Analysis demonstrates distinct clonal evolution in glioblastoma, highlighting invasive regions' signaling in patients.
Glioblastoma (GBM) invasion is shaped by dynamic clonal evolution within the spatial and cellular architecture of the brain. To investigate this process, we integrated multiparametric MRI, whole-exome sequencing (WES), bulk RNA-seq and single-nucleus RNA-seq (snRNA-seq) from 69 IDH-wildtype GBM patients, using spatially resolved biopsies from contrast-enhancing (CE) core tumor and non-enhancing (NE) invasive regions. Phylogenetic analysis revealed distinct clonal architectures. CE-enriched clones carried truncal mutations in conanical drivers of cell cycle and RTK signaling (TP53, PTEN, EGFR, PDGFRA/B), and private alterations in DNA repair genes (CDH11, PAX7, RAD51B). In contrast, NE-enriched clones exhibited private mutations in MAPK and Hippo pathways components (STAG2, BRAF, MAP2K3, CTNNA1), suggesting region-specific evolutionary trajectories. Furthermore, snRNAseq cell-cell communication analysis uncovered enriched ligand-receptor signaling in NE regions between malignant cells and brain-resident populations, including PTN—PTPRZ1 (myeloid), NRG-ERBB4 and SLIT-ROBO (neuronal, astrocytic, and oligodendrocytic). Bulk RNAseq deconvolution confirmed increased representation of neurons and glial cells in biopsies harboring NE-specific clones. These findings define a unique population of GBM clones localized at the infiltrative margin, marked by private MAPK/Hippo mutations and enhanced intracellular communication with the surrounding brain microenvironment. The recurrent engagement of neural-glial signaling pathways suggests that these NE-associated clones co-opt normal cellular networks to support invasion, immune evasion, and persistence following surgical resection. This study establishes a mechanistic link between spatial clonal evolution and tumor-host communication at the GBM infiltrative region and provide a framework for targeting cell-cell signaling circuits that sustain invasive tumor ecosystems and escape therapeutic treatment.
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Beniwal et al. (2025) studied this question.
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