Glioma Diagnosis and Treatment

This study characterizes the heterogeneity of the GBM periphery, showing that non-enhancing areas have neoplastic features and that tumor infiltration correlates with patient sex, age, and resection extent, impacting prognosis.

This study identifies a bidirectional OSMR-CLIC1 crosstalk that drives oncogenic pathways in glioblastoma and suggests targeting this interaction as a therapeutic strategy.

This study uses deuterium metabolic imaging to characterize metabolic heterogeneity in mouse glioblastoma models, linking glucose turnover kinetics to tumor phenotype differences and invasion capacity.

This study develops and validates a TTF prototype for glioblastoma therapy, showing reduced tumor growth and increased apoptosis in vitro and in vivo.

This paper introduces a murine ex vivo platform for brain cancer drug screening and modeling, designed to address limitations in in vitro and in vivo studies by incorporating tumor microenvironment dynamics.

This study investigates how mTOR inhibition reverses glioma-induced changes in excitatory neurons, showing effects on mRNA, dendritic spines, and neuronal activity.

This paper introduces gtePIDP, a multi-omics framework that identifies phenotypically impactful driver pathways in GBM by integrating mutation, expression, and regulatory data.

This paper uses DNA methylation-based deconvolution to analyze glioblastoma cellular composition and identifies astrocyte-to-oligodendrocyte ratios as prognostic markers for patient survival.

This study shows that combining radiation with forskolin induces a differentiation-like state in glioma cells, reducing proliferation and extending survival in mouse models.

This study identifies up-regulated hub genes and potential VEGFA inhibitors in glioblastomas using gene expression data and virtual screening, proposing new therapeutic targets and biomarkers.

This study shows that glioma-induced DNMT3A reduction in microglia leads to DNA demethylation and an anti-tumoral phenotype, suggesting DNMT3A as a therapeutic target for glioblastoma.

This study uses MALDI-TOF MS and machine learning to identify serum biomarkers for astrocytoma diagnosis, achieving 94.5% accuracy in distinguishing GBM from healthy controls.

This study shows that mutant IDH impairs PDGFB's chromatin binding, leading to chromosome instability and accelerated gliomagenesis.

This paper identifies tGLI1 as a mediator of GBM resistance to CDK4/6 inhibitors and shows that ketoconazole sensitizes GBM to CDK4/6 therapy and chemoradiation.

This study identifies functional GABAergic neuron-to-glioma synapses in diffuse midline gliomas that promote tumor proliferation and shows that drugs modulating GABAergic signaling affect glioma growth.

The paper shows that delivering CAR-T cells via a hydrogel in the resection cavity improves survival in mice with recurrent glioblastoma.

This study examines how genomic background and developmental state affect signaling pathways and therapy response in GBM patient-derived cells, finding that differentiation increases TMZ resistance and activates DNA-damage interferon responses.

The paper identifies epigenetic regulation of key pathways and novel druggable targets in glioblastoma by comparing chromatin remodelling in neoplastic and neural stem cells.

This study shows that delivering 4-1BBL via AAV enhances IL-12-induced anti-glioblastoma immunity in mouse models by boosting CD8 T cell activity and survival.

The paper uses multiomic data to identify cell state transitions in GBM and proposes potential drug targets to alter these transitions.

This study identifies inverse correlation between MUC1 and MUC4 expression in gliomas and links them to immunological and transport pathways, with implications for prognosis and therapy.

This study develops a cerebral organoid model to study tumor infiltration and migration supported by astrocytes in an autologous setting, showing tumor-like cells exhibit invasive properties and are influenced by the glial environment.

The paper identifies context-dependent gene essentiality in GBM using CRISPR screening and develops a platform to link biomarkers to therapeutic targets.

This study identifies clinical, genetic, and spatial factors affecting glioblastoma multiforme survival using retrospective patient data.

This study identifies shared molecular mechanisms regulating quiescence in neural and glioma stem cells and suggests TGF-β inhibition as a potential therapeutic strategy.

This study develops CRISPR-engineered glioblastoma organoids to model tumor progression, revealing transcriptional and spatial changes in neurodevelopmental gene networks.

The paper identifies ACP1 and AURKB as regulators of cortactin-driven actin remodeling in glioblastoma invasion using CRISPRi screens in 3D hydrogels.

This study identifies BRAT1 as a key driver of glioblastoma growth and invasion, showing that its inhibition with CurD reduces tumor migration and enhances radiation sensitivity.

This paper introduces MDBrainT, a DNA methylation-based deconvolution method to predict cell composition in brain tumor microenvironments, revealing distinct patterns across tumor types and molecular subtypes that correlate with patient outcomes.

This study shows human glioblastoma cells integrate into brain-wide neuronal circuits, exhibit diverse connectivity, and respond to neuromodulatory inputs like acetylcholine, which promotes invasion and survival.