[Abstract unavailable

Summary Accurate pathological diagnosis is crucial for optimal management of cancer patients. For the ~100 known central nervous system (CNS) tumour entities, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variability in the histopathological diagnosis of many tumour types. We herein present the development of a comprehensive approach for DNA methylation-based CNS tumour classification across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that availability of this method may have substantial impact on diagnostic precision compared with standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility we have designed a free online classifier tool (www.molecularneuropathology.org) requiring no additional onsite data processing. Our results provide a blueprint for the generation of machine learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

SUMMARYPurpose: Focal cortical dysplasias (FCD) are localized regions of malformed cerebral cortex and are very frequently associated with epilepsy in both children and adults. A broad spectrum of histopathology has been included in the diagnosis of FCD. An ILAE task force proposes an international consensus classification system to better characterize specific clinicopathological FCD entities.

Summary Hippocampal sclerosis (HS) is the most frequent histopathology encountered in patients with drug‐resistant temporal lobe epilepsy (TLE). Over the past decades, various attempts have been made to classify specific patterns of hippocampal neuronal cell loss and correlate subtypes with postsurgical outcome. However, no international consensus about definitions and terminology has been achieved. A task force reviewed previous classification schemes and proposes a system based on semiquantitative hippocampal cell loss patterns that can be applied in any histopathology laboratory. Interobserver and intraobserver agreement studies reached consensus to classify three types in anatomically well‐preserved hippocampal specimens: HS International League Against Epilepsy (ILAE) type 1 refers always to severe neuronal cell loss and gliosis predominantly in CA1 and CA4 regions, compared to CA1 predominant neuronal cell loss and gliosis (HS ILAE type 2), or CA4 predominant neuronal cell loss and gliosis (HS ILAE type 3). Surgical hippocampus specimens obtained from patients with TLE may also show normal content of neurons with reactive gliosis only (no‐HS). HS ILAE type 1 is more often associated with a history of initial precipitating injuries before age 5 years, with early seizure onset, and favorable postsurgical seizure control. CA1 predominant HS ILAE type 2 and CA4 predominant HS ILAE type 3 have been studied less systematically so far, but some reports point to less favorable outcome, and to differences regarding epilepsy history, including age of seizure onset. The proposed international consensus classification will aid in the characterization of specific clinicopathologic syndromes, and explore variability in imaging and electrophysiology findings, and in postsurgical seizure control.

SummaryBackgroundInternational consensus recognises four medulloblastoma molecular subgroups: WNT (MBWNT), SHH (MBSHH), group 3 (MBGrp3), and group 4 (MBGrp4), 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.MethodsIn 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.FindingsSeven robust and reproducible primary molecular subgroups of childhood medulloblastoma were identified. MBWNT remained unchanged and each remaining consensus subgroup was split in two. MBSHH was split into age-dependent subgroups corresponding to infant (<4·3 years; MBSHH-Infant; n=65) and childhood patients (≥4·3 years; MBSHH-Child; n=38). MBGrp3 and MBGrp4 were each split into high-risk (MBGrp3-HR [n=65] and MBGrp4-HR [n=85]) and low-risk (MBGrp3-LR [n=50] and MBGrp4-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]).InterpretationThe discovery of seven novel, clinically significant subgrou...