Triple-negative breast 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
• PD-L1 26
• HER2 24
• PD-1 36
• BRCA1 5
• STAT3 1
• STING 0
• EGFR 4
• PI3K 1
• AKT 0
• BRCA2 2
• PARP 1
• TP53 1
• mTOR 0
• TROP2 6
• AR 1
• PTEN 0
• VEGF 4
• CDK4/6 3
• HIF-1 0
• MYC 0
• GPX4 0
• YAP 0
• CTNNB1 0
• JAK 1
• HDAC 0
• MAPK 0
• BCL-2 0
• CXCR4 1
• ERK 0
• NRF2 0
• PPAR 0
• B7-H3 4
• EZH2 0
• FAK 0
• PRMT5 0
• CD47 0
• HSP90 0
• PSMA 4
• IL-6 0
• PIK3CA 2
• CTLA-4 1
• HER3 2
• TNF 0
• COX-2 0
• IGF1R 0
• MEK 0
• FGFR 0
• MDM2 2
• MET 0
• MUC1 3
• NLRP3 0
• PALB2 0
• AMPK 0
• CD40 0
• CSF1R 1
• JNK 0
• METTL3 0
• MMP-9 0
• PKM2 0
• SIRT1 0

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

1 of 1+ institutions, ordered by recent publications and open trials. This is not a ranking of quality.

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

No trial in this view states that it shares participant data.

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

• Single-Cell Analysis 46
• Organoids 9
• Mendelian Randomization Analysis 2
• CRISPR-Cas Systems 10
• Gene Expression Profiling 110
• Sequence Analysis, RNA 8
• Whole Genome Sequencing 4
• Exome Sequencing 5
• Proteomics 32
• Metabolomics 14
• Mass Spectrometry 3
• Flow Cytometry 11
• Immunohistochemistry 49
• Liquid Biopsy 4
• Circulating Tumor DNA 16
• Xenograft Model Antitumor Assays 254
• Positron-Emission Tomography 13
• Magnetic Resonance Imaging 34
• Machine Learning 28
• Deep Learning 15
• Cohort Studies 21
• Genome-Wide Association Study 3

• NeoGen-BC: A synergistic framework combining generative protein language models and multi-window deep learning for designing shared neoantigens in breast cancer.

  Biochem Biophys Res Commun, Sept 2026

• A Deep Learning-Enabled SERS Platform for Decoding Tumor Heterogeneity and Dynamic Therapeutic Monitoring at the Cellular Level.

  ACS Sens, Aug 2026

• Deep Learning-Driven Anticancer Drug Discovery: Emodepside as a Potential Therapeutic Candidate for Triple-Negative Breast Cancer.

  J Chem Inf Model, Aug 2026

• An Explanatory Deep Learning Pipeline for the Prediction and Visualization of Spatially Resolved Biomarker Expression in Triple-Negative Breast Cancer.

  Am J Pathol, Aug 2026

• Object detection in histology: A multi-dataset benchmark and test-time inference.

  PLoS One, Jul 2026

• A multimodal deep learning classifier for prediction of HER2-low expression in triple-negative breast cancer.

  BMC Med Imaging, Jul 2026

• Predicting neoadjuvant breast cancer therapy response using BRIDGE from tumor transcriptomics and histopathology.

  Ann Oncol, May 2026

• Evidential reasoning-enabled deep learning for reliable treatment outcome prediction in cancer therapy.

  Artif Intell Med, May 2026

• Integrating tumor habitat heterogeneity with a hybrid deep learning architecture for ultrasound radiomics: a dual-center study on non-invasive prediction of PD-L1 expression in triple-negative breast cancer.

  Breast Cancer Res, Apr 2026

• An Exploratory Study on Prognostic Prediction and Interpretability Analysis in Early-stage Triple-negative Breast Cancer Using Pathological Images.

  Biomed Environ Sci, Mar 2026

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