Tripla negatív emlőrák: ki dolgozik rajta

Intézményenként egy kártya. Válassz célpontot, és csak az azon dolgozó csoportok maradnak.

• Minden célpont
• PD-L1 26
• HER2 24
• PD-1 36
• BRCA1 5
• STAT3 1
• STING 0
• EGFR 4
• PI3K 1
• AKT 0
• BRCA2 2
• TP53 1
• PARP 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

4+ intézményből 4, a friss publikációk és a nyitott vizsgálatok szerint rendezve. Ez nem minőségi rangsor.

Funded research projects that name this disease in their title, terms or summary and have not ended yet: who is funded, where, how much and until when. Organisations only; the funder's page has the details.

• European Commission (Horizon Europe) · HORIZON-TMA-MSCA-PF-EF

  DuoLipo-TNP: Dual-Responsive Liposome Platform for Selective Delivery of Triphosphate Nucleotide Prodrugs in Triple-Negative Breast Cancer

  Cardiff University· Cardiff, Egyesült Királyság· EU contribution 260 348 EUR· until 2029. ápr.· 2 countries

• European Commission (Horizon Europe) · HORIZON-TMA-MSCA-PF-EF

  Mapping antigenic niches of tumor-infiltrating B cells in triple-negative breast cancer (MAP-BC)

  Karolinska Institutet· Stockholm, Svédország· EU contribution 252 180 EUR· until 2028. dec.

• European Commission (Horizon Europe) · HORIZON-TMA-MSCA-SE

  Biomimetic MXene Nanoplatforms for Targeted Combination Therapy of Triple-Negative Breast Cancer (BioMIX)

  Latvijas Universitate· Riga, Lettország· EU contribution 1 147 740 EUR· until 2030. okt.· 12 countries

• European Commission (Horizon Europe) · HORIZON-EIC

  Next generation therapeutic vaccine for targeted cancer treatment (VacciNEXT)

  Basinnov Life Sciences Unipessoal Lda· Lisboa, Portugália· EU contribution 2 827 529 EUR· until 2029. szept.· 3 countries

• European Commission (Horizon Europe) · HORIZON-TMA-MSCA-PF-EF

  Co-culture System with Microfluidics and Onboard Sensors for Breast Cancer study (CoSMOS-BC)

  Universidad del Pais Vasco/ Euskal Herriko Unibertsitatea· Leioa, Spanyolország· EU contribution 209 915 EUR· until 2028. aug.

  The disease is named only in the funder's project summary, not in the title.

5 of 24 running projects, newest first. Listed amounts together: 18,5 M EUR.

Sources: NIH RePORTER (U.S. National Institutes of Health, public domain) and CORDIS (European Commission, CC BY 4.0). Changes: filtered by disease, organisations matched to ROR.

Vizsgálatok, amelyek regiszteradata szerint az egyéni résztvevői adatokat (IPD) megosztják.

Ebben a nézetben egy vizsgálat sem jelzi, hogy megosztaná a résztvevői adatokat.

Publikációk erről a betegségről egy MeSH-módszerkifejezés szerint, például szekvenálási vagy képalkotó módszerre.

• 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, 2026. szept.

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

  ACS Sens, 2026. aug.

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

  J Chem Inf Model, 2026. aug.

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

  Am J Pathol, 2026. aug.

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

  PLoS One, 2026. júl.

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

  BMC Med Imaging, 2026. júl.

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

  Ann Oncol, 2026. máj.

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

  Artif Intell Med, 2026. máj.

• 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, 2026. ápr.

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

  Biomed Environ Sci, 2026. márc.

Megmutatjuk, a betegség mely célpontjait említi az absztrakt, és onnan a rajtuk dolgozókhoz jutsz.