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Article: Frequent Modulation of the Sterol Regulatory Element Binding Protein (SREBP) by Chemical Exposure in the Livers of Rats.

Corton, J Christopher

Computational toxicology (Amsterdam, Netherlands)

2019 Volume 10, Page(s) 113–129

Abstract: Inappropriate activation of sterol regulatory element-binding proteins (SREBPs) can lead to non-alcoholic fatty liver disease (NAFLD). To link chemical exposure to SREBP activity, a previously characterized gene expression biomarker (Rooney et al., 2019) ...

Abstract	Inappropriate activation of sterol regulatory element-binding proteins (SREBPs) can lead to non-alcoholic fatty liver disease (NAFLD). To link chemical exposure to SREBP activity, a previously characterized gene expression biomarker (Rooney et al., 2019) was used to identify microarray comparisons from rat liver that exhibited significant positive or negative correlation to the biomarker. The effects of 620 chemicals on SREBP activity were examined across 9305 chemical-dose-time microarray comparisons. SREBP was found to be frequently modulated by chemical exposure with 54% of the chemicals affecting SREBP activity. Activators included inhibitors of cholesterogenesis that act to inhibit HMG-CoA reductase (statins) or inhibit Cyp51 (conazoles). Most chemical effects were transient, lasting usually no more than 2-4 days. Modulation of SREBP in most cases led to coordinated increases or decreases in lipogenic and cholesterogenic genes. However, 570 chemical exposure conditions were identified in which regulation was uncoupled. Most of these conditions affected cholesterogenic genes in the absence of parallel effects on lipogenic genes. Together, these findings show that SREBP is a frequent target of chemical exposure and expression of lipogenic and cholesterogenic genes can be uncoupled.
Language	English
Publishing date	2019-03-07
Publishing country	Netherlands
Document type	Journal Article
ISSN	2468-1113
ISSN	2468-1113
DOI	10.1016/j.comtox.2019.01.007
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Article ; Online: A Gene Expression Biomarker Predicts Heat Shock Factor 1 Activation in a Gene Expression Compendium.

Cervantes, Patrick W / Corton, J Christopher

Chemical research in toxicology

2021 Volume 34, Issue 7, Page(s) 1721–1737

Abstract: The United States Environmental Protection Agency (US EPA) recently developed a tiered testing strategy to use advances in high-throughput transcriptomics (HTTr) testing to identify molecular targets of thousands of environmental chemicals that can be ... ...

Abstract	The United States Environmental Protection Agency (US EPA) recently developed a tiered testing strategy to use advances in high-throughput transcriptomics (HTTr) testing to identify molecular targets of thousands of environmental chemicals that can be linked to adverse outcomes. Here, we describe a method that uses a gene expression biomarker to predict chemical activation of heat shock factor 1 (HSF1), a transcription factor critical for proteome maintenance. The HSF1 biomarker was built from transcript profiles derived from A375 cells exposed to a HSF1-activating heat shock protein (HSP) 90 inhibitor in the presence or absence of HSF1 expression. The resultant 44 identified genes included those that (1) are dependent on HSF1 for regulation, (2) have direct interactions with HSF1 assessed by ChIP-Seq, and (3) are in the molecular chaperone family. To test for accuracy, the biomarker was compared in a pairwise manner to gene lists derived from treatments with known HSF1 activity (HSP and proteasomal inhibitors) using the correlation-based Running Fisher test; the balanced accuracy for prediction was 96%. A microarray compendium consisting of 12,092 microarray comparisons from human cells exposed to 2670 individual chemicals was screened using our approach; 112 and 19 chemicals were identified as putative HSF1 activators or suppressors, respectively, and most appear to be novel modulators. A large percentage of the chemical treatments that induced HSF1 also induced oxidant-activated NRF2 (∼46%). For five compounds or mixtures, we found that NRF2 activation occurred at lower concentrations or at earlier times than HSF1 activation, supporting the concept of a tiered cellular protection system dependent on the level of chemical-induced stress. The approach described here could be used to identify environmentally relevant chemical HSF1 activators in HTTr data sets.
MeSH term(s)	Cell Line ; Gene Expression Profiling/methods ; Gene Expression Regulation/drug effects ; Heat Shock Transcription Factors/genetics ; Heat-Shock Response/drug effects ; Humans ; Toxicity Tests/methods ; Transcriptome/drug effects
Chemical Substances	HSF1 protein, human ; Heat Shock Transcription Factors
Language	English
Publishing date	2021-06-25
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	639353-6
ISSN	1520-5010 ; 0893-228X
ISSN (online)	1520-5010
ISSN	0893-228X
DOI	10.1021/acs.chemrestox.0c00510
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Article ; Online: Hepatic Transcriptome Comparative In Silico Analysis Reveals Similar Pathways and Targets Altered by Legacy and Alternative Per- and Polyfluoroalkyl Substances in Mice.

