CNSC-23. MULTIDIMENSIONAL SPATIAL AND MOLECULAR MODELING OF REFRACTORY GLIOBLASTOMA EVOLUTION

Abstract Glioblastoma (GBM) is a high-grade glioma marked by high intratumoral molecular heterogeneity, resistance to therapy and poor prognosis. Leveraging a multisampling approach, we investigated the relation between genomic and physical distance, and whether this information was captured by imaging phenotypes and patient outcomes. We profiled 79 spatially distinct tumor regions from 24 GBM patients (F/M = 0.60; median age = 65.5 years) using deep whole-exome sequencing (>300x coverage). Genomic distance was quantified by pairwise Euclidean distance of somatic mutational profiles and integrated with 3D neuronavigation-based spatial coordinates and progression-free survival (PFS). Two distinct growth patterns emerged: expansive, defined by strong correlation between molecular and spatial distance (RE = 0.6), and stochastic, characterized by molecular divergence uncoupled from spatial proximity (RS = -0.2). High molecular distance correlated with reduced PFS (R = -0.5538, p = 0.026), and stochastic expansion predicted unfavorable outcome (p = 0.035), frequently localized to the frontal lobe. Radiomic analysis from contrast-enhanced T1-weighted MRI revealed that molecular distance was positively correlated with heterogeneous texture features (e.g., GLCM entropy, NGTDM complexity; p < 0.05). Stochastic tumors were enriched for radiomic heterogeneity (e.g.), while expansive tumors displayed homogeneous imaging textures, suggesting convergent phenotypic adaptation in genomically diverse tumors. Functional annotation using neuromaps demonstrated that tumors with high molecular distance exhibited positive correlations with differentiation- and angiogenesis-related metrics (SA_axis, genePC1, CBV), and negative associations with expression of neurotransmitter receptors (acetylcholine, serotonin, dopamine). Stochastic tumors correlated with increased Magnetoencephalography (MEG) derived timescales, implicating higher neural network engagement and spatial fluctuations. These findings suggest a link between type of clonal expansion, radiomic-based structural imaging phenotype, and functional neuroanatomy in GBM, providing a multidimensional framework to interpret tumor behavior and identify clinically relevant radiogenomic signatures.