Identification of Novel Kinase-Transcription Factor-mRNA-miRNA Regulatory Network in Nasopharyngeal Carcinoma by Bioinformatics Analysis

Abstract

Purpose: Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck. This study aimed to investigate the crucial genes and regulatory networks involved in the carcinogenesis of NPC using a bioinformatics approach.

Methods: Five mRNA and two miRNA expression datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between NPC and normal samples were analyzed using R software. The WebGestalt tool was used for functional enrichment analysis, and protein-protein interaction (PPI) network analysis of DEGs was performed using STRING database. Transcription factors (TFs) were predicted using TRRUST and Transcriptional Regulatory Element Database (TRED). Kinases were identified using X2Kgui. The miRNAs of DEGs were predicted using miRWalk database. A kinase-TF-mRNA-miRNA integrated network was constructed, and hub nodes were selected. The hub genes were validated using NPC datasets from the GEO and Oncomine databases. Finally, candidate small-molecule agents were predicted using CMap.

Results: A total of 122 DEGs and 44 DEMs were identified. DEGs were associated with the immune response, leukocyte activation, endoplasmic reticulum stress in GO analysis, and the NF-κB signaling pathway in KEGG analysis. Four significant modules were identified using PPI network analysis. Subsequently, 26 TFs, 73 kinases, and 2499 miRNAs were predicted. The predicted miRNAs were cross-referenced with DEMs, and seven overlapping miRNAs were selected. In the kinase-TF-mRNA-miRNA integrated network, eight genes (PTGS2, FN1, MMP1, PLAU, MMP3, CD19, BMP2, and PIGR) were identified as hub genes. Hub genes were validated with consistent results, indicating the reliability of our findings. Finally, six candidate small-molecule agents (phenoxybenzamine, luteolin, thioguanosine, reserpine, blebbistatin, and camptothecin) were predicted.

Conclusion: We identified DEGs and an NPC regulatory network involving kinases, TFs, mRNAs, and miRNAs, which might provide promising insight into the pathogenesis, treatment, and prognosis of NPC.

Keywords: bioinformatics; differentially expressed genes; kinase; microRNA; nasopharyngeal carcinoma; transcription factor.

Figure 1

A flowchart of the study design.

Figure 2

Identification of differentially expressed genes (DEGs) and miRNAs (DEMs). (A) The volcano plots for four mRNA expression datasets (GSE53819, GSE12452, GSE64634, and GSE40290); red dots indicate up-regulated DEGs; blue dots present down-regulated DEGs; and gray dots indicate nonsignificant DEGs. (B) Venn diagrams exhibit a total of 122 DEGs, consisting of 37 up-regulated and 85 down-regulated genes were identified in the four mRNA expression datasets. (C) The volcano plots for two miRNA expression datasets (GSE22587 and GSE43039). (D) Venn diagram shows 44 DEMs were identified in the two miRNA expression datasets.

Figure 3

GO and KEGG pathway enrichment analyses of differentially expressed genes (DEGs). (A) Circular dendrogram depicts the relationship between genes and GO terms of biological process. (B) Circular dendrogram depicts the relationship between genes and GO terms of cellular component. (C) Circular dendrogram depicts the relationship between genes and GO terms of molecular function. (D) Bubble plot exhibits the relationship between genes and KEGG pathways.

Figure 4

Protein–protein interaction (PPI) network of the differentially expressed genes (DEGs). (A) PPI network of the DEGs. The nodes represent proteins encoded by genes and the edges represent connections between the nodes. Red-colored nodes represent up-regulated genes, blue-colored nodes represent down-regulated genes. (B–E) Significant modules in the PPI network obtained by the MNC algorithm.

Figure 5

Construction of the kinase-transcription factor (TF)–mRNA–miRNA interaction network. (A) The TF–mRNA network. (B) The kinase–TF network. (C) Venn diagram shows seven overlapping differentially expressed miRNA (DEMs) were identified between the miRWalk database and the DEMs identified in the two miRNA microarray datasets (GSE22587 and GSE43039). (D) The mRNA–miRNA network. (E) The kinase–TF–mRNA–miRNA interaction network. Red-colored circles: up-regulated genes; blue-colored circles: down-regulated genes; green rectangles: TFs; purple hexagon represent kinase; kelly rhombus: miRNA.

Figure 6

Validation of the expression of hub genes in the Oncomine database. (A) PTGS2; (B) FN1; (C) MMP1; (D) PLAU; (E) MMP3; (F) CD19; (G) BMP2; (H) PIGR. Under these box plots, 0 indicates normal; 1 indicates nasopharyngeal carcinoma (NPC).

Figure 7

Three-dimensional structure of six candidate small molecule agents in nasopharyngeal carcinoma (NPC). (A) phenoxybenzamine; (B) luteolin; (C) thioguanosine; (D) reserpine; (E) blebbistatin; and (F) camptothecin.