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Rapid and reliable detection of disease-associated DNA methylation patterns has major potential to advance molecular diagnostics and underpin research investigations. We describe the development and validation of minimal methylation classifier (MIMIC), combining CpG signature design from genome-wide datasets, multiplex-PCR and detection by single-base extension and MALDI-TOF mass spectrometry, in a novel method to assess multi-locus DNA methylation profiles within routine clinically-applicable assays. We illustrate the application of MIMIC to successfully identify the methylation-dependent diagnostic molecular subgroups of medulloblastoma (the most common malignant childhood brain tumour), using scant/low-quality samples remaining from the most recently completed pan-European medulloblastoma clinical trial, refractory to analysis by conventional genome-wide DNA methylation analysis. Using this approach, we identify critical DNA methylation patterns from previously inaccessible cohorts, and reveal novel survival differences between the medulloblastoma disease subgroups with significant potential for clinical exploitation.

Background: International consensus recognises four medulloblastoma molecular subgroups: WNT (MB WNT ), SHH (MB SHH ), group 3 (MB Grp3 ), and group 4 (MB Grp4 ), each defined by their characteristic genome-wide transcriptomic and DNA methylomic profiles. These subgroups have distinct clinicopathological and molecular features, and underpin current disease subclassification and initial subgroup-directed therapies that are underway in clinical trials. However, substantial biological heterogeneity and differences in survival are apparent within each subgroup, which remain to be resolved. We aimed to investigate whether additional molecular subgroups exist within childhood medulloblastoma and whether these could be used to improve disease subclassification and prognosis predictions., Methods: In this retrospective cohort study, we assessed 428 primary medulloblastoma samples collected from UK Children's Cancer and Leukaemia Group (CCLG) treatment centres (UK), collaborating European institutions, and the UKCCSG-SIOP-PNET3 European clinical trial. An independent validation cohort (n=276) of archival tumour samples was also analysed. We analysed samples from patients with childhood medulloblastoma who were aged 0-16 years at diagnosis, and had central review of pathology and comprehensive clinical data. We did comprehensive molecular profiling, including DNA methylation microarray analysis, and did unsupervised class discovery of test and validation cohorts to identify consensus primary molecular subgroups and characterise their clinical and biological significance. We modelled survival of patients aged 3-16 years in patients (n=215) who had craniospinal irradiation and had been treated with a curative intent., Findings: Seven robust and reproducible primary molecular subgroups of childhood medulloblastoma were identified. MB WNT remained unchanged and each remaining consensus subgroup was split in two. MB SHH was split into age-dependent subgroups corresponding to infant (<4·3 years; MB SHH-Infant ; n=65) and childhood patients (≥4·3 years; MB SHH-Child ; n=38). MB Grp3 and MB Grp4 were each split into high-risk (MB Grp3-HR [n=65] and MB Grp4-HR [n=85]) and low-risk (MB Grp3-LR [n=50] and MB Grp4-LR [n=73]) subgroups. These biological subgroups were validated in the independent cohort. We identified features of the seven subgroups that were predictive of outcome. Cross-validated subgroup-dependent survival models, incorporating these novel subgroups along with secondary clinicopathological and molecular features and established disease risk-factors, outperformed existing disease risk-stratification schemes. These subgroup-dependent models stratified patients into four clinical risk groups for 5-year progression-free survival: favourable risk (54 [25%] of 215 patients; 91% survival [95% CI 82-100]); standard risk (50 [23%] patients; 81% survival [70-94]); high-risk (82 [38%] patients; 42% survival [31-56]); and very high-risk (29 [13%] patients; 28% survival [14-56])., Interpretation: The discovery of seven novel, clinically significant subgroups improves disease risk-stratification and could inform treatment decisions. These data provide a new foundation for future research and clinical investigations., Funding: Cancer Research UK, The Tom Grahame Trust, Star for Harris, Action Medical Research, SPARKS, The JGW Patterson Foundation, The INSTINCT network (co-funded by The Brain Tumour Charity, Great Ormond Street Children's Charity, and Children with Cancer UK)., (Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

