Published in

Springer (part of Springer Nature), Acta Neuropathologica, 3(125), p. 359-371

DOI: 10.1007/s00401-012-1077-2

Links

Tools

Export citation

Search in Google Scholar

DNA methylation profiling of medulloblastoma allows robust subclassification and improved outcome prediction using formalin-fixed biopsies.

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Molecular sub-classification is rapidly informing the clinical management of medulloblastoma. However, the disease remains associated with poor outcomes and therapy-associated late-effects, and the majority of patients are not characterized by a validated prognostic biomarker. Here, we investigated the potential of epigenetic DNA methylation for disease sub-classification, particularly in formalin-fixed biopsies, and to identify biomarkers for improved therapeutic individualization. Tumor DNA methylation profiles were assessed, alongside molecular and clinical disease features, in 230 patients primarily from the SIOP-UKCCSG PNET3 clinical trial. We demonstrate by cross-validation in frozen training and formalin-fixed test sets that medulloblastoma comprises four robust DNA methylation subgroups (termed WNT, SHH, G3 and G4), highly related to their transcriptomic counterparts, and which display distinct molecular, clinical and pathological disease characteristics. WNT patients displayed an expected favorable prognosis, while outcomes for SHH, G3 and G4 were equivalent in our cohort. MXI1 and IL8 methylation were identified as novel independent high-risk biomarkers in cross-validated survival models of non-WNT patients, and were validated using non-array methods. Incorporation of MXI1 and IL8 into current survival models significantly improved the assignment of disease-risk; 46% of patients could be classified as ‘favorable-risk’ (>90% survival) compared to 13% using current models, while the high-risk group was reduced to 16% from 30%. DNA methylation profiling enables the robust sub-classification of four disease sub-groups in frozen and routinely-collected/archival formalin-fixed biopsy material, and the incorporation of DNA methylation biomarkers can significantly improve disease-risk stratification. These findings have important implications for future risk-adapted clinical disease management.