Comprehensive analysis of lncRNA-associated competing endogenous RNA network and immune infiltration in idiopathic pulmonary fibrosis

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a life-threatening lung disorder with an unknown aetiology. The roles of long non-coding RNAs (lncRNAs) and its related competing endogenous RNAs (ceRNA) network in IPF remains poorly understood. In this study, we aimed to build a lncRNA-miRNA-mRNA network and explore the pathogenesis of IPF. METHODS: We screened differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between IPF and control lung tissues from two datasets. The ceRNA network was built according to the interactions between DElncRNA, miRNA, and DEmRNA. Functional enrichment analysis of DemRNAs was performed using Metascape. CIBERSORT (Cell type Identification by Estimating Relative Subsets Of known RNA Transcripts) was applied to estimate the fraction of 22 immune cells in IPF and controls lung tissue samples. Then we investigated the correlation between immune cells and clinical traits. RESULTS: We constructed a lncRNA-miRNA-mRNA network, which was composed of two DElncRNAs, 18 miRNAs, 66 DemRNAs. Functional enrichment analysis showed that the DEmRNAs mainly participated in MicroRNAs in cancer. By applying CIBERSORT, we found that IPF tissue samples had a higher proportion of plasma cells, resting mast cells and a lower proportion of resting NK cells, monocytes, neutrophils compared with control tissue samples. Also, our results indicated that immune cells were associated with the severity of IPF. CONCLUSIONS: In summary, this is the first study to build lncRNA-miRNA-mRNA ceRNA network of IPF, which may improve our understanding of IPF pathogenesis. Our study indicates that immune cells in lung tissues may predict disease severity and participate in the development of IPF. Future prospective studies are required to confirm the findings of the current study.