DNA methylation classification in diffuse glioma shows little spatial heterogeneity after adjusting for tumor purity

Abstract

Intratumoral heterogeneity is a hallmark of diffuse gliomas. We used neuronavigation to acquire 133 imageguided and spatially-separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma, which we characterized using DNA methylation arrays. Samples were obtained from regions with and without imaging abnormalities. Methylation profiles were analyzed to devise a three-dimensional reconstruction of genetic and epigenetic heterogeneity. Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and largely explains apparent epigenetic spatial heterogeneity. Indeed, we observed that DNA methylation subtypes are highly conserved in space after adjusting for tumor purity. Genome-wide heterogeneity analysis showed equal or increased heterogeneity among normal tissue when compared to tumor. These findings were validated in a separate cohort of 61 multi-sector tumor and 64 normal samples. Our findings underscore the infiltrative nature of diffuse gliomas and suggest that heterogeneity in DNA methylation is innate to somatic cells and not a characteristic feature of this tumor type.

Single-cell multimodal glioma analyses reveal epigenetic regulators of cellular plasticity and environmental stress response

“…Our observation that genetic events likely precede epigenetic and transcriptomic diversification led us to ask whether epigenetic diversity accelerates tumor evolution by promoting cell survival in resource-deprived tumor environments (e.g., hypoxia or therapeutic exposures). To address this question and extend the generalizability of our findings, we sought to determine variable intratumoral DNA methylation levels in large-scale bulk glioma studies (Barthel et al, 2019;Ceccarelli et al, 2016;Verburg et al, 2020). Since these datasets were generated using DNA methylation microarrays, we used our single-cell DNA methylation data to define a microarray metric that quantified the DNA methylation instability of gene regions prone to epimutation ( Figure 1E and Figure 5A).…”

“…We next applied the DNA methylation instability metric to 119 image-guided stereotactic biopsies taken from spatially distinct regions across IDH-wild-type (n = 57 biopsies, 6 patients) and IDH-mutant (n = 62 biopsies, n = 8 patients) tumors (Verburg et al, 2020). This enabled us to quantify the physical distance between a biopsied sample and specific radiographic features that delineate the tumor's center (e.g., magnetic resonance imaging contrast-enhanced region, Figure S14D).…”