To understand scar pathology, develop new drugs, and provide a platform for personalized medicine, physiologically relevant human scar models are required, which are characteristic of different scar pathologies. Hypertrophic scars and keloids are two types of abnormal scar resulting from unknown abnormalities in the wound healing process. While they display different clinical behavior, differentiation between the two can be difficult-which in turn means that it is difficult to develop optimal therapeutic strategies. The aim of this study was to develop in vitro reconstructed human hypertrophic and keloid scar models and compare these to normotrophic scar and normal skin models to identify distinguishing biomarkers. Keratinocytes and fibroblasts from normal skin and scar types (normotrophic, hypertrophic, keloid) were used to reconstruct skin models. All skin models showed a reconstructed differentiated epidermis on a fibroblast populated collagen-elastin matrix. Both abnormal scar types showed increased contraction, dermal thickness, and myofibroblast staining compared to normal skin and normotrophic scar. Notably, the expression of extracellular matrix associated genes showed distinguishing profiles between all scar types and normal skin (hyaluronan synthase-1, matrix-metalloprotease-3), between keloid and normal skin (collagen type IV), between normal scar and keloid (laminin α1), and between keloid and hypertrophic scar (matrix-metalloprotease-1, integrin α5). Also, inflammatory cytokine and growth factor secretion (CCL5, CXCL1, CXCL8, CCL27, IL-6, HGF) showed differential secretion between scar types. Our results strongly suggest that abnormal scars arise from different pathologies rather than simply being on different ends of the scarring spectrum. Furthermore, such normal skin and scar models together with biomarkers, which distinguish the different scar types, would provide an animal free, physiologically relevant scar diagnostic and drug testing platform for the future.

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http://dx.doi.org/10.1089/ten.TEC.2017.0464DOI Listing

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