Modeling of Early Key Events Based on Genomics and potential applications for

1. Modeling of Early Key Events Based on Genomics and potential applications for nuclear-receptor-mediated toxicity Harvey Clewell Director, Center for Human Health Assessment The Hamner Institutes for Health Sciences Research Triangle Park, NC

2. Exposure Tissue Dose Biological Interaction Perturbation Systems Inputs Biological Function Molecular Target(s) “Chemical Mode of Action Link” Impaired Function Adaptation Disease Morbidity & Mortality Mode of Action from a Systems Biology Perspective: Chemical Perturbation of Biological Processes

3. Uses of Genomic Data (1): Hazard Identification–Identify pattern of gene changes associated with a particular effect • can provide insights into key elements in mode of action • essentially qualitative • typically, little concern for tissue dosimetry (Liu et al. 2005)

4. Uses of Genomic Data (2): Functional Genomics– Characterize interactions of compound with gene regulatory network using temporal analysis and iterative gene over-expression / inhibition • can elucidate key elements of cellular dose-response (e.g., switch-like behaviors) • time-consuming, requires sophisticated analyses • modeling of gene regulation is in its infancy Increasing Stimulus Input Pulse (Conolly 2004)

5. 400 (Snow et al. 2002) 300 APE/Ref-1 mRNA Trx mRNA Activity / Amount (% control) 200 Pol b 100 Ligase I 0 0 5 10 15 20 25 µM AsIII Uses of Genomic Data (3): Dose-Response – Collection of data on genomic responses to a compound over a range of cell/tissue exposure concentrations to identify dose-response for keygenomic bio-indicators of response - provides evidence for dose-dependent mode of action • requires tissue dosimetry or phenotypic anchoring

6. Analysis of Mutation Frequency in p53 and K-ras Oncogenes in Nasal Tissues of Rats Exposed to Inhaled Formaldehyde • NCTR analysis • Found no increase in p53 or K-ras mutations after 90 days of exposure to formaldehyde at up to 15 ppm • Demonstrates lack of mutagenic activity in vivo at carcinogenic concentrations

7. High Content Imaging Assays (HCA) • in vitro, cell-based imaging assays in multi-well plates • Primary cells or cell lines similar to target tissue (human and rodent) • Capable of performing large numbers of replicates, doses, and time points • High statistical power to detect departure from linearity or threshold • Can apply to provide oxidative and DNA stress measures 7

8. Example 1: Formaldehyde causes nasal cancer in rats… 60 Kerns et al., 1983 50 Monticello et al., 1990 40 (%) 30 Tumor Response 20 10 0 0 0.7 2 6 10 15 Exposure Concentration(ppm)

9. …but it’s a normal constituent of cells Formaldehyde Hydrate Labile methyl groups and one-carbon metabolism Endogenous Production DNA & Protein Addition Products Glutathione Conjugation DIsplacement DNA - Protein Crosslinks NAD+ Formaldehyde Dehydrogenase (FDH) NADH + H+ Oxidation + HCOOH GSH Formic acid

10. Genomic Dose-Response AnalysisResults • No evidence of genomic changes at 0.7 ppm exposure • Transient response (at 5 days) in animals exposed to 2 ppm • different from response at 6 ppm • suggestive of cellular adaptation • Inflammatory and oxidative stress responses at 6 ppm • maintained throughout entire exposure period • Evidence of change in mode of action between 2 and 6 ppm • Consistent with transition from adaptive to toxic state • Indications of cell-surface targets at lower concentrations vs. internal targets at higher concentrations

11. Genomic Data Benchmark Analysis Gene Expression Dose Response Data One-Way Analysis of Variance to Identify Genes Changing with Dose Power Model Linear Model Polynomial Model (2°) Polynomial Model (3°) Nested test to Select Best Polynomial Model Select Best Model Remove Genes with BMD > Highest Dose Group Genes by Gene Ontology Category Estimate BMD and BMDL for each Gene Ontology Category

12. Comparison Between Transcriptomic Dose Response and Tumor Response Formaldehyde Time Course BMD for cell labeling index: 4.9 ppm BMD for tumors: 6.4 ppm (Schlosser, Risk Anal., 2003)

13. Comparison Between Transcriptomic Dose Response and Tumor Response Critical Gene Changes 60 Kerns et al., 1983 50 Monticello et al., 1990 40 30 Tumor Response (%) 20 10 0 0 0.7 2 6 10 15 Exposure Concentration (ppm)

14. Conclusions: Formaldehyde • Genomic analysis demonstrates the need to differentiate regions of adaptive response from those with overt tissue damage (> 6 ppm) • Mutation analysis demonstrates no evidence of mutagenic activity at clearly toxic and tumorigenic concentrations • Results provide mechanistic support for U-shaped cell proliferation dose-response curves seen in cancer bioassay and the modeling results of Conolly et al. 2004

