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ARA Case Study #26 Team: L.H. Pottenger, M.M. Moore, E. Zeiger, T. Zhou

Assessment of Low-Dose Dose-Response Relationships (Non-linear or Linear) for Genotoxicity, Focused on Induction of Mutations & Clastogenic Effects. ARA Case Study #26 Team: L.H. Pottenger, M.M. Moore, E. Zeiger, T. Zhou. Disclaimer: this does not represent the views or policy of US FDA.

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ARA Case Study #26 Team: L.H. Pottenger, M.M. Moore, E. Zeiger, T. Zhou

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  1. Assessment of Low-Dose Dose-Response Relationships (Non-linear or Linear) for Genotoxicity, Focused on Induction of Mutations & Clastogenic Effects ARA Case Study #26 Team: L.H. Pottenger, M.M. Moore, E. Zeiger, T. Zhou Disclaimer: this does not represent the views or policy of US FDA ARA Workshop #2

  2. Case study #26-G/M • WHAT: Dose-response for genotoxic effects from DNA-reactive chemicals • WHY: Driver for risk assessment • HOW: Review published data vs. guidance on recommended data/approaches • Conclusions & Issues ARA Workshop #2

  3. WHAT & WHYLow-Dose Dose-Response for Genotoxic Effects • Definitions: • Low-Dose: Range of human relevance (not MTD) • Mutation: Heritable change in genetic information (gene mutation; chromosomal event such as reciprocal translocation) • Included clastogenicity (micronucleus) data (not heritable) • Non-linear/threshold: Threshold is a subset of non-linear • Endogenous/Background for adducts & genotoxic effects • Genotoxic effects are a driver for decisions on cancer risk assessment dose-response models (mutagenic MOA) • Dose-response of key events is critical input into MOA analysis (mutation is early key event in mutagenic MOA) • Shape of dose-response for key events should be empirically defined with chemical-specific data, when available, and supported with hypothesis-driven theory ARA Workshop #2

  4. HOW: Our Process • Discussed possible criteria • Based on • Pottenger & Gollapudi, 2010 • Swenberg et al., 2008 • Several datasets preferred (different labs is best) • Adequate doses, replicates & controls; reproducible results • Preferably with dosimetry data • Apply dose-response modelling techniques • Statistical parameters to determine best fit • Selected & assigned candidate chemicals: • EO, EMS/ENU, MMS/MNU, Acrylamide/Glycidamide • Shared relevant publications • Developed chemical-specific appendices • Agreed general conclusions • Identified issues ARA Workshop #2

  5. Conceptual Key Events Frameworks Mutation Cancer Pottenger & Gollapudi, 2010 Swenberg et al., 2008 ARA Workshop #2

  6. Conclusions • Apparent linearity for biomarkers of exposure (hemoglobin & DNA adducts). • EMS(/ENU): Hb [& DNA adducts] • MMS(/MNU): DNA adducts based on 13C-MMS • EO: inadequate data; not clear if low-dose linear or not (14C-EO AMS data) • Clear, statistically supported evidence for low-dose non-linear/threshold dose-response for induction of mutations and clastogenicity for at least some DNA-reactive chemicals. • EMS: in vivo & in vitro statistical best fit for non-linear/threshold dose-response model • MMS/MNU: in vitro statistical best fit for non-linear/threshold dose-response model ARA Workshop #2

  7. EMS in vivo dosimetry Gocke and Muller, 2009 Apparent linearity for in vivo induction of protein (hemoglobin) [and DNA (N7-ethylG)] adducts by EMS ARA Workshop #2

  8. EMS in vivo clastogenicity Gocke and Muller, 2009 Clear, statistically supported evidence for best fit of low-dose data on in vivo induction of clastogenicity by EMS to non-linear/threshold dose-response model. ARA Workshop #2

  9. EMS in vivo clastogenicity & dosimetry Gocke and Muller, 2009 Clear, evidence for low-dose non-linear/threshold dose-response for in vivo induction of clastogenicity by EMS, even at doses with increasing internal dose (Hb adducts). ARA Workshop #2

  10. EMS in vivo mutation Gocke and Muller, 2009 Clear, statistically supported evidence for low-dose non-linear/threshold dose-response for in vivo induction of mutation by EMS. ARA Workshop #2

  11. Issues • Current effort was a limited analysis of available data (with time & expertise constraints) • Develop hypothesis (theoretical underpinnings) to explain a non-linear/threshold dose-response for genotoxicity • Only a few examples evaluated statistically supported best fit of dose-response models. • Additional evaluation (i.e., statistical approaches to dose-modelling) should be considered • Additional examples/datasets are always useful • Eventually develop categories based on MOA/key events & hypothesis-driven theoretical understanding of MOA ARA Workshop #2

  12. Questions? ARA Workshop #2

  13. Endogenous/Background DNA adducts J. Swenberg, personal communication ARA Workshop #2

  14. EMS in vivo mutation & clastogenicity Gocke and Muller, 2009 Clear, statistically supported evidence for low-dose non-linear/threshold dose-response for induction of mutation and clastogenicity by EMS. ARA Workshop #2

  15. MMS and MNU in vitro mutation & dosimetry Pottenger et al., 2009 ARA Workshop #2

  16. MMS in vitro mutation & dosimetry Swenberg et al., 2008; Doak et al., 2007 ARA Workshop #2

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