MDB-24. A DATA-DRIVEN APPROACH FOR THE IDENTIFICATION OF NEW SYNERGISTIC DRUG COMBINATIONS AGAINST NEURAL CANCERS

Abstract High-risk medulloblastomas are tumours with a poor survival prognosis (≤ 50%), which currently treated radiation therapy and DNA-damaging chemotherapy. The severe side effects of these treatments, including developmental problems secondary tumours, underscore the need for new treatments reduced toxicity. An attractive target such is Myc-family proteins since high-risk amplify either N-Myc (SHH-MB, G4-MB) or c-Myc (G3-MB). While from Myc family themselves often referred to as pharmacologically intractable, their levels activity can be modulated by indirect targeting, e.g. inhibition located upstream downstream c-Myc/N-Myc. diverse cellular processes pathways that involved in, however, suggest several must interrupted simultaneously achieve lasting effect. To identify multimodal interventions against Myc, we performed principal component analysis RNA sequencing data patient-derived medulloblastoma cells (MB002, G3, MYC-amplified) DAOY (SHH-group, no MYC amplification) were 120 small molecules. In subsequent analysis, focused on selection ~ 40 genes represent common regulators targets N-Myc. Applying particular markers, expect drugs affect different associated at opposite ends PC1 PC2 axis should have synergistic Additionally, expected closer each other, closely related pathways, would effect antagonistic. Our PCA distribution method used select combinations in manner easily extended compounds. This approach may allow fast screening compounds estimation treatment