Modeling the tumor microenvironment to improve cancer treatment
Official title: Probabilistic Multiscale Modeling of the Tumor Microenvironment
Funded at Sloan-Kettering Inst Can Research · NIH-11003743 · Data updated 2026-11-12
This study is working on a new way to understand the environment around tumors to help doctors figure out how to treat cancer better, using advanced techniques to look closely at everything from single cells to groups of patients.
Quick facts
| Grant type | R37 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Sloan-Kettering Inst Can Research NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | January 1, 2023 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $625,692 |
| NIH project number | 5R37CA271186-03 |
| Project ID | NIH-11003743 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are cancer patients whose treatment responses may be influenced by the spatial architecture of their tumors.
✕Less likely to help
Patients with non-cancerous conditions or those whose tumors do not exhibit significant spatial architectural features may not benefit from this research.
What this research studies
This research focuses on developing advanced statistical models to analyze the tumor microenvironment (TME), which plays a crucial role in how tumors respond to treatment and metastasize. By utilizing high-resolution measurements and innovative Bayesian statistical methods, the project aims to create a framework called BayesTME that can evaluate the TME at various scales, from individual cells to overall patient stratification. The research will integrate diverse datasets to enhance the understanding of TME properties and improve treatment strategies for cancer patients.
Why it matters
Potential benefit: If successful, this research could lead to more effective cancer treatments tailored to the specific characteristics of a patient's tumor microenvironment.
How similar studies have gone: Other research has shown promise in using Bayesian approaches for analyzing complex biological data, indicating potential success for this novel application.
Where this research is happening
-
Sloan-Kettering Inst Can Research
New York, United States Active
Researchers
- Principal investigator: Tansey, Wesley — Sloan-Kettering Inst Can Research
- Study coordinator: Tansey, Wesley
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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.