Using computer models to find new ways to enhance immune responses against cancer.
Official title: In silico screening for immune surveillance adaptation in cancer using Common Fund data resources
Funded at University of Pittsburgh at Pittsburgh · NIH-10773268 · Data updated 2026-11-12
This study is looking for ways to make cancer treatments work better by figuring out how cancer cells hide from the immune system, so that new therapies can help boost your body's natural defenses against cancer.
Quick facts
| Grant type | R03 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pittsburgh at Pittsburgh NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project start | September 20, 2023 |
| Project end | September 19, 2025 |
| Funding year | 2023 |
| Award (this year) | $318,000 |
| NIH project number | 1R03OD036494-01 |
| Project ID | NIH-10773268 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adults diagnosed with various types of cancer who may benefit from enhanced immunotherapy approaches.
✕Less likely to help
Patients with non-cancerous conditions or those who are not eligible for immunotherapy may not receive any benefit from this research.
What this research studies
This research aims to improve cancer immunotherapy by identifying how cancer cells adapt to evade immune detection. By utilizing advanced computational tools and large-scale datasets, the project will screen for potential therapeutic agents that can modulate immune responses in the tumor microenvironment. The approach involves analyzing genomic features of cancer cells through deep learning to predict their interactions with immune cells. Patients may benefit from new treatment strategies that enhance the effectiveness of existing cancer therapies.
Why it matters
Potential benefit: If successful, this research could lead to innovative therapies that improve immune responses against cancer, potentially enhancing treatment outcomes for patients.
How similar studies have gone: Other research has shown promise in using computational models to enhance cancer treatment strategies, indicating that this approach could be effective.
Where this research is happening
-
University of Pittsburgh at Pittsburgh
Pittsburgh, United States Active
Researchers
- Principal investigator: Chiu, Yu-Chiao — University of Pittsburgh at Pittsburgh
- Study coordinator: Chiu, Yu-Chiao
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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.