Developmental tumors in children and young adults carry few genetic alterations, yet they have diverse clinical presentation. Focusing on Ewing sarcoma, we sought to establish the prevalence and characteristics of epigenetic heterogeneity in genetically homogeneous cancers. We performed genome-scale DNA methylation sequencing for a large cohort of Ewing sarcoma tumors and analyzed epigenetic heterogeneity on three levels: between cancers, between tumors, and within tumors. We observed consistent DNA hypomethylation at enhancers regulated by the disease-defining EWS-FLI1 fusion protein, thus establishing epigenomic enhancer reprogramming as a ubiquitous and characteristic feature of Ewing sarcoma. DNA methylation differences between tumors identified a continuous disease spectrum underlying Ewing sarcoma, which reflected the strength of an EWS-FLI1 regulatory signature and a continuum between mesenchymal and stem cell signatures. There was substantial epigenetic heterogeneity within tumors, particularly in patients with metastatic disease. In summary, our study provides a comprehensive assessment of epigenetic heterogeneity in Ewing sarcoma and thereby highlights the importance of considering nongenetic aspects of tumor heterogeneity in the context of cancer biology and personalized medicine.


DNA Methylation (WGBS & RRBS) Histone and EWS-FLI1 Marks (ChIP-seq)
Sequencing Data Raw sequencing data are available from SRA/GEO at accession #GSE88826. Raw sequencing data are available from SRA/GEO at accession #GSE89026.
Processed Results DNA methylation calls (zipped BED files, 5.7 GB).
Also available from GEO at accession #GSE88826.
ChIP-seq histone peaks (zipped BED files, 161 MB)
Also available from GEO at accession #GSE89026.
Genome Browser Tracks Ewing sarcoma samples: Track hub, Autoload USA mirror, Autoload Euro mirror
Reference samples: Track hub, Autoload USA mirror, Autoload Euro mirror
Histone and EWS-FLI1 marks for 3 Ewing tumors: Track hub, Autoload USA mirror, Autoload Euro mirror

Source code

We have made source code for this publication available in a source code archive.

File Description
rrbs.py A pipeline to process raw RRBS data (adapter trimming, alignment, methylation calling). This python pipeline is built using the Pypiper pipeline framework and can be used with Looper to process multiple samples in parallel on any computational infrastructure, including either local compute (a laptop or standalone server) or a shared cluster running resource management software (such as SLURM, SGE, or LFS).
MIRA.R R functions for calculating the Methylation-based Inference of Regulatory Activity (MIRA) score.
PIM.R R functions for calculating the Proportion of sites with Intermediate Methylation (PIM) score.


Genome sequencing for 79 samples are available from EBI EGA at accession number EGAS00001000855.


Sheffield NC, Pierron G, Klughammer J, Datlinger P, Schönegger A, Schuster M, Hadler J, Guillemot D, Lapouble E, Freneaux P, Champigneulle J, Bouvier R, Walder D, Ambros IM, Hutter C, Sorz E, Amaral AT, Álava Ed, Schallmoser K, Strunk D, Rinner B, Liegl-Atzwanger B, Huppertz B, Leithner A, Pinieux Gd, Terrier P, Laurence V, Michon J, Ladenstein R, Holter W, Windhager R, Dirksen U, Ambros PF, Delattre O, Kovar H, Bock C, Tomazou EM (2017). DNA methylation heterogeneity defines a disease spectrum in Ewing sarcoma. Nature Medicine, DOI: 10.1038/nm.4273.

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