Abstract
The age of the patients at diagnosis (age at diagnosis) is a self-contained element of danger for the prognosis of patients with papillary thyroid carcinoma (PTC), which has been well recognized and continuously adopted by the international cancer staging system. However, few studies have investigated its intrinsic mechanisms. In this study, we aim to comprehensively reveal the age-related pathogenesis of PTC and identify potential prognostic biomarkers. We divided the samples into two groups, young and elderly, to filter differentially expressed genes in The Cancer Genome Atlas (TCGA), with an age of 55 years serving as a cutoff. Moreover, we combined univariate, LASSO, and multivariate Cox regression analyses to construct age-related signatures for predicting progression-free survival. Additionally, functional enrichment analysis, immune infiltration analysis, differential expression analysis, clinicopathological correlation analysis, and drug sensitivity analysis were performed in different risk subgroups and expression subgroups. We screened 88 upregulated genes and 58 downregulated genes. Both the LASSO regression model that is validated in TCGA and the model of six age-related prognostic genes (IGF2BP1, GPRC6A, IL37, CRCT1, SEMG1, and PSG7) can be used to evaluate the progression-free survival of PTC patients. The GO, KEGG, and GSEA analyses revealed that each key gene was closely associated with PTC development. Furthermore, CD8(+) T cells decreased significantly, while regulatory T cells increased dramatically in the high-risk and PSG7 high expression groups. PSG7 was remarkably correlated with clinicopathological parameters (pathologic stage, T stage, and N stage) of PTC patients, and PSG7 expression was elevated in tumor samples from both TCGA and the Gene Expression Omnibus and was strongly associated with progressive stage and poor prognosis. Our results provide an innovative understanding of the age-related molecular mechanisms of PTC development. PSG7 was identified to exert a critical role in PTC progression and may serve as a promising strategy for predicting the prognosis of PTC.