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. 2018 Dec;42(6):3256-3268.
doi: 10.3892/ijmm.2018.3892. Epub 2018 Sep 24.

Potential regulatory role of circular RNA in idiopathic pulmonary fibrosis

Affiliations

Potential regulatory role of circular RNA in idiopathic pulmonary fibrosis

Rongrong Li et al. Int J Mol Med. 2018 Dec.

Abstract

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive type of interstitial pneumonia with unknown causes, poor prognosis and no effective therapy available. Circular RNAs (circRNAs), which serve as potential therapeutic targets and diagnostic biomarkers for certain diseases, represent a recent hotspot in the field of RNA research. In the present study, a total of 67 significantly dysregulated circRNAs were identified in the plasma of IPF patients by using a circRNA microarray. Among these circRNAs, 38 were upregulated, whereas 29 were downregulated. Further validation of the results by polymerase chain reaction analysis indicated that Homo sapiens (hsa)_circRNA_100906, hsa_circRNA_102100 and hsa_circRNA_102348 were significantly upregulated, whereas hsa_circRNA_101225, hsa_circRNA_104780 and hsa_circRNA_101242 were downregulated in plasma samples of IPF patients compared with those in samples from healthy controls. The majority of differentially expressed circRNAs were generated from exonic regions. The host genes of the differentially expressed circRNAs were involved in the regulation of the cell cycle, adherens junctions and RNA transport. The competing endogenous RNA (ceRNA) network of the circRNAs/micro(mi)RNAs/mRNAs indicated that circRNA‑protected mRNA participated in transforming growth factor‑β1, hypoxia‑inducible factor‑1, Wnt, Janus kinase, Rho‑associated protein kinase, vascular endothelial growth factor, mitogen‑activated protein kinase, Hedgehog and nuclear factor κB signalling pathways or functioned as biomarkers for pulmonary fibrosis. Furthermore, luciferase reporter assays confirmed that hsa_circRNA_100906 and hsa_circRNA_102348 directly interact with miR‑324‑5p and miR‑630, respectively, which were downregulated in IPF patients. The present study provided a novel avenue for exploring the underlying molecular mechanisms of IPF disease.

