Liquid Biopsy-Based Metabolomics in Epithelial Ovarian Cancer: Challenges, Methodological Advances and Translational Considerations

Epithelial ovarian cancers (EOCs) histotypes are characterized by marked molecular heterogeneity and limited effectiveness of current screening and monitoring strategies. Earlier identification of tumor-associated alterations may support timely intervention, especially in genetically predisposed or early-onset patient populations. While liquid biopsy approaches have primarily focused on circulating DNA, RNA, and proteins, increasing evidence indicates that cancer-associated metabolic reprogramming generates measurable informative signals in peripheral biofluids. This review summarizes recent progress in liquid biopsy-derived metabolomics in EOCs, covering analytical platforms applied to serum, plasma, urine, and ascites. Recurrent metabolic signatures linked to tumor burden, disease stage, treatment response, and clinical outcome are described, and their significance in discriminating malignant and non-malignant conditions is critically discussed. Collectively, these findings suggest that metabolomics may provide complementary functional information alongside genomic and histopathological profiling. Although its clinical implementation still requires further validation and methodological standardization, ongoing advances in analytical technologies and the integration of high-dimensional metabolic data into machine learning-based frameworks may progressively support the identification of early tumor-associated alterations and contribute to more accurate disease stratification and biologically informed clinical management.