Patient-derived organoids as predictor of clinical response in ovarian cancer: a systematic review

Patient-derived organoids (PDOs) have emerged as promising preclinical models for functional drug testing in ovarian cancer, with potential to support personalized treatment selection. However, their predictive value for clinical treatment response remains unclear. This systematic review evaluated the predictive accuracy of ovarian cancer PDOs for treatment efficacy. A systematic search of was conducted from inception to January 29, 2026. Eligible studies included patients with high-grade epithelial ovarian, fallopian tube, or primary peritoneal cancer from whom PDOs were generated for in vitro drug testing and directly correlated with clinical outcomes. The primary outcome was predictive accuracy, defined as concordance/ correlation between in vitro PDO drug response and in vivo patient outcomes. Because of substantial heterogeneity, a narrative synthesis was performed. Twelve studies published between 2019 and 2026 were included. Cohort sizes ranged from 6 to 61 patients and comprised two prospective validation studies and ten retrospective translational or feasibility studies. Clinical endpoints were heterogeneous and included radiologic, biochemical and histopathologic response, progression-free survival, and descriptive clinical course. Four studies reported statistically significant associations between PDO drug response and clinical outcome, six reported concordant findings without formal statistical testing, two showed limited or mixed concordance, and one relied on descriptive comparison only. The strongest evidence came from two prospective studies, which reported accuracies of 89% and 91.7%. Ovarian cancer PDOs show promise as functional predictors of treatment response, but current evidence is limited by small cohorts, methodological heterogeneity, and scarce prospective validation. Standardized prospective studies are needed to define their clinical applicability.