Evidence map›Paper›PMID 39972627›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2025

Lessons learned from evaluating defined chemical mixtures in a high-throughput estrogen receptor assay system.

Fred Parham, Kristin M Eccles, Cynthia V Rider, Srilatha Sakamuru, Menghang Xia, Ruili Huang, Raymond R Tice, Gregg E Dinse, Michael J DeVito

Abstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of 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

9 authors.

Fred ParhamDivision of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.ORCID 0000-0003-1315-0051
Kristin M EcclesDivision of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.ORCID 0000-0002-6629-430X
Cynthia V RiderDivision of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA.ORCID 0000-0002-4497-518X
Srilatha SakamuruNational Center for Advancing Translational Sciences, Bethesda, MD 20850, USA.ORCID 0000-0002-9693-1832
Menghang XiaNational Center for Advancing Translational Sciences, Bethesda, MD 20850, USA.ORCID 0000-0001-7285-8469
Ruili HuangNational Center for Advancing Translational Sciences, Bethesda, MD 20850, USA.
Raymond R TiceRTice Consulting, Hillsborough, NC 27278, USA.ORCID 0000-0002-5917-4297
Gregg E DinseDLH, LLC, Bethesda, MD 20817, USA.ORCID 0000-0003-1456-5582
Michael J DeVitoCenter for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27709, USA.ORCID 0000-0003-1258-4894

Funding

Combined Exposures and Mixtures Research ProgramZIAES103373 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI RIDER, CYNTHIA · 2022 to 2025
$5.6M
Division of Translational Toxicology ProgramIntramural NIH HHS ZIA ES103373Intramural Research ProgramNCATS NIH HHS HHSN273201600011CNIEHS NIH HHS HHSN273201600011CNIEHS NIH HHS ZIA ES103373NIHSocial & Scientific Systems
6 · The paper itself

Abstract

In this article, we provide a proof of concept evaluating the utility of the U.S. Tox21 high-throughput screening approach to assess the hazard of chemical mixtures using 2 estrogen receptor (ER) assays. A subset of chemicals identified in Phase I of the Tox21 program as active in the ER agonist assay were used to design mixtures for testing in Phase II. Individual chemicals and mixtures were evaluated in 2 cell-based ER alpha (ERα) activation assays: One incorporating a transfected ligand-binding domain in an ERα β-lactamase reporter cell line (ER-bla) and the full-length endogenous receptor in the MCF7 cell line with a luciferase reporter gene (ER-luc). Concentration-response data from individual chemicals were used to predict the joint effect based on mixtures modeling methods and were compared with observed mixtures data to assess model fit. The models tended to overpredict mixture responses in the ER-bla assay, whereas predictions were closer to observed responses in the ER-luc assay, indicating that a full-length endogenous ER is a preferred model for high-throughput mixture analysis. Lessons learned from this research include the importance of analyzing the individual chemicals used for predictions and the mixtures in the same experimental paradigm to minimize variation, developing methods for imputing missing values from incomplete concentration-response curves, and establishing criteria to determine when inactive chemicals should be omitted from mixture predictions.

Indexed as

Estrogen Receptor alphaHigh-Throughput Screening AssaysDose-Response Relationship, DrugGenes, ReporterHumansMCF-7 CellsESR1 protein, humanEstrogen Receptor alphaestrogen receptor agonistsgeneralized concentration additionhigh-throughput screeningindependent actionmixturesTox21

Identifiers

PMID39972627
PMCPMC12038247

What OpenQuestion holds

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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 OpenQuestion graph.