Development and validation of immunogenic cell death-applied prediction model for esophageal carcinoma

Evidence suggests that immunogenic cell death (ICD) releases cancer antigens that promote cytotoxic T-cell responses, potentially improving immunotherapy. However, the relationship between ICDs and esophageal cancer (EC) remains unclear. This study aimed to determine the role of ICDs in EC and to construct an ICD-based prognostic panel. RNA-seq data of EC and the corresponding clinical information were downloaded from the UCSC-Xena platform to explore the association between ICD gene expression and EC prognosis. The GSE53625 dataset was used to validate the proposed model. Differentially expressed genes (DEGs) between different molecular subtypes were identified to construct a new ICD-related prognosis panel and generate molecular subtypes using ConsensusClusterPlus. We created a prognostic profile based on the ICD and a nomogram based on the risk score. Compared with normal samples, ICD gene expression of malignant samples were significantly increased. 161 patients with EC were successfully divided into three subtypes (SubA, SubB, and SubC). Patients with EC in the SubC group had the best survival and lowest ICD score, whereas patients in the SubB group had the worst prognosis. DEGs between subtypes were evaluated, and risk panels were established using LASSO-Cox regression analysis. The prognosis of low-risk patients was significantly better than that of high-risk patients in both cohorts. The area under the curve of the receiver operating characteristic curve indicated that the risk group had a good prognostic value. Our study identified the molecular subtypes of EC and ICD-based prognostic signatures. Our three-gene risk panel could serve as a biomarker for effectively assessing the prognostic risk of patients with EC.