Robarts, Dakota R / Dai, Jiayin / Lau, Christopher / Apte, Udayan / Corton, J Christopher

Toxics

2023 Volume 11, Issue 12

Abstract: Per- and poly-fluoroalkyl substances (PFAS) are a large class of fluorinated carbon chains that include legacy PFAS, such as perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexane sulfonate ( ... ...

Abstract	Per- and poly-fluoroalkyl substances (PFAS) are a large class of fluorinated carbon chains that include legacy PFAS, such as perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexane sulfonate (PFHxS). These compounds induce adverse health effects, including hepatotoxicity. Potential alternatives to the legacy PFAS (HFPO-DA (GenX), HFPO4, HFPO-TA, F-53B, 6:2 FTSA, and 6:2 FTCA), as well as a byproduct of PFAS manufacturing (Nafion BP2), are increasingly being found in the environment. The potential hazards of these new alternatives are less well known. To better understand the diversity of molecular targets of the PFAS, we performed a comparative toxicogenomics analysis of the gene expression changes in the livers of mice exposed to these PFAS, and compared these to five activators of PPARα, a common target of many PFAS. Using hierarchical clustering, pathway analysis, and predictive biomarkers, we found that most of the alternative PFAS modulate molecular targets that overlap with legacy PFAS. Only three of the 11 PFAS tested did not appreciably activate PPARα (Nafion BP2, 6:2 FTSA, and 6:2 FTCA). Predictive biomarkers showed that most PFAS (PFHxS, PFOA, PFOS, PFNA, HFPO-TA, F-53B, HFPO4, Nafion BP2) activated CAR. PFNA, PFHxS, PFOA, PFOS, HFPO4, HFPO-TA, F-53B, Nafion BP2, and 6:2 FTSA suppressed STAT5b, activated NRF2, and activated SREBP. There was no apparent relationship between the length of the carbon chain, type of head group, or number of ether linkages and the transcriptomic changes. This work highlights the similarities in molecular targets between the legacy and alternative PFAS.
Language	English
Publishing date	2023-11-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2733883-6
ISSN	2305-6304 ; 2305-6304
ISSN (online)	2305-6304
ISSN	2305-6304
DOI	10.3390/toxics11120963
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Article ; Online: Determinants of gene expression in the human liver: Impact of aging and sex on xenobiotic metabolism.

Corton, J Christopher / Lee, Janice S / Liu, Jie / Ren, Hongzu / Vallanat, Beena / DeVito, Michael

Experimental gerontology

2022 Volume 169, Page(s) 111976

Abstract: There is a need to characterize the potential susceptibility of older adults to toxicity from environmental chemical exposures. Liver xenobiotic metabolizing enzymes (XMEs) play important roles in detoxifying and eliminating xenobiotics. We examined ... ...

