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.

Gastric cancer (GC) is one of the most common types of cancer and the second leading cause of cancer-associated mortality. Identification of novel biomarkers is critical to prolonging patient survival. MicroRNAs (miRNAs) proved to play diverse roles in the physiological and pathological state in cancers including GC. Herein we aimed at performing a meta-analysis on miRNA profiling studies that used microarray platforms. Relevant studies were retrieved from PubMed and GEO databases. We used the robust rank aggregation to perform the meta-analysis. Moreover, for meta-Signature miRNAs target genes, we performed pathway enrichment and GO molecular function enrichment analysis. A total of 19 upregulated miRNAs and seven downregulated miRNAs in GC samples were identified. However, only three upregulated and one downregulated miRNA reached statistical significance after multiple test correction. Here we showed that hsa-miR-21-5p, hsa-miR-93-5p, hsa-miR-25-3p, and hsa-miR-375 are differentially expressed in GC samples.