DNA methylation–based deconvolution study of glioblastoma heterogeneity and identification of cell compositions associated with patient survival

Background Isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) is an aggressive, heterogeneous brain tumor with limited treatment options. This study employs DNA methylation-based deconvolution of GBM to define its cellular composition and its association with patient outcomes. Methods We generated oligodendroglial precursor cells at various developmental stages from enriched human neural progenitor cultures and used their DNA methylation signatures, along with published signatures of brain tumor cell types and the tumor microenvironment, to deconvolve 263 adult GBMs (Heidelberg cohort). An independent cohort of 199 GBMs from The Cancer Genome Atlas (TCGA) and GEO, all treated with standard-of-care therapy, was similarly deconvolved. Kaplan-Meier survival analysis was used to assess the prognostic value of the neoplastic components. Results GBM deconvolution uncovered distinct cellular compositions that differed between the neoplastic and non-neoplastic component. The neoplastic fractions averaged 70% of the tumor bulk and were predominantly composed of oligodendrocyte-like (43%) cell populations, in addition to oligodendrocyte precursor-like (27%), astrocyte-like (19%), and mesenchymal stem cell-like (11%) populations. The non-neoplastic fractions were enriched for macrophages, vascular cells, and immune cell populations. A higher oligodendrocyte-like signature was linked to poorer survival (median survival 14.3 vs. 15.3 months; P = .017), while a higher astrocyte-like signature correlated with improved survival (15.3 vs. 13.4 months; P = .044). Further, a higher astrocyte-to-oligodendrocyte ratio was associated with significantly longer survival (15.8 vs. 11.9 months; P < .00011). Conclusions The methylation-based deconvolution data and analyses provided insight into GBM heterogeneity and highlighted the prognostic potential of the astrocyte-to-oligodendrocyte ratio and its application in personalized treatment strategies.