Literature DB >> 26001754

Quantitative analysis of the relative mutagenicity of five chemical constituents of tobacco smoke in the mouse lymphoma assay.

Xiaoqing Guo1, Robert H Heflich1, Stacey L Dial1, Patricia A Richter2, Martha M Moore3, Nan Mei4.   

Abstract

Quantifying health-related biological effects, like genotoxicity, could provide a way of distinguishing between tobacco products. In order to develop tools for using genotoxicty data to quantitatively evaluate the risk of tobacco products, we tested five carcinogens found in cigarette smoke, 4-aminobiphenyl (4-ABP), benzo[a]pyrene (BaP), cadmium (in the form of CdCl2), 2-amino-3,4-dimethyl-3H-imidazo[4,5-f]quinoline (MeIQ) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), in the mouse lymphoma assay (MLA). The resulting mutagenicity dose responses were analyzed by various quantitative approaches and their strengths and weaknesses for distinguishing responses in the MLA were evaluated. L5178Y/Tk (+/-) 3.7.2C mouse lymphoma cells were treated with four to seven concentrations of each chemical for 4h. Only CdCl2 produced a positive response without metabolic activation (S9); all five chemicals produced dose-dependent increases in cytotoxicity and mutagenicity with S9. The lowest dose exceeding the global evaluation factor, the benchmark dose producing a 10%, 50%, 100% or 200% increase in the background frequency (BMD10, BMD50, BMD100 and BMD200), the no observed genotoxic effect level (NOGEL), the lowest observed genotoxic effect level (LOGEL) and the mutagenic potency expressed as a mutant frequency per micromole of chemical, were calculated for all the positive responses. All the quantitative metrics had similar rank orders for the agents' ability to induce mutation, from the most to least potent as CdCl2(-S9) > BaP(+S9) > CdCl2(+S9) > MeIQ(+S9) > 4-ABP(+S9) > NNK(+S9). However, the metric values for the different chemical responses (i.e. the ratio of the greatest value to the least value) for the different chemicals ranged from 16-fold (BMD10) to 572-fold (mutagenic potency). These results suggest that data from the MLA are capable of discriminating the mutagenicity of various constituents of cigarette smoke, and that quantitative analyses are available that can be useful in distinguishing between the exposure responses. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society 2015.

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Year:  2015        PMID: 26001754      PMCID: PMC6419102          DOI: 10.1093/mutage/gev039

Source DB:  PubMed          Journal:  Mutagenesis        ISSN: 0267-8357            Impact factor:   3.000


  7 in total

1.  DNA damage in oral epithelial cells of individuals chronically exposed to indoor radon (222Rn) in a hydrothermal area.

Authors:  Diana Paula Silva Linhares; Patrícia Ventura Garcia; Catarina Silva; Joana Barroso; Nadya Kazachkova; Rui Pereira; Manuela Lima; Ricardo Camarinho; Teresa Ferreira; Armindo Dos Santos Rodrigues
Journal:  Environ Geochem Health       Date:  2016-11-09       Impact factor: 4.609

2.  Quantitative differentiation of whole smoke solution-induced mutagenicity in the mouse lymphoma assay.

Authors:  Xiaoqing Guo; Robert H Heflich; Stacey L Dial; Mamata De; Patricia A Richter; Nan Mei
Journal:  Environ Mol Mutagen       Date:  2017-11-09       Impact factor: 3.216

3.  Comparative Genotoxicity of TEMPO and 3 of Its Derivatives in Mouse Lymphoma Cells.

Authors:  Xiaoqing Guo; Ji-Eun Seo; Steven M Bryce; Jenna A Tan; Qiangen Wu; Stacey L Dial; Martha M Moore; Nan Mei
Journal:  Toxicol Sci       Date:  2018-05-01       Impact factor: 4.849

4.  Limited mutagenicity of electronic cigarettes in mouse or human cells in vitro.

Authors:  Stella Tommasi; Steven E Bates; Rachel Z Behar; Prue Talbot; Ahmad Besaratinia
Journal:  Lung Cancer       Date:  2017-08-03       Impact factor: 5.705

5.  Comparative potency analysis of whole smoke solutions in the bacterial reverse mutation test.

Authors:  Fanxue Meng; Nan Mei; Jian Yan; Xiaoqing Guo; Patricia A Richter; Tao Chen; Mamata De
Journal:  Mutagenesis       Date:  2021-08-27       Impact factor: 3.000

6.  Aristolochic Acid-Induced Genotoxicity and Toxicogenomic Changes in Rodents.

Authors:  Xi-Lin Li; Xiao-Qing Guo; Hai-Rong Wang; Tao Chen; Nan Mei
Journal:  World J Tradit Chin Med       Date:  2020-03-13

Review 7.  Benchmark Dose Modeling of In Vitro Genotoxicity Data: a Reanalysis.

Authors:  Xiaoqing Guo; Nan Mei
Journal:  Toxicol Res       Date:  2018-10-15
  7 in total

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