Literature DB >> 22987251

Quantitative approaches for assessing dose-response relationships in genetic toxicology studies.

B B Gollapudi1, G E Johnson, L G Hernandez, L H Pottenger, K L Dearfield, A M Jeffrey, E Julien, J H Kim, D P Lovell, J T Macgregor, M M Moore, J van Benthem, P A White, E Zeiger, V Thybaud.   

Abstract

Genetic toxicology studies are required for the safety assessment of chemicals. Data from these studies have historically been interpreted in a qualitative, dichotomous "yes" or "no" manner without analysis of dose-response relationships. This article is based upon the work of an international multi-sector group that examined how quantitative dose-response relationships for in vitro and in vivo genetic toxicology data might be used to improve human risk assessment. The group examined three quantitative approaches for analyzing dose-response curves and deriving point-of-departure (POD) metrics (i.e., the no-observed-genotoxic-effect-level (NOGEL), the threshold effect level (Td), and the benchmark dose (BMD)), using data for the induction of micronuclei and gene mutations by methyl methanesulfonate or ethyl methanesulfonate in vitro and in vivo. These results suggest that the POD descriptors obtained using the different approaches are within the same order of magnitude, with more variability observed for the in vivo assays. The different approaches were found to be complementary as each has advantages and limitations. The results further indicate that the lower confidence limit of a benchmark response rate of 10% (BMDL(10) ) could be considered a satisfactory POD when analyzing genotoxicity data using the BMD approach. The models described permit the identification of POD values that could be combined with mode of action analysis to determine whether exposure(s) below a particular level constitutes a significant human risk. Subsequent analyses will expand the number of substances and endpoints investigated, and continue to evaluate the utility of quantitative approaches for analysis of genetic toxicity dose-response data.
Copyright © 2012 Wiley Periodicals, Inc.

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Year:  2012        PMID: 22987251     DOI: 10.1002/em.21727

Source DB:  PubMed          Journal:  Environ Mol Mutagen        ISSN: 0893-6692            Impact factor:   3.216


  32 in total

1.  Concentration-response studies of the chromosome-damaging effects of topoisomerase II inhibitors determined in vitro using human TK6 cells.

Authors:  P Gollapudi; V S Bhat; D A Eastmond
Journal:  Mutat Res       Date:  2019-05-15       Impact factor: 2.433

2.  Comparison of in vitro and in vivo clastogenic potency based on benchmark dose analysis of flow cytometric micronucleus data.

Authors:  Jeffrey C Bemis; John W Wills; Steven M Bryce; Dorothea K Torous; Stephen D Dertinger; Wout Slob
Journal:  Mutagenesis       Date:  2015-06-06       Impact factor: 3.000

3.  Biomarkers of exposure and effect in human lymphoblastoid TK6 cells following [13C2]-acetaldehyde exposure.

Authors:  Benjamin C Moeller; Leslie Recio; Amanda Green; Wei Sun; Fred A Wright; Wanda M Bodnar; James A Swenberg
Journal:  Toxicol Sci       Date:  2013-02-19       Impact factor: 4.849

Review 4.  Setting Occupational Exposure Limits for Genotoxic Substances in the Pharmaceutical Industry.

Authors:  Ester Lovsin Barle; Gian Christian Winkler; Susanne Glowienke; Azeddine Elhajouji; Jana Nunic; Hans-Joerg Martus
Journal:  Toxicol Sci       Date:  2016-05       Impact factor: 4.849

Review 5.  Estimating the carcinogenic potency of chemicals from the in vivo micronucleus test.

Authors:  Lya G Soeteman-Hernández; George E Johnson; Wout Slob
Journal:  Mutagenesis       Date:  2015-07-10       Impact factor: 3.000

6.  Incorporation of metabolic activation potentiates cyclophosphamide-induced DNA damage response in isogenic DT40 mutant cells.

Authors:  Kiyohiro Hashimoto; Shunichi Takeda; James A Swenberg; Jun Nakamura
Journal:  Mutagenesis       Date:  2015-06-17       Impact factor: 3.000

7.  Opportunities to integrate new approaches in genetic toxicology: an ILSI-HESI workshop report.

Authors:  Errol Zeiger; Bhaskar Gollapudi; Marilyn J Aardema; Scott Auerbach; Darrell Boverhof; Laura Custer; Peter Dedon; Masamitsu Honma; Seiichi Ishida; Andrea L Kasinski; James H Kim; Mugimane G Manjanatha; Jennifer Marlowe; Stefan Pfuhler; Igor Pogribny; William Slikker; Leon F Stankowski; Jennifer Y Tanir; Raymond Tice; Jan van Benthem; Paul White; Kristine L Witt; Véronique Thybaud
Journal:  Environ Mol Mutagen       Date:  2014-12-06       Impact factor: 3.216

8.  Predictions of genotoxic potential, mode of action, molecular targets, and potency via a tiered multiflow® assay data analysis strategy.

Authors:  Stephen D Dertinger; Andrew R Kraynak; Ryan P Wheeldon; Derek T Bernacki; Steven M Bryce; Nikki Hall; Jeffrey C Bemis; Sheila M Galloway; Patricia A Escobar; George E Johnson
Journal:  Environ Mol Mutagen       Date:  2019-02-27       Impact factor: 3.216

9.  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

Review 10.  Contributions of DNA repair and damage response pathways to the non-linear genotoxic responses of alkylating agents.

Authors:  Joanna Klapacz; Lynn H Pottenger; Bevin P Engelward; Christopher D Heinen; George E Johnson; Rebecca A Clewell; Paul L Carmichael; Yeyejide Adeleye; Melvin E Andersen
Journal:  Mutat Res Rev Mutat Res       Date:  2015-12-02       Impact factor: 5.657

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