Comprehensive proteogenomic characterization reveals clinically relevant molecular subtypes associated with medulloblastoma progression

Abstract

Current treatment strategies for medulloblastoma remain ineffective owing to extensive tumor heterogeneity. We generated five platforms of omics data including liquid chromatography and mass spectrometry-based proteome and performed integrated multi-omic characterization to improve the conventional molecular classification of medulloblastoma. We identified seven refined distinct subtypes. The sonic hedgehog (SHH) group was reclassified into two subgroups, SHH alpha and SHH beta, whereas group 4 was divided into three subgroups, G4 alpha, G4 beta, and G4 gamma. SHH and group 4 subtypes exhibit two distinct neuronal differentiation trajectories: granular neuron and unipolar brush cell differentiation (SHH beta and G4 gamma, respectively), both of which associated with more favorable clinical outcomes. Furthermore, we uncovered unique proteomic and kinomic properties that conferred increased treatment vulnerabilities to targeted therapeutic interventions against each of the three medulloblastoma subtypes associated with poor clinical outcomes. We demonstrated the therapeutic potential of exploiting these vulnerabilities by utilizing a proteasome inhibitor and subtype-specific agents, including CDK1/2, PARP, CLK1, and MET inhibitors. Mechanistic insights were further elucidated through in-depth proteome analyses. Our study qualifies the use of proteomic signatures and activation of neuronal differentiation trajectories to tailor selective therapeutic opportunities for distinct subgroups of patients with medulloblastoma.