Identification of a novel immunogenic cell death-related classifier to predict prognosis and optimize precision treatment in hepatocellular carcinoma

Accumulating studies have highlighted the biological significance of immunogenic cell death (ICD) in cancer immunity. However, the influence of ICD on tumor microenvironment (TME) formation and immune response in Hepatocellular carcinoma (HCC) remains largely unexplored. In this study, we systematically analyzed the mRNA profiles of ICD-related genes in 1847 HCC patients and identified three molecular subtypes with significantly different immune features and prognostic stratification. A reliable risk model named ICD score was constructed via machine learning algorithms to assess the immunological status, therapeutic responses, and clinical outcomes of individual HCC patients. High ICD score indicated an immune-excluded TME phenotype, with lower anticancer immunity and shorter survival time. In contrast, low ICD score corresponded to abundant immune cell infiltration, high sensitivity to immunotherapy and a positive prognosis, indicating an "immune-hot" phenotype. Pan-cancer analysis further validated a negative association between ICD score and the immune cell infiltration levels. In conclusion, our findings revealed that the ICD score could serve as a robust prognostic biomarker to predict the benefits of immunotherapy and optimize the clinical decision-making of HCC patients.