Collagen type XIV is proportionally lower in the lung tissue of patients with IPF

Binary fabrication of decellularized lung extracellular matrix hybridgels for in vitro chronic obstructive pulmonary disease modeling

Limited treatments and a lack of appropriate animal models have spurred the study of scaffolds to mimic lung disease in vitro. Decellularized human lung and its application in extracellular matrix (ECM) hydrogels has advanced the development of these lung ECM models. Controlling the biochemical and mechanical properties of decellularized ECM hydrogels continues to be of interest due to inherent discrepancies of hydrogels when compared to their source tissue. To optimize the physiologic relevance of ECM hydrogel lung models without sacrificing the native composition we engineered a binary fabrication system to produce a Hybridgel composed of an ECM hydrogel reinforced with an ECM cryogel. Further, we compared the effect of ECM-altering disease on the properties of the gels using elastin poor Chronic Obstructive Pulmonary Disease (COPD) vs non-diseased (ND) human lung source tissue. Nanoindentation confirmed the significant loss of elasticity in hydrogels compared to that of ND human lung and further demonstrated the recovery of elastic moduli in ECM cryogels and Hybridgels. These findings were supported by similar observations in diseased tissue and gels. Successful cell encapsulation, distribution, cytotoxicity, and infiltration were observed and characterized via confocal microscopy. Cells were uniformly distributed throughout the Hybridgel and capable of survival for 7 days. Cell-laden ECM hybridgels were found to have elasticity similar to that of ND human lung. Compositional investigation into diseased and ND gels indicated the conservation of disease-specific elastin to collagen ratios. In brief, we have engineered a composited ECM hybridgel for the 3D study of cell-matrix interactions of varying lung disease states that optimizes the application of decellularized lung ECM materials to more closely mimic the human lung while conserving the compositional bioactivity of the native ECM. STATEMENT OF SIGNIFICANCE: The lack of an appropriate disease model for the study of chronic lung diseases continues to severely inhibit the advancement of treatments and preventions of these otherwise fatal illnesses due to the inability to recapture the biocomplexity of pathologic cell-ECM interactions. Engineering biomaterials that utilize decellularized lungs offers an opportunity to deconstruct, understand, and rebuild models that highlight and investigate how disease specific characteristics of the extracellular environment are involved in driving disease progression. We have advanced this space by designing a binary fabrication system for a ECM Hybridgel that retains properties from its source material required to observe native matrix interactions. This design simulates a 3D lung environment that is both mechanically elastic and compositionally relevant when derived from non-diseased tissue and pathologically diminished both mechanically and compositionally when derived from COPD tissue. Here we describe the ECM hybridgel as a model for the study of cell-ECM interactions involved in COPD.

Identification of Hub Genes and Prediction of Targeted Drugs for Rheumatoid Arthritis and Idiopathic Pulmonary Fibrosis

There is a potential link between rheumatoid arthritis (RA) and idiopathic pulmonary fibrosis (IPF). The aim of this study is to investigate the molecular processes that underlie the development of these two conditions by bioinformatics methods. The gene expression samples for RA (GSE77298) and IPF (GSE24206) were retrieved from the Gene Expression Omnibus (GEO) database. After identifying the overlapping differentially expressed genes (DEGs) for RA and IPF, we conducted functional annotation, protein-protein interaction (PPI) network analysis, and hub gene identification. Finally, we used the hub genes to predict potential medications for the treatment of both disorders. We identified 74 common DEGs for further analysis. Functional analysis demonstrated that cellular components, biological processes, and molecular functions all played a role in the emergence and progression of RA and IPF. Using the cytoHubba plugin, we identified 7 important hub genes, namely COL3A1, SDC1, CCL5, CXCL13, MMP1, THY1, and BDNF. As diagnostic indicators for RA, SDC1, CCL5, CXCL13, MMP1, and THY1 showed favorable values. For IPF, COL3A1, SDC1, CCL5, CXCL13, THY1, and BDNF were favorable diagnostic markers. Furthermore, we predicted 61 Chinese and 69 Western medications using the hub genes. Our research findings demonstrate a shared pathophysiology between RA and IPF, which may provide new insights for more mechanistic research and more effective treatments. These common pathways and hub genes identified in our study offer potential opportunities for developing more targeted therapies that can address both disorders.