Abstract LB-038: Predicting breast cancer therapy response using a patient-derived xenograft organoid screening platform

Patient-derived xenografts (PDX) are valuable, clinically-relevant models of cancer. Their close genomic, phenotypic, and temporal association with patient tumors makes them well-suited for pre-clinical and co-clinical studies that assess the potential of new therapeutics. However, PDX models are not amenable to large-scale drug sensitivity studies due to their high cost and low throughput capacity. To address this, we established and characterized long-term PDX organoid (PDxO) cultures from breast cancer (BC) PDXs and evaluated their utility in therapeutic studies. To establish PDxO culture conditions, we extensively tested medium supplements, including growth factors, kinase inhibitors, conditioned medium, and antioxidants, along with extracellular matrix composition in 3D gels. Using optimized culture conditions for each BC subtype, we established PDxOs from 16 PDX lines in the HCI series, with a PDX to PDxO success rate of 85%. Around 20% of PDxOs contained aggressive mouse stroma, which had to be eliminated by FACS for long-term culture success. PDxOs were maintained for over 1 year, during which we tracked viability, doubling time, organoid size, genomics, epithelial character, and tumorigenicity. Doubling times stabilized after 60 days of initial culture, with a mean of 6.4±1.7 days for triple negative (TN) lines and 7.2±1 days for ER + lines. Mean organoid size remained stable, with ER + PDxOs significantly smaller than TN PDxOs, at 91 and 262 cells/organoid respectively (p=0.0012). PDxOs histologically resembled their PDX counterparts when stained for HE p = 0.045-0.12, across 3 PDXs and 9 compounds). Ongoing work aims to confirm concordance between PDX and PDxO models. Our work demonstrates that PDxO models are cost-efficient, easy to maintain, and grow indefinitely - making them renewable and accessible cancer models. PDxOs are a powerful parallel resource to PDX models, especially useful for efficient determination of PDX drug response. We are currently expanding our PDxO bank to include 100 models which will be deposited with the NCI as part of the PDXNet effort. Citation Format: Katrin P. Guillen, Sandra D. Scherer, Yi Qiao, Satya S. Pathi, James M. Graham, Maihi Fujita, Yoko S. DeRose, Jason Gertz, Gabor T. Marth, Katherine E. Varley, Alana L. Welm, Bryan E. Welm. Predicting breast cancer therapy response using a patient-derived xenograft organoid screening platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-038.