The behavior of genomic signatures of genotoxicity: Effect of dose level and exposure duration

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National Toxicology Program at NIEHS ILSI/HESI Workshop on

1 The behavior of genomic signatures of genotoxicity: Effect of level and exposure duration Scott S Auerbach, Ph.D., D.A.B.T. National Toxicology Program at NIEHS ILSI/HESI Workshop on Genetic Toxicology: Opportunities to Integrate New Approaches April 5,

2 Thank you! ILSI/HESI and the organizers for the invitation to speak

3 Disclaimer The statements, opinions or conclusions contained therein do not necessarily represent the statements, opinions or conclusions of NTP, NIEHS, NIH or the United States government.

4 What is toxicology testing? Massive query of all of biological space with the purpose of detecting statistically significant changes Genetox, Cancer, Repro, Immuno, Neuro, etc Animals represent highly integrated, high dimensional biosensors Most important piece of information is the shape of the response curve and the Point of Departure (POD) for the most sensitive endpoint With environmental chemicals the POD is typically use to set exposure limits

5 Benchmark Dose POD Exposure Limit Benchmark Dose: The of a substance that is expected to result in a prespecified level of effect, the benchmark response level or BMR Typically the BMR is defined as % shift in the background rate of response (BMD) How is it determined? Dose-response data for the biological effect is fit with a statistical model and a BMD is identified that results in a defined level of response over that observed in control populations Why is it important? The lower bound of the BMD is used as a POD to set exposure limits

6 Benchmark

The Real World Challenge To perform a comprehensive toxicological assessment using traditional methods that will allow for the identification of a POD it is time consuming, expensive and requires a

7 The Real World Challenge To perform a comprehensive toxicological assessment using traditional methods that will allow for the identification of a POD it is time consuming, expensive and requires a large number of animals 8, chemicals approved for use in commerce Little to no toxicity data on most Significant concern about potential effects on public health REACH, Montebello Agreement Deadlines for formulating hazard data and generating risk characterization Significant need for new approaches

8 Potential New Approaches Structure Activity Challenges with chemical space of training sets Significant quantitative challenges Yes/no is not good enough High throughput screening Large number of chemicals studied in limited biological space Human cell systems Often missing critical ADME related processes Quantitative and qualitative translation of results to in vivo is a challenge

9 Potential New Approaches () A compromise: Short-term in vivo toxicogenomics (TGMX) studies Similar to traditional toxicity studies Broad, integrated query of biological space Provides quantitative data that can be used for -response modeling and POD determination Testing takes place in an integrated system Allows for testing in different models of different physiological states Challenges As with HTS, what do the metrics mean? How does TGMX scale quantitatively against traditional endpoints? More or less sensitive? Effect of exposure duration?

10 Cancer TGMX Signature Development Immunotox Reproduction Dose TGMX Signature Cancer Development Immunotox Reproduction Dose TGMX vs. Traditional Assessments Scenario TGMX is protective Scenario TGMX is NOT protective BMD Values

11 Approach: Dose-response comparison, Genomics vs Tumors Identify a set of genotoxic (mutagenic, DNA alkylators) and nongenotoxic (PPARα activators) hepatocarcinogens that have existing cancer bioassay data and -response liver gene expression data in rats Model the liver tumor -response using BMDS to determine tumor BMD Derive gene signatures using DrugMatrix liver gene expression data for DNA Damage (mutagenic, DNA alkylators) and PPARα activation Male SD rat, Affymetrix data Determine signature variance at multiple levels and durations of exposure using TG-GATEs liver gene expression data Male SD rat, Affymetrix data Model -response of signature variance to determine a BMD (BMR = SD Compare signature BMD with Liver tumor BMD

12 Derivation of Genomic Signatures

NextBio Signature Development Important Concept: Gene Score in a Bioset Example: genes in a bioset from an RNA expression study Genes are sort by absolute fold change and then assigned a gene score

13 NextBio Signature Development Important Concept: Gene Score in a Bioset Example: genes in a bioset from an RNA expression study Genes are sort by absolute fold change and then assigned a gene score with the most differentially expressed gene = and the least = If there was genes in the bioset Top differentially expressed=, nd =99.9, 3 rd =99.8, etc Signature Derivation using Meta-Analysis Tool Assuming genes are directly correlated: Gene X overall gene score= 97= Gene Y overall gene score = 5=5+5+5

