The ToxCast TM Program predicting hazard, characterizing toxicity - - PDF document

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The ToxCast TM Program predicting hazard, characterizing toxicity - - PDF document

The ToxCast TM Program predicting hazard, characterizing toxicity pathways and prioritizing the toxicity testing of environmental chemicals This work was reviewed by EPA and approved for presentation but does not Office of Research and


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The ToxCastTM Program – predicting hazard, characterizing toxicity pathways and prioritizing the toxicity testing of environmental chemicals

This work was reviewed by EPA and approved for presentation but does not

Office of Research and Development

necessarily reflect official Agency policy. Mention of trade names or commercial

National Center for Computational Toxicology

products does not constitute endorsement or recommendation by EPA for use.

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1

Office of Research and Development National Center for Computational Toxicolo

The Need For a New Approach

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January 23, 2009 2

Office of Research and Development National Center for Computational Toxicology

Too Many Chemicals Too High a Cost

Cancer DevTox NeuroTox ReproTox ImmunoTox PulmonaryTox

Millions $

EPA’s Need for Chemical Prioritization

1 10 100 1000 10000 100000 Data Collection

IRIS TRI Pesticide Actives CCL 1&2 Pesticide Inerts HPV MPV Current MPV Historical TSCA Inventory

11,000 90,000

…and not enough data.

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January 23, 2009 3

Office of Research and Development National Center for Computational Toxicology

Ways to Prioritize:

  • Animal studies

– cost, time, ethical considerations

  • QSAR

– domain of applicability, availability of models

  • Bioactivity Profiling

– biologically relevant chemical characterization – HTS methods – ToxCast

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ToxCastTM : a computational toxicology approach based on high-throughput bioactivity profiling

  • Research program of EPA’s National Center for Computational Toxicology
  • Addresses chemical screening and prioritization needs for pesticidal inerts,

anti-microbials, CCLs, HPVs and MPVs

  • Comprehensive use of HTS technologies to generate

biological fingerprints and predictive signatures

  • Coordinated with NIH: NTP and NHGRI/NCGC via Tox21
  • Committed to stakeholder involvement and public release of data
  • Communities of Practice- Chemical Prioritization; Exposure
  • NCCT website- http://www.epa.gov/ncct/toxcast
  • ACToR- Aggregated Computational Toxicology Resource

http://actor.epa.gov/actor/

Office of Research and Development

January 23, 2009

National Center for Computational Toxicology

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Phased Development of ToxCast

Phase Number of Chemicals Chemical Criteria Purpose Number of Assays Cost per Chemical Target Date

I 320 Data Rich (pesticides) Signature Development 552 $20k FY08 Ib 15 Nanomaterials Pilot 166 $10K FY09 IIa >300 Data Rich Chemicals Validation >400 ~$20-25k FY09 IIb >100 Known Human Toxicants Extrapolation >400 ~$20-25k FY09 IIc >300 Expanded Structure and Use Diversity Extension >400 ~$20-25k FY10 IId >12 Nanomaterials PMN >200 ~$15-20K FY09-10 III Thousands Data poor Prediction and Prioritization >300 ~$15-20k FY11-12

January 23, 2009 5

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ToxCast_320 Phase I Chemicals

309 unique structures 3 triplicates, 5 duplicates for QC 8 metabolites 291 total pesticide actives 273 registered pesticide actives 22 pesticide inerts 33 antimicrobials 23 IUR 13 HPV 11 HPV Challenge 73 OW PCCL 11 CCL1 10 CCL2 25 CCL3 122 IRIS chemicals

Office of Research and Development National Center for Computational Toxicology

Misc

56 of 73 proposed Tier 1 EDSP

Acetylcholine esterase inhibitors conazole fungicides Sodium channel modulators pyrethroid ester insecticides

  • rganothiophosphate acaricides

dinitroaniline herbicides pyridine herbicides thiocarbamate herbicides imidazolinone herbicides

  • rganophosphate insecticides

phenyl organothiophosphate insecticides aliphatic organothiophosphate insecticides amide herbicides aromatic fungicides chloroacetanilide herbicides chlorotriazine herbicides growth inhibitors

  • rganophosphate acaricides
  • xime carbamate insecticides

phenylurea herbicides pyrethroid ester acaricides strobilurin fungicides unclassified acaricides unclassified herbicides

January 23, 2009 6

MOA Classes with > 3 chemicals

Classification based on OPPIN

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Office of Research and Development National Center for Computational Toxicology

