Dataset Information

Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level

ABSTRACT: Medulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies – mainly studying nucleic acids – has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pGroup3myc), and synapses/immunological processes (pSHHs, pGroup3 and pGroup4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favourable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures. This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE243796 | GEO | 2024/04/22

REPOSITORIES: GEO

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Project description:BACKGROUND: Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.METHODS: Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.RESULTS: Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.CONCLUSIONS: IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.

Dataset Information

Multiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level

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