Abstract / Summary
Skin cutaneous melanoma (SKCM) is an aggressive malignancy with variable prognosis and response to immunotherapy. Regulatory T cells (Tregs) play a crucial role in immune suppression within the tumor microenvironment. However, the clinical significance of Treg-related genes in SKCM remains unclear. We constructed a Treg-related gene signature for SKCM using bulk RNA-seq data from TCGA and three GEO cohorts. Machine learning algorithms were employed to identify prognostic genes associated with Tregs, and a Lasso-Cox model was used to derive a Treg-score. The prognostic value of the Treg-score was validated across multiple cohorts. Associations between Treg-score, immune infiltration, immune escape, and response to immunotherapy were assessed in several independent datasets. Drug sensitivity was also predicted. In vitro, MCAM, a key Treg-related gene, was experimentally validated for its role in SKCM cell proliferation and metastasis. The Treg-score effectively stratified patients into high- and low-risk groups with distinct survival outcomes. High Treg-scores correlated with an immune-cold tumor microenvironment, characterized by lower immune cell infiltration and reduced response to immunotherapy. Conversely, low Treg-scores indicated an immune-hot phenotype and higher likelihood of responding to immunotherapy. Drug sensitivity analysis suggested high-risk patients may benefit from chemotherapy and targeted therapies. MCAM was confirmed as a functional driver of SKCM progression. We developed a Treg-related gene signature that predicts prognosis and is associated with immunotherapy benefit in SKCM. The Treg-score provides a valuable tool for risk stratification and personalized treatment decision-making in melanoma.