Research

We use patient-derived skin tissues to investigate the complex interactions among immune, stromal, and epithelial cells within the diseased tissue microenvironment. Multiplex tissue imaging and quantitative image analysis allow us to characterize inflammatory architecture and identify disease-associated cellular populations and their spatial organization.

We apply single-cell and single-nucleus transcriptomics to define the diversity of cell types and functional states present in inflammatory skin disease. Spatial transcriptomic approaches allow us to place these molecular states back into their native tissue context and determine where disease-associated cells, pathways, and interactions occur.

We integrate transcriptomic, spatial, imaging, and computational data to identify disease-associated cellular niches and investigate how cells communicate within them. By analyzing signaling pathways and ligand–receptor networks, we generate hypotheses about the intercellular mechanisms that organize and sustain inflammation.

Computational associations alone cannot establish causality. We therefore test candidate mechanisms experimentally using human cell culture systems, gene perturbation approaches including CRISPR-Cas9, and molecular and biochemical assays. These experiments allow us to determine whether specific genes and signaling pathways are functionally required for disease-associated cellular phenotypes.

Our overall strategy is iterative: observations in patient tissues generate mechanistic hypotheses, experimental models are used to test causality, and the resulting insights are brought back to human disease. Through this approach, we aim to uncover fundamental mechanisms of skin inflammation and identify biologically grounded opportunities for new therapeutic strategies.