Evidence map›Paper›PMID 32661532›Full record

ArticleMetallomics : integrated biometal science2020

Identification of novel activators of the metal responsive transcription factor (MTF-1) using a gene expression biomarker in a microarray compendium.

Abigail C Jackson, Jie Liu, Beena Vallanat, Carlton Jones, Mark D Nelms, Grace Patlewicz, J Christopher Corton

Open access · bronzeAbstract read
In one paragraph

Article in Metallomics : integrated biometal science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

14 citing papers in PubMed, 26 citations in OpenAlex.

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  14. Evaluating adaptive stress response gene signatures using transcriptomics.Computational toxicology (Amsterdam, Netherlands) · 2021
    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

7 authors at 2 institutions in 1 country.

Abigail C JacksonCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov and Department of Chemistry, Duke University, Durham, NC 27708, USA.ORCID 0000-0002-2113-3449
Jie LiuCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov.
Beena VallanatCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov.
Carlton JonesCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov.
Mark D NelmsCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov and Oak Ridge Institute for Science and Education, Oak Ridge, TN, USA.
Grace PatlewiczCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov.
J Christopher CortonCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, 109 T.W. Alexander Dr. MD-B105-3, Research Triangle Park, NC 27711, USA. corton.chris@epa.gov.ORCID 0000-0002-6197-2036
Environmental Protection Agency · USOak Ridge Associated Universities · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Environmental exposure to metals is known to cause a number of human toxicities including cancer. Metal-responsive transcription factor 1 (MTF-1) is an important component of metal regulation systems in mammalian cells. Here, we describe a novel method to identify chemicals that activate MTF-1 based on microarray profiling data. MTF-1 biomarker genes were identified that exhibited consistent, robust expression across 10 microarray comparisons examining the effects of metals (zinc, nickel, lead, arsenic, mercury, and silver) on gene expression in human cells. A subset of the resulting 81 biomarker genes was shown to be altered by knockdown of the MTF1 gene including metallothionein family members and a zinc transporter. The ability to correctly identify treatment conditions that activate MTF-1 was determined by comparing the biomarker to microarray comparisons from cells exposed to reference metal activators of MTF-1 using the rank-based Running Fisher algorithm. The balanced accuracy for prediction was 93%. The biomarker was then used to identify organic chemicals that activate MTF-1 from a compendium of 11 725 human gene expression comparisons representing 2582 chemicals. There were 700 chemicals identified that included those known to interact with cellular metals, such as clioquinol and disulfiram, as well as a set of novel chemicals. All nine of the novel chemicals selected for validation were confirmed to activate MTF-1 biomarker genes in MCF-7 cells and to lesser extents in MTF1-null cells by qPCR and targeted RNA-Seq. Overall, our work demonstrates that the biomarker for MTF-1 coupled with the Running Fisher test is a reliable strategy to identify novel chemical modulators of metal homeostasis using gene expression profiling.

Indexed as

Drug DiscoveryDNA-Binding ProteinsGene ExpressionGene Expression ProfilingGene Expression RegulationHumansMCF-7 CellsTranscription Factor MTF-1Transcription FactorsDNA-Binding ProteinsTranscription Factor MTF-1Transcription Factors

Identifiers

PMID32661532
PMCPMC10776036
OpenAlexW3040328846

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.