Abstract

Abstract Ependymoma (EPN) is the second most common malignant paediatric brain tumour with a five-year survival rate of only 25% following relapse. While molecular heterogeneity between EPN tumours is well understood, little is known concerning spatially-distinct intratumour heterogeneity within patients. In this context, we present a multi-omics integration of expression data at transcriptomic and metabolomic levels revealing intratumour heterogeneity and novel therapeutic targets. Surgically resected ependymoma tissue from two epigenetic subgroups, posterior fossa-A (PF-A) and supratentorial RELA, were first homogenised and polar metabolites, lipids and RNA simultaneously extracted from the same cellular population. Using liquid chromatography-mass spectrometry (LC-MS) and RNAseq 115 metabolites and 1580 upregulated genes were identified between the two subgroups, therefore validating previously reported genetic clustering of these two subtypes. Sampling of anatomically distinct regions was performed between eight PF-A EPN patients and multi-omic data was compared across 28 intratumour regions, with at least 3 different regions per patient. Integration of genes and metabolites revealed 124 dysregulated metabolic pathways, encompassing 156 genes and 49 metabolites. A large number of interactions occur in the gluconeogenesis and glycine pathways in 6 out of 8 patients, putatively representing therapeutically relevant ubiquitous metabolic pathways critical for EPN survival. Each anatomical region also presented at least one unique gene-metabolite interaction demonstrating heterogeneity within and across PF-A EPN tumours. A subset of the eight most prevalent genes across patients (GAD1, NT5C, FBP1, FMO3, HK3, TALDO1, NT5E, ALDH3A1) were selected for in vitro metabolic assays using 10 repurposed cytotoxic agents against PF-A EPN cell lines derived from intratumour regions of the same patient. 5/8 genes map within the gluconeogenesis metabolic pathway, further highlighting its significance within PF-A EPN. This is the first instance where multi-omic data integration and intratumour heterogeneity has been investigated for paediatric EPN revealing novel potential targets in the context of gene-metabolite correlations.

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