Abstract Background Within the WHO2021 CNS Tumour Classification, oncohistone H3-mutations define around half of paediatric-type diffuse high grade glioma, however the remaining tumours (H3-WT-PDHGG) are less well described. Methods Published and unpublished DNA sequencing from n = 1601 H3-WT-PDHGG cases were integrated with n = 1847 cases with methylation array profiling, along with bulk (n = 251) and single-cell (n = 65) RNAseq data. Results Within H3-WT high-grade glioma, a total of 11 MNP12. 8-defined subgroups were found to have a peak incidence 18years, excluding infant hemispheric glioma. Clustering of methylation data by tSNE/UMAP highlighted two highly distinct superclusters, with multiple subgroups within each. SuperclusterI was defined by radiation-induced secondary and/or hypermutant tumours, incorporating HGG-E (n = 44), cerebellar-enriched tumours (n = 38), and the paediatric RTK1 group (n = 295), further split into A, B and C subgroups. There were profound molecular differences between RTK1A and B/C subgroups, with 1A harbouring few CNAs and many more SNVs (SETD2, NF1), even in the absence of a hypermutator phenotype (also enriched compared to RTK1B/C), as well as a significantly longer overall survival. Distinct from these subgroups was SuperclusterII, which included pedHGG-RTK2A/B (n = 117), but also pedHGGA/B (n = 84) and pedHGG-MYCN (n = 122) subgroups, in addition to the predominantly H3-WT DMG-EGFR (n = 86). Although seemingly disparate, a common feature of these tumours was a highly infiltrative phenotype, either involving multiple cerebral lobes (gliomatosis cerebri) or thalami (bithalamic glioma). Analogous to pedHGG-RTK1, RTK2A harboured few CNAs and more CNVs (BCOR, PIK3CA), and a longer survival compared with 2B. Integrating subgroup-specific differential methylation and gene expression identified subgroup-specific epigenetic regulation of numerous developmentally-restricted transcription factors associated with their distinct neurodevelopmental origins; combining deconvolution approaches to bulk analyses with integrated scRNAseq allowed for identification of subgroup-specific immune cell annotation. Conclusion H3-WT-PDHGG segregate into two major classes with common clinical features, but each with multiple subgroups harbouring key molecular and phenotypic differences.
Mackay et al. (Fri,) studied this question.