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  • Title: A reexamination of the PPAR-alpha activation mode of action as a basis for assessing human cancer risks of environmental contaminants.
    Author: Guyton KZ, Chiu WA, Bateson TF, Jinot J, Scott CS, Brown RC, Caldwell JC.
    Journal: Environ Health Perspect; 2009 Nov; 117(11):1664-72. PubMed ID: 20049115.
    Abstract:
    BACKGROUND: Diverse environmental contaminants, including the plasticizer di(2-ethylhexyl)phthalate (DEHP), are hepatocarcinogenic peroxisome proliferators in rodents. Peroxisome proliferator-activated receptor-alpha (PPAR-alpha) activation and its sequelae have been proposed to constitute a mode of action (MOA) for hepatocarcinogenesis by such agents as a sole causative factor. Further, based on a hypothesized lower sensitivity of humans to this MOA, prior reviews have concluded that rodent hepatocarcinogenesis by PPAR-alpha agonists is irrelevant to human carcinogenic risk. DATA SYNTHESIS: Herein, we review recent studies that experimentally challenge the PPAR-alpha activation MOA hypothesis, providing evidence that DEHP is hepatocarcinogenic in PPAR-alpha-null mice and that the MOA but not hepatocarcinogenesis is evoked by PPAR-alpha activation in a transgenic mouse model. We further examine whether relative potency for PPAR-alpha activation or other steps in the MOA correlates with tumorigenic potency. In addition, for most PPAR-alpha agonists of environmental concern, available data are insufficient to characterize relative human sensitivity to this rodent MOA or to induction of hepatocarcinogenesis. CONCLUSIONS: Our review and analyses raise questions about the hypothesized PPAR-alpha activation MOA as a sole explanation for rodent hepatocarcinogenesis by PPAR-alpha agonists and therefore its utility as a primary basis for assessing human carcinogenic risk from the diverse compounds that activate PPAR-alpha. These findings have broad implications for how MOA hypotheses are developed, tested, and applied in human health risk assessment. We discuss alternatives to the current approaches to these key aspects of mechanistic data evaluation.
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