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. 2020 Mar 23;12(3):203.
doi: 10.3390/toxins12030203.

Molecular Mechanism of Aflatoxin-Induced Hepatocellular Carcinoma Derived from a Bioinformatics Analysis

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Molecular Mechanism of Aflatoxin-Induced Hepatocellular Carcinoma Derived from a Bioinformatics Analysis

Peirong Cai et al. Toxins (Basel). .

Abstract

Exposure to aflatoxin is considered to be one of the causes of hepatocellular carcinoma (HCC). With the development of bioinformation, we sought to reveal the occurrence and development of aflatoxin-induced HCC through data research. We identified differentially expressed genes (DEGs) of datasets GSE127791 (Aflatoxin-treated pluripotent stem cell derived human hepatocytes vs. controls) and GSE64041 (liver carcinoma with unknown cause vs. non-cancerous tissue) by GEO2R to find the common DEGs. Gene ontology (GO) and KEGG path enrichment analysis were used to annotate the function of DEGs. Hub genes were screened from identified DEGs by protein-protein interaction (PPI) network analysis. The prognostic value of hub genes in cancer databases were evaluated. We obtained 132 common DEGs and 11 hub genes. According to cluster analysis and protein co-expression networks, we screened out the key genes, histidine-rich glycoprotein (HRG) and phosphoenolpyruvate carboxykinase 2 (PCK2). Oncomine database and survival curve analysis showed that the decline in HRG and PCK2 expression in the development of HCC indicated poor prognosis. We speculated that the decreased expression of HRG and PCK2 after aflatoxin exposure to hepatocyte may be related to aflatoxin induced hepatocyte injury and carcinogenesis. In addition, the decreased expression of HRG and PCK2 in the occurrence and development of HCC suggests a poor prognosis of HCC.

Keywords: HRG; PCK2; aflatoxin; bioinformatics analysis; hepatocellular carcinoma (HCC).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Screening of differentially expressed genes (DEGs) and analysis of the protein-protein interaction (PPI) network. (A) The common DEGs were screened by the intersection of GSE127791 and GSE64041. (B) Demonstration of PPI in DEGs by Cytoscape. (C) Analysis of DEGs based on PPI analysis results.(D) The most important module was obtained from a PPI network with 16 nodes and 42 edges. Upregulated genes are marked in red; downregulated genes are marked in light purple.
Figure 2
Figure 2
Pathway enrichment analysis. (A) Enrichment analysis of KEGG pathway. The Y-axis represents the category of KEGG, and the X-axis represents -log10 (P-value). (B) Biological process in enrichment analysis of GO pathway. The Y-axis represents the category of biological process, and the X-axis represents -log10 (P-value). (C) Cellular components in enrichment analysis of GO pathway. The Y-axis represents the category of cellular components, and the X-axis represents -log10 (P value). (D) Molecular functions in enrichment analysis of GO pathway. The Y-axis represents the category of molecular functions, and the X-axis represents -log10 (P value).
Figure 3
Figure 3
Using University of California Santa Cruz (UCSC) Xena to construct hierarchical clustering of hub genes. In the gene expression module, red represents upregulated, green represents downregulated, and black represents no change. In the symple ID module, different colors represent different samples.
Figure 4
Figure 4
Using cBioportal online tool to construct a network of hub genes and their co-expression genes. The black outline of the thick line represents the central gene, while the light black represents the co-expression gene.
Figure 5
Figure 5
Oncomine analysis of the expression of normal tissues vs. HCC. The threshold is as follows: P-value = 0.01, fold change = 2, gene rank = top 10%.
Figure 6
Figure 6
The overall survival analysis of Histidine-rich glycoprotein (HRG) and phosphoenolpyruvate carboxykinase 2 (PCK2) in HCC using the Kaplan-Meier curve method. An alpha value of P ≤ 0.01 is considered a statistically significantly difference. (A) The survival curve of HRG. (B) The survival curve of PCK2. The red curve indicates an increase in gene expression and the light black curve indicates decreased gene expression.
Figure 7
Figure 7
Physiological functions of HRG and PCK2 in normal cells. (A) HRG inhibits vascularization and tumor establishment. HRG, histidine-rich glycoprotein; PIGF, placental growth factor; VEGFR-1, Vascular endothelial growth factor receptor 1; bFGF, basic fibroblast growth factor; (B) PCK involved in gluconeogenesis. PCK, phosphoenolpyruvate carboxykinase; G6P, glucose 6-phosphate; PEP, phosphoenolpyruvate; OAA, oxaloacetate; α-KG, α-ketoglutarate.

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