DOI: https://doi.org/10.36347/sasjm.2025.v11i12.005

Pages: 1154-1168

Ovarian cancer is among the deadliest gynecologic malignancies, primarily due to its asymptomatic onset and absence of endorsed population-level screening. Here, we overview the evidence on screening strategies and emerging biomarkers published from July 2021 to September 2025 that might contribute to increase the accuracy of detection. We conducted a systematic review of published and unpublished literature with searches in PubMed, Scopus, Embase, Web of Science, and Google Scholar for clinical trials, cohort studies, systematic reviews/meta-analyses and molecular biomarker studies. There is evidence to show that traditional markers, such as CA-125 and HE4 has limited sensitivity in early-stage disease although these are routine markers used in clinic. Innovative modalities such as circulating tumor DNA, exosomes microRNAs, epigenetic signatures, proteomic panels and metabolomic fingerprints as well as radiomics-based imaging biomarkers show a substantially increased performance. Multimarket algorithms involving machine-learning techniques with evidence to date appear most promising for early detection of HGSC. But limitations risks include heterogeneity across studies, small sample sizes, no cross-ethnic validation and variable analytic standards. Present readouts indicate that combining multi-omics biomarkers with artificial intelligence and risk-prediction models could indeed change ovarian cancer screening. There is an urgent need of large prospective trials for clinical translation. In summary, this review indicates the appearance of new evidence for some potentially likely biomarkers that could contribute to future diagnostic routes.