Personalized cancer subtyping and risk prediction with multi-omics data
Official title: Personalization of graphical models using multi-omics data for subtype discovery andprognosis
Funded at Wayne State University · NIH-11551038 · Data updated 2026-11-12
A cancer research project aims to classify tumors and predict risk by integrating multiple molecular data types to tailor treatments for patients.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Wayne State University NIH-funded |
| Lab location | 1 site (Detroit, United States) |
| Project start | September 15, 2023 |
| Project end | August 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $612,698 |
| NIH project number | 7U01CA274573-04 |
| Project ID | NIH-11551038 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with cancer whose tumors may advance or resist standard targeted therapies could be candidates for future personalized approaches.
✕Less likely to help
Patients whose tumors do not fit detectable pathway patterns or who are not eligible for pathway-based subtyping may see limited benefit.
What this research studies
This project looks at how cancer subtypes and prognosis can be determined by combining genomics, metabolomics, methylation, and other molecular data to go beyond single-gene targets. The team has already created a Sample-Level Pathway Analysis framework and is extending it to include more data types to find common pathway mechanisms across patients. The goal is to identify patient-specific subtypes that reveal which therapies are most likely to work and how resistance might develop. Results could lead to more accurate classification and better personalized treatment strategies.
Why it matters
Potential benefit: If successful, patients could receive more precisely matched therapies based on their tumor biology and pathway activity.
How similar studies have gone: Previous work shows that pathway-level analyses can differentiate cancer subtypes better than single-gene analyses, supporting potential benefit of this approach.
Where this research is happening
-
Wayne State University
Detroit, United States Active
Researchers
- Principal investigator: Nguyen, Tin C — Wayne State University
- Study coordinator: Nguyen, Tin C
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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.