In this study, whole genome differential methylation analysis, along with state‐of‐the‐art computational methods such as the recursive feature elimination technique and supervised/unsupervised machine learning models, was used to identify 38 epigenetic signature genes (ESGs) and four core‐ESGs (cg19933311: TRPC5; cg09651654: APOBEC1; cg27299712: PLEKHG5; cg03150409: WHSC1) in endometrial tumors from Black and White women, incorporating genetic ancestry estimation. This evidence concerns the gene APOBEC1 and endometrium neoplasm.