Background and objective Melanoma exhibits profound biological complexity, driven by immune evasion, phenotypic plasticity, and resistance to therapy. While programmed cell death (PCD) shapes tumor–immune interactions, its mechanistic landscape in melanoma remains incompletely defined. This study aims to comprehensively characterize PCD-related signatures and their associations with tumor heterogeneity, prognosis, and immunotherapeutic outcomes. Methods Single-cell RNA sequencing data from melanoma cohorts (cutaneous and acral subtypes) were used to assess PCD activity via AUCell-based scoring across major cell types. Cell-type–specific analyses examined heterogeneity, metabolic dependencies, and pathway correlations. Intercellular communication was analyzed using CellChat. Bulk RNA sequencing data were then integrated to identify PCD-related gene signatures, and machine learning models (LASSO, Ridge, XGBoost) were applied to develop a prognostic model. Immune infiltration, immunogenomic correlations, and immunotherapy responses were further evaluated using ESTIMATE, CIBERSORT, TMB, IPS, and external ICB-treated cohorts. Results Among all cell types, melanoma cells exhibited the highest PCD activation, with disulfidptosis, immunogenic cell death (ICD), and autosis being the most prominent. High PCD activity was linked to advanced clinical stage, lymphatic metastasis, and poor prognosis. Melanoma subpopulations with hyperactivated PCD displayed elevated copy number variation (CNV) burden, enhanced fibroblast/endothelial interactions, and invasive transcriptional profiles. A 15-gene prognostic signature was developed, effectively stratifying survival and immunotherapy response across multiple cohorts. Low-risk tumors demonstrated favorable immune infiltration (CD8 + T cells, M1 macrophages), higher tumor mutational burden (TMB), and greater immunogenicity, while high-risk tumors exhibited immune exclusion, cancer-associated fibroblast (CAF) enrichment, and adverse mutations. Conclusion This study highlights the functional and clinical significance of PCD heterogeneity in melanoma and provides a validated prognostic model for patient stratification and therapeutic decision-making. These findings underscore the potential of targeting PCD dynamics as a novel approach in melanoma management.
Hu et al. (Wed,) studied this question.