Advances and challenges in the origin and evolution of ovarian cancer organoids - Zhang, Mengpei; Yin, Rutie; Li, Kemin (Frontiers in Oncology, 2024)
Despite advancements in cancer research, epithelial ovarian cancer remains a leading threat to women's health with a low five-year survival rate of 48%. Prognosis for advanced cases, especially International Federation of Gynecology and Obstetrics (FIGO) III-IV, is poor. Standard care includes surgical resection and platinum-based chemo, but 70-80% face recurrence and chemoresistance. In recent years, threedimensional (3D) cancer models, especially patients-derived organoids (PDOs), have revolutionized cancer research for personalized treatment. By transcending the constraints of conventional models, organoids accurately recapitulate crucial morphological, histological, and genetic characteristics of diseases, particularly in the context of ovarian cancer. The extensive potential of ovarian cancer organoids is explored, spanning from foundational theories to cutting-edge applications. As potent preclinical models, organoids offer invaluable tools for predicting patient treatment responses and guiding the development of personalized therapeutic strategies. Furthermore, in the arena of drug evaluation, organoids demonstrate their unique versatility as platforms, enabling comprehensive testing of innovative drug combinations and novel candidates, thereby pioneering new avenues in pharmaceutical research. Notably, organoids mimic the dynamic progression of ovarian cancer, from inception to systemic dissemination, shedding light on intricate and subtle disease mechanisms, and providing crucial insights. Operating at an individualized level, organoids also unravel the complex mechanisms underlying drug resistance, presenting strategic opportunities for the development of effective treatment strategies. This review summarizes the emerging role of ovarian cancer organoids, meticulously cultivated cellular clusters within three-dimensional models, as a groundbreaking paradigm in research.