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The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space
The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space
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The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space
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The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space
The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space
Journal Article

The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

2018
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Overview
Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of DNA methylation in matched primary and recurring glioblastoma tumors, using data from a highly annotated clinical cohort that was selected through a national patient registry. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected FFPE samples, and we validate bisulfite sequencing as a multipurpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional characteristics of the profiled tumor samples. On the basis of these data, we identified subtle differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study establishes an open resource for dissecting DNA methylation heterogeneity in a genetically diverse and heterogeneous cancer, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology for a national cohort, thereby leveraging existing samples and data collected as part of routine clinical practice. In-depth methylation analysis of formalin-fixed paraffin-embedded glioblastoma samples demonstrates heterogeneity between primary and recurring tumors and enables prediction of composition of the tumor microenvironment and insights into progression.