The identification of key tumorigenic events in Sonic Hedgehog (SHH) subgroup medulloblastomas (MBSHH) will be essential for the development of individualized therapies and improved outcomes. However, beyond confirmation of characteristic SHH pathway mutations, recent genome-wide sequencing studies have not revealed commonly mutated genes with widespread relevance as potential therapeutic targets. We therefore examined any role for epigenetic DNA methylation events in MBSHH using a cross-species approach to candidate identification, prioritization and validation. MBSHH-associated DNA methylation events were first identified in 216 subgrouped human medulloblastomas (50 MBSHH, 28 Wnt/Wingless, 44 Group 3 and 94 Group 4) and their conservation then assessed in tumors arising from four independent murine models of Shh medulloblastoma, alongside any role in tumorigenesis using functional assessments in mouse and human models. This strategy identified widespread regional CpG hypo-methylation of VAV1, leading to its elevated expression, as a conserved aberrant epigenetic event, which characterizes the majority of MBSHH tumors in both species, and is associated with a poor outcome in MBSHH patients. Moreover, direct modulation of VAV1 in mouse and human models revealed a critical role in tumor maintenance, and its abrogation markedly reduced medulloblastoma growth. Further, Vav1 activity regulated granule neuron precursor germinal zone exit and migration initiation in an ex vivo model of early postnatal cerebellar development. These findings establish VAV1 as a critical epigenetically regulated oncogene with a key role in MBSHH maintenance, and highlight its potential as a validated therapeutic target and prognostic biomarker for the improved therapy of medulloblastoma.

Molecular subclassification 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 subclassification, 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 from 30 to 16 %. DNA methylation profiling enables the robust subclassification of four disease subgroups 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.

Medulloblastoma arises in the cerebellum and is the most common malignant brain tumour of childhood, however its molecular basis is not well understood. To assess the role of aberrant epigenetic events in medulloblastoma and identify critical genes in its development, we profiled the promoter methylation status of 11 candidate tumour-suppressor genes (TSGs; p14(ARF), p15(INK4b), p16(INK4a), CASP8, HIC1, EDNRB, TIMP3, TP73, TSLC1, RIZ1 and RASSF1A) in medulloblastoma cell lines, primary tumours and the normal cerebellum. Gene-specific TSG methylation was a significant feature of both medulloblastomas and the cerebellum. Extensive hypermethylation of RASSF1A was detected frequently in medulloblastomas but not in the normal cerebellum (41/44 primary tumours versus 0/5 normal cerebella). In contrast, complete methylation of HIC1 and CASP8 in a subset of primary tumours (17/44 and 14/39) occurred against a consistent background of partial methylation in the normal cerebellum. These data therefore indicate that extensive methylation of RASSF1A, HIC1 and CASP8 are tumour-specific events in medulloblastoma. Moreover, methylation of these genes in medulloblastoma cell lines was associated with their epigenetic transcriptional silencing and methylation-dependent re-expression following treatment with the DNA methyltransferase inhibitor, 5-aza-2'-deoxycytidine. The remaining genes studied showed either low frequency methylation (p14(ARF), p16(INK4a), RIZ1; <7% of cases), no evidence of methylation (p15(INK4b), TIMP3, TP73, TSLC1), or comparable patterns of methylation in the normal cerebellum (EDNRB), suggesting that their hypermethylation does not play a major role in medulloblastoma. Our data demonstrate that tumour-specific hypermethylation affects only a subset of genes, and does not support the existence of a concordant methylation phenotype in this disease. We conclude that epigenetic TSG inactivation is a significant feature of medulloblastoma, and identify RASSF1A, HIC1 and CASP8 as potentially critical genes in its pathogenesis. Furthermore, methylation observed in the normal cerebellum emphasises the requirement for appropriate control tissues when assessing the tumour-specificity of TSG hypermethylation.