Analysis of Transcription Factor-Related Regulatory Networks Based on Bioinformatics Analysis and Validation in Hepatocellular Carcinoma

Abstract

Hepatocellular carcinoma (HCC) accounts for a significant proportion of liver cancer, which has become the second most common cause of cancer-related mortality worldwide. To investigate the potential mechanisms of invasion and progression of HCC, bioinformatics analysis and validation by qRT-PCR were performed. We found 237 differentially expressed genes (DEGs) including EGR1, FOS, and FOSB, which were three cancer-related transcription factors. Subsequently, we constructed TF-gene network and miRNA-TF-mRNA network based on data obtained from mRNA and miRNA expression profiles for analysis of HCC. We found that 42 key genes from the TF-gene network including EGR1, FOS, and FOSB were most enriched in the p53 signaling pathway. The qRT-PCR data confirmed that mRNA levels of EGR1, FOS, and FOSB all were decreased in HCC tissues. In addition, we confirmed that the mRNA levels of CCNB1, CCNB2, and CHEK1, three key markers of the p53 signaling pathway, were all increased in HCC tissues by bioinformatics analysis and qRT-PCR validation. Therefore, we speculated that miR-181a-5p, which was upregulated in HCC tissues, could regulate FOS and EGR1 to promote the invasion and progression of HCC by p53 signaling pathway. Overall, the study provides support for the possible mechanisms of progression in HCC.

Figure 1

Process of TF-related regulatory network construction and key genes identification in HCC.

Figure 2

Identification of 237 common DEGs from the four cohort profile data sets. (a) 57 commonly upregulated DEGs. (b) 180 commonly downregulated DEGs. Different color areas represented different datasets. The cross areas meant the commonly changed DEGs. DEGs were identified with classical t-test; statistically significant DEGs were defined with p<0.05 and |logFC|>1 as the cut-off criterion.

Figure 3

Enrichment analysis of DEGs.

Figure 4

TF-related regulatory network. (a) TF-target network of these 42 key genes in HCC. (b) The brief framework of this network. TF-target network consisted of 42 nodes and 62 edges. The ellipses in the TF-gene network represented mRNAs with red (upregulated) and green (downregulated), and the diamonds represented TFs. The ellipses with a number were the clustered genes in the brief framework and the number of genes is shown inside. The interaction relationship between TFs and mRNAs were represented by arrows, and the direction of the arrow was from the source to the target. Different colors in the lines represented the different interaction relationship between the TFs and targets: red was for activation, green for repression, and grey for unknown.

Figure 5

miRNA-TF-mRNA regulatory network for HCC. The squares in the network represented miRNAs, and the ellipses represented mRNAs, and the diamonds represented TFs. The nodes in red were upregulated, whereas the nodes in green were downregulated. The interaction relationship among TFs, mRNAs, and miRNAs was represented by arrows, and the direction of the arrow was from the source to the target. Different colors in the lines represented the different interaction relationship among TFs, mRNAs, and miRNAs: red was for activation, green for repression, and grey for unknown.

Figure 6

Enrichment analysis of key genes.

Figure 7

Study of the clinical association of EGR1, FOS, FOSB, CCNB1, CCNB2, and CHEK1 with the clinicopathologic parameters of hepatocellular carcinoma. (a) Boxplots depicting RNA expression levels of key genes in HCC (n = 371) versus nonmalignant liver (n = 50) from TCGA. (b) Kaplan-Meier plots comparing the overall survival rates in HCC cases (n=365) with high expression or without low/medium expression. The data was recruited from UALCAN. P<0.05 was considered statistically significant. (c) Correlation analysis of three TFs and three p53 markers. The data was recruited from Linkedomics (http://www.linkedomics.org).

Figure 8

Validation of key genes and hsa-miR-181a-5p expression in 20 pairs of HCC and adjacent nontumor tissues by qRT-PCR. Detection of EGR1, FOS, FOSB, CCNB1, CCNB2, and CHEK1 mRNA expression and hsa-miR-181a-5p expression in HCC versus adjacent nontumor tissues was performed using qRT-PCR. Levels of EGR1, FOS, and FOSB mRNA were 0.493±0.558-, 0.494±0.476-, and 0.500±0.551-fold downregulated in tumor tissues, respectively, compared to those in the adjacent nontumor ones. And the levels of CCNB1, CCNB2, and CHEK1 mRNA were 3.938±3.887-, 3.225±3.388-, and 3.186±3.508-fold upregulated. The relative expression of hsa-miR-181a-5p was 1.694±1.236-fold upregulated. ∗p<0.05, ∗∗p<0.01, and ∗∗∗p<0.001.