Single-cell profiling of immunogenic cell death in melanoma reveals prognostic signatures and therapeutic targets
Year: 2026
Type: article
Abstract: BACKGROUND: Cutaneous melanoma is one of the most aggressive forms of skin cancer, marked by rapid progression, early metastasis, and high resistance to conventional therapies. Although targeted therapies and immune checkpoint blockade have improved patient outcomes, many still relapse or fail to respond. This underscores the need for novel biomarkers to refine risk stratification and predict therapeutic responses. Immunogenic cell death (ICD) is a critical process linking tumor cell death to immune activation, which could enhance melanoma treatment responses. OBJECTIVE: This study investigates the role of ICD in melanoma by integrating bulk transcriptomic data with single-cell RNA sequencing (scRNA-seq) to develop a prognostic model based on ICD, and to explore its clinical relevance. METHODS: Bulk transcriptomic data were sourced from TCGA and GEO, while single-cell RNA-seq data were obtained from GSE215120. ICD-related genes were curated from the literature, and ICD scores were calculated using ssGSEA and GSVA. Machine learning algorithms were used to construct and validate a prognostic model. Immune infiltration and tumor microenvironment (TME) were analyzed to assess the relationship between ICD activity and immune responses. RESULTS: High ICD scores correlated with poor prognosis, and ICD activity was predominantly observed in stromal and myeloid cells. MYO10, identified as a key gene in the ICD signature, was associated with immune evasion and poor clinical outcomes. The ICD-based risk score (ICDRS) demonstrated superior prognostic power in multiple melanoma cohorts and reflected immune activation and TME characteristics. CONCLUSION: The ICDRS, incorporating MYO10, provides a robust prognostic tool for melanoma and highlights MYO10 as a potential therapeutic target for improving immune responses in melanoma therapy.
Source: Discover Oncology
Authors: Jingwen Huang, Taoxuan Jiang, Yiyang Han, Chunsheng Yang
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,690
OpenAlex ID: W7124431589
