisting of 11 ICD-related genes was established via the least absolute shrinkage and selection operator regression (LASSO) method. We have retrieved similar studies in recent years and compared them with our study using the time-dependent receiver operating characteristic (ROC) curves. Gene set variation analysis (GSVA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore the association between the signature and tumor microenvironment (TME). Two distinct subtypes associated with ICD in GC were identified, each with a different prognosis. The ICD-high expression subtype was associated with higher immune cell infiltration and a better prognosis. The ICD-related gene signature containing 11 genes (CGB5, Z84468.1, APOA5, EPHA8, CLEC18C, TLR7, MUC7, MUC15, CTLA4, CALB2, and UGT2B28), could independently and accurately predict the prognosis of GC. In this study, an ICD-based classification was conducted to assist in the diagnosis and personalized therapy for GC. The ICD-related genes risk score model was established to predict prognosis.© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.