Evidence map›Paper›PMID 41430741›Full record

ArticleBMC pharmacology & toxicology2025

TELO2 mediates parabens-induced breast carcinogenesis: a comprehensive network analysis.

Jing Ren, Xiaofen Li, Bin Dong, Zhulin Bu, Yuhui Wu, Yuting Li, Lin Yang, Huaixi Xing, Yuting Dai, Shuosheng Zhang and 1 more

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Jing RenSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Xiaofen LiSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Bin DongSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Zhulin BuSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Yuhui WuSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Yuting LiSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Lin YangSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Huaixi XingSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Yuting DaiFirst Clinical College, Shanxi University of Chinese Medicine, Jinzhong, 030619, China.
Shuosheng ZhangSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China.
Xianglong MengSchool of Traditional Chinese Medicine and Food Engineering, Shanxi University of Chinese Medicine, No. 121 University Street, Yuci District, Jinzhong, 030619, China. xianglongmeng@sxtcm.edu.cn.

Funding

Natural Science Foundation of Shanxi Province 20210302124694
6 · The paper itself

Abstract

backgroundParabens (PBs) are associated with an increased risk of breast cancer, yet their underlying molecular mechanisms remain poorly understood. This study aimed to comprehensively elucidate the targets and mechanisms of PBs in breast cancer by integrating network toxicology, bioinformatics, Mendelian randomization (MR), molecular docking, and other complementary methodologies.

resultsNetwork toxicology analysis identified 2,851 potential PB targets, with 172 significantly linked to breast cancer. Pathway enrichment revealed that PBs predominantly influence the Phosphatidylinositol 3-kinase-Akt (PI3K-Akt) signaling pathway and the cell cycle pathway. Two-sample MR identified TELO2 as a significant risk factor for both malignant and benign breast cancer (malignant: IVW OR = 1.06, 95% CI: 1.001-1.126, p = 0.047; benign: IVW OR = 1.13, 95% CI: 1.009-1.270, p = 0.034). Bioinformatics analysis demonstrated that TELO2 expression was significantly elevated in breast cancer tissues (p < 0.05) and exhibited high diagnostic accuracy (AUC: 0.803 in TCGA and 0.876 in GSE20685). Furthermore, mediation analysis revealed that modulating natural killer T (NKT) cells significantly mediated the TELO2-breast cancer link, with a mediation proportion of 20.46%. Molecular docking confirmed stable binding interactions between PBs and the TELO2 protein. Moreover, an mRNA-microRNA (miRNA)-long non-coding RNA (lncRNA) regulatory network centered on TELO2 identified 19 miRNAs and 189 lncRNAs as potential regulators of its expression.

conclusionsOur integrative findings suggest that parabens may exert deleterious effects in the context of breast cancer by specifically targeting the TELO2 gene and its associated regulatory networks and pathways. These findings not only advance our understanding of the environmental drivers of BC but also pave the way for future research aimed at mitigating the disease's health burden through targeted interventions against harmful environmental exposures.

Indexed as

Breast NeoplasmsCarcinogenesisParabensFemaleGene Regulatory NetworksHumansMolecular Docking SimulationSignal TransductionParabensBioinformaticsBreast cancerMendelian randomizationNetwork toxicologyParabens

Identifiers

PMID41430741
PMCPMC12837177

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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.