CADD-33. PERSONALIZED PHARMACOGENOMICS USING GLIOMA PATIENT-DERIVED ORTHOTOPIC XENOGRAFTS (PDOXS). (5th November 2018) - Hau, Ann-Christin; Golebiewska, Anna; Oudin, Anaïs; Houben, Linsey; Stieber, Daniel; Hertel, Frank; Niclou, Simone
Abstract: It is well recognized that long term cell cultures are poor models to study human cancer, largely because of loss of clonal heterogeneity, accumulation or loss of genomic alterations and adaptation to a highly artificial environment. Patient-derived orthotopic xenografts (PDOX) based on organotypic three-dimensional tumor spheroids from human glioma samples are proposed to represent a reliable and clinically-relevant animal model. We have generated a living biobank of PDOX models from 34 glioma patients (grade III and IV), including longitudinal patient samples with matched recurrent tumors. Using an efficient orthotopic xenografting procedure we obtain an overall tumor take-rate of close to 80%. We show that our glioma PDOX retain the genetic and epigenetic profiles of primary patient biopsies throughout several generations of xenotransplantation. In particular they not only faithfully recapitulate gene amplification and expression of EGFR and EGFRvIII variant in a reproducible manner, also amplification and expression of rarer patient-specific EGFR variants is maintained. Overall genome-wide transcriptomic profiles of PDOX remain very similar to patient biopsies and correlate better with the GBM cohort of TCGA (538 GBM samples) than conventional cell lines. Observed differences at the transcriptomic level are largely based on the replacement of human to mouse stromal cells, which impacts on the molecular sub-classification of GBM. We conclude that glioma PDOX models closely reflect patient heterogeneity and treatment response, and thus represent appropriate avatars for reproducible pre-clinical trials. Furthermore, by combining profiling of the somatic mutational landscape with large-scale drug screening, PDOX-derived tumor organoids can elucidate druggable targets and tumor response profiles in a personalized patient-specific manner.