Wang Zheng, Qu Shuoying, Zhu Jie, Chen Fengzhe, Ma Lixian
Department of Infectious Diseases, Shandong University Qilu Hospital, Jinan 250012, China.
Department of Clinical Laboratory, Shandong University Qilu Hospital, Jinan 250012, China.
J Thorac Dis. 2020 May;12(5):1856-1865. doi: 10.21037/jtd-19-2842.
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.
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.
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.
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.
特发性肺纤维化（IPF）是一种病因不明的危及生命的肺部疾病。长链非编码RNA（lncRNAs）及其相关的竞争性内源性RNA（ceRNA）网络在IPF中的作用仍知之甚少。在本研究中，我们旨在构建lncRNA- miRNA- mRNA网络并探讨IPF的发病机制。
我们从两个数据集中筛选了IPF与对照肺组织之间差异表达的lncRNAs（DElncRNAs）和mRNAs（DEmRNAs）。根据DElncRNA、miRNA和DEmRNA之间的相互作用构建ceRNA网络。使用Metascape对DEmRNAs进行功能富集分析。应用CIBERSORT（通过估计已知RNA转录本的相对子集进行细胞类型鉴定）来估计IPF和对照肺组织样本中22种免疫细胞的比例。然后我们研究了免疫细胞与临床特征之间的相关性。
我们构建了一个lncRNA- miRNA- mRNA网络，该网络由两个DElncRNAs、18个miRNAs、66个DEmRNAs组成。功能富集分析表明，DEmRNAs主要参与癌症中的MicroRNAs。通过应用CIBERSORT，我们发现与对照组织样本相比，IPF组织样本中浆细胞、静息肥大细胞的比例较高，而静息NK细胞、单核细胞、中性粒细胞的比例较低。此外，我们的结果表明免疫细胞与IPF的严重程度相关。
总之，这是第一项构建IPF的lncRNA- miRNA- mRNA ceRNA网络的研究，这可能会提高我们对IPF发病机制的理解。我们的研究表明，肺组织中的免疫细胞可能预测疾病严重程度并参与IPF的发展。未来需要进行前瞻性研究来证实本研究的结果。