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Figures

Figure 1
Figure 1
circRNA expression profile in IPF patients. (A) Variations (or reproducibility) of circRNA expression between the experiment and control groups were visualized in a scatter plot. The values on the X- and Y-axis are the normalized signal values of the samples (log2 scaled) or the averaged normalized signal values of groups of samples (log2 scaled). The green lines represent the fold change of 1.5. The circRNAs above the top green line and below the bottom green line indicate circRNAs with a fold change of >1.5 between the two compared samples. (B) Hierarchical clustering reveals the distinguishable circRNA expression profiling between IPF patients and normal human samples. Each column represents a sample and each row represents a circRNA. High or low relative expression is displayed as a red or green strip, respectively. Each group contains three different samples. (C) Volcano plots are useful tools for visualizing differential expression between two different conditions. The vertical lines correspond to a 1.5-fold up- and downregulation, and the horizontal line represents a P-value of 0.05. The red dots in the plot represent the differentially expressed circRNA with statistical significance. (D) Distribution of differentially expressed circRNAs in human chromosomes. Ctrl, control; IPF, idiopathic pulmonary fibrosis; circRNA, circular RNA; NC, normal control; hsa, Homo sapiens.
Figure 2
Figure 2
Validation of the differential expression of circRNAs in IPF and normal control samples. The expression levels of circRNAs were detected usingreverse-transcription quantitative polymerase chain reaction. Gene expression was quantified using the ΔCt method with normalization to GAPDH expression levels. An higher ΔCt value indicates lower expression. Values are expressed as the mean ± standard deviation (n=10). *P<0.05, **P<0.01 or ***P<0.001 vs. the NC determined via unpaired Student’s t-tests. IPF, idiopathic pulmonary fibrosis; circRNA, circular RNA; NC, normal control.
Figure 3
Figure 3
Correlation of differential expression of circRNAs with their host genes. (A) Bar graph presenting the circRNA category. (B and C) Results of a Kyoto Encyclopedia of Genes and Genomes pathway analysis displaying the participant pathways of host genes. (D-I) Designated orientations and exon structure of detected six circRNA. For example, has_circRNA_104780 is formed when the 5′ splice site at the end of exon 4 is joined to the 3′ splice site at the beginning of exon 2 (purple). circRNA, circular RNA; Chr, chromosome; Sig, significantly enriched, UTR, untranslated region; hsa, Homo sapiens. ELP2, elongator acetyltransferase complex subunit 2; GRHPR, glyoxylate and hydroxypyruvate reductase; ANKRD42, ankyrin repeat domain 42; ZMYM2, zinc finger MYM-type containing 2; CDC27, cell division cycle 27; PAN3, poly(A) specific ribonuclease subunit PAN3.
Figure 4
Figure 4
Interaction network of circRNAs and miRNAs. (A) circRNA-miRNA interaction network consisting of 38 upregulated circRNAs, 29 downregu-lated circRNAs and their target miRNAs. They were connected by 333 edges based on seed sequence pairing interactions. (B) Interaction of 10 circRNAs (including 6 verified circRNAs: hsa_circRNA_100906, hsa_circRNA_102100, hsa_circRNA_102348, hsa_circRNA_101225, hsa_circRNA_104780 and hsa_circRNA_101242; and 4 circRNAs with high expression and predicted binding, which serves an important role in lung fibrosis) and their target miRNAs presented in a magnified network. Red and green nodes represent upregulated and downregulated circRNAs, respectively. Purple nodes indicate miRNAs. miR/miRNA, microRNA; circRNA, circular RNA; hsa, Homo sapiens.
Figure 5
Figure 5
Detailed annotation for circRNA/miRNA interaction based on TargetScan and miRanda. The ‘2D Structure’ column presents the sequences of circRNA and miRNA. The ‘Local AU’ column displays 30 nucleotides upstream and downstream of the seed sequence. The ‘Position’ column indicates the probable position of the miRNA response element on the circRNA. (A and B) Interaction between hsa_circRNA_101242 and hsa_miR-21-3p or hsa_miR-338-3p, respectively. (C and D) Interaction between hsa_circRNA_100906 and hsa_miR-330-5p or hsa_miR-324-5p, respectively. (E-H) Display of the interaction of (E) hsa_circRNA_101225 and hsa_miR-326, (F) hsa_circRNA_102348 and hsa_miR-630, (G) hsa_circRNA_102100 and hsa_miR-532-5p and (H) hsa_circRNA_104780 and hsa_miR-650. miR/miRNA, microRNA; circRNA, circular RNA; UTR, untranslated region; hsa, Homo sapiens.
Figure 6
Figure 6
Direct interaction between circRNA and miRNA. (A and B) Expression levels of miR-630 and miR-324-5p in IPF patients. ΔCt values were determined to quantify gene expression. Higher ΔCt value indicates lower expression. C. elegans miRNA 39-3p was used as a normalization control. Values are expressed as the mean ± standard deviation (n=10). **P<0.01 vs. the NC group measured via unpaired Student’s t-tests. (C) Wild-type and mutated miR-324-5p binding site on hsa_circRNA_100906. (D) hsa_circRNA_102348 sequences containing wild-type or mutated miR-630 binding sites. (E and F) Dual-luciferase reporter assay demonstrated direct binding or miR-324-5p and miR-630 with circRNA-100906 and circRNA-102348, respectively. Values are expressed as the mean ± standard deviation. ***P<0.001; ###P<0.001 measured via analysis of variance and Student-Newman-Keuls test. miR/miRNA, microRNA; IPF, idiopathic pulmonary fibrosis; circRNA, circular RNA; NC, normal control; WT, wild-type; MT, mutated type; Luc, luciferase; R, Renilla.
Figure 7
Figure 7
Prediction ofcompeting endogenous RNA network of circRNAs/miRNAs/mRNAs. (A) Bioinformatics prediction of the circRNA/miRNA/mRNA network. Red represents circRNA, green represents mRNA and blue represents miRNA. (B) Kyoto Encyclopedia of Genes and Genomes analysis of pathways enriched by the targeted mRNAs. miR/miRNA, microRNA; circRNA, circular RNA. JAK, Janus kinase; STAT, signal transducer and activator of transcription; PI3K, phosphoinositide-3 kinase; HIF, hypoxia-inducible factor; TGF, transforming growth factor; VEGF, vascular endothelial growth factor; MAPK, mitogen-activated protein kinase.

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