42P The establishment of a large tumor organoid biobank using a well characterized/annotated patient-derived xenograft (PDX) library to enable drug discovery and translational research

Patient-derived xenograft (PDX), a cancer stem cell (CSC)-derived in vivo model, is an accepted model of choice for preclinical and translational research due to its proven predictive power. Patient-derived cancer organoids (PDOs), also CSC-derived 3D culture of carcinoma with defined structures, harbor carcinoma’s multicellular components and mimics cancer lesion structures/heterogeneity, both genomicly and histopathologically. PDO was first described by Hans Clevers Lab and proven to be a predictive model for preclinical research, similar to PDX. We have used the Hubrecht organoid technology (HUB approach to systematically create the worlds-first biobank of organoids derived from a well annotated PDX library (the world’s largest with >2,500, covering a variety of carcinomas, with extensive pathology, genomic and treatment information), referred to as PDXOs. We then systematically profiled these PDXOs by WES (whole exome sequencing)/RNAseq (transcriptome sequencing), histopathology and standard of care (SOC) treatment. At present, we have established > 150 PDXOs covering > 15 cancer types, including bladder, breast, colorectal, gastric, liver, lung, ovarian and pancreatic cancer, cholangiocarcinoma, etc. Histopathological analysis showed cellular/structural similarities (ductal, mucous or carcinoid) between PDXO and original PDX, suggesting that tissue specific structural features were maintained in the 3D organoids. A high throughput screening (HTS in 384 well) format was established using the PDXOs and SOC sensitivity testing was conducted. The preliminary results largely correlated to the SOC response seen in vivo for the corresponding PDXs. In summary, we have successfully established a large biobank of the PDXOs that mirror the original PDXs, creating a unique library of matched in vitro/in vivo models with high translational power and enabling HTS, thus likely become an important tool for the future oncology drug discovery and development tools.