Integrative Molecular and Immune Profiling in Advanced Unresectable Melanoma: Tumor Microenvironment and Peripheral...

Background/Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized advanced melanoma treatment, yet many patients fail to achieve sustained clinical benefit. Several biomarkers, including tumor microenvironment (TME) signature, PD-1/PD-L1 expression, and IFN-γ signaling, have been proposed. However, robust predictive markers remain elusive. This study aimed to identify molecular markers of response by analyzing tumor and peripheral immune signatures. Methods: This study analyzed 21 advanced melanoma patients treated with ICIs. Formalin-fixed, paraffin-embedded tumors underwent RNA-sequencing targeting 1392 immuno-oncology probes. Genes significantly associated with progression-free survival (PFS) by log-rank test underwent hierarchical clustering analysis (HCA). Differential expression and xCell analyses were then performed on the resulting clusters. Cox multivariate analysis was applied to identify independent PFS predictors. Pre-treatment peripheral blood mononuclear cells were analyzed by mass cytometry, followed by FlowSOM and UMAP clustering. Results: Fifty-five genes significantly associated with PFS identified two molecular clusters via HCA. Cluster A demonstrated prolonged PFS (59.4 vs. 2.4 months, p = 0.0004), while Cluster B was characterized by downregulated IFN-γ signaling, antigen presentation pathways, and reduced immune score. Multivariate Cox analysis confirmed molecular cluster as an independent PFS predictor (p < 0.001). Mass cytometry revealed higher frequencies of circulating PD-1+ CD4+ effector memory (EM) T subpopulations among responders. Conclusions: This study highlights the potential role of molecular and immune profiling in predicting ICI response in advanced melanoma. The identification of distinct molecular clusters underscores significant TME heterogeneity, with immune-cold tumor clusters associated with poorer outcomes. Furthermore, circulating PD-1+ T subpopulations emerged as potential markers of ICI response, suggesting their value in improving patient stratification.