Papillary thyroid carcinoma (PTC) is the main pathological subtype of thyroid cancer. Given the strong association between T cells and PTC, this study focused on the prognostic value and potential molecular mechanisms of T cell proliferation-related genes (TPRGs) in PTC. ScRNA-seq data were analyzed to identify key cells and subpopulations based on public databases. Candidate genes were determined by intersecting differentially expressed genes (DEGs) from differential expression analysis of key subpopulations, high- and low-TPRGs score groups, and bulk RNA-seq data. Prognostic genes were then determined via Cox regression and a machine learning algorithm. A risk model was formed. PTC patients were grouped into high-risk and low-risk groups by risk score. Subsequently, the immune microenvironment was analyzed. Finally, cell communication analysis and pseudotime analysis were accomplished. T/NK cells were selected as key cells. Moreover, CD4 memory cells were selected as the key subpopulation. Meanwhile, KLRB1, TSHZ2, and TRABD2A were spotted as prognostic genes. The risk model had better prognostic value. Additionally, 5 DICs were spotted in two risk groups. Besides, the scores of IPS-CTLA4 and PD-L1 blocker, IPS-CTLA4 blocker, and IPS-PD-1 blocker were lower in the HRG group. In addition, the most substantial receptor-ligand interaction in T/NK cells was found to be CLEC2C-KLRB1. Moreover, as T/NK cells differentiated, the expression level of KLRB1 was observed to rise slowly at first and then decline rapidly. KLRB1, TSHZ2, and TRABD2A were spotted as prognostic genes, providing new PTC prognosis and treatment strategies.