Recent advances in the early detection of ovarian cancer

Abstract

Ovarian cancer (OC), predominantly epithelial OC, remains the most lethal gynecological malignancy. Owing to its often asymptomatic or non-specific clinical presentation, approximately 70 % of patients are diagnosed at advanced stages (FIGO III–IV), typically characterized by extensive peritoneal dissemination. Although early detection is critical for improving survival outcomes, current standard diagnostic modalities, including serum CA125 and transvaginal ultrasound, lack sufficient sensitivity and specificity for population-level screening of early-stage disease. This review comprehensively evaluates emerging biomarkers and advanced diagnostic technologies, with a particular focus on liquid biopsy analytes, including circulating tumor DNA, microRNAs, and uterine liquid biopsies. We further discuss the clinical utility of multi-biomarker panels and artificial intelligence (AI)-driven models that integrate genomic, proteomic, and radiomic data, while highlighting their current performance limitations and stage-dependent diagnostic accuracy. Despite the considerable potential of liquid biopsies and AI-based approaches, challenges related to assay standardization and the need for large-scale prospective validation remain major barriers to widespread clinical implementation. Overall, this review underscores the need for robust, multimodal diagnostic strategies that may enable earlier detection and ultimately reduce OC-associated mortality.