Abstract

Abstract AIMS Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic innovation in neuro- oncology. Gliomas typically exhibit a spectrum of genetic mutations, reflecting multiple, potentially complex molecular interactions, and vary widely in their imaging appearances across size, morphology, texture, anatomical distribution, and many other spatial properties. This multifaceted diversity obscures the relationship be- tween tumour genotypic and imaging features, and their joint influence on disease evolution and treatment susceptibility. Though opaque to simple statistical methods, it may nonetheless be accessible to models with the expressivity to capture complex interactions between many different factors. METHOD Studying an international sample of 4064 IDH-wildtype glioblastoma, IDH-mutant oligodendroglioma and astrocytoma, deploying an in-house developed state-of-the-art lesion segmentation model, here we map the characteristic distribution of tumour tissue components across the brain and link their spatial properties lesion genetics and epigenetics. RESULTS We identify radical differences in tumour spatial topology related not only to diagnosis, but also age, sex, and genetic/epigenetic markers inclusive of TERT, EGFR, and MGMT methylation status. Lesions were equally common across left and right cerebral hemispheres, but significantly larger at presentation when right-sided (p<0.0001), indicating these lesions present later. Both glioblastoma and astrocytoma were commonly temporally based, though oligodendroglioma were often frontal. EGFR amplification was more common in right temporal lesions, whilst MGMT methylation and TERT appeared more bilateral. CONCLUSIONS Our results reveal the deep topological structure of gliomas, enabling richer, more closely individuating phenotyping, the development of more robust predictive models of treatment and prognosis, and illuminating multi- modal associations of potential mechanistic significance.

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