Understanding how cells communicate in different tissue environments
Official title: Developing a Novel Causal Discovery Framework to Unveil Individualized Cell-Cell Communication Networks
Funded at University of Pittsburgh at Pittsburgh · NIH-11043882 · Data updated 2026-11-12
This study is looking at how cells talk to each other in different tissues, which could help us understand diseases like cancer and inflammation better, by using advanced computer techniques to see how changes in one cell can impact its neighbors.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pittsburgh at Pittsburgh NIH-funded |
| Lab location | 1 site (Pittsburgh, United States) |
| Project start | March 1, 2025 |
| Project end | February 28, 2030 |
| Funding year | 2025 |
| Award (this year) | $705,795 |
| NIH project number | 1R01HG014023-01 |
| Project ID | NIH-11043882 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals with specific tissue samples from conditions such as cancer or lung inflammation.
✕Less likely to help
Patients without accessible tissue samples or those with conditions not related to cell communication may not benefit from this research.
What this research studies
This research aims to create a new computational framework that combines deep learning and causal discovery algorithms to explore how cells communicate with each other in various tissue environments. By analyzing individual tissue samples, the study will identify the unique cell-cell communication networks that exist in both healthy and diseased states. The approach involves developing a novel individualized causal Bayesian network that can model these interactions, allowing for a better understanding of how changes in one cell can affect its neighbors. This could lead to insights into the cellular dynamics in conditions like cancer or inflammation.
Why it matters
Potential benefit: If successful, this research could lead to personalized treatment strategies by revealing how individual cells interact in various diseases.
How similar studies have gone: Other research has shown promise in using computational frameworks for understanding cell interactions, but this specific approach is novel.
Where this research is happening
-
University of Pittsburgh at Pittsburgh
Pittsburgh, United States Active
Researchers
- Principal investigator: Chen, Lujia — University of Pittsburgh at Pittsburgh
- Study coordinator: Chen, Lujia
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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.