Table_3_The Pyroptosis-Related Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Gastric Cancer.XLSX

Gastric cancer (GC) is one of the leading causes of cancer-related deaths and shows high levels of heterogeneity. The development of a specific prognostic model is important if we are to improve treatment strategies. Pyroptosis can arise in response to H. pylori, a primary carcinogen, and also in response to chemotherapy drugs. However, the prognostic evaluation of GC to pyroptosis is insufficient. Consensus clustering by pyroptosis-related regulators was used to classify 618 patients with GC from four GEO cohorts. Following Cox regression with differentially expressed genes, our prognosis model (PS-score) was built by LASSO-Cox analysis. The TCGA-STAD cohort was used as the validation set. ESTIMATE, CIBERSORTx, and EPIC were used to investigate the tumor microenvironment (TME). Immunotherapy cohorts by blocking PD1/PD-L1 were used to investigate the treatment response. The subtyping of GC based on pyroptosis-related regulators was able to classify patients according to different clinical traits and TME. The difference between the two subtypes identified in this study was used to develop a prognosis model which we named “PS-score.” The PS-score could predict the prognosis of patients with GC and his/her overall survival time. A low PS-score implies greater inflammatory cell infiltration and better response of immunotherapy by PD1/PD-L1 blockers. Our findings provide a foundation for future research targeting pyroptosis and its immune microenvironment to improve prognosis and responses to immunotherapy.

胃癌（GC）是癌症相关死亡的主要病因之一，且具有显著的异质性。若要优化临床治疗策略，构建特异性预后模型具有重要意义。细胞焦亡既可由主要致癌病原体幽门螺杆菌（H. pylori）诱导产生，也可在化疗药物作用下发生。但目前针对胃癌细胞焦亡相关的预后评估仍较为匮乏。本研究借助细胞焦亡相关调控因子开展一致性聚类，对来自4个GEO队列的618例胃癌患者进行分型。随后基于差异表达基因进行Cox回归分析，通过LASSO-Cox分析构建了预后模型（PS-score），并以TCGA-STAD队列作为模型验证集。采用ESTIMATE、CIBERSORTx及EPIC算法对肿瘤微环境（TME）进行分析，同时利用程序性死亡受体1/程序性死亡受体配体1（PD1/PD-L1）阻断免疫治疗队列探究患者的治疗响应情况。基于细胞焦亡相关调控因子的胃癌分型，能够依据不同临床特征与肿瘤微环境特征对患者进行分类。本研究基于鉴定得到的两种亚型间的差异构建了预后模型，将其命名为“PS-score”，该模型可有效预测胃癌患者的预后及总生存时长。PS-score分值较低的患者，其炎性细胞浸润程度更高，且对PD1/PD-L1阻断剂的免疫治疗响应更佳。本研究结果为未来以细胞焦亡及其免疫微环境为靶点，改善胃癌患者预后及免疫治疗响应的相关研究提供了理论基础。