Therapeutic targets of formononetin for treating prostate cancer at the single-cell level

Abstract

Prostate cancer is one of the serious health problems of older male, about 13% of male was affected by prostate cancer. Prostate cancer is highly heterogeneity disease with complex molecular and genetic alterations. So, targeting the gene candidates in prostate cancer in single-cell level can be a promising approach for treating prostate cancer. In the present study, we analyzed the single cell sequencing data obtained from 2 previous reports to determine the differential gene expression of prostate cancer in single-cell level. By using the network pharmacology analysis, we identified the therapeutic targets of formononetin in immune cells and tissue cells of prostate cancer. We then applied molecular docking to determine the possible direct binding of formononetin to its target proteins. Our result identified a cluster of differential gene expression in prostate cancer which can serve as novel biomarkers such as immunoglobulin kappa C for prostate cancer prognosis. The result of network pharmacology delineated the roles of formononetin's targets such CD74 and THBS1 in immune cells' function of prostate cancer. Also, formononetin targeted insulin receptor and zinc-alpha-2-glycoprotein which play important roles in metabolisms of tissue cells of prostate cancer. The result of molecular docking suggested the direct binding of formononetin to its target proteins including INSR, TNF, and CXCR4. Finally, we validated our findings by using formononetin-treated human prostate cancer cell DU145. For the first time, our result suggested the use of formononetin for treating prostate cancer through targeting different cell types in a single-cell level.

Keywords: formononetin; heterogeneity; immune response; network pharmacology; prostate cancer; single cell; therapeutic targets.

Figure 1

Differential gene expression in prostate cancer in single-cell level. (A) Single cell sequencing analysis using the downloaded dataset showed the number of genes measured per cell, the sum of the gene expression measured per cell, and the percentage of mitochondria-related genes in the prostate cancer in single-cell level. N represented adjacent normal tissues; T represented prostate cancerous tissues. (B) Principal component analysis (PCA) showed the similarity of the samples. (C) Uniform manifold approximation and projection (Umap) classified the single cell into 19 cell clusters. (D) Each cluster was classified into different cell type using SingleR automatic annotation package, including B cell, NK cell, T cell, monocyte, epithelial cells, endothelial cells, and smooth muscle cells.

Figure 2

Identification of formononetin’s targets against prostate cancer in single-cell level. Venn diagram showed the number and gene symbol of common genes between formononetin and (A) B cell, (B) T cell, (C) NK cell, (D) monocyte, (E) epithelial cell, (F) endothelial cell, and (G) smooth muscle cell.

Figure 3

Formononetin targeted genes related to immune responses in immune cells of prostate cancer. Gene Ontology (GO) enrichment analysis showed the biological roles of formononetin in (A) immune response, (B) interleukins and cytokines production, and (C) leukocyte of immune cell cluster of prostate cancer. (D) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed the roles of formononetin’s targets in apoptosis, and antigen presentation through the regulation of cell signaling pathways of immune cells. Lower panel of each figure was the Circos plot to show the involvement of gene in each item. The size of bubble represented the number of gene. The color of bubble represented the significance of the biological processes and pathways.

Figure 4

Formononetin targeted genes related to metabolisms in tissue cells of prostate cancer. (A) GO enrichment analysis showed the biological roles of formononetin in metabolisms of tissue cells cluster of prostate cancer. (B) KEGG enrichment analysis showed the roles of formononetin’s targets in insulin resistance, cell adhesion, and necroptosis through the regulation of cell signaling pathways of tissue cells. Lower panel of each figure was the Circos plot to show the involvement of gene in each item. The size of bubble represented the number of gene. The color of bubble represented the significance of the biological processes and pathways.

Figure 5

Potential binding of formononetin with its target proteins TP53 and CDK1. Molecular docking showed the binding of formononetin with (A) CD74 protein (PDB ID: 4P01), (B) INSR protein (PDB ID: 5E1S), (C) TNF protein (PDB ID: 6X86), and (D) CXCR4 protein (PDB ID: 3ODU).

Figure 6

Formononetin altered the expression of its targets in prostate cancer cell line. (A) qPCR analysis showed that formononetin induced the expression of mRNA of TNF, THBS1, HSP90AA1, and HBB in prostate cancer cell. (B) Formononetin treatment also induced the protein level of TNF and reduced the protein level of CD74 in prostate cancer cell.