Abstract
BACKGROUND: Glioblastoma (GBM) exhibits significant intratumoral heterogeneity. However, the presence and extent of intratumoral heterogeneity of stem-like and differentiated cell components based on methylation profiles remain poorly understood. Furthermore, the utility of integrating methylation profiles with radiomic features (radiomethylomics) for predicting these cellular states has not been explored. METHODS: We analyzed 248 samples from 133 GBM patients, including 157 samples from 42 patients whose tumors were sampled at multiple points. Two distinct methylation-based deconvolution analyses were performed to assess cellular composition. Radiomethylomic models were developed using support vector machines with features extracted from multi-parametric MRI. RESULTS: Multi-sampling analysis revealed that the proportion of stem-like cells among total malignant cells was homogeneously preserved within tumors. Tumors harboring a higher proportion of stem-like cells (stem-like tumors) showed significantly shorter overall survival and diminished benefits from O6-methylguanine DNA methyltransferase (MGMT) promoter methylation. Stem-like tumors showed a strong correlation with the RTK I subtype. Integrating physiological MRI features (diffusion tensor imaging and dynamic susceptibility contrast) with conventional sequences enhanced the performance of radiomethylomic models for predicting stem-like tumor status and prognostic stratification. CONCLUSIONS: Our findings reveal a homogeneous preservation of the proportion of stem-like cells over total malignant cells within GBM, establishing its significance as a tumor-wide feature. The development of radiomethylomic signatures shows potential for noninvasive assessment of tumor stemness, ultimately facilitating personalized treatment strategies in light of the prognostic impact of the feature.