Predicting which triple-negative breast cancers are most dangerous
Early prediction of lethal phenotypes in triple negative breast cancer using multiscale, multi-modality platforms
This project uses AI plus tumor, blood, scan, and clinical data to find which people with triple-negative breast cancer are most likely to develop life-threatening disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Emory University NIH-funded |
| Lab location | 1 site (Atlanta, United States) |
| Project ID | NIH-11299582 on NIH RePORTER |
What this research studies
If you have triple-negative breast cancer (TNBC), researchers will combine information from your tumor tissue, scans, blood tests, and medical records to look for patterns linked to deadly outcomes. They will apply artificial intelligence and advanced Bayesian models to merge these different types of data across biological scales. The team aims to create a tool that helps doctors decide who needs stronger treatment after surgery and who might safely avoid extra therapy. Joining would likely involve sharing tissue and medical data and possibly visiting Emory or partner clinics for sample collection or follow-up.
Who could benefit from this research
Good fit: Adults diagnosed with triple-negative breast cancer, especially those treated with or considering adjuvant chemotherapy and who can provide tumor tissue and medical records, are the ideal candidates.
Not a fit: People without triple-negative breast cancer, those with advanced metastatic disease outside the adjuvant setting, or those unable to provide tissue or records are unlikely to benefit from this project.
Why it matters
Potential benefit: If successful, this could help doctors target stronger treatment to those at highest risk and avoid unnecessary treatment for lower-risk patients.
How similar studies have performed: Previous TNBC subtype and tumor-infiltrating-lymphocyte approaches have had limited predictive success, and while AI prognostic tools have shown promise in other cancers, applying multi-modal AI to predict lethal TNBC is still relatively novel.
Where this research is happening
Atlanta, United States
- Emory University — Atlanta, United States (Active)
Researchers
- Principal investigator: Badve, Sunil S. — Emory University
- Study coordinator: Badve, Sunil S.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.