Evidence map›Paper›PMID 41667778›Full record

ArticleScientific reports2026

Integrative network toxicology and experimental evidence reveal mechanisms underlying diethyl phthalate-induced initiation and progression of endometrial cancer.

Xi Chen, Zijing Wang, Fengfeng Wang, Yuexiao Wu, Dan Hu, Yuemei Cheng, Yijuan Xing, Junhong Du, Tao Jiang, Yongxiu Yang and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Xi ChenThe First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, China.
Zijing WangThe First Clinical Medical College, General Hospital of Ningxia Medical University, Yinchuan, 750004, China.
Fengfeng WangWushan Hospital of Traditional Chinese Medicine, Tianshui, 741306, Gansu, China.
Yuexiao WuThe First Clinical Medical College of Lanzhou University, Lanzhou, 730000, Gansu, China.
Dan HuDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China.
Yuemei ChengDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China.
Yijuan XingDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China.
Junhong DuDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China.
Tao JiangDepartment of Anal-Colorectal Surgery, General Hospital of Ningxia Medical University, 804 Shengli Road, Yinchuan, 750004, China. jtyy1209@163.com.
Yongxiu YangDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China. yxyanglzu@163.com.
Xiaolei LiangDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China. liangxl07@lzu.edu.cn.
Xuehan BiDepartment of Obstetrics and Gynecology, the First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China. bxh2022@163.com.

Funding

Gansu Provincial Key Research and Development Project 24YFFA038Joint Fund of Gansu Province 25JRRA1258National Natural Science Foundation of China 81960278National Natural Science Foundation of China 82260543National Natural Science Foundation of China 82360303Science and Technology Innovation Major Project of the Health Commission of Gansu Province GSWSZD2025-0
6 · The paper itself

Abstract

Diethyl phthalate (DEP) is a ubiquitous environmental endocrine-disrupting chemical (EDC). Epidemiological studies have suggested a potential association between DEP exposure and an increased risk of endometrial cancer (EC); however, its underlying molecular mechanisms remain largely unclear. Four GEO datasets were integrated, and differential expression analysis combined with weighted gene co-expression network analysis (WGCNA) was performed to identify candidate genes potentially linking DEP exposure to EC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore relevant signaling pathways. Machine learning models, coupled with Shapley Additive Explanations (SHAP), were employed to prioritize key genes. Molecular docking and molecular dynamics (MD) simulations were used to assess the binding affinity between DEP and the identified targets. A series of in vitro experiments in EC cell lines were subsequently conducted to validate the biological effects of DEP. Nineteen overlapping DEP-EC genes were identified, predominantly enriched in the MAPK, cAMP, and cGMP-PKG signaling pathways. Among them, FOS, NR4A1, ADRA2C, JUN, and SLC6A2 were prioritized as core genes through machine learning and SHAP analysis. Molecular simulations confirmed stable binding between DEP and these targets. In vitro assays demonstrated that DEP exposure induces oxidative stress, significantly enhances ERK1/2 and AKT phosphorylation, upregulates Cyclin D1/CDK4 expression, promotes G1/S phase transition, and facilitates EC cell proliferation. These findings suggest that DEP may promote endometrial carcinogenesis by triggering oxidative stress-mediated signaling crosstalk and accelerating cell cycle progression. This study establishes a multi-layered methodological framework-from computational screening and machine learning to experimental validation-offering novel mechanistic insights into the carcinogenic potential of environmental endocrine disruptors such as DEP.

Indexed as

Endocrine DisruptorsEndometrial NeoplasmsGene Regulatory NetworksPhthalic AcidsCell Line, TumorCell ProliferationDisease ProgressionFemaleGene Expression Regulation, NeoplasticHumansMachine LearningMolecular Docking SimulationMolecular Dynamics SimulationSignal Transductiondiethyl phthalateEndocrine DisruptorsPhthalic AcidsDiethyl phthalateEndometrial cancerMachine learningMolecular dynamics simulationNetwork toxicology

Identifiers

PMID41667778
PMCPMC12960819

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.