Human Relevance/ Cost/Complexity Throughput/ Simplicity

High-Throughput Screening Assays

10s-100s/yr 10s-100s/day 1000s/day 10,000s- 100,000s/day LTS HTS MTS uHTS

batch testing of chemicals for pharmacological/toxicological endpoints using automated liquid handling, detectors, and data acquisition

Gene-expression

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January 23, 2009 8

Office of Research and Development National Center for Computational Toxicology

ToxCast Phase I Datasets

  • ToxCast 1.0 (April, 2007)

– Enzyme inhibition/receptor binding HTS (Novascreen) – NR/transcription factors (Attagene, NCGC) – Cellular impedance (ACEA) – Complex cell interactions (BioSeek) – Hepatocelluar HCS (Cellumen) – Hepatic, renal and airway cytotoxicity (IVAL) – In vitro hepatogenomics (IVAL, Expression Analysis) – Zebrafish developmental toxicity (Phylonix)

  • ToxCast 1.1 (January, 2008)

– Neurite outgrowth HCS (NHEERL) – Cell proliferation (NHEERL) – Zebrafish developmental toxicity (NHEERL)

  • ToxCast 1.2 (June, 2008)

– XME Gene Regulation (CellzDirect) – HTS Genotoxicity (Gentronix) – Organ toxicity; dosimetry (Hamner Institutes) – Toxicity and signaling pathways (Invitrogen) – C. elegans WormTox (NIEHS) – Gene markers from microscale cultured hepatocytes (MIT) – 3D Cellular Zebrafish vascular/cardiotoxicity (Zygogen) – microarray with metabolism (Solidus) – HTS stress response (NHEERL+NCGC)

20 Assay sources 554 Endpoints

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ToxCast Assays

Biochemical Assays

  • Protein families

– GPCR – NR – Kinase – Phosphatase – Protease – Other enzyme – Ion channel – Transporter

  • Assay formats

– Radioligand binding – Enzyme activity – Co-activator recruitment

Office of Research and Development National Center for Computational Toxicology

Cellular Assays

  • Cell lines

– HepG2 human hepatoblastoma – A549 human lung carcinoma – HEK 293 human embryonic kidney

  • Primary cells

– Human endothelial cells – Human monocytes – Human keratinocytes – Human fibroblasts – Human proximal tubule kidney cells – Human small airway epithelial cells

  • Biotransformation competent cells

– Primary rat hepatocytes – Primary human hepatocytes

  • Assay formats

– Cytotoxicity – Reporter gene – Gene expression – Biomarker production

January 23, 2009

– High-content imaging for cellular phenotype

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Biochemical Assay Results

228 Assays 320 Chemicals Log IC50 (M)

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Office of Research and Development National Center for Computational Toxicology

Boric Acid Prochloraz Bisphenol A HPTE

Examples of Chemical Activity in Biochemical Assays

(IC50 log M) (IC50 log M) (IC50 log M) (IC50 log M)

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Office o Nation

PCA Mapping of CYP Inhibition

OPs Conazoles

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CYP Inhibition

Chemical Class

Conazoles OPs

IC50 (log M)

  • chemical class specificity
  • usually many cyps inhibited or none
  • may need to consider mechanism of inhibiton
  • may need to consider induction of cyps
  • may provide predictions of bioavailability
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Dopamine, dopamine transporter Estrogen Receptor Glucocorticoid receptor Opioid receptors Progesterone receptor Androgen receptor HPTE Methoxychlor

ToxCast and Biotransformation

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Cellular Assays

  • Types of Assays

– Known toxicity pathways and targets

  • biomarker measurements
  • reporter gene assays

– General cytotoxicity – Toxicity cellular phenotypes

  • Cell lines and primary cells
  • Generally screened at up to 100 M or used maximally

tolerated concentration defined by general cytotoxicity determination

  • Concentration-response format used and EC50 generated
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January 23, 2009 16

Office of Research and Development National Center for Computational Toxicology

Primary Human Cell Systems (BioSeek, Inc.)