14 Treatments used to develop liver DNA damage signature -ACETYLAMINOFLUORENE at 3mg-kg-d in CMC by oral gavage 3d AFLATOXIN B at.3mg-kg-d in CMC by oral gavage 3d AFLATOXIN B at.3mg-kg-d in CMC by oral gavage 5d CARMUSTINE at mg-kg-d in corn oil by oral gavage d CARMUSTINE at mg-kg-d in corn oil by oral gavage 3d CARMUSTINE at mg-kg-d in corn oil by oral gavage 5d CARMUSTINE at mg-kg-d in corn oil by oral gavage 3d CARMUSTINE at mg-kg-d in corn oil by oral gavage 5d LOMUSTINE at 8.75mg-kg-d in corn oil by oral gavage 5d MITOMYCIN C at.7mg-kg-d in saline by intraveneous d MITOMYCIN C at.7mg-kg-d in saline by intraveneous 3d MITOMYCIN C at.7mg-kg-d in saline by intraveneous 5d N-NITROSODIETHYLAMINE at.7mg-kg-d in saline by oral gavage 5d N-NITROSODIETHYLAMINE at mg-kg-d in saline by intraperitoneal 5d N-NITROSODIETHYLAMINE at 3mg-kg-d in saline by oral gavage.5d N-NITROSODIETHYLAMINE at 3mg-kg-d in saline by oral gavage d N-NITROSODIETHYLAMINE at 3mg-kg-d in saline by oral gavage 3d PROCARBAZINE at 5mg-kg-d in water by oral gavage 5d

15 DNA Damage Signature Biology Top 5 Genes cyclin G ATP-binding cassette, sub-family B (MDR/TAP), member B myeloblastosis oncogene-like aldehyde dehydrogenase family, member A carboxylesterase (intestine, liver) Top Network: Cell Cycle, Cancer, Genetic Disorder Top Pathways

16 Treatments used to develop liver PPARα signature BEZAFIBRATE at mg-kg-d in corn oil by oral gavage 3d BEZAFIBRATE at mg-kg-d in corn oil by oral gavage 7d BEZAFIBRATE at 7mg-kg-d in corn oil by oral gavage 3d BEZAFIBRATE at 7mg-kg-d in corn oil by oral gavage 7d CLOFIBRIC ACID at 8mg-kg-d in corn oil by oral gavage d CLOFIBRIC ACID at 8mg-kg-d in corn oil by oral gavage 3d CLOFIBRIC ACID at 8mg-kg-d in corn oil by oral gavage 5d FENOFIBRATE at mg-kg-d in corn oil by oral gavage 3d FENOFIBRATE at mg-kg-d in corn oil by oral gavage 7d FENOFIBRATE at 5mg-kg-d in corn oil by oral gavage.5d FENOFIBRATE at 5mg-kg-d in corn oil by oral gavage d FENOFIBRATE at 5mg-kg-d in corn oil by oral gavage 3d FENOFIBRATE at 5mg-kg-d in corn oil by oral gavage 5d FENOFIBRATE at 3mg-kg-d in corn oil by oral gavage 5d FENOFIBRATE at 3mg-kg-d in corn oil by oral gavage 5d GEMFIBROZIL at mg-kg-d in corn oil by oral gavage 7d NAFENOPIN at 338mg-kg-d in corn oil by oral gavage 3d NAFENOPIN at 338mg-kg-d in corn oil by oral gavage 5d PIRINIXIC ACID at 3mg-kg-d in CMC by oral gavage d PIRINIXIC ACID at 3mg-kg-d in CMC by oral gavage 3d PIRINIXIC ACID at 3mg-kg-d in CMC by oral gavage 5d

17 PPARα Signature Biology Top 5 Genes acyl-coa thioesterase acyl-coa thioesterase vanin peroxisomal biogenesis factor alpha enoyl-coenzyme A, hydratase/3- hydroxyacyl Coenzyme A dehydrogenase Top Network: Energy Production, Lipid Metabolism, Small Molecule Biochemistry Top Pathways

18 Signature gene fold change variance Signature-level Genomic Benchmark Dose BMR = A change in the mean of the control = to St. Dev.

19 Genomic Signature Dose-Response Modeling Log Ratio (mean of control) Table Dose Gene Gene Gene Variance Mean variance of group St Dev of group variance Dose N Mean Variance St Dev Variance BMDS. Exponential Hill Polynomial Linear Power Select best fit model by AIC BMD BMR = Dose require to shift mean response by SD

20 Genotoxins N-nitrosodiethylamine, Monocrotaline, -acetylaminoflourine Variance of the DNA Damage Signature

21 N-Nitrosodethylamine (NDEA) Human exposure: drinking water, smoke and certain foods DNA alkylator and mutagen following bioactivation Ames: + Mouse micronucleus: - Cancer Rat: Liver (Tumor BMD =. mg/kg), Forestomach, Kidney Positive results in results in wide variety of species IARC: Group A: Probably carcinogenic to humans ROC Reasonably anticipated to be human carcinogen Doses used in genomic study:, 3,, 3 mg/kg

