Pilocytic astrocytomas (PAs) are the most common brain tumors in pediatric patients and can cause significant morbidity, including chronic neurological deficiencies. They are characterized by activating alterations in the mitogen-activated protein kinase pathway, but little else is known about their development. To map the global DNA methylation profiles of these tumors, we analyzed 62 PAs and 7 normal cerebellum samples using Illumina 450K microarrays. These data revealed two subgroups of PA that separate according to tumor location (infratentorial versus supratentorial), and identified key neural developmental genes that are differentially methylated between the two groups, including NR2E1 and EN2. Integration with transcriptome microarray data highlighted significant expression differences, which were unexpectedly associated with a strong positive correlation between methylation and expression. Differentially methylated probes were often identified within the gene body and/or regions up- or downstream of the gene, rather than at the transcription start site. We also identified a large number of differentially methylated genes between cerebellar PAs and normal cerebellum, which were again enriched for developmental genes. In addition, we found a significant association between differentially methylated genes and SUZ12 binding sites, indicating potential disruption of the polycomb repressor complex 2 (PRC2). Taken together, these data suggest that PA from different locations in the brain may arise from region-specific cells of origin, and highlight the potential disruption of key developmental regulators during tumorigenesis. These findings have implications for future basic research and clinical trials, as therapeutic targets and drug sensitivity may differ according to tumor location.
Pilocytic astrocytoma DNA methylation Development SUZ12
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This project was supported by grants from The Brain Tumour Charity, UK. Additional support was provided by the PedBrain Tumor Project contributing to the International Cancer Genome Consortium, funded by German Cancer Aid (109252) and by the German Federal Ministry of Education and Research (BMBF, grants #01KU1201A, MedSys #0315416C and NGFNplus #01GS0883), and the Dutch Cancer Foundations KWF (2010-4713) and KIKA to M. Kool. We thank Matthias Schick, Roger Fischer and Melanie Bewerunge-Hudler of the German Cancer Research Center (DKFZ) Genomics and Proteomics Core Facility for excellent technical support.
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