A Combination of RNA-Seq Analysis and Use of TCGA Database for Determining the Molecular Mechanism and Identifying Potential Drugs for GJB1 in Ovarian Cancer

Abstract

Background: There has been increasing evidence for the vital role played by gap junction protein beta-1 (GJB1) in ovarian cancer (OC) and for the possibility of this protein serving as a therapeutic target. However, the detailed mechanism of GJB1 in OC has not yet been clearly determined. The current study aimed to establish the molecular mechanisms of the involvement of GJB1 in OC and to further predict potential drugs targeting this protein.

Methods: To better understand the molecular mechanisms of the involvement of GJB1 in OC, RNA-Seq transcriptome sequencing was performed. Then, we carried out an RNA-Seq analysis to determine the genes differentially co-expressed with GJB1. Subsequently, we carried out bioinformation methods to study the upstream regulatory transcriptional factor (TF) of GJB1. Further, the binding of FOXA1 and GJB1 promoter was tested using ChIP-qPCR. Moreover, we performed pathway enrichment to identify the downstream regulatory mechanisms of GJB1. Furthermore, potential drugs targeting GJB1 were screened using AutoDock 4.2.

Results: We constructed the transcriptional factor FOXA1 regulatory network based on the AnimalTFDB, JASPAR, RNA-Seq, TCGA cohort and ChIP-qPCR to study the upstream regulation of GJB1. In addition, two key pathways for the involvement of GJB1 in OC-namely the "ECM-receptor interaction" and "focal adhesion" KEGG pathways-were identified. Furthermore, ZINC000005552022 was found in a screening to be a potentially promising drug targeting GJB1.

Conclusion: Our study results suggested that the transcriptional factor FOXA1 regulates the involvement of GJB1 in OC through ECM-receptor interaction and focal adhesion KEGG pathways, and that ZINC000005552022 may have promising potential as a drug targeting GJB1; this finding might be used to help accelerate drug development and improve the outcomes for patients with OC.

Keywords: ChIP-qPCR; KEGG; omics; transcriptional factor; virtual screening.

Figure 1

Flow diagram of the current study: data collection, preprocessing, analysis, and validation.

Figure 2

Determination of genes differentially expressed between HeLa-GJB1 and control (Cntrl) groups. (A) Volcano plot of all unique genes from the genes differentially expressed between HeLa-GJB1 and Cntrl groups. Vertical and horizontal lines indicate the significance thresholds of |log2 Fold Change| > 2 and false discovery rate (FDR) < 0.05, respectively. (Blue and red dots indicate significantly downregulated and significantly upregulated genes, respectively; while black dots indicate genes with nonsignificant changes in expression levels). (B) Heat map of the top 50 DEGs (Red indicate upregulated and Blue indicate downregulated). (C) Circos plot of the top 10 genes co-expressed with GJB1 (Red indicate positive co-expression and Green indicate negative co-expression).

Figure 3

Constructing the TF upstream regulatory network of GJB1 in ovarian cancer (OC). (A) Venn diagram of the results of the analyses of AnimalTFDB, JASPAR, genes positively co-expressed with GJB1 using RNA-Seq, and upregulated differentially expressed genes (DEGs) in TCGA. (B) Sequence logo display of the binding site of the FOXA1 transcription factor (TF) on the GJB1 promoter. (C and D) Chromatin immunoprecipitation was performed using antibodies against FOXA1 or using a control IgG in (C) A2780 and (D) SKOV3 cells. Here, DNA immunoprecipitated by the IgG or the anti-FOXA1 antibody was in each case observed to be enriched compared with the input chromatin. Data are expressed each as mean ± SD (n = 3). *p < 0.05 compared with the IgG group (unpaired t-test).

Figure 4

Downstream regulation mechanism of GJB1 in OC. (A) KEGG over-representation test based on genes differentially expressed according to an RNA-sequencing (RNA-Seq) analysis achieved using clusterProfiler (p < 0.01). (B) The results of gene set enrichment analysis (GSEA) of RNA-Seq and a TCGA cohort (p < 0.05 and FDR < 25%, False discovery rate (FDR). (C) Protein–protein interaction network was constructed based on the String database.

Figure 5

The potential drugs based on the three-dimensional (3D) structure of GJB1. (A) The active site of GJB1 was found using AutoDock 4.2 2019–1. (B) The structure of ZINC000005552022 based on ZINC15 database. (C) AutoDock-derived structure of ZINC000005552022 bound to GJB1. The yellow dashed line represents a hydrogen bond, and the blue one a π-π interaction.