Glioma Diagnosis and Treatment

This study shows dopamine receptor antagonists have sex-dependent effects on neural stem/progenitor cells, potentially reducing radiation-induced cognitive decline in glioblastoma treatment.

This paper develops a functional precision medicine approach using metabolic imaging to predict glioblastoma treatment response early in ex-vivo organoids, identifying responder and non-responder groups and a new molecular signature.

The paper uses single-cell analysis of GBM patient samples and xenografts to identify regulatory networks driving treatment-induced tumor evolution and proposes a framework for precision medicine.

This study introduces an individual-level structural abnormality detection method for frontal glioma patients and finds unique and shared atrophy patterns linked to molecular biomarkers.

The paper identifies PD1 signaling regulation as a prognostic marker in glioblastoma using gene regulatory network analysis across two cohorts.

This paper shows that combining ONC201 with radiation improves GBM treatment efficacy by targeting glioma-initiating cells in vitro and in vivo without increased toxicity.

This study shows that combining quetiapine, atorvastatin, and radiation extends survival in glioblastoma mouse models by exploiting a metabolic vulnerability.

This paper shows that glioblastoma produces ImpL2, which disrupts neuronal insulin signaling, leading to neurodegeneration and premature death, and that restoring insulin signaling can rescue these effects.

The paper introduces the Chinese Glioma Genome Atlas (CGGA), a resource providing genomic and clinical data for glioma patients, along with analysis tools for data exploration and research.

This paper demonstrates that overexpressing neural transcription factors can convert glioblastoma cells into neurons, inhibiting their proliferation and offering a potential therapeutic strategy.

The paper finds that higher cerebral blood volume in infiltrated peripheral edema is associated with the proneural glioblastoma subtype.

This study shows that purine metabolism affects DNA repair and therapy resistance in glioblastoma, suggesting that targeting purine synthesis could improve treatment outcomes.

This study tracks glioma progression in mice, showing decreased neuronal synchrony, disrupted neurovascular coupling, and seizure-related hypoxia in infiltrated cortex.

This study compares tumor cell phenotype and heterogeneity differences between IDH1 mutant and wild-type gliomas using integrated multi-omics data.

This study analyzes mutation distribution in GBM tumors using 3D spatial organization and network-guided methods, revealing four patient clusters with distinct mutation patterns and pathways.

This study evaluates intraoperative contrast-enhanced ultrasound (iCEUS) for monitoring glioma resection and its correlation with microvessel density across glioma grades.

The paper quantifies low perfusion compartments in glioblastoma using MRI and correlates them with patient survival outcomes.

The paper compares machine learning and logistic regression for predicting 2-year mortality in a small glioma dataset, finding similar performance between ML methods and logistic regression.

The paper investigates copy number loss of the ERBB4 gene in glioblastoma, finding it is not a driver mutation or predisposing factor, despite initial hypotheses from cell line data.

This study shows that targeting Nlgn3 secretion via ADAM10 inhibitors can block high-grade glioma growth in mouse models.

The paper trains a machine learning classifier on cancer transcriptomes to detect NF1 inactivation in glioblastoma, showing it can predict NF1 status based on gene expression and mutation data.