15. Normal Epithelial Cell Necrosis Apoptosis Tumors Example 2: Genomic Analysis to Identify the Dose-Response for Early Cellular Responses to Inorganic Arsenic Arsenite, trivalent MMA Adaptive State Stressed State Biochemical effects GSH/GSSG ratio Interactions with proteins Inflammation Cytotoxicity DNA damage Proliferation HSP proteins Oxidative stress Goal of Genomic Dose-Response Studies: To identify key elements of each state and the points of transition

16. Dose-Response for the In Vitro Effects of Arsenite in Primary Cells (Gentry et al. 2009)

17. Inorganic arsenic concentrations in mouse bladder after 12 weeks of exposure to arsenic in drinking water

18. Gene expression changes (up/down) at weeks 1 and 12 (1.5-fold or greater, p<0.05) 1677/125 831/84 490/16 25/294 19/259 0/7 17/7 0 Down-regulation at week 1 changes to up-regulation at week 12

20. Summary of BMD AnalysisConducted for GO categories with genes showing D/R at p<0.05 1 week: Majority of GO category median BMDs: 9-15 ppm Lowest BMDs for categories (N>6): 1.5 ppm Lowest BMDs for single genes: 0.7 ppm 12 week: Majority of GO category median BMDs: 6-11 ppm Lowest BMDs for categories (N>6): 1.7 ppm Lowest BMDs for single genes: 0.7 ppm

21. GO categories (N>6) with lowest BMDs at week 1

22. GO categories (N>6) with lowest BMDs at week 12

23. Proposed “Sequence of Events” for Inorganic Arsenic Carcinogenicity Exposure: As(5); As(3); mixed forms Active chemical in tissue: As(III), MMA(III) Protein binding: As(III) + RSH RS - As Oxidative stress DNA repair inhibition Inflammation Cell proliferation DNA damage DNA mutation Tumors

24. Conclusions Dose and duration of arsenic exposure interact to produce an cellular response that evolves over time Median BMDs for gene categories cluster around the 10 ppm dose, with a small number of BMDs around the 2 ppm dose. The lowest BMDs for single genes are above the lowest dose of 0.5 ppm. The genomic responses are largely consistent with an adaptive response at lower concentrations / shorter durations, but with increasing toxicity as concentration and duration increase

25. In Vitro Exposure of Human Urothelial Cells to Mixtures of Trivalent Arsenic Compounds Relative Concentrations Based on Measurements of Arsenic Compounds in Urine of Humans Exposed to Arsenic in Drinking Water

26. Results: In Vitro Exposure of Human Urothelial Cells to Mixtures of TrivalentArsenic Compounds Number of Genes with Significant Change in Expression Dose LevelTotal Arsenic (uM)Number of Significant Genes 1 0.06 0 2 0.18 0 3 0.6 0 4 1.8 1 5 6.0 36 Genomic alterations restricted to total arsenic concentrations above 1 micromolar The most significant genes at Dose 5 are consistent with oxidative stress response

27. The inter-individual variability is much larger than the change in expression elicited by arsenic treatment.

28. Conclusions: Arsenic Genomic responses to arsenic in vitro exposures were observed in human uroepithelial cells at total arsenic concentrations greater than 1 micromolar These results are consistent with the in vivo genomic responses observed in bladders of mice exposed to inorganic arsenic in drinking water, where significant genomic changes were observed at bladder concentrations above 1 micromolar Human interindividual variability in gene expression is large in comparison with the effect of environmental arsenic exposures, complicating the use of genomic changes as biomarkers

29. Potential Impact of Population Variability on Cancer Dose-Response for Arsenic in Drinking Water 0.01 Average Individual Dose-Response Sensitive / Resistant Individual Dose-Response Population Dose-Response 0.001 Susceptibility Factors: - Dietary intake • Nutritional status • Other exposures - selenium - mutagens - Genetic factors - metabolism (GST) - cell control (P53) Linear Extrapolation Risk 0.0001 0.00001 (Clewell, 2001) 0.001 0.01 0.1 1.0 Concentration in Drinking Water (mg/L)

30. Application to Nuclear-Receptor-Mediated Toxicity Nuclear receptor binding is just one of many possible early events linking an active compound or metabolite to a cellular response Downstream events from receptor activation can include multiple effects -- induction of metabolism -- mitogenic signaling -- DNA damage The dose-responses for these pleiotropic effects can differ significantly, resulting in dose-dependent transitions and changes in mode of action Genomic, proteomic, and mutational dose-response analysis can be used to identify key early events, dose-dependent transitions, and the mode-of-action element that drives carcinogenicity (toxicity, proliferation, or mutation)