Prognostic and Immunotherapeutic Value of Regulatory T Cell Marker Gene Signature in Melanoma

Yurong  Liu; Jianlan  Liu; Keyu  Jiang; Xiaolong  Cheng; Jian  Tang; Binlin  Luo

doi:10.18502/ijaai.v24i2.18150

Yurong Liu The First Clinical Medical College, Nanjing Medical University, Nanjing, China
Jianlan Liu Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
Keyu Jiang Department of Plastic and Burns Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
Xiaolong Cheng Department of Plastic and Burns Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
Jian Tang Department of Plastic and Burns Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
Binlin Luo Department of Plastic and Burns Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China

DOI: https://doi.org/10.18502/ijaai.v24i2.18150

Keywords: : Immunotherapy; Melanoma; Regulatory T cell; Single cell sequencing; Tumor microenvironment

Abstract

Regulatory T cells (Tregs) are central to establishing an immunosuppressive tumor microenvironment (TME), which promotes cancer progression and influences therapeutic outcomes. However, the prognostic significance of Treg-related genes (TRGs) in predicting immunotherapy response in melanoma remains insufficiently characterized. This study seeks to elucidate the role of TRGs in the antitumor immune response of melanoma.

The ordinary transcriptome and single-cell RNA sequencing (scRNA-seq) data were obtained from the gene expression omnibus and the cancer genome atlas databases. A multi-tiered quality control process was applied to scRNA-seq data, followed by cell annotation, cell-cell communication, and enrichment analysis to investigate Treg function in the melanoma microenvironment. Weighted gene coexpression network analysis (WGCNA) was employed to identify modules associated with Treg infiltration.

Key prognostic genes were identified using univariate Cox regression analysis and integrated into a prognostic model through least absolute shrinkage and selection operator and stepwise regression methods. The analysis revealed a Treg-related gene signature (TRGS) comprising CHD3, FOSB, SEMA4D, PSME1, FYN, PRKACB, and ARID5A. Higher TRGS-based risk scores were significantly associated with worse prognoses, immune cell infiltration, and stromal scores.

TRGS was identified as an independent prognostic indicator for melanoma, offering novel insights into the role of Tregs in modulating the TME. This study highlights the potential clinical utility of TRGs in melanoma diagnostics and personalized immunotherapy, providing a robust foundation for future therapeutic strategies.