Abstract	There is a need to characterize the potential susceptibility of older adults to toxicity from environmental chemical exposures. Liver xenobiotic metabolizing enzymes (XMEs) play important roles in detoxifying and eliminating xenobiotics. We examined global gene expression in the livers of young (21-45 years) and old (69+ years) men and women. Differentially expressed genes (DEG) were identified using two-way ANOVA (p ≤ 0.05). We identified 1437 and 1670 DEGs between young and old groups in men and women, respectively. Only a minor number of the total number of genes overlapped (146 genes). Aging increased or decreased pathways involved in inflammation and intermediary metabolism, respectively. Aging led to numerous changes in the expression of XME genes or genes known to control their expression (~90 genes). Out of 10 cytochrome P450s activities examined, there were increased activities of CYP1A2 and CYP2C9 enzymes in the old groups. We also identified sex-dependent genes that were more numerous in the young group (1065) than in the old group (202) and included changes in XMEs. These studies indicate that the livers from aging humans when compared to younger adults exhibit changes in XMEs that may lead to differences in the metabolism of xenobiotics.
MeSH term(s)	Male ; Humans ; Female ; Aged ; Xenobiotics/metabolism ; Xenobiotics/toxicity ; Cytochrome P-450 Enzyme System/genetics ; Cytochrome P-450 Enzyme System/metabolism ; Liver/metabolism ; Aging/genetics ; Aging/metabolism ; Gene Expression
Chemical Substances	Xenobiotics ; Cytochrome P-450 Enzyme System (9035-51-2)
Language	English
Publishing date	2022-10-13
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	390992-x
ISSN	1873-6815 ; 0531-5565
ISSN (online)	1873-6815
ISSN	0531-5565
DOI	10.1016/j.exger.2022.111976
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Article ; Online: Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity.

Corton, J Christopher / Liu, Jie / Kleinstreuer, Nicole / Gwinn, Maureen R / Ryan, Natalia

Chemico-biological interactions

2022 Volume 363, Page(s) 109995

Abstract: High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen ... ...

Abstract	High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76-85% for guideline uterotrophic assays, and 3) 87-88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. As part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.
MeSH term(s)	Animals ; Biomarkers ; Breast Neoplasms/genetics ; Endocrine Disruptors ; Female ; Gene Expression ; High-Throughput Screening Assays ; Humans ; Receptors, Estrogen/genetics ; Receptors, Estrogen/metabolism
Chemical Substances	Biomarkers ; Endocrine Disruptors ; Receptors, Estrogen
Language	English
Publishing date	2022-06-11
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	218799-1
ISSN	1872-7786 ; 0009-2797
ISSN (online)	1872-7786
ISSN	0009-2797
DOI	10.1016/j.cbi.2022.109995
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Article ; Online: A set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays.

Lewis, Robert W / Hill, Thomas / Corton, J Christopher

Toxicology

2020 Volume 443, Page(s) 152547

Abstract: Traditional methods for cancer risk assessment are retrospective, resource-intensive, and not feasible for the vast majority of environmental chemicals. In earlier studies, we used a set of six biomarkers to accurately identify liver tumorigens in ... ...

