Abstract GMM-021: UTILIZATION OF PATIENT-DERIVED TUMOR XENOGRAFT (PDX) MODELS IN ONCOLOGY

Abstract

Abstract BACKGROUND: The 5-year survival rate of patients with recurrent epithelial ovarian cancer is only 30%, in part due to relapse and resistance to first-line platinum-based chemotherapy. Even with marked progress toward understanding ovarian cancer biology, the translation of research findings into new therapies is still an enormous barrier to progress. Recent data suggests a 90% failure rate for new oncology drugs in the clinic. Development and preclinical testing of new cancer therapies has been limited by the availability of clinically relevant models that recapitulate the molecular and phenotypic characteristics of primary ovarian cancers. To overcome this barrier, we have initiated collaborative project between Stephenson Cancer Center (SCC) and Oklahoma Medical Research Foundation (OMRF) with the goal to generate a biobank of patient-derived xenograft (PDX) models derived directly from ovarian cancer patients undergoing therapy. RESULTS: PDX tumor models are generated in the Patient-Derived Xenograft and Preclinical Therapeutics (PDX-PCT) Core at OMRF and used to improve preclinical evaluation of new drugs towards more personalized medicine. We have collected blood samples and tumor tissues from consenting patients having primary debulking surgery at Stephenson Cancer Center since 2015 (>140 unique patients). Fresh tumor tissue is minced into small tumor chunks (~2 mm) and implanted into immunocompromised mice. PDXs are expanded for 3-4 passages and characterized based on tumor type, histology and molecular characteristics. Immunohistochemical and molecular analysis showed that histology of the original patient tumors as well as the expression of commonly used markers for high-grade serous ovarian cancer such as cytokeratin, PAX8 and WT1 are perfectly maintained in the derivative PDX lines. Genotyping of patients' tumors and their corresponding PDXs using Illumina's Exome Array revealed that single nucleotide polymorphism (SNP) profile found in the original tumors is perfectly maintained in PDX lines. One of the PDX limitations is that human tumor stromal and immune cells are being replaced with mouse equivalents upon in vivo propagation of PDXs, which negatively affects quality of genomic or proteomic analyses. To overcome this challenge, we optimized a method to deplete mouse cells from PDX tumors by magnetic cells separation. Our data showed that ovarian cancer PDXs contain around 28-54% of human tumor cells, where the rest are mouse cells. We also optimized protocols to utilize pure population of human tumor cells isolated from PDXs to transduce these with lentiviral vectors expressing GFP and/or luciferase to generate luciferized PDXs. Luciferized ovarian PDXs are excellent models used for non-invasive orthotopic tumor growth and drug response monitoring. CONCLUSIONS: Collection of our PDXs illustrates heterogeneity and diversity of human ovarian tumors. However, each PDX maintains essential molecular features of the original patients' tumor. Our goal is to generate clinically faithful ovarian tumor models that will provide a platform to learn more about cancer biology and to screen these for new better therapies. Citation Format: Magdalena Cybula, Katherine Moxley, Lin Wang, Luyao Wang, Magdalena Bieniasz. UTILIZATION OF PATIENT-DERIVED TUMOR XENOGRAFT (PDX) MODELS IN ONCOLOGY [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr GMM-021.