P10.21.B Pharmacogenomics profiling of gliomas for precision medicine. (5th September 2022) - Lipsa, A; Hau, A; Ermini, L; Toth, R; Oudin, A; Klink, B; Hertel, F; Mittelbronn, M; Golebiewska, A; Niclou, S
Abstract: Background: Molecular characterization based on genomic, transcriptomic and epigenetic profiling has led to a better delineation of various glioma subtypes and highlighted the individual paths of glioma evolution upon treatment and recurrence. However, due to cellular and molecular diversity of these tumors, the pharmacological treatment of gliomas, in particular of its most malignant subtype Glioblastoma (GBM), remains a major challenge. To address this challenge, we here apply a pharmacogenomics approach, modelling the disease in matched patient-derived preclinical models and profiling the differential drug response among individual patients and glioma subtypes Material and Methods: We generated a cohort of 45 Patient-Derived Orthotopic Xenografts (PDOX) from a collection of over 400 glioma patients. We used a multi-parametric approach based on genetic, transcriptomic and longitudinal profiling of patients and their matched xenografts for a comprehensive subgrouping of our glioma cohort. Based on PDOX-derived 3D tumor organoids we carried out a targeted drug screen focused on epigenetic regulators. A high throughput drug screening using an unbiased large chemical library containing a unique collection of FDA approved compounds with high pharmacological diversity is currently ongoing. Results: Our glioma cohort with matched PDOX and 3D tumor organoids represents diverse subgroups of glioma patients, including a unique collection of primary and relapsed tumors from the same patient. Our preliminary drug screen analysis on 3D organoids highlights selective susceptibility to certain epigenetic inhibitors in primary disease but not in the same patient's relapse. Results of matching genomics and functional data will be presented. Conclusion: An integrated personalized approach to profile gliomas at multiple genomic and functional levels allows for pharmacogenomic subgrouping of patients for personalized treatment strategies. This analysis will allow to link genotypes to functional phenotypes and hopefully identify therapeutic options for selected glioma sub-populations.