Glioblastoma: who works on it

One card per institution. Filter by target, by country, or show only institutions in EU-13 (Horizon Europe widening) countries.

• All targets
• MGMT 20
• EGFR 14
• IDH 10
• STAT3 3
• TP53 0
• AKT 0
• mTOR 1
• PI3K 1
• PD-1 7
• ERK 0
• PD-L1 5
• STING 0
• YAP 0
• B7-H3 7
• MAPK 0
• PARP 1
• CTNNB1 0
• PTEN 1
• VEGF 5
• AMPK 0
• BRAF 1
• TERT 3
• FGFR 1
• PRMT5 5
• CDK4/6 0
• HDAC 0
• HIF-1 1
• IL-6 0
• NRF2 0
• PSMA 4
• MYC 2
• COX-2 0
• CXCR4 0
• EZH2 0
• CD47 0
• HER2 2
• JAK 0
• MEK 0
• MET 1
• METTL3 0
• TLR4 0
• ATM 2
• GPX4 0
• MDM2 0
• BCL-2 0
• CDKN2A 0
• CTLA-4 0
• FAK 0
• HSP90 0
• JNK 0
• MMP-9 1
• TNF 0
• CD19 0
• NF1 1
• NTRK 1
• TREM2 0
• AR 0
• CD40 1
• HMGB1 0
• IDO1 0

EU-13 is a filter, not a ranking: it only narrows the list.

24 of 35+ institutions, ordered by recent publications and open trials. This is not a ranking of quality.

Terminated, withdrawn and suspended trials with the reason the sponsor gave in the registry, quoted word for word.

• Terminated

  Study to Evaluate the Efficacy and Safety of Pemigatinib in Participants With Previously Treated Glioblastoma or Other Primary Central Nervous System Tumors Harboring Activating FGFR1-3 Alterations

  NCT05267106· Incyte Corporation· Updated 30 Dec 2025

  “Recruitment ceased after a pre-planned futility interim analysis indicated a low probability to confer a clinically meaningful improvement in objective response when compared to currently available therapies. There were no safety related concerns.”Registry text, quoted unchanged. Source

Trials whose registry record says individual participant data (IPD) will be shared.

• Nivolumab in Patients With IDH-Mutant Gliomas With and Without Hypermutator Phenotype

  NCT03718767· National Cancer Institute (NCI)· Source

• BGB-290 and Temozolomide in Treating Isocitrate Dehydrogenase (IDH)1/2-Mutant Grade I-IV Gliomas

  NCT03749187· University of California, San Francisco· Source

• Comprehensive Analysis of Chemotherapy and Targeted Therapy Outcomes in Recurrent Malignant Gliomas

  NCT07448480· Blokhin's Russian Cancer Research Center· Source

• Study to Evaluate the Efficacy and Safety of Pemigatinib in Participants With Previously Treated Glioblastoma or Other Primary Central Nervous System Tumors Harboring Activating FGFR1-3 Alterations

  NCT05267106· Incyte Corporation· Source

Find publications on this disease by a MeSH method term, for example a sequencing or imaging method.

• Single-Cell Analysis 93
• Organoids 33
• Mendelian Randomization Analysis 14
• CRISPR-Cas Systems 11
• Gene Expression Profiling 150
• Sequence Analysis, RNA 10
• Exome Sequencing 2
• Proteomics 47
• Metabolomics 21
• Mass Spectrometry 9
• Flow Cytometry 16
• Immunohistochemistry 22
• Liquid Biopsy 10
• Circulating Tumor DNA 3
• Xenograft Model Antitumor Assays 226
• Positron-Emission Tomography 37
• Magnetic Resonance Imaging 234
• Machine Learning 266
• Deep Learning 43
• Cohort Studies 54
• Genome-Wide Association Study 13

• Development and internal validation of machine learning models for predicting prediabetes in China.

  PLoS One, Nov 2026

• Rigorous nested cross-validation and external generalization-gap analysis of a machine-learning classifier for U-251 glioblastoma cytotoxicity.

  PLoS One, Nov 2026

• Reconstructing the single-cell spatiotemporal dynamics of glioblastoma invasion.

  Nat Commun, Nov 2026

• Persistent atrial fibrillation in older adults: Comparison of seven models and development of a gradient boosting machine classifier in a single-center observational study.

  Medicine (Baltimore), Oct 2026

• Associations of International Normalized Ratio and Hematocrit With Stroke Status and Machine Learning Mortality Prediction in Critical Care Databases.

  J Vis Exp, Oct 2026

• Predicting under-five child mortality in Zambia: Machine learning versus parametric survival models.

  PLoS One, Oct 2026

• Predicting cholesterol screening behavior using machine learning: Social-ecological approach.

  Health Informatics J, Oct 2026

• Machine Learning-Based Risk Prediction Models for Peripheral Artery Disease: A Nationally Representative Analysis of NHANES 1999-2004.

  Clin Appl Thromb Hemost, Oct 2026

• Cardiac troponin T and 28-day mortality in traumatic brain injury: a retrospective cohort study and machine learning prediction model.

  Front Neurol, Oct 2026

• Construction of risk prediction models for psoriasis based on 45 dietary nutrients using machine learning and SHAP analysis.

  Asia Pac J Clin Nutr, Oct 2026

See which targets of this disease your abstract mentions, and go to the people working on them.