HGG-29. INTEGRATED MOLECULAR PROFILING OF >2000 PAEDIATRIC-TYPE DIFFUSE HIGH-GRADE GLIOMA TUMOURS AND >100 PATIENT-DERIVED MODELS

Résumé fourni par la source

Abstract BACKGROUND Paediatric-type diffuse high-grade glioma (PDHGG) is recognised in the WHO2021 CNS Tumour Classification as biologically distinct from ‘adult-types’, and comprises four major categories based on distinct biology and clinical presentation, though sub-types within these are less well-defined. METHODS Published and unpublished genome/exome/targeted sequencing from n=1593 cases were integrated with n=2027 cases with methylation array profiling, with an overlap of n=761. These were supplemented with varying availability of bulk/single-cell RNAseq, ChIP-seq and ATAC-seq, and analysed alongside data from ~100 patient-derived models representing 16 PDHGG sub-types. RESULTS Around half of cases were diffuse midline glioma with H3K27 alterations (DMG-H3K27), which can be split into sub-types based upon either the specific histone alteration (DMG-H3.3K27M/-H3.1K27M/-EZHIP) or co-segregating pathway activating mutations (DMG-EGFR/-MAPK/-ACVR1). These showed distinct copy number, transcriptomic and epigenetic signatures depending on the anatomical location, replicated in ~50 models established as 2D/3D cultures and CDX/PDX. By contrast, diffuse hemispheric glioma with H3G34 mutations (DHG-H3G34) presented a homogenous genomic landscape (TP53/ATRX/PDGFRA) but with a higher degree of transcriptional diversity in both tumours and models. In high-grade glioma, H3/IDH-wild-type (HGG-WT) samples, receptor tyrosine kinase (RTK) subtypes are split by the presence or absence of co-segregating mutations (BCOR/SETD2/NF1) and copy number changes. Across methylation-based subtypes, genetic drivers are associated with distinct phenotypes or drug responses independent of location. EGFR mutations are largely confined to the highly infiltrative pedHGG_RTK2 hemispheric (enriched in gliomatosis cerebri) and DMG-EGFR (bithalamic glioma) subtypes, whilst PDGFRAmutations span DMG-H3.3K27M, DHG-H3G34, and pedHGG-RTK1, and exhibit a differential drug response to targeted therapies depending on the nature of the alteration. Hypermutant tumours are split between pedHGG-RTK1A and the emerging ‘HGG-E’ subtype. CONCLUSIONS These data aim to catalogue the diversity of PDHGG subtypes in order to identify biologically rational targets, and credential patient-derived models which can be exploited for mechanistic/preclinical studies.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.