AI to predict which tumor-made neoantigens trigger T cells and immunotherapy benefit
Applying deep learning to predict T cell receptor binding specificity of neoantigens and response to checkpoint inhibitors
This project uses artificial intelligence to learn which tumor changes (neoantigens) make a person's T cells attack cancer and whether that pattern links to benefit from checkpoint inhibitor drugs.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Tx Md Anderson Can Ctr NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project ID | NIH-11424608 on NIH RePORTER |
What this research studies
Researchers will combine tumor and immune data from people with cancer and apply deep learning and transfer-learning methods to predict which neoantigens bind specific T cell receptors and which neoantigen patterns relate to response to checkpoint inhibitors. They will build standardized analysis pipelines and benchmarking datasets so models can be compared and shared. The team will mainly work with existing genomic and immunological data rather than testing a new drug in patients. The goal is to create tools that could guide personalized immunotherapy choices and target selection for future treatments.
Who could benefit from this research
Good fit: Ideal candidates are people with cancer who have tumor sequencing and immune profiling data or who are receiving or being considered for checkpoint inhibitor therapy.
Not a fit: People without tumor or immune sequencing data, those not affected by cancer, or patients receiving treatments unrelated to immunotherapy are unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this work could help doctors predict who is likely to benefit from checkpoint inhibitor immunotherapy and guide personalized immune-based treatments.
How similar studies have performed: Previous models can predict some aspects of neoantigen presentation and immunogenicity with limited accuracy, but accurate prediction of specific TCR–neoantigen binding is still largely novel and remains a major challenge.
Where this research is happening
Houston, United States
- University of Tx Md Anderson Can Ctr — Houston, United States (Active)
Researchers
- Principal investigator: Wang, Tao — University of Tx Md Anderson Can Ctr
- Study coordinator: Wang, Tao
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.