Dynamic hybrid-hydrogel lung models decouple matrix composition, stiffness, and fibroblast memory to define distinct drivers of fibrotic progression
Dynamic hybrid-hydrogel lung models decouple matrix composition, stiffness, and fibroblast memory to define distinct drivers of fibrotic progression
Blomberg, R.; Mueller, M. C.; Vu, T.; Essmaeil, D. H.; Riches, D. W. H.; Magin, C. M.
AbstractIdiopathic pulmonary fibrosis is a devastating chronic lung disease characterized by progressive scarring of the lung, which leads to impaired gas exchange and ultimately death. While research has provided us with extensive understanding on end-stage disease, the factors that lead to forward-feedback loops of fibrotic progression are still not fully known. Cell intrinsic activation, pathological extracellular matrix (ECM) composition, and increased tissue stiffness are all hallmarks of advanced fibrosis, but the relative contribution of these factors to disease has been difficult to disentangle using classic in vivo models. In this study we created biomaterials-based 3D lung models that incorporate geometrically relevant co-culture of lung epithelial cells and fibroblasts with tunable stiffness, ECM-containing hybrid-hydrogels. Using this model system, we demonstrated that environmental stiffness has the strongest effect on overall fibroblast activation. RNAseq analysis revealed unique gene-level changes in both fibroblasts and epithelial cells due to both composition and stiffness, highlighting the importance of incorporating both factors into any in vivo disease models. Overall, these results reinforce the value of biomaterials-based models in understanding disease pathogenesis, and their potential for screening of treatment responses.