Mining Nicotinamide Metabolism Related Genes in Endometrial Cancer Based on TCGA Database and Constructing Prognostic Models

The uploaded content constitutes the original dataset utilized in our study titled “Mining Nicotinamide Metabolism-Related Genes in Endometrial Cancer Based on the TCGA Database and Construction of Prognostic Models.” It includes downloaded data, processed analytical data, and the scripts used for analyses based on the TCGA and GEO databases. The dataset is organized in accordance with the sequence of figures presented in the manuscript. In uterine corpus endometrial carcinoma (UCEC), lymph node metastasis occurs frequently and substantially affects patient prognosis. Therefore, identifying novel biomarkers to improve prognostic evaluation and guide therapeutic decision-making is of great clinical importance. In this study, UCEC data from The Cancer Genome Atlas (TCGA) were analyzed and validated using the Gene Expression Omnibus (GEO) database. Eighteen nicotinamide metabolism-related differentially expressed genes (NMRDEGs) were identified. Subsequent univariate Cox regression analysis revealed six key prognostic genes—AURKA, CDKN3, FOXM1, CDKN2A, TK1, and CDK1—which were used to construct a risk prediction model. Furthermore, protein–protein interaction (PPI) analysis identified additional core regulatory genes, including CDK2, CCNA2, TP53, and FOXM1. This work represents the first systematic investigation of the prognostic significance of nicotinamide metabolism-related genes in endometrial cancer. It enhances current understanding of the disease’s metabolic mechanisms and provides a theoretical foundation and potential molecular targets for developing novel therapeutic strategies and personalized medicine.