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  • 1
    Keywords: EXPRESSION ; SURVIVAL ; PATHWAY ; CLASSIFICATION ; DISEASE ; DISTINCT ; TUMORS ; IMPACT ; prognosis ; BIOMARKERS ; NERVOUS-SYSTEM ; C-MYC ; MYCN ; medulloblastoma ; CHILDHOOD MEDULLOBLASTOMA ; SUBGROUPS ; MYC ; STRATIFICATION ; Molecular subgroup
    Abstract: The MYC oncogenes are the most commonly amplified loci in medulloblastoma, and have previously been proposed as biomarkers of adverse disease prognosis by us and others. Here, we report focussed and comprehensive investigations of MYCC, MYCN and MYCL in an extensive medulloblastoma cohort (n = 292), aimed to define more precisely their biological significance and optimal clinical application to direct improved disease risk-stratification and individualisation of therapy. MYCC and MYCN expression elevations were multifactorial, associated with high-risk (gene amplification, large-cell/anaplastic pathology (LCA)) and favourable-risk (WNT/SHH molecular subgroups) disease features. Highly variable cellular gene amplification patterns underlay overall MYC copy number elevations observed in tumour biopsies; we used these alternative measures together to define quantitative methodologies and thresholds for amplification detection in routinely collected tumour material. MYCC and MYCN amplification, but not gain, each had independent prognostic significance in non-infants (〉/=3.0-16.0 years), but MYCC conferred a greater hazard to survival than MYCN when considered across this treatment group. MYCN's weaker group-wide survival relationship may be explained by its pleiotropic behaviour between clinical disease-risk groups; MYCN predicted poor prognosis in clinical high-risk (metastatic (M+) or LCA), but not standard-risk, patients. Extending these findings, survival decreased in proportion to the total number of independently significant high-risk features present (LCA, M+ or MYCC/MYCN amplification). This cumulative-risk model defines a patient group characterised by 〉/=2 independent risk-factors and an extremely poor prognosis (〈15% survival), which can be identified straightforwardly using the reported MYC amplification detection methodologies alongside clinical assessments, enabling targeting for novel/intensified therapies in future clinical studies.
    Type of Publication: Journal article published
    PubMed ID: 22139329
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  • 2
    Abstract: 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.
    Type of Publication: Journal article published
    PubMed ID: 23291781
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