TBIO-07. Pediatric tumor classification through genome-wide methylation profiling of extracellular vesicle DNA

Abstract

BACKGROUND: Genome-wide methylation profiling reliably classifies pediatric central nervous system (CNS) tumors. Extracellular vesicles (EVs) are released by pediatric CNS tumor cells (pCC) and contain high molecular weight tumor 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 pCC-derived EVs reflects genome-wide tumor methylation profiles and allows tumor subtype classification. Currently, the tests are being expanded to include blood samples (n=80 patients). METHODS: DNA was isolated from EVs secreted by pediatric CNS tumor cells (pCC) as well as from the shortly cultured tumor cells and from the original tumor samples (n=4 patients). Pediatric Fibroblasts and EVs derived thereof were used as a non-tumorous control. EVs were classified by nanoparticle analysis (NTA), immunoblotting, imaging flow cytometry (IFCM and electron microscopy. Genome-wide DNA methylation profiling was performed using an 850k Illumina EPIC array and results were classified according to the DKFZ brain tumor classifier and further analysed by t-SNE and Copy number alteration analysis (CNA). RESULTS: The size range of pCC-derived EVs was 120-150 nm, as measured by NTA. The majority of secreted EVs exhibited high expression of common EV markers (i.e. CD9, CD63 and CD81), as characterized by IFCM. Genome-wide DNA methylation profiling of pCC-derived EVs correctly identified the methylation class of the original tumor (i.e. pilocytic astrocytoma, medulloblastoma). In addition, t-SNE analysis and copy number alterations matched the pattern of the parental pCC and original tumor samples. CONCLUSION: EV DNA faithfully reflects the tumor methylation class and copy number alterations present in the parental cells and the original tumor. Methylation profiling of circulating tumor EV DNA could become a useful tool to detect and classify pediatric CNS tumors.