Mapping how cells in your tissues communicate with each other
Developing a Novel Causal Discovery Framework to Unveil Individualized Cell-Cell Communication Networks
This project builds computer tools to create personalized maps of how cells send signals to one another in individual tissue samples, including healthy, aging, and diseased tissues.
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 ID | NIH-11292392 on NIH RePORTER |
What this research studies
From your perspective, researchers will use tissue samples (like biopsies or surgical specimens) and apply advanced deep-learning and causal modeling to reveal which cells are sending signals and which cells respond. The approach focuses on individualized maps so each tissue sample gets its own cell‑to‑cell communication network rather than a one-size-fits-all picture. The tools will look for ligand–receptor signaling paths that could causally change neighboring cells' states and explain tissue differences across people. The team plans to test the methods on examples such as normal tissues, aging samples, inflammation biopsies, and tumor specimens.
Who could benefit from this research
Good fit: People who can provide tissue samples (for example a biopsy or surgically removed tissue) from conditions like cancer, lung inflammation, or aging-related tissue changes would be suitable candidates to contribute samples.
Not a fit: This project is a computational and sample-based effort, so it is unlikely to provide direct or immediate treatment benefits to patients seeking immediate medical care.
Why it matters
Potential benefit: If successful, this could help identify why tissues behave differently between people and point to new, more personalized targets for prevention or treatment.
How similar studies have performed: Prior research has used single-cell data to map cell interactions, but applying individualized causal Bayesian network methods to reveal causal cell‑cell signaling in each sample is largely new.
Where this research is happening
Pittsburgh, United States
- University of Pittsburgh at Pittsburgh — Pittsburgh, United States (Active)
Researchers
- Principal investigator: Chen, Lujia — University of Pittsburgh at Pittsburgh
- Study coordinator: Chen, Lujia
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.