SummaryBackgroundMedulloblastoma is associated with rare hereditary cancer predisposition syndromes; however, consensus medulloblastoma predisposition genes have not been defined and screening guidelines for genetic counselling and testing for paediatric patients are not available. We aimed to assess and define these genes to provide evidence for future screening guidelines.MethodsIn this international, multicentre study, we analysed patients with medulloblastoma from retrospective cohorts (International Cancer Genome Consortium [ICGC] PedBrain, Medulloblastoma Advanced Genomics International Consortium [MAGIC], and the CEFALO series) and from prospective cohorts from four clinical studies (SJMB03, SJMB12, SJYC07, and I-HIT-MED). Whole-genome sequences and exome sequences from blood and tumour samples were analysed for rare damaging germline mutations in cancer predisposition genes. DNA methylation profiling was done to determine consensus molecular subgroups: WNT (MBWNT), SHH (MBSHH), group 3 (MBGroup3), and group 4 (MBGroup4). Medulloblastoma predisposition genes were predicted on the basis of rare variant burden tests against controls without a cancer diagnosis from the Exome Aggregation Consortium (ExAC). Previously defined somatic mutational signatures were used to further classify medulloblastoma genomes into two groups, a clock-like group (signatures 1 and 5) and a homologous recombination repair deficiency-like group (signatures 3 and 8), and chromothripsis was investigated using previously established criteria. Progression-free survival and overall survival were modelled for patients with a genetic predisposition to medulloblastoma.FindingsWe included a total of 1022 patients with medulloblastoma from the retrospective cohorts (n=673) and the four prospective studies (n=349), from whom blood samples (n=1022) and tumour samples (n=800) were analysed for germline mutations in 110 cancer predisposition genes. In our rare variant burden analysis, we compared these against 53 105 sequenced controls from ExAC and identified APC, BRCA2, PALB2, PTCH1, SUFU, and TP53 as consensus medulloblastoma predisposition genes according to our rare variant burden analysis and estimated that germline mutations accounted for 6% of medulloblastoma diagnoses in the retrospective cohort. The prevalence of genetic predispositions differed between molecular subgroups in the retrospective cohort and was highest for patients in the MBSHH subgroup (20% in the retrospective cohort). These estimates were replicated in the prospective clinical cohort (germline mutations accounted for 5% of medulloblastoma diagnoses, with the highest prevalence [14%] in the MBSHH subgroup). Patients with germline APC mutations developed MBWNT and accounted for most (five [71%] of seven) cases of MBWNT that had no somatic CTNNB1 exon 3 mutations. Patients with germline mutations in SUFU and PTCH1 mostly developed infant MBSHH. Germline TP53 mutations presented only in childhood patients in the MBSHH subgroup and explained more than half (eight [57%] of 14...

Objective Functional magnetic resonance imaging is sensitive to the variation in language network patterns. Large populations are needed to rigorously assess atypical patterns, which, even in neurological populations, are a minority. Methods We studied 220 patients with focal epilepsy and 118 healthy volunteers who performed an auditory description decision task. We compared a data-driven hierarchical clustering approach to the commonly used a priori laterality index (LI) threshold (LI < 0.20 as atypical) to classify language patterns within frontal and temporal regions of interest. We explored (n = 128) whether IQ varied with different language activation patterns. Results The rate of atypical language among healthy volunteers (2.5%) and patients (24.5%) agreed with previous studies; however, we found 6 patterns of atypical language: a symmetrically bilateral, 2 unilaterally crossed, and 3 right dominant patterns. There was high agreement between classification methods, yet the cluster analysis revealed novel correlations with clinical features. Beyond the established association of left-handedness, early seizure onset, and vascular pathology with atypical language, cluster analysis identified an association of handedness with frontal lateralization, early seizure onset with temporal lateralization, and left hemisphere focus with a unilateral right pattern. Intelligence quotient was not significantly different among patterns. Interpretation Language dominance is a continuum; however, our results demonstrate meaningful thresholds in classifying laterality. Atypical language patterns are less frequent but more variable than typical language patterns, posing challenges for accurate presurgical planning. Language dominance should be assessed on a regional rather than hemispheric basis, and clinical characteristics should inform evaluation of atypical language dominance. Reorganization of language is not uniformly detrimental to language functioning.