Mechanical perspectives on fibroblasts in wound healing and tumorigenesis

Abstract

Fibroblasts play a critical role in pathological conditions such as wound healing and tumorigenesis. When analyzing fibroblasts, which do not have a specific biomarker, in such complex pathological processes, the conventional molecular biological approach has limitations. In this regard, in the dissertation, the combination of a biomolecular approach and cell mechanics-based approach was applied to extensively investigate the role of fibroblasts in the pathophysiology of the wound healing process and tumorigenesis. From a cell mechanics pointof view, a cell is regarded as a physical system, and the physical phenotypes of the cell are analyzed and evaluated as the final product of complex gene expression. In the first study, a novel model of the wound healing process and scar formation was suggested by observing the response of fibroblasts to tensile stimulation. In the second study,a new positive feedback loop for breast cancer was proposed by mimicking specific cancer-associated fibroblasts and analyzing the effects of these cells on breast cancer progression. Finally, an artificial intelligence (AI)classification system for subtypes of cancer-associated fibroblasts was developed based on cell mechanical properties. The AI platform was then tested with in vitro breast cancer-associated fibroblast models to verify the applicability of the alternative and novel classification platform.