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

Abstract

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.

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Fig. 1: DNA methylation landscape of glioblastoma disease progression.
Fig. 2: Glioblastoma transcriptional subtypes inferred from DNA methylation profiles.
Fig. 3: DNA methylation and the tumor microenvironment.
Fig. 4: DNA methylation and histopathological tumor characteristics.
Fig. 5: DNA methylation heterogeneity in glioblastoma disease progression.
Fig. 6: DNA methylation differences between primary and recurring tumors.

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Acknowledgements

We thank all patients who have donated their samples for this study. We also thank G. Wilk, M. Muck, S. Schmid, and U. Andel for technical assistance with immunohistochemical stainings, macrodissection, and tumor tissue shavings; S. Mages for contributing to the interactive data visualization; the Biomedical Sequencing Facility at CeMM for assistance with next-generation sequencing; and all members of the Bock lab for their help and advice. The study was funded in part by an Austrian Science Fund grant (FWF KLI394) to A.W., a Marie Curie Career Integration Grant (European Union’s Seventh Framework Programme grant agreement no. PCIG12-GA-2012-333595) to C.B., an ERA-NET project grant (EpiMark FWF I 1575-B19) to C.B., an Austrian Science Fund grant (FWF I2714-B31) to G.L. and K.-H.N, and an ERC Starting Grant (European Union’s Horizon 2020 research and innovation programme, grant agreement no. 640396) to B.B. Moreover, C.B. is supported by a New Frontiers Group award of the Austrian Academy of Sciences and by an ERC Starting Grant (European Union’s Horizon 2020 research and innovation programme, grant agreement no. 679146). Activities of the Austrian Brain Tumor Registry are supported by unrestricted research grants of Roche Austria to J.A.H. and the Austrian Society of Neurology to S.O. Some of the samples used for this research project were kindly provided by Biobank Graz.

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Contributions

J. Klughammer, A.W., and C.B. designed the study. B.K., T.R., K.-H.N., J.F., N.P., M.N., M.A., M.M., T.S., G.L., B.B., J.A.H., and A.W. established and annotated the cohort. A.N. and P.D. performed DNA methylation profiling. D.A. performed low-coverage whole-genome sequencing. M.S. performed RNA-seq. J. Klughammer performed the data analysis. N.F., N.C.S, and B.E. contributed to data analysis. P.M., C.F.F., J. Kerschbaumer, C.T., A.E.G., G.S., M.K., S.O., F.M., S.W., J.T., J.B., J. Pichler, J.H., S.K., K.M.A., G.v.C., F.P., C.S., J. Preiser, T.H., P.A.W., W.K., F.W., T.B.-K., M.S., S.S., K.D., M.P., E.K., G.W., and C.M. contributed tumor samples and clinical data. J. Klughammer, A.W., and C.B. wrote the manuscript with contributions from all authors.

Corresponding author

Correspondence to Adelheid Woehrer.

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The optimized RRBS protocol that was used in this study has been licensed to Diagenode s.a. (Liège, Belgium) and commercialized as a kit and service.

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Patient summary table

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Survival analysis summary table

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Association analysis summary table

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Klughammer, J., Kiesel, B., Roetzer, T. et al. The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space. Nat Med 24, 1611–1624 (2018). https://doi.org/10.1038/s41591-018-0156-x

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