The molecular landscape and associated clinical experience in infant medulloblastoma: prognostic significance of second-generation subtypes.

AIMS: Biomarker-driven therapies have not been developed for infant medulloblastoma (iMB). We sought to robustly sub-classify iMB, and proffer strategies for personalized, risk-adapted therapies. METHODS: We characterized the iMB molecular landscape, including second-generation subtyping, and the associated retrospective clinical experience, using large independent discovery/validation cohorts (n = 387). RESULTS: iMBGrp3 (42%) and iMBSHH (40%) subgroups predominated. iMBGrp3 harboured second-generation subtypes II/III/IV. Subtype II strongly associated with large-cell/anaplastic pathology (LCA; 23%) and MYC amplification (19%), defining a very-high-risk group (0% 10yr overall survival (OS)), which progressed rapidly on all therapies; novel approaches are urgently required. Subtype VII (predominant within iMBGrp4 ) and subtype IV tumours were standard risk (80% OS) using upfront CSI-based therapies; randomized-controlled trials of upfront radiation-sparing and/or second-line radiotherapy should be considered. Seventy-five per cent of iMBSHH showed DN/MBEN histopathology in discovery and validation cohorts (P < 0.0001); central pathology review determined diagnosis of histological variants to WHO standards. In multivariable models, non-DN/MBEN pathology was associated significantly with worse outcomes within iMBSHH . iMBSHH harboured two distinct subtypes (iMBSHH-I/II ). Within the discriminated favourable-risk iMBSHH DN/MBEN patient group, iMBSHH-II had significantly better progression-free survival than iMBSHH-I , offering opportunities for risk-adapted stratification of upfront therapies. Both iMBSHH-I and iMBSHH-II showed notable rescue rates (56% combined post-relapse survival), further supporting delay of irradiation. Survival models and risk factors described were reproducible in independent cohorts, strongly supporting their further investigation and development. CONCLUSIONS: Investigations of large, retrospective cohorts have enabled the comprehensive and robust characterization of molecular heterogeneity within iMB. Novel subtypes are clinically significant and subgroup-dependent survival models highlight opportunities for biomarker-directed therapies.

Minimal methylation classifier (MIMIC): A novel method for derivation and rapid diagnostic detection of disease-associated DNA methylation signatures.

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.