Cecile L Maire1, Marceline M Fuh2, Kerstin Kaulich3, Krystian D Fita1, Ines Stevic1, Dieter H Heiland4, Joshua A Welsh5, Jennifer C Jones5, André Görgens6,7,8, Tammo Ricklefs1, Lasse Dührsen1, Thomas Sauvigny1, Simon A Joosse9,10, Guido Reifenberger3, Klaus Pantel9, Markus Glatzel11, Andras G Miklosi12, James H Felce12, Marco Caselli12, Valerio Pereno12, Rudolph Reimer13, Hartmut Schlüter14, Manfred Westphal1, Ulrich Schüller11,15, Katrin Lamszus1, Franz L Ricklefs1. 1. Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 2. Department of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 3. Institute of Neuropathology, University of Duesseldorf, Duesseldorf, Germany. 4. Department of Neurosurgery, Medical Center University of Freiburg, Freiburg, Germany. 5. Translational Nanobiology Section, Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA. 6. Department of Laboratory Medicine, Clinical Research Center, Karolinska Institute, Stockholm, Sweden. 7. Institute for Transfusion Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany. 8. Evox Therapeutics Limited, Oxford, UK. 9. Department of Tumor Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 10. Mildred Scheel Cancer Career Center HaTriCS4, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 11. Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 12. Oxford Nanoimaging Limited (ONI), Oxford, UK. 13. Heinrich-Pette-Institut, Leibniz Institute for Experimental Virology, Hamburg, Germany. 14. Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 15. Department of Pediatric Hematology and Oncology, and Research Institute Children's Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
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.
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.
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