Evidence map›Paper›PMID 41373010›Full record

ArticleBMC pharmacology & toxicology2025

Exploring the toxicological impact of DEHP exposure on colorectal cancer through network toxicology, machine learning and bioinformatics analysis.

Ling Wang, Yuning Qin, Wenbin Fan

Abstract read
In one paragraph

Article in BMC pharmacology & toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ling WangChongqing University of Chinese Medicine, Chongqing, China.
Yuning QinChongqing Medical University, Chongqing, China.
Wenbin FanChongqing University of Chinese Medicine, Chongqing, China. FWBCQ123@163.com.

Funding

the First-Class Undergraduate Course Development Program of Chongqing Municipal Colleges-Proctology in Integrated Chinese and Western Medicine, Chongqing College of Traditional Chinese Medicine Grant No. YJGH [2024] No. 3-131the Science and Technology Research Program of Chongqing Municipal Education Commission Grant No. KJQN202315143
6 · The paper itself

Abstract

objectiveColorectal cancer (CRC) ranks among the most prevalent malignant tumors, yet its underlying mechanisms remain not fully understood. The role of environmental factors is critical in its development and progression. Di-(2-ethylhexyl) phthalate (DEHP), a widespread environmental contaminant, poses significant hazards to human health. Prior research indicates that exposure to DEHP can disrupt cellular processes like proliferation, differentiation, and apoptosis, which may contribute to cancer development. Nevertheless, the specific role and molecular pathways involved with DEHP in CRC are still poorly defined.

methodsWe integrated multiple public databases to identify overlapping targets of DEHP and CRC. Machine learning methods were applied to prioritize core targets, whose expression levels and diagnostic performance were then validated in the Gene Expression Omnibus (GEO) datasets. The association between core targets and immune cell infiltration was evaluated using CIBERSORT-based deconvolution. Finally, molecular docking was performed to predict the interactions between DEHP and the hub proteins, and, based on the docking results, an explicit-solvent molecular dynamics (MD) simulation of the top-ranked DEHP–target complex was conducted to further assess binding stability.

resultsAnalysis of publicly available databases revealed 57 potential targets that were significantly enriched in signaling pathways related to “microRNAs in cancer” and “chemical carcinogenesis–receptor activation.” Machine learning methods identified five primary targets: CASP3, BCL6, BRD4, PPARA, and PRKCD. The expression levels of these genes in CRC tissues were significantly different from those in control tissues and showed reasonable diagnostic performance, as well as correlations with immune cell infiltration. Molecular docking suggested that DEHP can bind all five hub proteins, with PPARA exhibiting the most favorable binding affinity (− 6.7 kcal/mol). The 100-ns MD simulation further supported this binding mode by demonstrating that the DEHP–PPARA complex maintains a dynamically stable conformation with persistent key interactions.

conclusionsOur findings generate preliminary mechanistic hypotheses on how DEHP exposure may contribute to CRC by perturbing known cancer-related pathways and reshaping the intestinal immune microenvironment, with PPARA emerging as a key candidate mediator. The study highlights the utility of combining network toxicology, machine learning, immune deconvolution, molecular docking, and MD simulations to evaluate the potential carcinogenic risks of environmental pollutants.

Indexed as

Colorectal NeoplasmsDiethylhexyl PhthalateMachine LearningPlasticizersComputational BiologyHumansMolecular Docking SimulationMolecular Dynamics SimulationDiethylhexyl PhthalatePlasticizersColorectal cancerDEHPMachine learning algorithmMolecular dockingNetwork toxicology

Identifiers

PMID41373010
PMCPMC12802266

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.