Construction and validation of risk models of prognostic genes associated with parthanatos in papillary thyroid carcinoma based on bioinformatics

Abstract Object: This study aimed to elucidate the role of parthanatos-related genes (PRGs) in papillary thyroid carcinoma (PTC) and construct a prognostic risk model to guide personalized treatment. Methods: Using the GSE33630 dataset, differentially expressed PRGs were identified and analyzed via weighted gene co-expression network analysis (WGCNA) to pinpoint key module genes. Regression analysis selected seven prognostic genes for risk model construction. The model’s performance was validated, and a nomogram was developed for survival prediction. Further analyses included clinical feature