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.

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.

A tailored molecular profiling programme for children with cancer to identify clinically actionable genetic alterations.

BACKGROUND: For children with cancer, the clinical integration of precision medicine to enable predictive biomarker-based therapeutic stratification is urgently needed. METHODS: We have developed a hybrid-capture next-generation sequencing (NGS) panel, specifically designed to detect genetic alterations in paediatric solid tumours, which gives reliable results from as little as 50 ng of DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. In this study, we offered an NGS panel, with clinical reporting via a molecular tumour board for children with solid tumours. Furthermore, for a cohort of 12 patients, we used a circulating tumour DNA (ctDNA)-specific panel to sequence ctDNA from matched plasma samples and compared plasma and tumour findings. RESULTS: A total of 255 samples were submitted from 223 patients for the NGS panel. Using FFPE tissue, 82% of all submitted samples passed quality control for clinical reporting. At least one genetic alteration was detected in 70% of sequenced samples. The overall detection rate of clinically actionable alterations, defined by modified OncoKB criteria, for all sequenced samples was 51%. A total of 8 patients were sequenced at different stages of treatment. In 6 of these, there were differences in the genetic alterations detected between time points. Sequencing of matched ctDNA in a cohort of extracranial paediatric solid tumours also identified a high detection rate of somatic alterations in plasma. CONCLUSION: We demonstrate that tailored clinical molecular profiling of both tumour DNA and plasma-derived ctDNA is feasible for children with solid tumours. Furthermore, we show that a targeted NGS panel-based approach can identify actionable genetic alterations in a high proportion of patients.