Screening and Bioinformatics Analyses of Key miRNAs Associated with Toll-like Receptor Activation in Gastric Cancer Cells

Abstract

Background and Objectives: To screen key miRNAs and their target genes related to Toll-like receptor (TLR) activation in gastric cancer (GC) cells and analyze them bioinformatically. Materials and Methods: Venn diagrams were obtained to screen miRNAs that were upregulated/downregulated in both GSE54129 and GSE164174. The miRTarBase database was used to predict the target genes of upregulated miRNAs. The differentially expressed genes in the regulatory network were analyzed. miR-16-5p expression in different tissue samples and the variations in the methylation states of four hub genes were measured. Results: We found that GSE54129 included 21 normal gastric tissues and 111 gastric cancer tissues, GSE164174 included 1417 normal gastric tissues and 1423 gastric cancer tissues. Venn diagram analysis results showed that compared with the control group, a total of 68 DEmiRNAs were upregulated in the GSE54129 and GSE164174 datasets, and no common downregulated DEmiRNAs were found. On further analysis of the GSE108345 dataset, we obtained the competing endogenous RNA (ceRNA) network associated with the activation of TLRs, and listed the top 10 lncRNA-miRNA-mRNA networks, including 10 miRNAs, 86 mRNA and 134 lncRNAs. Cytological HuBBA scores yielded a total of 1 miRNA, 16 mRNAs and 45 lncRNAs, of which miR-16-5p scored the highest as it was considered a key miRNA for TLR activation in GC cells, which are important in response against microorganisms. The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that endocytosis, microRNAs in cancer and the PI3K-Akt signaling pathway are related to TLR signaling. The results of in vivo experiments indicated that miR-16-5p was highly expressed in gastric cancer cells and tissues. Conclusions: Hsa-miR-16-5p's target genes mainly play a role by regulating the expression of four genes-MCL1, AP2B1, LAMB1, and RAB11FIP2. The findings provide a scientific basis for the development of immunotherapy for GC.

Keywords: Toll-like receptor; bioinformatics; gastric cancer; miRNA.

Figure 1

Volcano plots for DEmiRNAs. (A) DEmiRNAs in the GSE54129 dataset; (B) DEmiRNAs in the GSE164174 dataset; (C) DEmiRNAs in the GSE108345 dataset. The horizontal coordinates indicate log2FoldChange, while vertical coordinates indicate the −log10P-value. Blue color indicates significantly downregulated DEmiRNAs, whereas red color indicates significantly upregulated DEmiRNAs.

Figure 2

Venn diagram for DEmiRNAs. (A) A total of 68 upregulated DEmiRNAs in both the GSE54129 and GSE164174 datasets; (B) no DEmiRNA is downregulated commonly in both the GSE54129 and GSE164174 datasets.

Figure 3

Results of pathway enrichment analysis (multiple miRNAs).

Figure 4

Results of pathway enrichment analysis (miR-16-5p).

Figure 5

Enrichment analysis for the target genes in the regulatory networks. The KEGG enrichment analysis results were sorted according to the p value, and the darker red color indicated that the smaller the p value, the higher the enrichment degree.

Figure 6

miR-16-5p was upregulated in GC cells and tissues. (A) Standard curves were constructed for miR-16-5p using qRT-PCR assay. (B) qRT-PCR was used to examine the relative levels of miR-16-5p in human MKN1, NUGC4 and AZ521) compared with that in GES-1 cells. (C,D) Fluorescence in situ hybridization (FISH) and qRT-PCR were used to examine the expression of miR-16-5p in 25 pair’s GC and adjacent tissues. * p < 0.05 vs. GES. *** p < 0.001 vs. control.