Abstract A52: An interspecies genomics based high‐throughput screen for novel treatments of ependymoma

Brain tumors are often chemoresistant and these diseases are heterogeneous complicating efforts to discover effective new therapies. We describe a powerful interspecies genomics approach that meticulously matches subgroup specific driver mutations with cellular compartments to model cancer subgroups for drug screening. First, we performed a comprehensive genomics analysis to identify disease subgroups among >200 ependymomas. Subgroup specific alterations included amplifications and homozygous deletions of genes not yet implicated in ependymoma. We then identified CNS cell compartments most likely to give rise to ependymoma subgroups by matching the transcriptomes of human tumors to those of distinct types of mouse neural stem cell (NSC). Remarkably, activation of oncogenes in appropriate NSCs generated ependymomas that modelled the histology and transcriptome of the human disease. Stem‐like tumor cells isolated from these mouse ependymomas were then cultured under conditions that promote stem cell growth as neurospheres. These conditions were adapted for use in an automated high‐throughput screening system. Control transduced NSCs were also included to identify ependymoma‐selective agents. Tumor and control spheres were seeded in 384 well plates and drug treated using pin tool transfer 24 hours after plating. Cells were exposed to drug for 96 hours before compound cytotoxicity measured using the cell‐titre glo luciferase based assay. We first performed replicate primary screens of a large ‘bioactive library’ including natural products, bioactive alkaloids and marketed drugs (5760 compounds [3460 unique in structure]) in a single concentration format (10uM). Active compound hit rate varied from 0.9% to 4.8% in spheres derived from mouse tumors and 3.1% in control NSCs. The primary screen was highly reproducible (263 and 261 hits in replicate assays, of which 226 of were common in an example tumor line). ROC analysis of primary screen data was used to assess predictive power of the screen. For all cells the ROC AUC was >0.89 (0.85–0.92 95% CI). We next performed secondary screens of all primary screen hits. These included full 10‐point dose response assays that identified a total of 292 active agents with activity in at least one cell population. Following analysis of the ‘bioactive library, we screened a collection of 320 FDA approved active pharmaceutical ingredients representing all drug classes and all approved chemotherapy agents in a 10‐point dose response format. The hit rate of this drug collection in all cell types was between 10.36% to 15.4% and hit compounds represented a variety of drug classes including chemotherapeutics, NSAIDs, antibiotics and dopamine‐like agents. These compounds and the related families and structures will be described in detail as well as the results of ongoing in vivo activity against the originating ependymoma mouse models. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A52.