ArticleToxicologic pathology2018
Differentiation Patterns of Uterine Carcinomas and Precursor Lesions Induced by Neonatal Estrogen Exposure in Mice.
Article in Toxicologic pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
- Neonatal diethylstilbestrol exposure disrupts uterine epithelial apical-basal polarity and partial EMT state.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Article
- Developmental estrogen exposure in mice disrupts uterine epithelial cell differentiation and causes adenocarcinoma via Wnt/β-catenin and PI3K/AKT signaling.PLoS biology · 2023Article
- Prenatal exposure to diethylstilbestrol has long-lasting, transgenerational impacts on fertility and reproductive development.Toxicological sciences : an official journal of the Society of Toxicology · 2023Article
- Development of adverse outcome pathways relevant for the identification of substances having endocrine disruption properties Uterine adenocarcinoma as adverse outcome.EFSA journal. European Food Safety Authority · 2023Article
- Mice Uterine Stem Cells are Affected by Neonatal Endocrine Disruption & Initiate Uteropathies in Adult Life Independent of Circulatory Ovarian Hormones.Stem cell reviews and reports · 2022Article
- Developmental exposure to phytoestrogens found in soy: New findings and clinical implications.Biochemical pharmacology · 2022Review
- High expression of SIX1 is an independent predictor of poor prognosis in endometrial cancer.American journal of translational research · 2021Article
- Uterine Patterning, Endometrial Gland Development, and Implantation Failure in Mice Exposed Neonatally to Genistein.Environmental health perspectives · 2020Article
- Endocrine Disruption and Reproductive Pathology.Toxicologic pathology · 2019Article
- SIX1 Regulates Aberrant Endometrial Epithelial Cell Differentiation and Cancer Latency Following Developmental Estrogenic Chemical Exposure.Molecular cancer research : MCR · 2019Article
- Uterine Epithelial Development and Enhancer of Zeste Homolog 2: It Is Important for More than Just Cancer.The American journal of pathology · 2019Article
- Epigenetic Changes in the Mature Uterus Following Neonatal Feeding of Tamoxifen in Female ICR Mice.Reproductive medicine and biologyArticle
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
Developmental exposure to estrogenic chemicals is an established risk factor for cancer of the female reproductive tract. This increase in risk has been associated with disruption of normal patterns of cellular differentiation during critical stages of morphogenesis. The goal of this study was to document uterine epithelial phenotypes over time following neonatal treatment with the synthetic estrogen diethylstilbestrol (DES) or the soy phytoestrogen genistein (GEN) in female CD-1 mice. Both DES and GEN induced three distinct populations of abnormal endometrial epithelial cells: luminal (SIX1+/P63-/CK14-/CK18+), basal (SIX1+/P63+/CK14+/CK18-), and mixed/bipotential (SIX1+/P63-/CK14+/CK18+), which were all established by early adulthood. In older animals, DES and GEN resulted in uterine carcinomas with mixed glandular, basal, and squamous cell elements. All carcinomas were composed largely of the three abnormal cell types. These findings identify novel epithelial differentiation patterns in the uterus and support the idea that disruption of cellular programming in early development can influence cancer risk later in life.
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Registered trials
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.