22 N-Nitrosodiethylamine (LC BMD =. mg/kg) Power Model with.95 Confidence Level Power Model with.95 Confidence Level Power Power 5 3d BMD =.9 mg/kg 8 7d BMD=.8 mg/kg 3 - BMDL BMD BMDL BMD :8 /8 Power Model with.95 Confidence Level : /8 Power Model with.95 Confidence Level 3 Power Power.5 d BMD =. mg/kg 3.5 8d BMD =. mg/kg BMDL BMD 8 :8 /8 -.5 BMDL BMD 8 : /8

23 Monocrotaline (MC) Pyrrolizidine alkaloid present in plants of the Crotalaria species Human exposure comes through contaminated food DNA Alkylator and mutagen following bioactivation Ames: + Mouse micronucleus: + Cancer Rats: Liver (Tumor BMD =. mg/kg) IARC Group B: Possibly carcinogenic to humans Doses used in genomic study:, 3,, 3 mg/kg

24 Monocrotaline (LC BMD =. mg/kg) Power Model with.95 Confidence Level Power Model with.95 Confidence Level 5 Power 3d BMD = 9.9 mg/kg Power 7d BMD= 3.3 mg/kg BMDL BMD - BMDL BMD :7 /8 Power Model with.95 Confidence Level :3 / Power Model with.95 Confidence Level Power d BMD =.7 mg/kg 3 Power 8d BMD = 9.5 mg/kg BMDL BMD BMDL BMD 8

25 -Acetylaminoflourene Prototype biochemical Little to no human exposure DNA alkylator and mutagen following bioactivation Ames: + Mouse micronucleus: + Cancer Rats: Hepatocellular carcinoma (BMD =.3 mg/kg) or cholangiocarcinoma, mammary-gland, testes, and Zymbal gland Doses for genomic study:, 3,, 3 mg/kg

26 -Acetylaminoflourene (LC BMD =.3 mg/kg) 9 Exponential Exponential Model with.95 Confidence Level Exponential Exponential Model with.95 Confidence Level BMDL BMD 3d BMD =. mg/kg :39 / Exponential Model with.95 Confidence Level BMDL BMD 3:37 / 7d BMD =.8 mg/kg Exponential Model with.95 Confidence Level Exponential Exponential 8 8 BMDLBMD d BMD =.5 mg/kg BMDLBMD 8d BMD =. mg/kg : / :3 /

27 Genomic Variance or L. tumor BMD (mg/kg) Genotoxic Liver Carcinogens: Genomic BMD vs. Liver Tumor BMD. 3d 7d d 8d TBMD.5x.8x.x NDEA MC -AAF.

28 Non-Genotoxins Gemfibrozil, Fenofibrate, WY-,3 Variance of the PPARα Signature

29 Gemfibrozil (Gem) A lipid-regulating agent that lowers elevated serum lipids primarily by decreasing serum triglycerides with a variable reduction in total cholesterol Non-genotoxic Ames: - Mouse micronucleus:? Acts via binding to PPARα in the liver Cancer Not considered carcinogenic in humans Rats Liver (BMD = 35 mg/kg), pancreas, testis, adrenal gland Doses for genomic study:, 3,, 3 mg/kg

30 Gemfibrozil (LC BMD = 35 mg/kg) Hill Model with.95 Confidence Level Hill Model with.95 Confidence Level Hill Hill BMDL BMD 5: / 3d BMD = 7. mg/kg Hill Model with.95 Confidence Level BMDLBMD 7d BMD =. mg/kg : / Hill Model with.95 Confidence Level Hill Hill BMDLBMD d BMD =.5 mg/kg BMDL BMD 8d BMD =. mg/kg

31 Fenofibrate (Fen) An antilipemic agent which reduces both cholesterol and triglycerides in the blood Non-genotoxic Ames: - Mouse micronucleus: - Acts via binding to the PPARα in the liver Cancer Not considered carcinogenic in humans Rats Liver (Estimated BMD = mg/kg), pancreas Doses for genomic study:,, mg/kg

32 Fenofibrate (Estimated* LC BMD = mg/kg) Exponential Model with.95 Confidence Level Exponential Model with.95 Confidence Level Exponential Exponential 8 8 BMDLBMD 3d BMD =.5 mg/kg BMDLBMD 7d BMD =. mg/kg 8 3:9 / Exponential Model with.95 Confidence Level 8 3:7 / Exponential Model with.95 Confidence Level Exponential Exponential 8 8 BMDLBMD d BMD =. mg/kg BMDLBMD 8d BMD =.9 mg/kg 8 3:33 / 8 3:3 /

33 WY-,3 (WY) Prototype biochemical with little to no human exposure Acts via PPARα and lowers serum lipids Non-genotoxic Ames: - Mouse micronucleus: - Cancer Rats High rates of liver tumors (BMD =. mg/kg) Doses for genomic study:,, 3, mg/kg

