Modeling keloid expansion: Integrating single-cell and spatial transcriptomics with mathematical approaches

Summary: Keloid is a tumor-like scarring disorder of human skin that arises in genetically predisposed individuals following injury. Unlike other pathological scars, keloids exhibit a distinctive horizontal propagation pattern. Here, we integrated single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), and agent-based mathematical modeling (ABM) to investigate the mechanisms driving keloid progression. Our integrated analysis on scRNA-seq and ST data revealed that heterogeneous fibroblast populations are uniquely enriched at the keloid periphery, forming a distinct spatial distribution pattern. To explore the signaling mechanisms underlying keloid propagation, we developed an ABM incorporating fibroblasts and extracellular collagen fibers. We evaluated multiple interaction models for fibroblast subtypes, and simulations demonstrated that keloid propagation was consistently recapitulated under specific models with defined activation and inhibition dynamics. These findings suggest that fibroblast-mediated signaling networks are key drivers of keloid expansion. Targeting these interactions may provide promising therapeutic strategies for next-generation keloid treatments. Yingzi Liu¹, Christian Guerrero-Juarez², Angeliz Casillas³, Qixuan Wang³, Qing Nie¹, Ji Li⁴, Maksim V. Plikus¹ 1. University of California Irvine, Irvine, CA, United States. 2. Carle Illinois College of Medicine, Urbana, IL, United States. 3. University of California Riverside, Riverside, CA, United States. 4. Xiangya Hospital Central South University, Changsha, Hunan, China. Bioinformatics, Computational Biology, and Imaging