MODL-04. ESTABLISHMENT OF A RELIABLE GLIOBLASTOMA TUMOR-ORGANOID PLATFORM ENABLES AUTOMATED HIGH-THROUGHPUT DRUG SCREENING ADVANCING PERSONALIZED MEDICINE

Abstract

Abstract Patient-derived tumor organoids (TOs) generated from tumor tissues within a few days are promising new models since under optimal conditions they preserve genotype, phenotype, the tumor microenvironment and the cellular heterogeneity of the parental tumor. This exciting new technology could provide representative avatars of the patient tumor in large numbers and thus can be exploited for drug discovery and drug screening purposes more efficiently than conventional cell lines or xenografted mouse models. We established standardized TOs from fresh glioblastoma (GBM) tissue after enzymatic dissociation into single cell suspensions and seeding cells into anti-adhesive 384-well plates. Over 1000 standardized TOs were generated per patient with a success rate of over 90%. Morphologically, TOs formed after two days. Size was stable over 10 days, with a slow outgrowth in some cases. A steady increase of the ATP signal over time indicated proliferative activity in TOs. Immunofluorescent stainings for tumor cells (GFAP), immune cells (macrophages and T-cells), and extracellular matrix (Tensascin C) confirmed a strong resemblance of TOs to their corresponding parental tumor, which was further substantiated by RNA-seq and DNA-methylation. Next, automated robot-based high-throughput drug screening (aHTS) on TOs was performed using a drug library of 166 FDA-approved antineoplastic drugs. Cell viability was assessed by CellTiter-Glo3D. In total, aHTS on TOs from 11 GBM patients including two recurrent GBMs showed a strong heterogeneity of drug responses. The top ten best-performing drugs consisted of 35 compounds targeting 14 different modes of action. Proteasome and HDAC-inhibitors demonstrated the highest efficacy. Respective targets were validated by knockdown experiments in GBM cells. Altogether, our data corroborate the future use of standardized GBM TOs as patient avatars for personalized drug testing by utilizing an automated high-throughput drug screening platform to better account for inter-patient-individual drug responses.