How cancers and viruses change their targets to escape the immune system
Official title: Quantifying phenotypic adaptation of biological systems in dynamic environments
Funded at Texas Engineering Experiment Station · NIH-11175374 · Data updated 2026-11-12
Researchers will build computer-based methods to understand and predict how cancers and viruses change their antigen signatures over time and how those changes affect a patient's immune response.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Texas Engineering Experiment Station NIH-funded |
| Lab location | 1 site (College Station, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $360,016 |
| NIH project number | 5R35GM155458-02 |
| Project ID | NIH-11175374 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal participants would include people with cancer or certain viral infections who can share clinical data and provide blood, tissue, or sequencing samples for analysis.
✕Less likely to help
People without immune-driven diseases or those unwilling to provide clinical samples are unlikely to benefit directly from this project.
What this research studies
This project will combine mathematical theory with real sequencing and time-course gene expression data to track how disease cells adapt over time. Researchers will build computational models that describe how antigen signatures evolve and how T cells respond. They will validate the models using clinical and experimental data in close collaboration with hospitals and laboratories. The work aims to connect dynamic immune changes to disease behavior in cancer and infectious conditions.
Why it matters
Potential benefit: If successful, this work could help doctors predict when a cancer or infection is likely to change and guide more personalized, timely treatments.
How similar studies have gone: Previous immune-sequencing and computational studies have provided useful insights, but combining theory-driven models with time-course clinical data in this way is relatively novel.
Where this research is happening
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Texas Engineering Experiment Station
College Station, United States Active
Researchers
- Principal investigator: George, Jason — Texas Engineering Experiment Station
- Study coordinator: George, Jason
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.