Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and n-glycan level
NEURO-ONCOLOGY(2023)
Abstract
Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically very heterogenous. To unravel phenotypically relevant MB subtypes, we compiled a harmonized proteome dataset of 167 MBs and integrated findings with DNA methylation and N-glycome data. Six proteome MB subtypes emerged, that could be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pGroup3-Myc), and synapses/immunological processes (pSHHs, pGroup3 and pGroup4). Multiomic analysis revealed different conservation levels of proteome features across MB subtypes at the DNA-methylation level. Aggressive pGroup3-Myc MBs and favorable pWNT MBs were most similar in cluster hierarchies concerning overall proteome patterns but showed different protein abundances of the vincristine resistance associated multiprotein complex TriC/CCT and of N-glycan turnover associated factors. The N-glycome reflected proteome subtypes and complex-bisecting N-glycans characterized pGroup3-Myc tumors. Our results shed light on new targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures.
Significance Whereas the application of omics technologies has significantly improved MB tumor classification and treatment stratification, it is still of debate, which features predict best clinical outcome. Moreover, treatment options - especially for high-risk groups - are still unsatisfactory. In contrast to nucleic acids, the proteome and their N-glycans may reflect the phenotype of a tumor in a more direct way and thus hold the potential to discover clinically relevant phenotypes and potentially targetable pathways. We show that these analyses are feasible on formalin fixed and paraffine embedded tissue. Compiling a comprehensive MB dataset, we detected new biomarkers and characteristics for high- and low-risk MB subtypes that were not reflected by other omic data modalities before. Specifically, we identified subtype specific abundance differences in proteins of the vincristine resistance associated multiprotein complex TriC/CCT and in proteins involved in N-glycan turnover. Changes in the N-glycans are considered as potential hallmarks of cancer and we show that N-glycan profiles can distinguish MB subtypes. These tumor-specific N-glycan structures hold a strong potential as new biomarkers, as well as immunotherapy targets.
Highlights
### Competing Interest Statement
The authors have declared no competing interest.
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