Enhanced expression of HLA-DR and CD69 on peripheral CD4 + T cells predicts better clinical outcomes in cutaneous melanoma

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Abstract Background Cutaneous melanoma (CM) is an aggressive skin cancer with rising incidence, representing a growing public health concern. Despite the remarkable success of immune-checkpoint inhibitors (ICIs) in the management of advanced disease, mortality remains high due to therapy resistance. Identifying reliable prognostic and predictive biomarkers is therefore essential to improve patient stratification, optimize treatment selection, and minimize unnecessary toxicity. Methods We comprehensively profiled the circulating immune landscape of 54 treatment-naïve CM patients by integrating flow cytometry immunophenotyping with clinicopathological data, and performed tumor gene expression analysis in a subset of 26 patients. Results Elevated HLA-DR and CD69 expression on circulating CD4 + T cells, together with reduced circulating CD8 + T cell frequency, emerged as candidate prognostic biomarkers associated with improved survival. Prognostic models combining these immune variables with clinical covariates accurately stratified patients by overall survival (89.5% sensitivity, 72.7% specificity; AUC = 0.872, p < 0.0001) and progression/recurrence risk (75% sensitivity and 71.4% specificity; AUC = 0.763, p = 0.001). In a subset of 43 patients subsequently treated with ICIs, elevated baseline HLA-DR and CD69 expression on circulating CD4 + T cells was also associated with therapeutic benefit. A predictive model integrating these markers with clinical covariates achieved good discriminatory performance (65.2% sensitivity, 88.9% specificity; AUC = 0.775, p = 0.0027). Tumor gene expression profiling supported the role of IFN-γ-related signatures, previously linked to ICI response, as complementary prognostic and predictive tools. Conclusion These findings highlight systemic CD4 + T cell activation status as a promising, easily measurable biomarker in CM, laying the foundation for future strategies to refine patient stratification and guiding immunotherapy decisions.

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