EPCO-48. RESOLVING INTRATUMORAL TRANSCRIPTIONAL HETEROGENEITY ACROSS THE CORE-EDGE SPATIAL AXIS IN GLIOBLASTOMA

Abstract Intratumoral heterogeneity promotes tumor progression, treatment resistance, and recurrence in glioblastoma (GBM), and the cellular tumor core and infiltrating edge represent transcriptionally distinct cellular ecosystems. In this study, we characterize and validate the molecular differences across the core-edge spatial axis in GBM by applying whole-transcriptome GeoMx Digital Spatial Profiling (DSP) to 5 IDH-wildtype tumors. Three 3-micron tissue cores were extracted from each tumor and arranged into a tissue microarray (TMA). Core and edge regions of interest (ROIs) were chosen through coregistration of H&E and immunofluorescent TMA scans. Following DSP, data for 44 ROIs (30 core and 14 edge) and 8530 RNA targets were bioinformatically analyzed. Single-sample gene set enrichment analysis aligned the DSP core and edge regional signatures to those of publicly annotated datasets, substantiating our profiling methodology. Unsupervised analyses revealed ROI clusters unique to each tumor specimen for both pre- and post-normalized data. To mitigate a potential patient-level effect in subsequent differential gene expression and pathway analyses, we leveraged a linear mixed-effect model using core versus edge as a fixed effect and tumor specimen as a random effect. Our analyses showed upregulation of epigenomic markers in core ROIs and neuronal markers in edge ROIs. Further, core and edge signatures were incongruent with the canonical GBM subtypes (Mesenchymal, Classical, Proneural) and malignant cell states (OPC-like, NPC-like, AC-like, MES-like). Cellular deconvolution analysis highlighted differential enrichment of neoplastic cells in core ROIs and neuroglia (astrocytes and oligodendrocytes) in edge ROIs. In summary, we leverage spatial profiling to further validate the geographic molecular heterogeneity of GBM, which is characterized by divergent neuronal programs within the infiltrating edge.