Prostate cancer: 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
• PSMA 271
• AR 15
• TP53 2
• PARP 13
• PTEN 4
• AKT 1
• BRCA2 7
• BRCA1 9
• PI3K 2
• STAT3 0
• PD-L1 6
• mTOR 1
• PD-1 13
• EZH2 7
• MYC 1
• B7-H3 8
• EGFR 2
• CTNNB1 1
• JNK 0
• ERK 0
• HIF-1 0
• VEGF 2
• BCL-2 0
• AMPK 0
• CDK4/6 4
• HER2 6
• MAPK 0
• NRF2 0
• FAK 0
• YAP 0
• PPAR 0
• IL-6 0
• STING 0
• COX-2 0
• CTLA-4 0
• DLL3 6
• GLP-1 1
• GPX4 0
• HSP90 0
• HDAC 0
• IL-15 4
• METTL3 1
• ATM 1
• BRD4 0
• HER3 2
• JAK 1
• CXCR4 0
• TROP2 3
• CD47 1
• IGF1R 0
• IL-1 0
• MET 1
• PALB2 4
• RB1 0
• TNF 0
• APOE 0
• FGFR 1
• KRAS 0
• MDM2 0
• MEK 0

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

24 of 26+ 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Terminated, withdrawn and suspended trials with the reason the sponsor gave in the registry, quoted word for word.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

  Golimumab and Apalutamide for the Treatment of Castration-Resistant Prostate Cancer, TRAMP Study

  NCT05960578· University of Washington· Updated 19 Oct 2026

  “The trial was ended sooner than expected due to a combination of factors, including slow accrual, lower than anticipated benefit to patients, and loss of funding from the study sponsor.”Registry text, quoted unchanged. Source

• Terminated

  Contributions to Hypertension With Androgen Deprivation Therapy

  NCT05700903· University of Colorado, Denver· Updated 2 Sept 2026

  “Study completed”Registry text, quoted unchanged. Source

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

• Study of Abiraterone Acetate or Enzalutamide, Atezolizumab, GnRH Analog and Radiation Therapy in Men With Newly Diagnosed Hormone-sensitive Prostate Cancer

  NCT04262154· Memorial Sloan Kettering Cancer Center· Source

• TulmiSTAR-02: A Phase I/II Open-label Study of Tulmimetostat in Combination With Darolutamide vs. Darolutamide, and Tulmimetostat With Abiraterone in Patients With Metastatic Hormone-sensitive Prostate Cancer (mHSPC)

  NCT07190300· Novartis Pharmaceuticals· Source

• A Study of Talazoparib With or Without Enzalutamide in People With Prostate Cancer Who Have Previously Received Abiraterone Acetate or Darolutamide

  NCT06844383· Prostate Cancer Clinical Trials Consortium· Source

• Intermittent Androgen Deprivation Therapy in the Era of AR Pathway Inhibitors

  NCT05974774· European Organisation for Research and Treatment of Cancer - EORTC· Source

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

• Single-Cell Analysis 41
• Organoids 15
• Mendelian Randomization Analysis 38
• CRISPR-Cas Systems 14
• Gene Expression Profiling 152
• Sequence Analysis, RNA 11
• Whole Genome Sequencing 9
• Exome Sequencing 4
• Proteomics 47
• Metabolomics 27
• Mass Spectrometry 16
• Flow Cytometry 58
• Immunohistochemistry 120
• Liquid Biopsy 30
• Circulating Tumor DNA 31
• Xenograft Model Antitumor Assays 287
• Positron-Emission Tomography 124
• Magnetic Resonance Imaging 460
• Machine Learning 122
• Deep Learning 101
• Cohort Studies 275
• Genome-Wide Association Study 60

• Identification of ageing-related genes in prostate cancer with type 2 Diabetes using machine learning: a multi-omics study focusing on SOX4, PRNP, and FOXO4.

  Artif Cells Nanomed Biotechnol, Oct 2026

• Development and External Validation of a Machine Learning-Derived Risk Stratification Score for Metastatic Castration-Resistant Prostate Cancer.

  JCO Clin Cancer Inform, Oct 2026

• Potential Molecular Links Between Triclosan Exposure and Prostate Cancer: An Integrative Computational Analysis.

  Int J Mol Sci, Oct 2026

• Untranslated Region-FNex: An Integrative Multimodal Framework for Functional Untranslated Region Variant Prioritization.

  J Chem Inf Model, Oct 2026

• Interpretable Machine Learning Prognostic Model Integrating Inflammatory-Nutritional Biomarkers for Post-Prostatectomy Biochemical Recurrence: Development, Internal Validation, and Translational Target Exploration.

  Curr Oncol, Oct 2026

• Predicting miRNA-Disease Associations Based on Contrastive Learning of Linear and Nonlinear Features.

  Genes (Basel), Oct 2026

• Explainable Machine Learning-Based Prediction of Progression-Free Survival in Prostate Cancer: Retrospective Cohort Study.

  JMIR Cancer, Oct 2026

• General versus site specific quantile random forest models for virtual patient-specific quality assurance of VMAT plans.

  J Appl Clin Med Phys, Oct 2026

• Development and external validation of an explainable machine-learning model for early complications following robot-assisted radical prostatectomy: a multicenter study.

  J Robot Surg, Oct 2026

• Development and evaluation of a combined machine learning model for the prediction of acute GU toxicity in prostate cancer radiotherapy.

  Phys Med, Sept 2026

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