Using tissue-level genomic maps to improve cancer risk predictions
Statistical Methods for Precision Prevention
This project develops new computer methods to read tumor and tissue molecular maps so doctors can better identify people at higher risk of aggressive cancer.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Fred Hutchinson Cancer Center NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project ID | NIH-11240304 on NIH RePORTER |
What this research studies
From a patient's point of view, researchers are building statistical and deep‑learning tools that learn from detailed genomic and spatial maps of tissues to find patterns linked to aggressive cancers. They will combine unsupervised and supervised machine learning to pull out common features across samples and link those features to individual risk factors. The team plans to integrate existing biomarker summaries and handle challenges like small sample sizes and differences between tissue images. Ultimately the work uses patient-derived genomic and tissue data to create risk-based prevention strategies.
Who could benefit from this research
Good fit: Ideal candidates would be people who have provided tumor or tissue samples, are enrolled in genomic or biospecimen studies, or have known elevated cancer risk that includes available molecular data.
Not a fit: People without available tissue or genomic data or those seeking an immediate change in clinical treatment are unlikely to see direct short-term benefit.
Why it matters
Potential benefit: If successful, this work could help identify people at higher risk for aggressive cancers so they can receive more personalized screening or preventive care.
How similar studies have performed: Genomics and machine-learning approaches have shown promise for predicting cancer outcomes, but combining spatial omics with deep learning for precision prevention is relatively new and exploratory.
Where this research is happening
Seattle, United States
- Fred Hutchinson Cancer Center — Seattle, United States (Active)
Researchers
- Principal investigator: Hsu, Li — Fred Hutchinson Cancer Center
- Study coordinator: Hsu, Li
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.