DNA methylation-based classification of glioneuronal tumours synergises with histology and radiology to refine accurate molecular stratification.

AIMS: Glioneuronal tumours (GNTs) are poorly distinguished by their histology and lack robust diagnostic indicators. Previously, we showed that common GNTs comprise two molecularly distinct groups, correlating poorly with histology. To refine diagnosis, we constructed a methylation-based model for GNT classification, subsequently evaluating standards for molecular stratification by methylation, histology and radiology. METHODS: We comprehensively analysed methylation, radiology and histology for 83 GNT samples: a training cohort of 49, previously classified into molecularly defined groups by genomic profiles, plus a validation cohort of 34. We identified histological and radiological correlates to molecular classification and constructed a methylation-based support vector machine (SVM) model for prediction. Subsequently, we contrasted methylation, radiological and histological classifications in validation GNTs. RESULTS: By methylation clustering, all training and 23/34 validation GNTs segregated into two groups, the remaining 11 clustering alongside control cortex. Histological review identified prominent astrocytic/oligodendrocyte-like components, dysplastic neurons and a specific glioneuronal element as discriminators between groups. However, these were present in only a subset of tumours. Radiological review identified location, margin definition, enhancement and T2 FLAIR-rim sign as discriminators. When validation GNTs were classified by SVM, 22/23 classified correctly, comparing favourably against histology and radiology that resolved 17/22 and 15/21, respectively, where data were available for comparison. CONCLUSIONS: Diagnostic criteria inadequately reflect glioneuronal tumour biology, leaving a proportion unresolvable. In the largest cohort of molecularly defined glioneuronal tumours, we develop molecular, histological and radiological approaches for biologically meaningful classification and demonstrate almost all cases are resolvable, emphasising the importance of an integrated diagnostic approach.

Identifying cellular signalling molecules in developmental disorders of the brain: Evidence from focal cortical dysplasia and tuberous sclerosis.

AIMS: We understand little of the pathogenesis of developmental cortical lesions, because we understand little of the diversity of the cell types that contribute to the diseases or how those cells interact. We tested the hypothesis that cellular diversity and cell-cell interactions play an important role in these disorders by investigating the signalling molecules in the commonest cortical malformations that lead to childhood epilepsy, focal cortical dysplasia (FCD) and tuberous sclerosis (TS). METHODS: Transcriptional profiling clustered cases into molecularly distinct groups. Using gene expression data, we identified the secretory signalling molecules in FCD/TS and characterised the cell types expressing these molecules. We developed a functional model using organotypic cultures. RESULTS: We identified 113 up-regulated secretory molecules in FCDIIB/TS. The top 12 differentially expressed genes (DEGs) were validated by immunohistochemistry. This highlighted two molecules, Chitinase 3-like protein 1 (CHI3L1) and C-C motif chemokine ligand 2 (CCL2) (MCP1) that were expressed in a unique population of small cells in close proximity to balloon cells (BC). We then characterised these cells and developed a functional model in organotypic slice cultures. We found that the number of CHI3L1 and CCL2 expressing cells decreased following inhibition of mTOR, the main aberrant signalling pathway in TS and FCD. CONCLUSIONS: Our findings highlight previously uncharacterised small cell populations in FCD and TS which express specific signalling molecules. These findings indicate a new level of diversity and cellular interactions in cortical malformations and provide a generalisable approach to understanding cell-cell interactions and cellular heterogeneity in developmental neuropathology.

A case series of Diffuse Glioneuronal Tumours with Oligodendroglioma-like features and Nuclear Clusters (DGONC).

In this study, we report three paediatric cases of Diffuse Glioneuronal Tumours with Oligodendroglioma-like features and Nuclear Clusters (DGONC).

Methylation-based algorithms for diagnosis: experience from neuro-oncology.

Brain tumours are the most common tumour-related cause of death in young people. Survivors are at risk of significant disability, at least in part related to the effects of treatment. Therefore, there is a need for a precise diagnosis that stratifies patients for the most suitable treatment, matched to the underlying biology of their tumour. Although traditional histopathology has been accurate in predicting treatment responses in many cases, molecular profiling has revealed a remarkable, previously unappreciated, level of biological complexity in the classification of these tumours. Among different molecular technologies, DNA methylation profiling has had the most pronounced impact on brain tumour classification. Furthermore, using machine learning-based algorithms, DNA methylation profiling is changing diagnostic practice. This can be regarded as an exemplar for how molecular pathology can influence diagnostic practice and illustrates some of the unanticipated benefits and risks. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

DNA methylation-based profiling for paediatric CNS tumour diagnosis and treatment: a population-based study.

