Improving prostate cancer prognosis using advanced AI and spatial analysis techniques
Official title: Multimodality spatial analysis in prostate cancer to improve prognostic estimation and cast light into the black box of pathology artificial intelligence algorithms
Funded at University of California, San Francisco · NIH-11029958 · Data updated 2026-11-12
This study is looking at how advanced technology can help us better understand prostate cancer, which many men face, by analyzing tumor samples to find new clues that could lead to more personalized and effective treatment options.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $680,433 |
| NIH project number | 1R01CA296792-01 |
| Project ID | NIH-11029958 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are men diagnosed with prostate cancer who are seeking more personalized prognostic information.
✕Less likely to help
Patients with non-prostate cancers or those who are not undergoing treatment for prostate cancer may not benefit from this research.
What this research studies
This research investigates how advanced artificial intelligence and spatial analysis can enhance the understanding of prostate cancer, which affects many men each year. By combining genomic and proteomic technologies with AI, the study aims to uncover hidden biological factors that influence cancer outcomes. Patients' tumor samples will be analyzed at a microscopic level to identify new markers that could improve prognostic estimates and treatment decisions. The goal is to provide clearer insights into the heterogeneity of prostate cancer, ultimately aiding in personalized patient care.
Why it matters
Potential benefit: If successful, this research could lead to more accurate prognostic tools for prostate cancer, helping patients receive tailored treatment plans.
How similar studies have gone: Other research has shown promise in using AI and genomic analysis to improve cancer prognostics, indicating that this approach could be effective.
Where this research is happening
-
University of California, San Francisco
San Francisco, United States Active
Researchers
- Principal investigator: Cooperberg, Matthew R — University of California, San Francisco
- Study coordinator: Cooperberg, Matthew R
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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.