Mucinous Ovarian Carcinoma (MOC) is a rare form of epithelial ovarian cancer that is histologically distinct from other subtypes. When diagnosed at late stage, prognosis is dire as the cancer typically responds poorly to standard ovarian platinum chemotherapy regimes. There is currently very limited pre-clinical or trial data available, and consequently there is no clear clinical consensus on the best first line therapy to offer these patients. Our lab has generated an inventory of unique MOC patient-derived organoids and aimed to use these in high-throughput drug screening to generate efficacy data on a range of commonly offered therapeutics in order to guide clinical practice.
Fresh and frozen patient tissue samples were obtained from Peter MacCallum Cancer Centre, the Royal Women’s Hospital and Westmead Hopsital and digested using a combination of mechanical and enzymatic methods. Single cells were seeded into matrigel domes and cultured with a specific cocktail of growth factors designed to stimulate and support organoid growth. DNA and RNA were extracted from matched organoid and parent tumour tissue pairs and RNA sequencing/WGS sequencing was performed, along with IHC of key diagnostic MOC markers. Characterised organoids were then seeded in 384 well plates and drugged with a panel of agents in a 10 point dilution curve. Staining and CTG analysis was performed to generate viability counts.
Characterisation of organoids including whole genome sequencing revealed these models successfully recapitulated MOC parent tumours. Organoid lines demonstrated varied responses to a range of single agent regimens.
These novel organoid models have proven a highly useful tool to provide drug efficacy data that is otherwise difficult to obtain in this rare cancer. Ultimately, there is the potential to use such models in personalised medicine and achieve better patient outcomes.