Quantitative analysis of the relative mutagenicity of five chemical constituents of tobacco smoke in the mouse lymphoma assay
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-amino...
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Published in | Mutagenesis Vol. 31; no. 3; pp. 287 - 296 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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England
01.05.2016
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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. |
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AbstractList | 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.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. 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 CdCl 2 ), 2-amino-3,4-dimethyl-3H-imidazo[4,5-f] quinoline (MelQ) 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 4 h. Only CdCl 2 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 (BMD 10 , BMD 50 , BMD 100 and BMD 200 ), 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 CdCl 2 (-S9) > BaP(+S9) > CdCl 2 (+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 (BMD 10 ) 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. 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. 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 CdCl sub(2)), 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 super(+/-) 3.7.2C mouse lymphoma cells were treated with four to seven concentrations of each chemical for 4h. Only CdCl sub(2) 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 (BMD sub(10), BMD sub(50), BMD sub(100) and BMD sub(200)), 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 CdCl sub(2)(-S9) > BaP(+S9) > CdCl sub(2)(+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 (BMD sub(10)) 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. |
Author | Dial, Stacey L. Richter, Patricia A. Moore, Martha M. Heflich, Robert H. Guo, Xiaoqing Mei, Nan |
AuthorAffiliation | 2 Center for Tobacco Products, Silver Spring, MD 20993, USA 3 Present address: Centers for Disease Control and Prevention, 4770 Buford Highway, Atlanta, GA 30341, USA 1 Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, Jefferson, AR 72079, USA 4 Ramboll Environ, 124 West Capitol Avenue, Suite 1890, Little Rock, AR 72201, USA |
AuthorAffiliation_xml | – name: 4 Ramboll Environ, 124 West Capitol Avenue, Suite 1890, Little Rock, AR 72201, USA – name: 2 Center for Tobacco Products, Silver Spring, MD 20993, USA – name: 1 Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, Jefferson, AR 72079, USA – name: 3 Present address: Centers for Disease Control and Prevention, 4770 Buford Highway, Atlanta, GA 30341, USA |
Author_xml | – sequence: 1 givenname: Xiaoqing surname: Guo fullname: Guo, Xiaoqing – sequence: 2 givenname: Robert H. surname: Heflich fullname: Heflich, Robert H. – sequence: 3 givenname: Stacey L. surname: Dial fullname: Dial, Stacey L. – sequence: 4 givenname: Patricia A. surname: Richter fullname: Richter, Patricia A. – sequence: 5 givenname: Martha M. surname: Moore fullname: Moore, Martha M. – sequence: 6 givenname: Nan surname: Mei fullname: Mei, Nan |
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PublicationYear | 2016 |
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SubjectTerms | Activation, Metabolic Aminobiphenyl Compounds - metabolism Aminobiphenyl Compounds - toxicity Animals Benzo(a)pyrene - metabolism Benzo(a)pyrene - toxicity Cadmium Chloride - toxicity Carcinogens - toxicity Cell Line, Tumor DNA Damage DNA, Neoplasm - drug effects DNA, Neoplasm - metabolism Lymphoma Mice Mutagenicity Tests Mutagens - toxicity Nitrosamines - metabolism Nitrosamines - toxicity Quinolines - metabolism Quinolines - toxicity Rats Smoke - analysis |
Title | Quantitative analysis of the relative mutagenicity of five chemical constituents of tobacco smoke in the mouse lymphoma assay |
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