Mechanism exploration of di(2-ethylhexyl) phthalate (DEHP)-induced breast cancer via network toxicology and molecular docking analysis

Abstract

Disease caused by plasticizers has received increasing attention. Di(2-ethylhexyl) phthalate (DEHP), one of the most widely exposed plasticizers, has been shown to be closely associated with the development of breast cancer (BRCA) in epidemiological studies, but the specific mechanistic targets and related pathways are still unclear. In this study, we aimed to elucidate the potential pathogenic targets and mechanisms of DEHP-induced BRCA through network toxicology and molecular docking. Databases including GeneCards, OMIM, ChEMBL, and SwissTargetPrediction were first used to identify DEHP-related targets and BRCA-related targets, and 691 potential targets were obtained from the intersection analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to clarify the biological functions and pathways of potential targets. Protein-protein interaction (PPI) analysis revealed the interactions between potential targets, and 14 hub targets of DEHP-induced BRCA were further screened. To verify the clinical significance of the hub targets, the expression of the target proteins was verified in the TCGA database, and the affinity between DEHP and 12 key targets (hub targets with p < 0.05) was determined via molecular docking. Our study provides a theoretical basis for DEHP-induced BRCA from the "Homo sapiens" perspective and reveals the potential risks caused by exposure to DEHP, thus providing new strategies for the prevention and treatment of DEHP-induced BRCA.

Keywords: Breast cancer; Di(2-ethylhexyl) phthalate; Molecular docking; Network toxicology.

Fig. 1

The workflow of our study. Step one: database mining, using the public database to identify DEHP-related targets, BRCA-related targets, and potential targets of DEHP-induced BRCA. Step two: exploring the biological functions of potential targets, including PPI, Go analysis, and KEGG pathways enrichment analysis. Step three: TCGA database validation of hub targets and molecular docking analysis of key targets.

Fig. 2

Intersection analysis (Venn plot) between BRCA-related targets and DEHP-related targets.

Fig. 3

(A) GO analysis (top 10) of the potential targets, including BP, CC, and MF three parts. (B) KEGG pathway enrichment analysis (top 20) of the potential targets.

Fig. 4

(A) PPI analysis of the 691 potential targets. (B) PPI analysis of the 14 hub targets. (C) KEGG pathway enrichment analysis (top 10) of the 14 hub targets.

Fig. 5

Expression analysis of hub targets between BRCA and normal tissues in the TCGA database.

Fig. 6

Molecular docking analysis results of key targets with DEHP. The molecular docking was achieved through AutoDock Vina (version 1.2.5, https://vina.scripps.edu/), and the visualization of the docking results was completed using PyMOL (version 3.9.1, https://www.pymol.org/).