34 WY-,3 (LC BMD =. mg/kg) Exponential Exponential Model with.95 Confidence Level Exponential Exponential Model with.95 Confidence Level 8 8 BMDLBMD 3d BMD =.3 mg/kg BMDLBMD 7d =.7 mg/kg 8 :9 / Exponential Model with.95 Confidence Level 8 Exponential Model with.95 Confidence Level :3 / Exponential Exponential 8 8 BMDLBMD d BMD =.7 mg/kg 8 :35 / BMDLBMD 8d BMD =.8 mg/kg 8 : /

35 Genomic variance or L. tumor BMD (mg/kg) Non-genotoxic Liver Carcinogens: Genomic BMD vs. Liver Tumor BMD.x.9x Gem Fen WY 3d 7d d 8d TBMD. 3x

36 Cancer TGMX Signature Development Immunotox Reproduction Dose TGMX Signature Cancer Development Immunotox Reproduction Dose DNA Alkylators: TGMX vs. Traditional Assessments Longer exposures will lead to genomic -response that approximate tumor response TGMX is protective Scenario Scenario TGMX is NOT protective BMD Values

37 Cancer TGMX Signature Development Immunotox Reproduction Dose TGMX Signature Cancer Development Immunotox Reproduction Dose PPARα activators: TGMX vs. Traditional Assessments Scenario TGMX is protective Scenario Non-genotoxic carcinogens rapidly achieve genomic TGMX signature is NOT BMDs protective that are lower than tumor BMDs BMD Values

38 Conclusions Genotoxins (DNA Alkylators) Genomic signature variance BMDs tend to be less sensitive than corresponding cancer BMDs Genomic signature variance BMDs becomes more sensitive with increased exposure duration Non-genotoxins (PPARα Activtors) Genomic signature variance BMDs tend to be considerably more sensitive than corresponding cancer BMDs Genomic signature variance BMDs becomes more sensitive with increased exposure duration

39 Acknowledgements NIEHS/NTP John Bucher JoAnne Lewis Alex Merrick Fred Parham Ray Tice Nigel Walker SRA International Dan Svoboda Iconix Pharmaceuticals/Entelos Alan Roter The Japanese Toxicogenomics Consortium

41 Extra Slides

42 NDEA PPARA. Power Power Model with.95 Confidence Level Power Power Model with.95 Confidence Level BMD =. mg/kg - -. BMDL BMD Power Model with.95 Confidence Level :5 /3 Power 3 BMDL BMD BMD = 7.9 mg/kg :5 /3 Power Model with.95 Confidence Level Power BMD = 3. mg/kg BMDL BMD :57 /3 BMDL BMD BMD =.8 mg/kg 8 7: /3

43 Signature Varaince BMD (mg/kg) NDEA - Signature Variance BMD Comparison DNA Damage PPARA 3 3d 7d d 8d

44 Fold change in Variance Fold change in Variance Fold change in Variance Fold change in Variance NDEA - Fold Change in Signature Variance 3d 7 7d 5 8 DNA Damage PPARA 3 DNA Damage PPARA Dose (mg/kg) d DNA Damage leads the way Dose (mg/kg) 8d Dose (mg/kg) DNA Damage PPARA 8 3 Dose (mg/kg) DNA Damage PPARA

45 Gemfibrozil DNA Damage Signature Hill Model with.95 Confidence Level Hill Model with.95 Confidence Level Hill.5 Hill BMDL BMD BMD = Hill Model with.95 Confidence Level 7:33 /3 Hill :3 /3 BMDL BMD BMD = Hill Hill Model with.95 Confidence Level BMD = BMDL BMD :37 /3 BMDL BMD BMD = :39 /3

46 Signature Variance BMD (mg/kg) Gemfibrozil - Signature Variance BMD Comparison 8 PPARA DNA Damage 3d 7d d 8d

47 Gemfibrozil Fold Change of Signature Variance 3 5 3d d 5 PPARA DNA Damage 5 5 PPARA DNA Damage d PPARα leads the way d 5 PPARA DNA Damage 5 PPARA DNA Damage

48 N-Nitrosodiethylamine (LC BMD =. mg/kg) Ccng Hill Model with.95 Confidence Level Hill Highest scoring signature gene Associated with G/M phase arrest in response to DNA damage Intermediate by which p53 mediates its role as an inhibitor of cellular proliferation Hill Model with.95 Confidence Level - BMDL BMD 3d BMD =. mg/kg :8 / Hill Model with.95 Confidence Level 8 Hill 7 Hill 5 3 7d BMD =. mg/kg d BMD =. mg/kg - BMDLBMD BMDLBMD

The use of dose response data for risk assessment

The use of dose response data for risk assessment Dr Diane Benford, Food Standards Agency, London diane.benford@foodstandards.gsi.gov.uk 11.07.14 GTTC EEMS Workshop 1 Previous advice on substances in food