Hydrogels have been developed and applied to various biomedical applications due to their biocompatibility. However, understanding of modulation between cells to hydrogel interface is still unclear, and parameters to explain the interaction are not sophisticated enough. In this report, we studied the effect of polymer chain flexibility on cell adhesion to various hydrogel constructs of collagen and fibrin gels. Specifically, novel method of semi-flexible model-based analysis confirmed that chain flexibility mediated microstructure of the hydrogels is a critical factor for cell adhesion on their surfaces. The proposed analysis showed possibility of more accurate prediction of biocompatibility of hydrogels, and it should be considered as one of the important criteria for polymer design and selections for enhancing both biocompatibility and biofunctionality.
Invasion and metastasis of cancer directly related to human death have been associated with interactions among many different types of cells and three-dimensional (3D) tissue matrices. Precise mechanisms related to cancer invasion and metastasis still remain unknown due to their complexities. Development of tumor microenvironment (TME)-mimicking system could play a key role in understanding cancer environments and in elucidating the relating phenomena and their driving forces. Here we report a facile and novel platform of 3D cancer cell-clusters using human adipose-derived mesenchymal stem cells (hASCs) and breast cancer cells (MDA-MB-231) within a collagen gel matrix to show cancer invasion in the cell and extracellular matrix (ECM). Both clusters A (hASC only) and AC (hASC and MDA-MB-231) exhibited different behaviors and expressions of migration and invasion, as observed by the relating markers such as fibronectin, α-SMA, and CXCR4. hASCs showed a protrusive migration from a cluster center, whereas MDA-MB-231 spread out radially followed by hASC migration. Finally, the effect of matrix was further discussed by varying collagen gel densities. The new biomimetic system of 3D cancer clusters developed here has the potential to be utilized for research on migration and invasion of cancer cells in extracellular matrices.
BackgroundExposure to air particulate matter (PM) is associated with various diseases in the human respiratory system. To date, most in vitro studies showing cellular responses to PM have been performed in cell culture using a single cell type. There are few studies considering how multicellular networks communicate in a tissue microenvironment when responding to the presence of PM. Here, an in vitro three-dimensional (3D) respiratory mucosa-on-a-chip, composed of human nasal epithelial cells, fibroblasts, and endothelial cells, is used to recapitulate and better understand the effects of urban particulate matter (UPM) on human respiratory mucosa.ResultsWe hypothesized that the first cells to contact with UPM, the nasal epithelial cells, would respond similar to the tissue microenvironment, and the 3D respiratory mucosa model would be a suitable platform to capture these events. First, whole transcriptome analysis revealed that UPM induced gene expression alterations in inflammatory and adhesion-related genes in human nasal epithelial cells. Next, we developed an in vitro 3D respiratory mucosa model composed of human nasal epithelial cells, fibroblasts, and endothelial cells and demonstrated that the model is structurally and functionally compatible with the respiratory mucosa. Finally, we used our model to expose human nasal epithelial cells to UPM, which led to a disruption in the integrity of the respiratory mucosa by decreasing the expression of zonula occludens-1 in both the epithelium and endothelium, while also reducing vascular endothelial cadherin expression in the endothelium.ConclusionsWe demonstrate the potential of the 3D respiratory mucosa model as a valuable tool for the simultaneous evaluation of multicellular responses caused by external stimuli in the human respiratory mucosa. We believe that the evaluation strategy proposed in the study will move us toward a better understanding of the detailed molecular mechanisms associated with pathological changes in the human respiratory system.
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