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000291810 1001_ $$00000-0002-5162-5233$$aGodbole, Shweta$$b0
000291810 245__ $$aMultiomic profiling of medulloblastoma reveals subtype-specific targetable alterations at the proteome and N-glycan level.
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000291810 520__ $$aMedulloblastomas (MBs) are malignant pediatric brain tumors that are molecularly and clinically heterogenous. The application of omics technologies-mainly studying nucleic acids-has significantly improved MB classification and stratification, but treatment options are still unsatisfactory. The proteome and their N-glycans hold the potential to discover clinically relevant phenotypes and targetable pathways. We compile a harmonized proteome dataset of 167 MBs and integrate findings with DNA methylome, transcriptome and N-glycome data. We show six proteome MB subtypes, that can be assigned to two main molecular programs: transcription/translation (pSHHt, pWNT and pG3myc), and synapses/immunological processes (pSHHs, pG3 and pG4). Multiomic analysis reveals different conservation levels of proteome features across MB subtypes at the DNA methylome level. Aggressive pGroup3myc MBs and favorable pWNT MBs are most similar in cluster hierarchies concerning overall proteome patterns but show different protein abundances of the vincristine resistance-associated multiprotein complex TriC/CCT and of N-glycan turnover-associated factors. The N-glycome reflects proteome subtypes and complex-bisecting N-glycans characterize pGroup3myc tumors. Our results shed light on targetable alterations in MB and set a foundation for potential immunotherapies targeting glycan structures.
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000291810 650_7 $$2NLM Chemicals$$aPolysaccharides
000291810 650_7 $$2NLM Chemicals$$aProteome
000291810 650_2 $$2MeSH$$aMedulloblastoma: metabolism
000291810 650_2 $$2MeSH$$aMedulloblastoma: genetics
000291810 650_2 $$2MeSH$$aHumans
000291810 650_2 $$2MeSH$$aPolysaccharides: metabolism
000291810 650_2 $$2MeSH$$aProteome: metabolism
000291810 650_2 $$2MeSH$$aCerebellar Neoplasms: metabolism
000291810 650_2 $$2MeSH$$aCerebellar Neoplasms: genetics
000291810 650_2 $$2MeSH$$aDNA Methylation
000291810 650_2 $$2MeSH$$aTranscriptome
000291810 650_2 $$2MeSH$$aChild
000291810 650_2 $$2MeSH$$aProteomics: methods
000291810 650_2 $$2MeSH$$aFemale
000291810 650_2 $$2MeSH$$aGene Expression Regulation, Neoplastic
000291810 650_2 $$2MeSH$$aMale
000291810 650_2 $$2MeSH$$aChild, Preschool
000291810 650_2 $$2MeSH$$aGene Expression Profiling: methods
000291810 7001_ $$aVoß, Hannah$$b1
000291810 7001_ $$00009-0007-5828-6637$$aGocke, Antonia$$b2
000291810 7001_ $$aSchlumbohm, Simon$$b3
000291810 7001_ $$00000-0002-2379-200X$$aSchumann, Yannis$$b4
000291810 7001_ $$aPeng, Bojia$$b5
000291810 7001_ $$00000-0003-3302-2719$$aMynarek, Martin$$b6
000291810 7001_ $$aRutkowski, Stefan$$b7
000291810 7001_ $$00000-0002-9769-7080$$aDottermusch, Matthias$$b8
000291810 7001_ $$aDorostkar, Mario M$$b9
000291810 7001_ $$0P:(DE-He78)8d9c904a6cea14d4c99c78ba46e41f93$$aKorshunov, Andrey$$b10$$udkfz
000291810 7001_ $$aMair, Thomas$$b11
000291810 7001_ $$0P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9$$aPfister, Stefan$$b12$$udkfz
000291810 7001_ $$00000-0002-5804-6031$$aKwiatkowski, Marcel$$b13
000291810 7001_ $$aHotze, Madlen$$b14
000291810 7001_ $$00000-0001-8604-8846$$aNeumann, Philipp$$b15
000291810 7001_ $$aHartmann, Christian$$b16
000291810 7001_ $$00000-0003-3280-6773$$aWeis, Joachim$$b17
000291810 7001_ $$aLiesche-Starnecker, Friederike$$b18
000291810 7001_ $$aGuan, Yudong$$b19
000291810 7001_ $$aMoritz, Manuela$$b20
000291810 7001_ $$aSiebels, Bente$$b21
000291810 7001_ $$aStruve, Nina$$b22
000291810 7001_ $$aSchlüter, Hartmut$$b23
000291810 7001_ $$00000-0002-8731-1121$$aSchüller, Ulrich$$b24
000291810 7001_ $$00000-0002-4689-1967$$aKrisp, Christoph$$b25
000291810 7001_ $$00000-0002-1162-8771$$aNeumann, Julia E$$b26
000291810 773__ $$0PERI:(DE-600)2553671-0$$a10.1038/s41467-024-50554-z$$gVol. 15, no. 1, p. 6237$$n1$$p6237$$tNature Communications$$v15$$x2041-1723$$y2024
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