Cellular and Molecular Biomarkers to Predict Immunotherapy Outcomes in Melanoma Patients

Melanoma remains one of the deadliest skin cancers, despite accounting for only a small proportion of overall skin cancer diagnoses. Although immune checkpoint inhibitors (ICIs) have significantly improved outcomes in advanced melanoma, nearly half of all patients fail to respond, highlighting the urgent need for clinically actionable biomarkers. In this study, we leveraged single-cell RNA sequencing (scRNA-seq) data from a publicly available melanoma cohort to dissect the mechanisms driving therapeutic resistance. Our analyses revealed a prominent enrichment of macrophages in non-responders, prompting the development of a macrophage-focused gene signature that was strongly associated with poor overall survival across multiple independent datasets, including The Cancer Genome Atlas (TCGA). Importantly, this signature demonstrated high predictive accuracy (AUC = 0.896) for identifying patients unlikely to benefit from ICIs. Functional validation using an in vitro co-culture model showed that M2-polarized macrophages robustly suppressed T cell proliferation, reinforcing their immunosuppressive role in the tumor microenvironment. These findings offer immediate translational relevance: the macrophage-derived gene signature could be incorporated into clinical workflows to guide therapeutic decision-making, sparing patients the financial and physical burdens of ineffective treatment. Moreover, targeting the immunosuppressive M2 macrophage axis may open new avenues for combination therapies, ultimately paving the way for more personalized and cost-effective management of advanced melanoma.