EARLY DIAGNOSIS OF OVARIAN CANCER: CURRENT CHALLENGES AND THE ROLE OF EMERGING BIOMARKERS

Resumo

Introduction: Ovarian cancer is one of the most lethal gynecological cancers worldwide, primarily due to its often late diagnosis, the silent progression of the disease, and the nonspecific nature of early symptoms—factors that make it difficult to detect in the early stages and significantly compromise patient prognosis. Although methods such as transvaginal ultrasound and serum CA-125 testing are widely used, they still have significant limitations regarding sensitivity and specificity, especially in population-based screening. In this context, research into emerging biomarkers emerges as a promising strategy to improve diagnostic accuracy and facilitate earlier interventions. Objective: to analyze the main current challenges related to the early identification of ovarian cancer, with an emphasis on the role of emerging biomarkers as promising tools for improving diagnostic accuracy, risk stratification, and patient prognosis. Methodology: This is an integrative literature review of a descriptive, exploratory, and qualitative nature, conducted through searches in the PubMed/MEDLINE, Scopus, Web of Science, SciELO, and Virtual Health Library (VHL) databases, using DeCS and MeSH descriptors related to the topic, such as “Ovarian Cancer,” “Early Diagnosis,” “Biomarkers,” “Tumor Markers,” “Screening,” and “Precision Medicine,” combined using the Boolean operators AND and OR. Studies published between 2020 and 2026, available in full in Portuguese, English, and Spanish, that addressed early diagnosis, traditional and emerging biomarkers, and screening strategies were included. Results and Discussion: The studies showed that CA-125, although still widely used, has low specificity when used alone, especially in the early stages of the disease. In contrast, biomarkers such as HE4, the ROMA algorithm, liquid biopsy, exosomal microRNAs, circulating tumor DNA, epigenetic biomarkers, and multi-omic approaches demonstrated higher diagnostic sensitivity and better predictive capacity. The combination of multiple biomarkers has shown superior performance compared to traditional methods used in isolation. Furthermore, it has been observed that the incorporation of technologies such as artificial intelligence and precision medicine has significantly expanded the identification of new biomarkers and individualized risk stratification, facilitating earlier diagnoses and more effective therapeutic interventions. However, challenges remain regarding large-scale clinical validation, methodological standardization, high costs, and limited access to these tools in public health systems. Conclusion: it is concluded that emerging biomarkers associated with new diagnostic technologies represent an important advancement in the fight against ovarian cancer, with the potential to reduce morbidity and mortality and improve patient survival. Despite these advances, the consolidation of these strategies depends on the expansion of multicenter studies, economic feasibility, and the incorporation of these tools into clinical practice, thereby strengthening a more preventive, personalized, and effective approach to oncology.