Cuproptosis is a kind of programmed cell death in which copper reacts with the cycloaliphatic component of the tricarboxylic acid (TCA) cycle. In this study, we devised a predictive model and a theoretical framework to examine the variations in the expression of the cuproptosis-related genes (CRGs) in ovarian cancer. Through screening the 11 CRGs, all samples were segmented into two risk groups and a prognostic model was built. Among the 11 CRGs, 10 genes showed a significant relationship with survival probability, demonstrating the model had good prediction ability and high accuracy. Age and FIGO stage were discovered to be strongly correlated with patient survival time by means of univariate Cox regression analysis. The patients over 65 in FIGO stages IIIA-IV had an increased risk. The enrichment analysis showed that the main metabolic pathways were those related to drug metabolism, tissue development, tyrosine metabolism and retinol metabolism. The PPI networks revealed that CDKN2A was the key gene. Finally, the in vitro and in vivo functional assays demonstrated that cuproptosis induced by CuET agent treatment could significantly inhibit ovarian cancer cell viability, migration and invasion as well as xenografted tumor growth where the CDKN2A expression level increased. Our results indicate that the comprehensive definition of differentially expressed CRGs in ovarian cancer will provide new insights for clinical remedy of ovarian cancer.