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. 2019 Jan 3;17(1):7.
doi: 10.1186/s12967-018-1761-7.

Identification of potential miRNA-mRNA regulatory network contributing to pathogenesis of HBV-related HCC

Weiyang Lou  1   2   3 , Jingxing Liu  4 , Bisha Ding  1   2   3 , Danni Chen  1   2   3 , Liang Xu  1   2   3 , Jun Ding  1   2   3 , Donghai Jiang  1   2   3 , Lin Zhou  1   2   3 , Shusen Zheng  5   6   7 , Weimin Fan  8   9   10   11
Affiliations

Identification of potential miRNA-mRNA regulatory network contributing to pathogenesis of HBV-related HCC

Weiyang Lou et al. J Transl Med. .

Abstract

Background: Hepatitis B virus (HBV) is one of the major risk factors of hepatocellular carcinoma (HCC). Increasing evidence indicates that microRNA (miRNA)-mRNA axis is involved in HCC. However, a comprehensive miRNA-mRNA regulatory network in HBV-related HCC is still absent. This study aims to identify potential miRNA-mRNA regulatory pathways contributing to pathogenesis of HBV-related HCC.

Methods: Microarray GSE69580 was downloaded from Gene Expression Omnibus (GEO) database. GEO2R and 'R-limma' were used to conduct differential expression analysis. The common miRNAs appeared in the two analytic sets were screened as potential differentially expressed miRNAs (DE-miRNAs). The prognostic roles of screened DE-miRNAs in HCC were further evaluated using Kaplan-Meier plotter database. Target genes of DE-miRNAs were predicted by miRNet. Then, protein-protein interaction (PPI) networks were established for these targets via the STRING database, after which hub genes in the networks were identified by Cytoscape. Functional annotation and pathway enrichment analyses for the target genes were performed through DAVID database. Three enriched pathways related to HBV-related HCC were selected for further analysis and potential target genes commonly appeared in all three pathways were screened. Cytoscape was employed to construct miRNA-hub gene network. The expression and correlation of potential miRNAs and targets were further detected in clinical HBV-related HCC samples by qRT-PCR.

Results: 7 upregulated and 9 downregulated DE-miRNAs were accessed. 5 of 7 upregulated DE-miRNAs and 5 of 7 downregulated DE-miRNAs indicated significant prognostic roles in HCC. 2312 and 1175 target genes were predicted for the upregulated and downregulated DE-miRNAs, respectively. TP53 was identified as the hub gene in the PPI networks. Pathway enrichment analysis suggested that these predicted targets were linked to hepatitis B, pathways in cancer, microRNAs in cancer and viral carcinogenesis. Further analysis of these pathways screened 20 and 16 target genes for upregulated and downregulated DE-miRNAs, respectively. By detecting the expression of 36 target genes, six candidate target genes were identified. Finally, a potential miRNA-mRNA regulatory network was established based on the results of qRT-PCR and expression correlation analysis.

Conclusions: In the study, potential miRNA-mRNA regulatory pathways were identified, exploring the underlying pathogenesis and effective therapy strategy of HBV-related HCC.

Keywords: Bioinformatic analysis; Hepatitis B virus (HBV); Hepatocellular carcinoma (HCC); Kaplan–Meier plotter (KM-plotter); MicroRNAs (miRNAs).

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Figures

Fig. 1
Fig. 1
Identification of potential DE-miRNAs. a, b The intersection of two differential expression analytic methods, GEO2R and R-limma: a for upregulated DE-miRNAs; b for downregulated DE-miRNA. c–l The significant prognostic roles of potential DE-miRNAs in HCC: c for hsa-miR-25; d for hsa-miR-501-3p; e for hsa-miR-93; f for hsa-miR-106b; g for hsa-miR-21; h for hsa-miR-139-5p; i for hsa-let-7c; j for hsa-miR-486-5p; k for hsa-miR-125b; l for hsa-miR-99a
Fig. 2
Fig. 2
The predicted target genes of potential DE-miRNAs. a For upregulated DE-miRNAs; b for downregulated DE-miRNAs
Fig. 3
Fig. 3
The top 30 hub genes in protein–protein interaction (PPI) network of predicted target genes. a For upregulated DE-miRNAs; b for downregulated DE-miRNAs
Fig. 4
Fig. 4
The GO annotation for the predicted target genes of potential DE-miRNAs. a1 Top 10 enriched biological process (BP) for target genes of upregulated DE-miRNAs; a2 top 10 enriched cellular component (CC) for target genes of upregulated DE-miRNAs; a3 top 10 enriched molecular function (MF) for target genes of upregulated DE-miRNAs; b1 top 10 enriched biological process (BP) for target genes of upregulated DE-miRNAs; b2 top 10 enriched cellular component (CC) for target genes of upregulated DE-miRNAs; b3 top 10 enriched molecular function (MF) for target genes of upregulated DE-miRNAs
Fig. 5
Fig. 5
The pathway enrichment analysis for the predicted target genes of potential DE-miRNAs. a The top 10 enriched KEGG pathways for target genes of upregulated DE-miRNAs; b the top 10 enriched KEGG pathways for target genes of downregulated DE-miRNAs; c the intersection of three pathways associated with HBV-related HCC for the target genes of upregulated DE-miRNAs; d the intersection of three pathways associated with HBV-related HCC for the target genes of downregulated DE-miRNAs
Fig. 6
Fig. 6
Identified potential miRNA–mRNA regulatory network contributing to pathogenesis of HBV-related HCC
Fig. 7
Fig. 7
The expression levels of five potential DE-miRNAs in clinical HBV-related HCC tissues compared to matched normal tissues. a For miR-93-5p; b for miR-106b-5p; c for miR-21-5p; d for miR-125b-5p; e for let7c-5p. *< 0.05; **< 0.01
Fig. 8
Fig. 8
The expression levels of six potential target genes in clinical HBV-related HCC tissues compared to matched normal tissues. a For JUN; b for STAT3; c for PIK3R1; d for E2F2; e for E2F3; f for NRAS. *< 0.05; **< 0.01; ***< 0.001; NS represents no significance
Fig. 9
Fig. 9
The correlation of potential DE-miRNAs and target genes. a For JUN and miR-93-5p; b for STAT3 and miR-93-5p; c for STAT3 and miR-106b-5p; d for STAT3 and miR-21-5p; e for PIK3R1 and miR-21-5p; f for E2F2 and miR-125b-5p; g for E2F3 and miR-125b-5p; h for NRAS and let7c-5p
Fig. 10
Fig. 10
The expression levels of target genes after transfection of the potential miRNA mimics. a Hep3B transfected with miRNA mimics exhibited higher expression of miRNAs than mimic negative control; b the alteration of target gene expression after transfection of miR-93-5p, miR-106b-5p, miR-21-5p, miR-125b-5p and let7c-5p mimics analyzed in Hep3B cell line using qRT-PCR. *< 0.05
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