Identification of the gene signatures related to NK/T cell communication to evaluate the tumor microenvironment and prognostic outcomes of patients with prostate adenocarcinoma.

Background: Prostate adenocarcinoma (PRAD) is a leading cause of male mortality, with NK/T cell communication being key areas of the research. Methods: The Seurat package was utilized to normalize and reduce the dimensionality of the single-cell data, and CellMarker 2.0 was employed for cell annotation. CellChat was utilized to construct the ligand-receptor interaction network of cell subsets. Differentially expressed genes (DEGs) were filtered by the limma package. Univariate Cox and the LASSO regression in the glmnet package were used to obtain biomarkers and develop a risk model. The survminer package was used to calculate the optimal threshold for dividing patients into high-risk and low-risk groups, and then Kaplan-Meier (KM) survival analysis was performed. Single-sample GSEA (ssGSEA), TIMER, and ESTIMATE packages were employed for immune infiltration analysis. Pathway analysis was conducted for the low- and high-risk groups using GSEA. Immunotherapy responses were evaluated by adopting TIDE method. Additional cellular validation (quantitative real-time PCR, CCK-8, Transwell, and scratch assay) was implemented to confirm the effects of feature genes on PRAD. Results: Compared with the benign group, NK/T cells were the cell type with the greatest changes in the tumor group, and their communication intensity was relatively high among all cell types. A RiskScore model was constructed as follows: Conclusion: The current research reveals key communication genes in PRAD, offering new possibilities for the exploration of new therapeutic targets.