Phthalates unleashed: decoding ovarian carcinogenesis through multi-omics networks, single-cell insights, and molecular docking

Abstract

Background: Despite epidemiological studies linking phthalates to ovarian cancer, their multi-target molecular mechanisms remain unresolved, hindering biomarker discovery and preventive strategies. This study integrates network toxicology, multi-omics analyses, and molecular docking to systematically delineate phthalate-driven oncogenic pathways, thereby bridging mechanistic gaps and informing targeted interventions.

Results: We identified 234 potential targets related to phthalate exposure and ovarian cancer. Enrichment analysis revealed that these genes are associated with HIF-1 signaling, and metabolic pathways that promote cancer progression. Seven core genes were identified, with six (GAPDH, CASP3, PPARG, ESR1, CYCS, SIRT1, and CCND1) exhibiting differential expression in the TCGA ovarian cancer cohort. Single-cell analysis confirmed their widespread expression across various cell types, underscoring their roles in tumor biology. Molecular docking revealed specific binding interactions between phthalates and six core proteins.

Conclusions: Integrated computational analyses indicate that phthalates (DEP, DMP, DOP) may drive ovarian carcinogenesis through metabolic reprogramming (HIF-1α/glycolysis), strong binding to SIRT1/PPARα regulators, and tumor microenvironment remodeling. These findings establish a framework for prioritizing environmental carcinogens and identifying exposure biomarkers, with implications for reevaluating phthalate safety and elucidating the SIRT1-HIF1-PPARα axis in cancer pathogenesis.

Keywords: Molecular docking; Network toxicology; Ovarian cancer; Phthalates; ScCancerExplorer.

Fig. 1

The workflow of the analysis

Fig. 2

Target analysis of ovarian cancer and phthalates. A Venn diagram of three phthalates targets from the database. B Venn diagram of phthalates and ovarian cancer targets. C, D PPI network of intersection targets and core genes of ovarian cancer and phthalates

Fig. 3

Functional enrichment analysis intersection targets (A) of ovarian cancer and phthalates. A Top 10 biological processes; B Top 10 cellular components; C molecular functions; D Top 10 KEGG pathway analysis. The size represents the number of genes, with larger dots indicating a greater number of genes. The color and the length of the bars represent the P-value, with lighter colors and longer bars indicating a smaller P-value

Fig. 4

Chord diagram showing the annotated core genes in top 10 enriched pathways. The darker the color, the stronger is the significance

Fig. 5

Expression of 6 core genes between ovarian cancer and healthy tissues in TCGA. A CCND1; B CYCS; C ESR1; D GAPDH; E PPARA; F SIRT1. * P < 0.01

Fig. 6

Key gene expression levels in ovarian cancer at the single-cell level in GSE173682. A Cellular subpopulation identification in ovarian cancer tissue, with each color representing a distinct subpopulation. B Cellular distribution across different stages of ovarian cancer, where different colors correspond to different cell types. C-H UMAP plots illustrate expression levels of six key genes (GAPDH, CASP3, PPARG, ESR1, CYCS, SIRT1) across cell subpopulations, with a color scale from blue (low) to red (high). I-N Violin plots illustrate expression levels of six key genes (GAPDH, CASP3, PPARG, ESR1, CYCS, SIRT1) in different cell types. The color coding from blue to red represents low to high expression levels, respectively

Fig. 7

Molecular docking results. A Docking results of DEP with SIRT1; B Docking results of DMP with SIRT1; C Docking results of DOP with SIRT1; D Docking results of DOP with PPARA