Abstract	Traditional methods for cancer risk assessment are retrospective, resource-intensive, and not feasible for the vast majority of environmental chemicals. In earlier studies, we used a set of six biomarkers to accurately identify liver tumorigens in transcript profiles derived from chemically-treated rats using either a Toxicological Priority Index (ToxPi) approach or using derived biomarker thresholds for cancer. The biomarkers consisting of 7-113 genes are used to predict the most common liver cancer molecular initiating events: genotoxicity, cytotoxicity and activation of the xenobiotic receptors AhR, CAR, ER, and PPARα. In the present study, we apply and evaluate the performance of these methods for cancer prediction in an independent rat liver study of 44 chemicals (6 h-7d exposures) examined by Affymetrix arrays. In the first approach, ToxPi ranking of biomarker scores consistently gave the highest scores to tumorigenic chemical-dose pairs; balanced accuracies for identification of liver tumorigenic chemicals were up to 89 %. The second approach used tumorigenic thresholds derived in the present study or from our earlier study that were set at the maximum value for chemical-dose exposures without detectable liver tumor outcomes. Using these thresholds, balanced accuracies were up to 90 %. Both approaches identified all tumorigenic chemicals. Almost all of the tumorigenic chemicals activated more than one MIE. We also compared biomarker responses between two types of profiling platforms (Affymetrix full-genome array, TempO-Seq 1500+ array containing ∼2600 genes) and found that the lack of the full set of biomarker genes on the 1500+ array resulted in decreased ability to identify chemicals that activate the MIEs. Overall, these results demonstrate that predictive approaches based on the 6 biomarkers could be used in short-term assays to identify chemicals and their doses that induce liver tumors, the most common endpoint in rodent bioassays.
MeSH term(s)	Animals ; Biological Assay ; Biomarkers, Tumor/genetics ; Carcinogens/toxicity ; Gene Expression ; Liver Neoplasms/chemically induced ; Liver Neoplasms/genetics ; Male ; Rats, Sprague-Dawley
Chemical Substances	Biomarkers, Tumor ; Carcinogens
Language	English
Publishing date	2020-08-02
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	184557-3
ISSN	1879-3185 ; 0300-483X
ISSN (online)	1879-3185
ISSN	0300-483X
DOI	10.1016/j.tox.2020.152547
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Article ; Online: A gene expression biomarker for predictive toxicology to identify chemical modulators of NF-κB.

Korunes, Katharine L / Liu, Jie / Huang, Ruili / Xia, Menghang / Houck, Keith A / Corton, J Christopher

PloS one

2022 Volume 17, Issue 2, Page(s) e0261854

Abstract: The nuclear factor-kappa B (NF-κB) is a transcription factor with important roles in inflammation, immune response, and oncogenesis. Dysregulation of NF-κB signaling is associated with inflammation and certain cancers. We developed a gene expression ... ...

Abstract	The nuclear factor-kappa B (NF-κB) is a transcription factor with important roles in inflammation, immune response, and oncogenesis. Dysregulation of NF-κB signaling is associated with inflammation and certain cancers. We developed a gene expression biomarker predictive of NF-κB modulation and used the biomarker to screen a large compendia of gene expression data. The biomarker consists of 108 genes responsive to tumor necrosis factor α in the absence but not the presence of IκB, an inhibitor of NF-κB. Using a set of 450 profiles from cells treated with immunomodulatory factors with known NF-κB activity, the balanced accuracy for prediction of NF-κB activation was > 90%. The biomarker was used to screen a microarray compendium consisting of 12,061 microarray comparisons from human cells exposed to 2,672 individual chemicals to identify chemicals that could cause toxic effects through NF-κB. There were 215 and 49 chemicals that were identified as putative or known NF-κB activators or suppressors, respectively. NF-κB activators were also identified using two high-throughput screening assays; 165 out of the ~3,800 chemicals (ToxCast assay) and 55 out of ~7,500 unique compounds (Tox21 assay) were identified as potential activators. A set of 32 chemicals not previously associated with NF-κB activation and which partially overlapped between the different screens were selected for validation in wild-type and NFKB1-null HeLa cells. Using RT-qPCR and targeted RNA-Seq, 31 of the 32 chemicals were confirmed to be NF-κB activators. These results comprehensively identify a set of chemicals that could cause toxic effects through NF-κB.
MeSH term(s)	Biomarkers/metabolism ; Cell Line ; Databases, Chemical ; Gene Expression Regulation/drug effects ; Gene Expression Regulation/genetics ; High-Throughput Screening Assays ; Humans ; I-kappa B Proteins/genetics ; I-kappa B Proteins/metabolism ; NF-kappa B/agonists ; NF-kappa B/antagonists & inhibitors ; NF-kappa B/metabolism ; NF-kappa B p50 Subunit/deficiency ; NF-kappa B p50 Subunit/genetics ; Small Molecule Libraries/chemistry ; Small Molecule Libraries/pharmacology ; Tumor Necrosis Factor-alpha/pharmacology
Chemical Substances	Biomarkers ; I-kappa B Proteins ; NF-kappa B ; NF-kappa B p50 Subunit ; Small Molecule Libraries ; Tumor Necrosis Factor-alpha
Language	English
Publishing date	2022-02-02
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0261854
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Article ; Online: A gene expression biomarker identifies inhibitors of two classes of epigenome effectors in a human microarray compendium.

