Functional clustering within glioblastoma identifies a network-integrated subtype with improved survival

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ID: 328314
2026
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Abstract
BACKGROUND: Glioblastoma (GBM) is traditionally viewed as disrupting brain network connectivity. Recent evidence of tumor-neuron synaptic interactions suggests gliomas may actively engage with the brain. We hypothesized that GBM tumors contain functionally distinct intratumoral subregions that differentially couple with resting-state networks (RSNs) and carry prognostic significance. METHODS: We applied fuzzy c-means clustering to resting-state fMRI data from 190 GBM patients to identify and count the number of intratumoral functional subregions. We used the participation ratio, a PCA-derived measure of signal dimensionality, as a continuous variable complement to cluster number. Cluster-level BOLD time series were correlated with seven canonical RSNs and compared to tumor location-matched voxels in 347 healthy subjects. Associations with survival and preoperative seizures were evaluated using Kaplan-Meier analysis, restricted mean survival time (RMST), multivariable Cox proportional hazards modeling, and multivariable logistic regression. RESULTS: Fifty-two of 190 GBMs exhibited multiple intratumoral functional clusters. Multi-cluster tumors were associated with longer survival and higher seizure prevalence. Elevated RSN coupling was more prevalent in multi-cluster tumors as compared to single-cluster tumors, with elevated coupling strongly predicting multi-cluster status. Distinct clusters often showed preferential coupling to different RSNs. CONCLUSIONS: A subset of GBM contains functionally distinct subregions that selectively engage large-scale brain networks, a pattern associated with favorable survival and increased seizure risk. These findings support a model in which certain tumors function as active participants within neurovascular networks, indicating a novel network-integrated subtype of GBM with implications for prognosis and disease staging.
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openalex_W7212012246 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Danting Zeng, Abraham Z. Snyder, Ki Yun Park, Benjamin Acland, Joshua S. Shimony, Eric C Leuthardt
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Journal journal of neuro-oncology
Year 2026
DOI
10.1093/neuonc/noag223
URL
https://doi.org/10.1093/neuonc/noag223
Keywords Keywords not found

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