Identification of Selenium Metabolism Related Prognostic Genes in Ovarian Cancer and Experimental Validation

Background Selenium and its derivatives have been recognized for their significant role in ovarian cancer (OV). Therefore, this study aims to identify prognostic genes linked to selenium metabolism and assess their influence on survival outcomes in OV. Methods This study used bioinformatics to identify prognostic genes in OV and construct a risk model and nomogram for survival prediction. Gene expression was validated in control and OV cell lines by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western blot, while single-cell analysis identified key cell types and tracked gene expression during differentiation. Results ITGB8, LPAR3, ECI2, GRB7, SPOCK2, PPL, UNC5B, and GALNT6 were recognized as prognostic genes associated with selenium metabolism in OV. A prognostic model was established, indicating that OV patients in low risk category experienced extended survival outcomes. Furthermore, a nomogram integrating risk score and stage exhibited predictive capability for OV survival. ECI2 and UNC5B demonstrated markedly decreased expression, whilst remaining prognostic genes were dramatically increased in OV cells. Nine cell types were annotated, with smooth muscle cells (SMCs) recognized as key cells, displaying elevated scores for selenium metabolism-related genes. Pseudotime analysis revealed that ECI2 expressed in SMC differentiation early and late stages. Conclusion This study identified eight prognostic genes related to selenium metabolism and developed a prognostic model for OV, offering a novel tool for assessing survival prognosis in OV.