Corton, J Christopher / Liu, Jie / Williams, Andrew / Cho, Eunnara / Yauk, Carole L

Chemico-biological interactions

2022 Volume 365, Page(s) 110032

Abstract: Biomarkers predictive of molecular and toxicological effects are needed to interpret emerging high-throughput transcriptomics (HTTr) data streams. To address the limited approaches available for identifying epigenotoxicants, we previously developed and ... ...

Abstract	Biomarkers predictive of molecular and toxicological effects are needed to interpret emerging high-throughput transcriptomics (HTTr) data streams. To address the limited approaches available for identifying epigenotoxicants, we previously developed and validated an 81-gene biomarker that accurately predicts histone deacetylase inhibition (HDACi) in transcript profiles derived from chemically-treated TK6 cells. In the present study, we sought to determine if this biomarker (TGx-HDACi) could be used to identify HDACi chemicals in other cell lines using the Running Fisher correlation test. Using microarray comparisons derived from human cells exposed to HDACi, we found considerable heterogeneity in correlation with the TGx-HDACi biomarker dependent on chemical exposure conditions and tissue from which the cell line was derived. Using a defined set of conditions that overlapped with our earlier study, the biomarker was able to accurately identify HDACi chemicals (90-100% balanced accuracy). In an in silico screen of 2427 chemicals in 9660 chemical versus control comparisons, the biomarker coupled with the Running Fisher test was able to identify 14 additional HDACi chemicals as well as other chemicals not previously associated with HDACi. Most notable were 12 inhibitors of bromodomain (BRD) and extraterminal (BET) family proteins including BRD4 that bind to acetylated histones. The BET protein inhibitors could be distinguished from the HDACi based on differences in the expression of a small set of biomarker genes. Our results indicate that the TGx-HDACi biomarker will be useful for identifying inhibitors of two classes of epigenome effectors in HTTr screening studies.
MeSH term(s)	Biomarkers ; Cell Cycle Proteins/metabolism ; Epigenome ; Gene Expression Profiling/methods ; Genetic Markers ; Histone Deacetylase Inhibitors/pharmacology ; Histone Deacetylases/metabolism ; Humans ; Nuclear Proteins/metabolism ; Oligonucleotide Array Sequence Analysis ; Transcription Factors ; Transcriptome
Chemical Substances	BRD4 protein, human ; Biomarkers ; Cell Cycle Proteins ; Genetic Markers ; Histone Deacetylase Inhibitors ; Nuclear Proteins ; Transcription Factors ; Histone Deacetylases (EC 3.5.1.98)
Language	English
Publishing date	2022-06-28
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	218799-1
ISSN	1872-7786 ; 0009-2797
ISSN (online)	1872-7786
ISSN	0009-2797
DOI	10.1016/j.cbi.2022.110032
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Article ; Online: A 50-gene biomarker identifies estrogen receptor-modulating chemicals in a microarray compendium.

Corton, J Christopher / Matteo, Geronimo / Chorley, Brian / Liu, Jie / Vallanat, Beena / Everett, Logan / Atlas, Ella / Meier, Matthew J / Williams, Andrew / Yauk, Carole Lyn

Chemico-biological interactions

2024 Volume 394, Page(s) 110952

Abstract: High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50- ...

