Regulatory T cell-associated signature: predicting prognosis and immunotherapy in ovarian cancer

Abstract

Background Immunosuppression is a key feature of cancer, promoting tumor growth and progression. Regulatory T cells (Tregs) are a specialized subset of T lymphocytes that mediate immunosuppression in cancer. However, the role of Treg-related genes in ovarian cancer (OC) remains largely unexplored.Methods To identify marker genes related to Tregs in OC, we utilized scRNA-seq analysis. Treg scores were then constructed using single-sample gene set enrichment analysis (ssGSEA) based on these markers. To identify gene modules with the strongest correlation with Treg scores in bulk RNA-seq data, we employed the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm. Multiple machine learning algorithms were then used to construct risk models with superior predictive performance, which were validated using external independent datasets. A risk score was developed for each OC sample based on the optimal model to evaluate differences in prognosis, immune infiltration, pathway activity, and immunotherapy between high and low-risk groups.Results We identified 365 genes regulating Treg activity using the WGCNA algorithm, and found that 70 of these genes were associated with the prognosis of OC based on univariate cox analysis. Using a combination of the Random Survival Forest (RSF) and Lasso algorithms, we constructed a risk model with the highest c-index based on the assigned risk scores. The model's performance was validated using four external datasets. Our analysis revealed that the low-risk group had a better prognosis, more immune cell infiltration, higher immune checkpoint expression, and significant differences in pathway enrichment and immunotherapy efficacy between the different risk groups.Conclusion Our findings provide new insights into the role of Treg cells in the development and progression of OC and highlight the potential for developing novel Treg-targeted therapies for the treatment of this disease.