This research uncovers key gene expression patterns in glioblastoma infiltration, suggesting new biomarkers for tumour invasion and recurrence.
Glioblastoma is the most common malignant brain tumour in adults. Despite extensive research, there haven’t been remarkable gains in resolving the seeds of glioblastoma recurrence, and the outcomes for many patients suffering from this devastating disease remain poor. Our knowledge on GBM heterogeneity is mostly restricted to the surgically resectable tumour core, while the functional characterization of tumour cells at the infiltrating edge remains largely elusive due to the presence of normal functional brain tissue in the peritumoural lesion. Edge-derived cells exhibit larger capacity for infiltrative expansion and are the main drivers of treatment failure and tumour recurrence, making them action targets for novel treatment approaches. To resolve the transcriptional heterogeneity of GBM within the spatial context, we profiled gene expression of tumour regions selected based on histological features (“core” and “infiltrating edge”) obtained from 4 primary and 2 matched pairs of primary/recurrent IDH-WT GBM patients with Visium HD. Using pathologically annotated H&E images integrated with spatial gene expression, we resolved patterns related to tissue structure and architecture in each sample to capture continuous patterns of gene expression variation. We used NicheCompass to deepen our understanding of tissue hierarchies, and spatially localized cellular processes in infiltrative GBM. We identified top spatially variable genes and active gene programs in this cell population using unsupervised cell phenotyping and examined their combined activity. Identified modules represent tumour cell hijacking of neuronal programs as described in the context of glioma-neuron synaptic communication and formation of neurite-like tumour microtubes and is consistent with OPC-like & NPC-like cell state enrichment at the tumour periphery. Identifying biomarkers that are specific to malignant edge-derived cells may serve as new diagnostic feature that would help assess treatment response before or within early phases of therapy and allow for individual tailoring of the treatment plan to slow disease progression.
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Ivanova et al. (2025) studied this question.
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