BACKGROUND: Marked variation exists in the use of genomic data in tumour diagnosis, and optimal integration with conventional diagnostic technology remains uncertain despite several studies reporting improved diagnostic accuracy, selection for targeted treatments, and stratification for trials. Our aim was to assess the added value of molecular profiling in routine clinical practice and the impact on conventional and experimental treatments. METHODS: This population-based study assessed the diagnostic and clinical use of DNA methylation-based profiling in childhood CNS tumours using two large national cohorts in the UK. In the diagnostic cohort-which included routinely diagnosed CNS tumours between Sept 1, 2016, and Sept 1, 2018-we assessed how the methylation profile altered or refined diagnosis in routine clinical practice and estimated how this would affect standard patient management. For the archival cohort of diagnostically difficult cases, we established how many cases could be solved using modern standard pathology, how many could only be solved using the methylation profile, and how many remained unsolvable. FINDINGS: Of 484 patients younger than 20 years with CNS tumours, 306 had DNA methylation arrays requested by the neuropathologist and were included in the diagnostic cohort. Molecular profiling added a unique contribution to clinical diagnosis in 107 (35%; 95% CI 30-40) of 306 cases in routine diagnostic practice-providing additional molecular subtyping data in 99 cases, amended the final diagnosis in five cases, and making potentially significant predictions in three cases. We estimated that it could change conventional management in 11 (4%; 95% CI 2-6) of 306 patients. Among 195 historically difficult-to-diagnose tumours in the archival cohort, 99 (51%) could be diagnosed using standard methods, with the addition of methylation profiling solving a further 34 (17%) cases. The remaining 62 (32%) cases were unresolved despite specialist pathology and methylation profiling. INTERPRETATION: Together, these data provide estimates of the impact that could be expected from routine implementation of genomic profiling into clinical practice, and indicate limitations where additional techniques will be required. We conclude that DNA methylation arrays are a useful diagnostic adjunct for childhood CNS tumours. FUNDING: The Brain Tumour Charity, Children with Cancer UK, Great Ormond Street Hospital Children's Charity, Olivia Hodson Cancer Fund, Cancer Research UK, and the National Institute of Health Research.

Association of low income with pulmonary disease progression in smokers with and without chronic obstructive pulmonary disease.

Low socioeconomic status has been associated with chronic obstructive pulmonary disease (COPD) but little is known about its impact on disease progression. We assessed the association of income to symptoms, pulmonary disease severity and progression in smokers with and without COPD. The COPDGene cohort of 4826 smokers who reported annual income in phase 2 was analysed. Those who reported annual income

Tumour compartment transcriptomics demonstrates the activation of inflammatory and odontogenic programmes in human adamantinomatous craniopharyngioma and identifies the MAPK/ERK pathway as a novel therapeutic target.

Adamantinomatous craniopharyngiomas (ACPs) are clinically challenging tumours, the majority of which have activating mutations in CTNNB1. They are histologically complex, showing cystic and solid components, the latter comprised of different morphological cell types (e.g. ß-catenin-accumulating cluster cells and palisading epithelium), surrounded by a florid glial reaction with immune cells. Here, we have carried out RNA sequencing on 18 ACP samples and integrated these data with an existing ACP transcriptomic dataset. No studies so far have examined the patterns of gene expression within the different cellular compartments of the tumour. To achieve this goal, we have combined laser capture microdissection with computational analyses to reveal groups of genes that are associated with either epithelial tumour cells (clusters and palisading epithelium), glial tissue or immune infiltrate. We use these human ACP molecular signatures and RNA-Seq data from two ACP mouse models to reveal that cell clusters are molecularly analogous to the enamel knot, a critical signalling centre controlling normal tooth morphogenesis. Supporting this finding, we show that human cluster cells express high levels of several members of the FGF, TGFB and BMP families of secreted factors, which signal to neighbouring cells as evidenced by immunostaining against the phosphorylated proteins pERK1/2, pSMAD3 and pSMAD1/5/9 in both human and mouse ACP. We reveal that inhibiting the MAPK/ERK pathway with trametinib, a clinically approved MEK inhibitor, results in reduced proliferation and increased apoptosis in explant cultures of human and mouse ACP. Finally, we analyse a prominent molecular signature in the glial reactive tissue to characterise the inflammatory microenvironment and uncover the activation of inflammasomes in human ACP. We validate these results by immunostaining against immune cell markers, cytokine ELISA and proteome analysis in both solid tumour and cystic fluid from ACP patients. Our data support a new molecular paradigm for understanding ACP tumorigenesis as an aberrant mimic of natural tooth development and opens new therapeutic opportunities by revealing the activation of the MAPK/ERK and inflammasome pathways in human ACP.

Comprehensive molecular characterisation of epilepsy-associated glioneuronal tumours.

Glioneuronal tumours are an important cause of treatment-resistant epilepsy. Subtypes of tumour are often poorly discriminated by histological features and may be difficult to diagnose due to a lack of robust diagnostic tools. This is illustrated by marked variability in the reported frequencies across different epilepsy surgical series. To address this, we used DNA methylation arrays and RNA sequencing to assay the methylation and expression profiles within a large cohort of glioneuronal tumours. By adopting a class discovery approach, we were able to identify two distinct groups of glioneuronal tumour, which only partially corresponded to the existing histological classification. Furthermore, by additional molecular analyses, we were able to identify pathogenic mutations in BRAF and FGFR1, specific to each group, in a high proportion of cases. Finally, by interrogating our expression data, we were able to show that each molecular group possessed expression phenotypes suggesting different cellular differentiation: astrocytic in one group and oligodendroglial in the second. Informed by this, we were able to identify CCND1, CSPG4, and PDGFRA as immunohistochemical targets which could distinguish between molecular groups. Our data suggest that the current histological classification of glioneuronal tumours does not adequately represent their underlying biology. Instead, we show that there are two molecular groups within glioneuronal tumours. The first of these displays astrocytic differentiation and is driven by BRAF mutations, while the second displays oligodendroglial differentiation and is driven by FGFR1 mutations.