New Methods to Understand How Genes and Environment Shape Cancer Outcomes
Official title: Novel Methods for Identifying Genetic Interactions for Cancer Prognosis
Funded at Yale University · NIH-11445699 · Data updated 2026-11-12
A cancer research project at Yale is developing advanced computer methods to better predict how genes and environmental factors influence cancer prognosis.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project start | August 21, 2026 |
| Project end | June 30, 2031 |
| Funding year | 2026 |
| Award (this year) | $424,882 |
| NIH project number | 2R01CA204120-09A1 |
| Project ID | NIH-11445699 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with cancers such as lung, skin, lymphoma, or thyroid cancer who may benefit from improved prognosis modeling.
✕Less likely to help
If prognosis modeling is not used in a patient's care plan, there may be no direct benefit.
What this research studies
This project focuses on improving how we model and predict cancer outcomes by studying how genes interact with environmental aspects. It builds on years of prior work to create stable, interpretable deep-learning methods that capture complex gene-environment relationships. The aim is to identify interactions that improve prognosis predictions for cancers like lung, skin, lymphoma, and thyroid cancer. The research plans to address stability and interpretability so clinicians can use the methods in real-world care.
Why it matters
Potential benefit: If successful, these methods could lead to more accurate prognosis predictions and better-tailored treatment decisions for cancer patients.
How similar studies have gone: Previous work showed deep learning approaches can outperform traditional methods in prognosis prediction, though with stability and interpretability challenges that this project aims to resolve.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Ma, Shuangge — Yale University
- Study coordinator: Ma, Shuangge
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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.