Designing T-cell receptors to recognize cancer targets
Official title: MATCHMAKERS - Solving TCR recognition and design via integrated high-throughput screening, structural, functional, and computational approaches
Funded at Children's Hosp of Philadelphia · NIH-11514455 · Data updated 2026-11-12
This project will combine large lab datasets, structural studies, and machine learning to create T-cell receptors that can find cancer antigens for people with cancer.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Children's Hosp of Philadelphia NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project start | May 1, 2024 |
| Project end | April 30, 2027 |
| Funding year | 2026 |
| Award (this year) | $434,021 |
| NIH project number | 3OT2CA297575-01S2 |
| Project ID | NIH-11514455 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are people with cancer who are interested in antigen-specific immunotherapy or willing to provide tumor or blood samples for research.
✕Less likely to help
Patients without targetable tumor antigens, those needing immediate standard treatment, or people with non-cancer conditions are unlikely to benefit directly.
What this research studies
Researchers will gather large collections of matched T-cell receptors and the tumor pieces they recognize from human samples and mouse models. They will run ultra-high-throughput lab screens and structural experiments to see how receptors bind cancer antigens. Computational teams will train AI models on those matched structure and function data to predict recognition and to design new receptors. The overall aim is to create tools that help guide safer, more precise T-cell therapies.
Why it matters
Potential benefit: If successful, this work could enable more precise T-cell therapies that target tumors better and reduce off-target effects.
How similar studies have gone: Some engineered T-cell therapies and prediction tools have shown early success, but combining large-scale structural, functional, and AI-driven datasets in this way is relatively new.
Where this research is happening
-
Children's Hosp of Philadelphia
Philadelphia, United States Active
Researchers
- Principal investigator: Sgourakis, Nikolaos — Children's Hosp of Philadelphia
- Study coordinator: Sgourakis, Nikolaos
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.