Stratification From Heterogeneity of the Cell-Death Signal Enables Prognosis Prediction and Immune Microenvironment Characterization in Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is the primary subtype of esophageal cancer (EC) characterized by a high incidence rate and extremely poor prognosis worldwide. Previous studies suggested that the specific cell death signal was linked to different immune subtypes in multiple cancers, while a comprehensive investigation on ESCC is to be performed yet. In the current study, we dissected different cell death signals in ESCC tumors and then integrated that functional information to stratify ESCC patients into different immunogenic cell death (ICD) subtypes. By systematically analyzing the transcriptomes of 857 patients and proteomic profile of 124 patients, we found that the signals of necroptosis, pyroptosis, and ferroptosis are positively associated with activated immunity in ESCC. We identified two ICD pattern terms, namely, ICD-high and ICD-low subtypes that positively correlated to both progression-free survival and overall survival. In addition, cell fraction deconvolution analysis revealed that more infiltrated leukocytes were enriched in ICD-high types, especially antigen-presenting cells, such as dendritic cells and macrophages. With the XGBoost algorithm, we further developed a 14-gene signature which can simplify the subtyping for allocating new samples, by which we validated the prognosis value of the signature and proved that the ICD score scheme could serve as a promising biomarker for stratifying patients with immunotherapy in several immune checkpoint blockade treatment cohorts. Collectively, we successfully constructed the ICD scheme, which enables predicting of the prognosis or immunotherapy efficacy in ESCC patients and uncovered the critical interplay between cell death signals and immune status in ESCC.