Abstract	High throughput transcriptomics (HTTr) profiling has the potential to rapidly and comprehensively identify molecular targets of environmental chemicals that can be linked to adverse outcomes. We describe here the construction and characterization of a 50-gene expression biomarker designed to identify estrogen receptor (ER) active chemicals in HTTr datasets. Using microarray comparisons, the genes in the biomarker were identified as those that exhibited consistent directional changes when ER was activated (4 ER agonists; 4 ESR1 gene constitutively active mutants) and opposite directional changes when ER was suppressed (4 antagonist treatments; 4 ESR1 knockdown experiments). The biomarker was evaluated as a predictive tool using the Running Fisher algorithm by comparison to annotated gene expression microarray datasets including those evaluating the transcriptional effects of hormones and chemicals in MCF-7 cells. Depending on the reference dataset used, the biomarker had a predictive accuracy for activation of up to 96%. To demonstrate applicability for HTTr data analysis, the biomarker was used to identify ER activators in a set of 15 chemicals that are considered potential bisphenol A (BPA) alternatives examined at up to 10 concentrations in MCF-7 cells and analyzed by full-genome TempO-Seq. Using benchmark dose (BMD) modeling, the biomarker genes stratified the ER potency of BPA alternatives consistent with previous studies. These results demonstrate that the ER biomarker can be used to accurately identify ER activators in transcript profile data derived from MCF-7 cells.
MeSH term(s)	Humans ; MCF-7 Cells ; Receptors, Estrogen/metabolism ; Receptors, Estrogen/genetics ; Benzhydryl Compounds/toxicity ; Phenols/pharmacology ; Phenols/toxicity ; Gene Expression Profiling ; Oligonucleotide Array Sequence Analysis ; Biomarkers/metabolism ; Estrogen Receptor Modulators/pharmacology
Chemical Substances	Receptors, Estrogen ; Benzhydryl Compounds ; bisphenol A (MLT3645I99) ; Phenols ; Biomarkers ; Estrogen Receptor Modulators
Language	English
Publishing date	2024-04-02
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	218799-1
ISSN	1872-7786 ; 0009-2797
ISSN (online)	1872-7786
ISSN	0009-2797
DOI	10.1016/j.cbi.2024.110952
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Article ; Online: Increased Cell Proliferation as a Key Event in Chemical Carcinogenesis: Application in an Integrated Approach for the Testing and Assessment of Non-Genotoxic Carcinogenesis.

Strupp, Christian / Corvaro, Marco / Cohen, Samuel M / Corton, J Christopher / Ogawa, Kumiko / Richert, Lysiane / Jacobs, Miriam N

International journal of molecular sciences

2023 Volume 24, Issue 17

Abstract: In contrast to genotoxic carcinogens, there are currently no internationally agreed upon regulatory tools for identifying non-genotoxic carcinogens of human relevance. The rodent cancer bioassay is only used in certain regulatory sectors and is ... ...

Abstract	In contrast to genotoxic carcinogens, there are currently no internationally agreed upon regulatory tools for identifying non-genotoxic carcinogens of human relevance. The rodent cancer bioassay is only used in certain regulatory sectors and is criticized for its limited predictive power for human cancer risk. Cancer is due to genetic errors occurring in single cells. The risk of cancer is higher when there is an increase in the number of errors per replication (genotoxic agents) or in the number of replications (cell proliferation-inducing agents). The default regulatory approach for genotoxic agents whereby no threshold is set is reasonably conservative. However, non-genotoxic carcinogens cannot be regulated in the same way since increased cell proliferation has a clear threshold. An integrated approach for the testing and assessment (IATA) of non-genotoxic carcinogens is under development at the OECD, considering learnings from the regulatory assessment of data-rich substances such as agrochemicals. The aim is to achieve an endorsed IATA that predicts human cancer better than the rodent cancer bioassay, using methodologies that equally or better protect human health and are superior from the view of animal welfare/efficiency. This paper describes the technical opportunities available to assess cell proliferation as the central gateway of an IATA for non-genotoxic carcinogenicity.
MeSH term(s)	Animals ; Humans ; Carcinogenesis ; Carcinogens/toxicity ; Agrochemicals ; Biological Assay ; Cell Proliferation
Chemical Substances	Carcinogens ; Agrochemicals
Language	English
Publishing date	2023-08-26
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms241713246
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