Ovarian cancer is the fifth leading cause of cancer death among women in Europe. Despite the fact that standard chemotherapeutic agents, used as a first-line therapy, are very effective in eliminating a vast majority of bulk ovarian cancer cells thereby inducing remission, 80% of women diagnosed with stage III or IV ovarian cancer later die due to relapse of the disease. In recent years, it has been shown that the relapsed cancer lesions emerge from relatively small subpopulations of surviving cells that exhibit drug resistance, likely driven by both genetic and non-genetic mechanisms.
Tailoring individualized therapeutic approaches for each patient (i.e. precision cancer medicine) has recently gained substantial attention as a way to improve cancer care. It is usually applied either by therapeutically targeting specific genetic mutations identified in cancers or by performing functional drug response profiling by exposing cancer cells derived directly from patients to a panel of cancer drugs and, based on the drug responses, informing therapeutic decisions in the clinic. However, as both genomic and functional precision medicine analyses are typically performed on bulk tumour mass, neither of these approaches address the challenge in ovarian cancer therapy (as well as many other types of cancers) where small drug-resistant cell subpopulations are responsible for relapses. Thus, there is a need for a method that would enable both identification of pre-existing drug-resistant cancer cell subpopulations and evaluation of therapies that could be used to target these subpopulations.
Organoids – patient-derived, stem cell-driven three-dimensional (3D) cell cultures – have been described as in vitro models that reproduce cellular heterogeneity, cell subpopulation representation and drug resistance of original tumours more closely than standard cell cultures. Organoids from several cancer types (e.g. colon, pancreas or prostate) have been recently applied for in vitro profiling of drug responses. So far, however, no large-scale endeavour utilizing ovarian cancer organoids derived directly from patient samples has been reported. Moreover, using non-physiologic growth-promoting culture media (e.g. abundant in glucose, growth factors and with non- physiological pH) in culture of cancer organoids has recently been questioned, as they can result in exaggerated cell growth rates, distorted cellular phenotypes and, likely, non-physiologic drug responses. Furthermore, drug responses of cells in commonly used in vitro culture conditions often do not reflect drug responses in vivo. Therefore, we hypothesized that by culturing ovarian cancer organoids in physiologic-like in vitro conditions, we would enrich the models in drug-resistant cell subpopulations and enable identification of compounds targeting drug-resistant cancer cells through drug-response profiling.
The project aimed to address following objectives:
• Objective 1: Apply an ovarian cancer organoid model, cultured in physiologic medium and enriched in drug-resistant cells, for large-scale drug response profiling
• Objective 2: Validate the most effective screening hits in patient-derived mouse xenografts (PDX)
