IPF is a progressive disease that is associated with a poorer prognosis and a shorter survival time even compared with some cancers[25, 26]. Lung transplantation is the only way for end-stage IPF patients, while several stumbling blocks including donor shortage, proper selection of candidates, primary graft dysfunction, and chronic lung allograft dysfunction limit the application of lung transplantation[27, 28]. Thus, comprehension of the pathological and molecular mechanisms of IPF is necessary for clinical diagnosis and treatment.
In this study, we analyzed the DEGs in lung tissues from IPF patients and normal controls. Several genes that are specifically expressed in the respiratory system were identified by bioinformatic analysis. In total, 183 DEGs were identified from two microarray expression profiling datasets (GSE15197, GSE48149), including 56 downregulated genes and 127 upregulated genes. GO and KEGG enrichment analyses were performed to explore interactions among the DEGs.
GO analyses revealed that the changes in the modules were mostly enriched in extracellular matrix organization, extracellular matrix, endoplasmic reticulum lumen, collagen trimer, collagen fibril organization, and extracellular matrix structural constituent conferring tensile strength. KEGG pathway analysis demonstrated that the DEGs were mainly enriched in the protein digestion and absorption signaling pathway, AGE-RAGE signaling pathway in diabetic complications, viral protein interaction with cytokine, cytokine receptor signaling pathway, IL-17 signaling pathway, and metabolism of xenobiotics by cytochrome P450.
The extracellular matrix serves as a reservoir for a number of growth factors and cytokines that are vital for cell differentiation and proliferation[29, 30]. Several studies have demonstrated that the pathological changes in the extracellular matrix of lung cancers were also found in IPF, such as increased collagen expression, altered collagen cross-linking, and subsequent increase in tissue stiffness[31, 32]. The role of AGE-RAGE signaling has been demonstrated in the progression of various types of cancer and other pathological disorders[33]. Li et.al found that the activation of the IL-17 signaling pathway could promote pyroptosis in pneumonia-induced sepsis [34]. Interestingly, these findings provided practical reasoning to consider IPF a caner-like disease from the aspect of activation of specific signaling pathways and altered expression of microRNAs.
Moreover, in our analysis, 51 tissue-specific expressed DEGs were identified, among which 25 were tissue-specifically expressed in the respiratory system. We performed a PPI network of the DEGs specifically expressed in the respiratory system and identified 7 upregulated genes (SERPINB5, COL17A1, CLCA2, KRT17, KRT5, CDH3) and 6 downregulated genes (CLDN18, CRTAC1, AGER, SFTPA2, SFTPA1, ABCA3). BiNGO was adopted to determine the BPs in which the identified DEGs specifically expressed in the respiratory system were involved in IPF. It indicated that the 13 genes were mainly involved in processes of hemidesmosome assembly, cell-substrate junction assembly, cell junction assembly, and cell component assembly.
Hemidesmosomes are specialized multiprotein transmembrane complexes that facilitate the binding of keratin intermediate filament (IF) in epithelial cells to the underlying basement membrane and ECM. This binding is essential for the maintenance of integrity and mechanical stability of the lung[35]. It is now generally agreed that the pathogenesis of IPF is related to epithelial injury from endogenous or exogenous events, which results in widespread fibrosis, which replaces the normal lung parenchyma[36]. Our analysis showed that the genes involved in the process of hemidesmosome assembly may play the main role in IPF. COL17A1 is a transmembrane protein that is a structural component of hemidesmosomes and has been reported to be regulated by promoter methylation in epithelial cancers[37]. Population studies initially implicated the role of specific genetic variants including MUC5B, TERT, TERC, SFTPC, and SFTPA2 in the development of IPF[38, 39]. Overall, these findings are consistent with our data mining results.
There are several limitations to our study. Firstly, since it was a public dataset, the information of age and health conditions as well as the usage of the medication of the individuals was unavailable, which appears to be a potential limitation. Secondly, it may be inspiring to examine the basic expression of these predicted DEGs in the development of IPF. Although data mining results suggested a series of DEGs playing main roles in IPF, as a chronic disease, we could know more about the process of the disease if we can detect the change of the DEGs. Thirdly, the role of DEGs that were specifically expressed in the non-respiratory systems still needs more investigation to illustrate the mechanism and provide potentially valuable information on IPF and other diseases.
In conclusion, our current analysis was designed to identify DEGs that may be involved in the pathogenesis of the progression of IPF. A total of 183 genes and 25 respiratory system specifically expressed DEGs were identified and may provide potential target genes for diagnosis and therapy of IPF. Among all of the DEGs, 13 DEGs specifically expressed in the respiratory system were identified with a PPI network. GO and KEGG analyses demonstrated that extracellular matrix organization, hemidesmosome assembly, and Protein digestion and absorption signaling pathway may be potential targets for the treatment of IPF. Further studies are still needed to study the relationship between these genes and IPF.