Better tests to detect and predict aggressive prostate cancer
Computational Feature Profiling and Modeling for Prostate Cancer Detection and Risk Stratification
This project builds computer models that combine tumor images and genetic markers to more accurately find and predict aggressive prostate cancer in men.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project ID | NIH-11238082 on NIH RePORTER |
What this research studies
If you take part, researchers will use medical records, biopsy specimens, blood tests, and genetic data from many men with prostate cancer. They will extract detailed image features from tumor biopsies and identify inherited genetic markers linked to aggressive disease. Those data will be combined using advanced AI methods (a convolutional neural network plus a graph convolutional network) to create new multi‑modal risk scores that aim to forecast which cancers will become aggressive. The goal is to help guide decisions about who needs immediate treatment and who might be safe on active surveillance.
Who could benefit from this research
Good fit: Men undergoing prostate biopsy, men recently diagnosed with prostate cancer, or men being followed on active surveillance are the most likely candidates.
Not a fit: Men with already advanced metastatic prostate cancer or people without prostate disease are unlikely to benefit from this work.
Why it matters
Potential benefit: Could help more men avoid unnecessary surgery or radiation by identifying which prostate cancers are unlikely to become dangerous.
How similar studies have performed: Previous studies using AI on pathology images and genetic tests have shown promise for improving prostate cancer risk prediction, but combining these data with graph-based models is a newer approach.
Where this research is happening
Los Angeles, United States
- University of California Los Angeles — Los Angeles, United States (Active)
Researchers
- Principal investigator: Arnold, Corey Wells — University of California Los Angeles
- Study coordinator: Arnold, Corey Wells
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.