Expression of circular RNA has-circ-0009158 and identification of associated miRNA-mRNA network in hepatocellular carcinoma

Abstract

Primary hepatocellular carcinoma (HCC) affects people all over the world. Circular RNAs are involved in the growth and development of several malignancies and regulate a number of biological processes. However, the roles of has-circ-0009158 in HCC remain unknown. This study explored the expression and associated miRNA-mRNA network of has-circ-0009158 in HCC. Quantitative real-time polymerase chain reaction was used to measure the expression of hsa-circ-0009158 in the HCC tissues of 143 patients and four human HCC cell lines. Then, the potential relationship of hsa-circ-0009158 expression with clinical characteristics and prognosis of patients was analyzed using the GO and KEGG databases. Correlated miRNA-mRNA networks were forecasted using the TCGA database and Cytoscape software. The hsa-circ-0009158 expression was significantly upregulated in HCC tissues and cell lines (P<0.001). The multivariate Cox analysis revealed that HCC patients were associated with high hsa-circ-0009158 expression. The bioinformatics analysis screened 1 miRNA, and 248 mRNAs associated with the circRNA in HCC. A pathway analysis suggested that the differentially expressed genes (DEGs) may be linked to the development and growth of HCC tumors. Ten hub genes (MELK, NCAPG, BUB1B, BIRC5, CDCA8, CENPF, BUB1, CDK1, TTK, TPX2) were identified from the PPI network based on the 248 genes. Additionally, the 10 hub genes that were verified had an association between high expression levels and low overall survival rates. As a result, the high expression of hsa-circ-0009158 was found to be a separate risk factor for recurrence and a poor prognosis in HCC patients.

Keywords: Circular RNA; hepatocellular carcinoma; hsa-circ-0009158; poor prognosis; recurrence.

Figure 1

Relative expression of hsa-circ-0009158 in HCC and adjacent normal tissues. A. Hsa-circ-0009158 expression was significantly upregulated in HCC tissues compared with the adjacent normal tissues (P<0.001). B. The waterfall plot showed that hsa-circ-0009158 was significantly and highly expressed in 85.3% of the HCC tissue.

Figure 2

Hsa-circ-0009158 expression in HCC cells and normal hepatocyte lines. Hsa-circ-0009158 was significantly up regulated in four HCC cell lines (PLC, Huh7, Hep3B, and SMMC-7721) compared to normal l-hepatocyte QSG-7701 (***P<0.001).

Figure 3

Prognostic significance of hsa-circ-0009158 expression in HCC patients. By multivariate Cox regression analysis, high hsa-circ-0009158 expression was identified as an independent prognostic factor in HCC patients. A. Cumulative recurrence-free survival curves of patients in high and low hsa-circ-0009158 expression groups. B. Cumulative survival curves of patients in high and low hsa-circ-0009158 expression groups. C. Forest plot of the results of multivariate Cox analysis for RFS. D. Forest plots of the results of multivariate Cox analysis for OS.

Figure 4

Prediction and prognosis of miRNA that interacted with has-circ-0009158. A. Venn diagram displaying the overlaps of miRNA predicted by the intersection of differential miRNAs in TCGA and prediction of in CircInteractome database. B. Volcano map displaying the differential genes present in the TCGA database. C. Venn diagram displaying the overlaps of mRNA predicted by the intersection of differential mRNAs in TCGA and prediction of in TargetScan database. D. Correlation between has-miR-942 and overlaps of mRNAs, the color red signifies a significant level of expression, and the color blue is a low level of expression.

Figure 5

GO and KEGG pathway analyses of DEGs. Bubble plot of DEGs GO analysis: BP (A), MF (B) and CC (C). (D) Bubble maps depicting the top 5 signaling pathways in the KEGG enrichment analysis of differential genes.

Figure 6

The PPI network is constructed based on DEmRNAs in cytoscape. A. PPI network of all DEGs, the color of nodes stands for the expression of the gene, dark orange signifies high expression, and blue colors suggest that a gene is expressed at low levels. Edges stand for the relevance of two genes to each other, dark purple represents a high level of correlation, and orange indicates a weak correction margin. B. The top 10 genes are ordered by the approaches of MCC, darker red means higher correlated genes. C. Corplot of the top 10 genes in TCGA, the blue color implies a higher degree of correlation.

Figure 7

The different expressions of the top 10 mRNAs from TCGA, the box plots in red refer to tumors, the blue box plots reflect normal samples.

Figure 8

Validation of the hub genes at the translational level by means of the HPA database. (A) TTK, (B) CDCA8, (C) TPX2, (D) MELK, (E) BIRC5, (F) BUB1, (G) CDK1, (H) NCAPG, (I) CENPF.

Figure 9

Overall survival of the top 10 hub genes in HCC patients from TCGA. Kaplan-Meier survival curves showing the association between (A) NCAPG, (B) BIRC5, (C) CDK1, (D) TPX2, (E) BUB1, (F) BUB1B, (G) TTK, (H) CDCA8, (I) MELK, (J) CENPF, and overall survival in TCGA HCC patients.