A transcriptomic analysis of malignant transformation of human embryonic esophageal epithelial cells by HPV18 E6E7

Abstract

Background: Esophageal cancer is one of the most common malignant tumours in humans. A series of esophageal cancer cell lines are accompanied by human papilloma virus (HPV) infection, but the mechanism behind HPV in cancer malignancy is not clear.

Methods: This research was conducted in different generations of HPV E6E7 gene-induced human foetal esophageal epithelial immortalised cells (Shantou Human Embryonic Esophageal Epithelial cell line; SHEE); the RNA sequencing transcriptomic analysis was performed to explore the mechanism of HPV infection in these cell lines.

Results: The results showed that there are 9,990 differential genes in late-stage cells compared with HPV18 E6E7-infected early foetal esophageal epithelial immortalised cells. Among these, 4,882 genes are upregulated, and 5,108 genes are downregulated. We used bioinformatics to analyze the expression and function of aberrantly expressed lncRNA, miRNA, mRNA and construct the competing endogenous RNA (ceRNA) network and protein protein interaction (PPI) network.

Conclusions: we predicted TP53TG1 promotes to malignant transformation of SHEEs by acting as a ceRNA to competitively bind to miR-6835 and regulate IGF2 expression. We also predicted IL6 serve as prognostic biomarkers and therapy target. With these results maybe provides new insights into the mechanisms of HPV carcinogenesis in esophageal cancer.

Keywords: Human papilloma virus (HPV); RNA-Seq; esophageal cancer; qRT-PCR.

Figure 1

Differential gene volcano map. The volcano map can visualize the overall distribution of genes with the significant difference, and the horizontal axis represents the fold change in the expression of the gene in different samples (Log2Fold Change), and the vertical axis indicates the significant difference in expression (−Log10Padj). The upward gene represented by the red dot and the downward gene indicated by a green dot.

Figure 2

Prominent differential gene heat map. Red indicates high gene expression, while Blue indicates low gene expression.

Figure 3

A heatmap of all lncRNAs in DEGs. Red indicates high gene expression, while Blue indicates low gene expression.

Figure 4

A heatmap of differentially expressed lncRNAs with an absolute value >5 of log2FC and the padj <0.05.

Figure 5

Gene ontology (GO) enrichment analysis of DEGs between SHEE P26 and P29.

Figure 6

The first 10 biological functions identified by KEGG analysis. * for significant differences.

Figure 7

The lncRNA-miRNA-mRNA Competing endogenous RNA network. light blue nodes represent mRNAs, dark blue nodes represent lncRNAs and red nodes represent miRNAs.

Figure 8

PPI network and Kaplan–Meier curve analysis. (A) PPI Network of differentially expressed mRNA; (B) the PPI Network of IL6 as a hub nodes; (C) Kaplan-Meier survival curves of IL6 in esophageal cancer.

Figure 9

Correlation between the results of qRT-PCR and RNA-Seq. Black bars represent RNA-Seq measurements, and red bars represent qRT-PCR experimental results, calculated using the 2^−ΔΔCt method and normalized to GAPDH.