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Title: Modeling receptor-mediated processes with dioxin: Implications for pharmacokinetics and risk assessment

Abstract

Dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin; TCDD), a widespread aromatic hydrocarbon, caused tumors in the liver and other sites when administered chronically to rats at doses as low as 0.01 [mu]g/kg/day. It functions in combination with a cellular protein, the Ah receptor, to alter gene regulation, and this resulting modulation of gene expression is believed to be obligatory for both dioxin toxicity and carcinogenicity. The U.S. EPA is reevaluating its dioxin risk assessment and, as part of this process, will be developing risk assessment approaches for chemicals, such as dioxin, whose toxicity is receptor-mediated. This paper describes a receptor-mediated physiologically based pharmacokinetic (PB-PK) model for the tissue distribution and enzyme-inducing properties of dioxin and discusses the potential role of these models in a biologically motivated risk assessment. In this model, ternary interactions among the Ah receptor, dioxin, and DNA binding sites lead to enhance production of specific hepatic proteins. This model was used to examine the tissue disposition of dioxin and the induction of both a dioxin-binding protein (presumably, cytochrome P4501A2), and cytochrome P4501A1. Tumor promotion correlated more closely with predicted induction of P4501A1 than with induction of hepatic binding proteins. Although increased induction of these proteins is not expected to be causally relatedmore » to tumor formation, these physiological dosimetry and gene-induction response models will be important for biologically motivated dioxin risk assessments in determining both target tissue dose of dioxin and gene products and in examining the relationship between these gene products and the cellular events more directly involved in tumor promotion.« less

Authors:
; ;  [1];  [2];  [3];  [4];  [5]
  1. Chemical Industry Inst. of Toxicology, Research Triangle Park, NC (United States)
  2. Univ. of North Carolina, Chapel Hill (United States)
  3. Environmental Protection Agency, Research Triangle Park, NC (United States)
  4. Free Univ., Berlin (Germany)
  5. Purdue Univ., West Lafayette, IN (United States)
Publication Date:
OSTI Identifier:
6692766
Resource Type:
Journal Article
Journal Name:
Risk Analysis; (United States)
Additional Journal Information:
Journal Volume: 13:1; Journal ID: ISSN 0272-4332
Country of Publication:
United States
Language:
English
Subject:
63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTANT EFFECTS ON LIVING ORGS. AND BIOL. MAT.; DIOXIN; RISK ASSESSMENT; TISSUE DISTRIBUTION; PHARMACOLOGY; BIOLOGICAL MODELS; RATS; HEPATOMAS; TOXICITY; CARCINOGENESIS; DNA; DOSIMETRY; GENE REGULATION; PROTEINS; US EPA; ANIMALS; CARCINOMAS; DISEASES; DISTRIBUTION; HETEROCYCLIC COMPOUNDS; MAMMALS; NATIONAL ORGANIZATIONS; NEOPLASMS; NUCLEIC ACIDS; ORGANIC COMPOUNDS; ORGANIC OXYGEN COMPOUNDS; PATHOGENESIS; RODENTS; US ORGANIZATIONS; VERTEBRATES; 560300* - Chemicals Metabolism & Toxicology

Citation Formats

Anderson, M E, Mills, J J, Gargas, M L, Keddersi, L, Birnbaum, L S, Neubert, D, and Greenlee, W F. Modeling receptor-mediated processes with dioxin: Implications for pharmacokinetics and risk assessment. United States: N. p., 1993. Web. doi:10.1111/j.1539-6924.1993.tb00726.x.
Anderson, M E, Mills, J J, Gargas, M L, Keddersi, L, Birnbaum, L S, Neubert, D, & Greenlee, W F. Modeling receptor-mediated processes with dioxin: Implications for pharmacokinetics and risk assessment. United States. https://doi.org/10.1111/j.1539-6924.1993.tb00726.x
Anderson, M E, Mills, J J, Gargas, M L, Keddersi, L, Birnbaum, L S, Neubert, D, and Greenlee, W F. 1993. "Modeling receptor-mediated processes with dioxin: Implications for pharmacokinetics and risk assessment". United States. https://doi.org/10.1111/j.1539-6924.1993.tb00726.x.
@article{osti_6692766,
title = {Modeling receptor-mediated processes with dioxin: Implications for pharmacokinetics and risk assessment},
author = {Anderson, M E and Mills, J J and Gargas, M L and Keddersi, L and Birnbaum, L S and Neubert, D and Greenlee, W F},
abstractNote = {Dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin; TCDD), a widespread aromatic hydrocarbon, caused tumors in the liver and other sites when administered chronically to rats at doses as low as 0.01 [mu]g/kg/day. It functions in combination with a cellular protein, the Ah receptor, to alter gene regulation, and this resulting modulation of gene expression is believed to be obligatory for both dioxin toxicity and carcinogenicity. The U.S. EPA is reevaluating its dioxin risk assessment and, as part of this process, will be developing risk assessment approaches for chemicals, such as dioxin, whose toxicity is receptor-mediated. This paper describes a receptor-mediated physiologically based pharmacokinetic (PB-PK) model for the tissue distribution and enzyme-inducing properties of dioxin and discusses the potential role of these models in a biologically motivated risk assessment. In this model, ternary interactions among the Ah receptor, dioxin, and DNA binding sites lead to enhance production of specific hepatic proteins. This model was used to examine the tissue disposition of dioxin and the induction of both a dioxin-binding protein (presumably, cytochrome P4501A2), and cytochrome P4501A1. Tumor promotion correlated more closely with predicted induction of P4501A1 than with induction of hepatic binding proteins. Although increased induction of these proteins is not expected to be causally related to tumor formation, these physiological dosimetry and gene-induction response models will be important for biologically motivated dioxin risk assessments in determining both target tissue dose of dioxin and gene products and in examining the relationship between these gene products and the cellular events more directly involved in tumor promotion.},
doi = {10.1111/j.1539-6924.1993.tb00726.x},
url = {https://www.osti.gov/biblio/6692766}, journal = {Risk Analysis; (United States)},
issn = {0272-4332},
number = ,
volume = 13:1,
place = {United States},
year = {Mon Feb 01 00:00:00 EST 1993},
month = {Mon Feb 01 00:00:00 EST 1993}
}