Patient-derived organoids and high grade serous ovarian cancer: from disease modeling to personalized medicine

Abstract Background High grade serous ovarian cancer (HGSOC) is among the deadliest human cancers and its prognosis remains extremely poor. Tumor heterogeneity and rapid acquisition of resistance to conventional chemotherapeutic approaches strongly contribute to poor outcome of patients. The clinical landscape of HGSOC has been radically transformed since the advent of targeted therapies in the last decade. Nevertheless, the lack of predictive biomarkers informing on the differential clinical benefit in select subgroups, and allowing patient-centric approaches, currently limits the efficacy of these novel therapies. Thus, rational selection of the best possible treatment for each patient represents a clinical priority in order to improve outcome, while limiting undesirable effects. Main body In this review, we describe the state of the art and the unmet needs in HGSOC management, illustrate the treatment options that are available and the biomarkers that are currently employed to orient clinical decisions. We also describe the ongoing clinical trials that are testing new therapeutic approaches for HGSOC. Next, we introduce the organoid technology as a promising, expanding strategy to study cancer and to develop personalized therapeutic approaches. In particular, we discuss recent studies that have characterized the translational potential of Patient’s Derived Organoids (PDOs) to inform on drug sensitivity of HGSOC patients. Conclusions PDOs can predict the response of patients to treatments and may therefore guide therapeutic decisions. Although preliminary results appear encouraging, organoids still need to be generated and expanded efficiently to enable drug screening in a clinically meaningful time window. A new generation of clinical trials based on the organoid technology should guarantee tailored approaches to ovarian cancer management, as it is now clear that the one-size-fits-all approach cannot lead to efficient and meaningful therapeutic advancements.