  • 8 Assay systems
  • 87 endpoints
  • 4 concentrations
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Functional Similarity Map of ToxCast Library

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23, 2009 18

Office of Research and Dev National Center for Computati

Mitochondrial Dysfunction and Endoplasmic Reticulum Stress Classes

trifloxystrobin pyraclostrobin myxothiazol benomyl fludioxonil paclitaxel

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Use of BioSeek Data in ToxCast

  • Individual assay endpoints become part of larger ToxCast data set for

developing predictive models

  • BioMAP signatures used to provide mechanistic understanding of

potential mechanism/mode of action

  • May be able to validate signatures with other phenotypic assays

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January 23, 2009

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January 23, 2009 20

Office of Research and Development National Center for Computational Toxicology

High-Content Screening of Cellular Phenotypic Toxicity Parameters (Cellumen, Inc.)

  • Technology: automated fluorescent microscopy
  • Objective: Determine effects of chemicals on toxicity

biomarkers in a cell culture of human liver hepatoma HepG2

Cell Cycle CSK Integrity DNA Damage Oxidative Stress Stress Pathway Activation Organelle Functions

Panel 1 design* :

  • Multiple mechanisms of toxicity
  • Acute, early & chronic exposure
  • 384-well capacity
  • HepG2
  • 1o rat hepatocytes
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CellCiphr CellCiphr™ ™ Cytotoxicity Panel Cytotoxicity Panel

  • 10-point conc-response (200 M-39 nM)
  • Three time points (1 hr, 24 hr, 72 hr)
  • 11 endpoints per assay

Biomarker Positive Control Z’ Stress Pathway Oxidative Stress Mitochondrial Function Mitochondrial Mass Cell Loss Cell Cycle DNA Degradation Nuclear Size DNA Damage Mitotic Arrest Cytoskeletal Integrity Anisomycin Camptothecin CCCP CCCP Camptothecin Paclitaxel Paclitaxel Paclitaxel Camptothecin Paclitaxel Paclitaxel .63 .7 .55 .35 .56 .54 .6 .63 .43 .63 .3

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January 23, 2009

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1 hr 24 hr 48 hr 1 hr 24 hr 48 hr 1 hr 24 hr 48 hr

Mitochondria Mass Mitochondria Membrane Potential Cytotoxicity

Correlation of BioSeek Mitochondrial Dysfunction Class with HCS Mitochondrial Function Endpoints

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Multiplexed Reporter Gene Assay (Attagene, Inc.)

  • Measures activation/inhibition of transcription factors (TF)
  • TF integrate signals arising from changing cellular

environments and coordinate cellular response to such change

  • Similar to genomics but many fewer TF than genes
  • Compounds with similar mechanism of toxicity should bear

similar patterns

  • Patterns should reflect the changes that precede or

accompany the compounds’ toxicity

  • Use signatures for prediction of toxicological outcomes of

compounds

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January 23, 2009

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January 23, 2009 24

Multiplexed Reporter Gene Assay

Library of RTUs Cell Transfection PCR amplification Transcription Reverse transcription RNA Isolation Labeling Processing (Hpa I) Separation and detection (capillary electrophoresis)

X

RE 2 RTU B RE 1

X

RTU A

{

X

RE 2 RTU B RE 1

X

RTU A

X X X X X X X

Hpa I A B

  • +

X X X X X X X X X X X

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Hierachical Cluster Attagene Results

PPAR ERE, ER Fold Change (log 2) { VDRE, PXR, PXRE DR5, RAR, RAR, RAR, BRE, AP1, NRF2/ARE

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Ja

Office of Research and Development National Center for Computational Toxicology

Nuclear Receptor Screening (NCGC)

  • 10 Nuclear Receptors (more in queue)
  • Cellular Reporter Assays
  • Agonist and Antagonist modes
  • Concentration-Response Format (15 conc)

AGONIST

Bisphenol A HPTE 17-estradiol

Bisphenol A HPTE

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Receptor binding assay Transactivation assay Enzyme inhibition assay Functional cell assay

ToxCast Assays in the PPAR Signaling Pathways

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Office of Research and Development National Center for Computational Toxicology

ToxCast Covers a Wide Swath of Biological Space

Human Rat GeneGO Ingenuity David-KEGG Total GeneID

81 34 60 39 42 9 317 51

Molecular Pathways Identified by Analyses of ToxCast Assays

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Biochemical Assays Toxicology Endpoints Physical chemical properties

Profile Matching

ToxCast Data Analysis

Genomic Signatures In silico Predictions

Find “Signatures” from in vitro & in silico assays that predict in vivo endpoints.

