Genome-wide methylation profiling of glioblastoma cell-derived extracellular vesicle DNA allows tumor classification

Maire CL, Fuh MM, Kaulich K, Fita KD, Stevic I, Heiland DH, Welsh JA, Jones JC, Görgens A, Ricklefs T, Dührsen L, Sauvigny T, Joosse SA, Reifenberger G, Pantel K, Glatzel M, Miklosi AG, Felce JH, Caselli M, Pereno V, Reimer R, Schlüter H, Westphal M, Schüller U, Lamszus K, Ricklefs FL (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Neuro-Oncology Oxford University Press

Book Volume: 23

Pages Range: 1087-1099

Journal Issue: 7

DOI: 10.1093/neuonc/noab012

Abstract

Background: Genome-wide DNA methylation profiling has recently been developed into a tool that allows tumor classification in central nervous system tumors. Extracellular vesicles (EVs) are released by tumor cells and contain high molecular weight DNA, rendering EVs a potential biomarker source to identify tumor subgroups, stratify patients and monitor therapy by liquid biopsy. We investigated whether the DNA in glioblastoma cell-derived EVs reflects genome-wide tumor methylation and mutational profiles and allows noninvasive tumor subtype classification. Methods: DNA was isolated from EVs secreted by glioblastoma cells as well as from matching cultured cells and tumors. EV-DNA was localized and quantified by direct stochastic optical reconstruction microscopy. Methylation and copy number profiling was performed using 850k arrays. Mutations were identified by targeted gene panel sequencing. Proteins were differentially quantified by mass spectrometric proteomics. Results: Genome-wide methylation profiling of glioblastoma-derived EVs correctly identified the methylation class of the parental cells and original tumors, including the MGMT promoter methylation status. Tumor-specific mutations and copy number variations (CNV) were detected in EV-DNA with high accuracy. Different EV isolation techniques did not affect the methylation profiling and CNV results. DNA was present inside EVs and on the EV surface. Proteome analysis did not allow specific tumor identification or classification but identified tumor-associated proteins that could potentially be useful for enriching tumor-derived circulating EVs from biofluids. Conclusions: This study provides proof of principle that EV-DNA reflects the genome-wide methylation, CNV, and mutational status of glioblastoma cells and enables their molecular classification.

Authors with CRIS profile

Dieter Henrik Heiland

Involved external institutions

Universitätsklinikum Hamburg-Eppendorf (UKE) DE Germany (DE) Heinrich-Heine-Universität Düsseldorf DE Germany (DE) National Cancer Institute (NCI) US United States (USA) (US) Karolinska Institute SE Sweden (SE) Oxford Nanoimaging Limited GB United Kingdom (GB) Heinrich-Pette-Institut (HPI), Leibniz-Institut für Experimentelle Virologie / Heinrich Pette Institute – Leibniz Institute for Experimental Virology DE Germany (DE) Universitätsklinikum Freiburg DE Germany (DE)

How to cite

APA:

Maire, C.L., Fuh, M.M., Kaulich, K., Fita, K.D., Stevic, I., Heiland, D.H.,... Ricklefs, F.L. (2021). Genome-wide methylation profiling of glioblastoma cell-derived extracellular vesicle DNA allows tumor classification. Neuro-Oncology, 23(7), 1087-1099. https://doi.org/10.1093/neuonc/noab012

MLA:

Maire, Cecile L., et al. "Genome-wide methylation profiling of glioblastoma cell-derived extracellular vesicle DNA allows tumor classification." Neuro-Oncology 23.7 (2021): 1087-1099.

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