MDB-38. COMPUTATIONAL DRUG SENSITIVITY PREDICTS MEDULLOBLASTOMA SUBGROUP-SPECIFIC THERAPEUTICS

Abstract Medulloblastoma is the most common malignant pediatric brain tumor. Tumors are typically characterized as Group 3, 4, SHH, or WNT. Current standard-of-care includes surgery, radiation, and chemotherapy; however, treatment response prognosis vary widely between subgroups. Additionally, surviving children frequently suffer from lifelong neurocognitive deficits. Therefore, novel therapeutic options urgently needed. Despite extensive characterization of medulloblastoma tumors into four molecular subgroups, few subgroup specific therapies have advanced to clinic. To address this, we developed a platform called DrugSeq, which predicts drug sensitivities in patients can stratify by subgroup. DrugSeq also identifies key pharmacotranscriptomic differences primary recurrent tumors. We first calculated disease signatures for each patient normalizing gene expression low grade glioma samples posterior fossa. Using previously transcriptional consensus (TCSs) that represent affect has on across panel cancer cell lines, then discordance signature TCS. Finally, using an ANOVA analysis identified drugs predicted differentially target Among our top anti-cancer compounds found several kinase inhibitors, bromodomain psychiatric with known penetrance. show distinct sensitivity predictions newly diagnosed tumors, such BET inhibition 3 4 despite no Future studies larger datasets may be able further subdivide age features within Collectively, identify facilitate stratification clinical trials, leading more successful targeted therapies.