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ToxRefDB website: http://www.epa.gov/ncct/toxrefdb/

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Martin et al., EHP 2008

ToxRefDB Chronic Rat Effects for 310 Chemicals

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Office of Research and Development National Center for Computational Toxicology

Selected Chronic Rat & Mouse Endpoints for ToxCast Predictive Modeling

Martin et al., EHP 2008

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Office of Research and Development National Center for Computational Toxicology

Martin et al., submitted

Selected Rat Reproductive Endpoints for ToxCast Predictive Modeling

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January 23, 2009 34

Office of Research and Development National Center for Computational Toxicology 20 40 60 80 100 120 Incomplete Ossification Unossified Full Supernumerary Incomplete Ossification Delayed ossification Full Supernumerary Short Unossified Bipartite Ossification Misshapen Misshapen Short Supernumerary Fused Absent Absent Fused Dilated renal pelvis Supernumerary Wavy Cleft palate Misaligned Bent Hydroureter Supernumerary Enlarged fontanel Enlarged fontanel Short Cervical Hernia Short Supernumerary Delayed ossification Hydrocephaly Hydrocephaly Local edema A A A C A C A C A A C A C A C A A C A A A A A A A C C A A C C A C A Malformation (A=Rat;C=Rabbit) # of Chemicals GN-GRL NS-BRN OF-CLP OF-JWH SK-APP SK-AXL SK-CRN TR-SOM TR-SPL UG-REN UG-URT

Selected Developmental Rat & Rabbit Endpoints for ToxCast Predictive Modeling

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Office of Research and Development National Center for Computational Toxicology

ToxCast Analysis Approaches

  • In vitro assays
  • Chemical structure information
  • Chemical classes
  • Physicochemical properties
  • In vivo endpoints

Hypothesis-driven Statistical Machine Learning

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Association Analysis / Signatures

LDA

  • Use Machine Learning methods

– SLR: Stepwise Logistic Regression

Assay 2

– LDA: Linear Discriminant Analysis – SVM: Support Vector Machines – Many others

  • For each binary endpoint, build models of form

Assay 1 Truth

– Predictor = F(assay values) – If

+

  • Predictor for a chemical meets criteria

+

– Then

Test

  • Predict endpoint to be positive for the chemical

TP FP FN TN

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January 23, 2009

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Methods described in: Judson et al 2008 A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model. BMC Bioinformatics 9:241 N1 A1 E1 A2 N2 N3 N4 N5 C1 B1 B2 B3 G1 A3 E2

HTS Assays cluster cluster

In Vivo In Vitro

Machine Learning: ToxCast Predictive Modeling of Chronic Rat Liver Apoptosis/Necrosis

(15) (23)

A B

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January 23, 2009 38

Hypothesis Driven: ToxCast Endocrine Profiling

56 EDSP Chemicals 35 ToxCast Assays

Vinclozolin Bisphenol A

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Office of Research and Development National Center for Computational Toxicology

Target Chemicals ~10,000 Chemicals with Toxicity Data (Training) HTS Characterization Discover & Validate “Hazard Model”

ToxCast Phase I & II

Chemicals wo/Phenotype Data (Test) Metabolite Prediction HTS Characterization Apply “Hazard Model” Mechanism-based Hazard Prediction Prioritized Chemicals

ToxCast Phase II & III

ToxCast Screening and Prioritization

http://www.epa.gov/comptox/toxcast Internal EPA use- do not copy, distribute or cite.

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Moving Forward with ToxCast

  • First predictive toxicity signatures based on ToxCast data

submitted for publication April 2009

  • ToxCast data available to collaborators now, publicly

available May 2009 at 1st ToxCast Data Analysis Summit

  • EPA & partners examining methods for analyzing ToxCast

data, identifying predictive signatures from Phase I for validation in Phase II

  • Phase II testing will commence June 2009 on upwards of

700 additional chemicals.

Office of Research and Development

January 23, 2009

National Center for Computational Toxicology

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Office of Research and Development National Center for Computational Toxicology

Applying Computational Toxicology Along Applying Computational Toxicology Along the Source to Outcome Continuum the Source to Outcome Continuum

Source/Stressor Formation Environmental Conc. External Dose Target Dose Biological Event Effect/Outcome

ToxRefDB ToxCast ToxMiner Reverse ToxicoKinetics ACToR ExpoCast

January 22, 2009

Reviewed by EPA and approved for presentation but does not necessarily reflect official Agency policy.

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Office of Research and Development National Center for Computational Toxicology

ToxCast Website: www.epa.gov/ncct/toxcast