基于转录组数据筛选食管鳞状细胞癌（ESCC）中程序性细胞死亡（PCD）相关基因并探讨其临床价值。从ESCC转录组和TCGA数据库的临床数据中筛选差异表达的PCD基因（DEPCDGs）。对 ESCC 中的预后 DEPCDG 进行单变量 COX 和 LASSO COX 以开发预后模型。通过 ssGSEA 和 CIBERSORT 确定不同 RiskScore 组中免疫细胞浸润的差异。通过肿瘤免疫功能障碍和排除 (TIDE) 和 IMvigor210 队列探讨了 RiskScore 在免疫治疗反应中的作用。在 ESCC 中挖掘了 14 个与预后相关的 DEPCDG。这些 DEPCDG 形成了一个具有良好预后预测性能的 RiskScore。 RiskScore 在三个数据集中表现出了出色的预测准确性。高RiskScore组中M2巨噬细胞和Tregs的丰度较高，而低RiskScore组中M1巨噬细胞的丰度较高。 RiskScore 还显示出良好的免疫治疗敏感性。 RT-qPCR分析显示AUP1、BCAP31、DYRK2、TAF9和UBQLN2在KYSE-150细胞中表达较高。敲低 BCAP31 可抑制迁移和侵袭。预后风险模型可以预测 ESCC 的预后，并可能成为风险分层和免疫治疗评估的有用生物标志物。

To screen programmed cell death (PCD)-related genes in esophageal squamous cell carcinoma (ESCC) based on transcriptomic data and to explore its clinical value.Differentially expressed PCD genes (DEPCDGs) were screened from ESCC transcriptome and clinical data in TCGA database. Univariate COX and LASSO COX were performed to on prognostically DEPCDGs in ESCC to develop prognostic model. Differences in immune cell infiltration in different RiskScore groups were determined by ssGSEA and CIBERSORT. The role of RiskScore in immunotherapy response was explored by Tumor Immune Dysfunction and Exclusion (TIDE) and IMvigor210 cohorts.14 DEPCDGs associated with prognosis were tapped in ESCC. These DEPCDGs form a RiskScore with good predictive performance for prognosis. RiskScore demonstrated excellent prediction accuracy in three data sets. The abundance of M2 macrophages and Tregs was higher in the high RiskScore group, and the abundance of M1 macrophages was higher in the low RiskScore group. The RiskScore also showed good immunotherapy sensitivity. RT-qPCR analysis showed that AUP1, BCAP31, DYRK2, TAF9 and UBQLN2 were higher expression in KYSE-150 cells. Knockdown BCAP31 inhibited migration and invasion.A prognostic risk model can predict prognosis of ESCC and may be a useful biomarker for risk stratification and immunotherapy assessment.