Transcript Progress on PFOS PBPK Models - Alliance for Risk Assessment

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
Mode of Action from a Systems Biology Perspective:
Chemical Perturbation of Biological Processes
Exposure
Tissue Dose
Biological Interaction
Perturbation
Systems
Inputs
Biological
Function
Molecular Target(s)
“Chemical Mode of Action Link”
Impaired
Function
Adaptation
Disease
Morbidity &
Mortality
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)
Uses of Genomic Data (2):
Functional Genomics – Characterize interactions of
compound with gene regulatory network using temporal
analysis and iterative gene over-expression / inhibition
Growth factor
- can elucidate key elements
of cellular dose-response
(e.g., switch-like behaviors)
PKC
MAPKKK
AA
MAPKK
PLA2
MAPK
Increasing
Stimulus
Input
Pulse
(Conolly 2004)
- time-consuming, requires
sophisticated analyses
MKP
- modeling of gene regulation
is in its infancy
Uses of Genomic Data (3):
- provides evidence for
dose-dependent
mode of action
- requires tissue dosimetry
or phenotypic anchoring
Activity / Amount (% control)
Dose-Response – Collection of data on genomic responses
to a compound over a range of cell/tissue exposure
concentrations to identify dose-response for key genomic
bio-indicators of response
400
(Snow et al. 2002)
300
APE/Ref-1 mRNA
Trx mRNA
200
Pol b
100
Ligase I
0
0
5
10
15
µM AsIII
20
25
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
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
Example 1: Formaldehyde causes nasal
cancer in rats…
60
Kerns et al., 1983
50
40
30
20
10
0
0
0.7
2
6
10
Exposure Concentration (ppm)
15
Tumor Response
(%)
Monticello et al., 1990
…but it’s a normal constituent of cells
Formaldehyde Hydrate
H
H
N-DNA
OH
DNA & Protein
Addition Products
H
H
Labile methyl groups
and one-carbon
Endogenous metabolism
OH
OH
Glutathione
Conjugation
Production
DIsplacement
H
DNA - Protein
Crosslinks
H
SG
OH
Formaldehyde
Dehydrogenase (FDH)
Oxidation
NAD+
NADH + H+
HCOOH
Formic acid
+ GSH
Genomic Dose-Response Analysis
Results
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
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°)
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
Polynomial
Model (3°)
Comparison Between Transcriptomic Dose
Response and Tumor Response
Formaldehyde Time Course
Time Point
6 hr
Mean
(ppm)
SD
5 day
Min
(ppm)
Count
Mean
(ppm)
19 day
SD
Min
(ppm)
Count
0.28
1.37
3
Mean
(ppm)
SD
Min
(ppm) Count
1.18
0.17
1.02
3
Lowest Response Categories
Protein Import into Nucleus
GO:0000059
Complement Activation,
Alternative
GO:0006957
Positive T-cell Selection
GO:0043368
2.02
0.34
1.53
4
1.58
Selected Categories Related to Carcinogenicity
Positive Regulation of Cell
Proliferation
GO:0008284
7.82
4.26
0.64
100
7.52
3.78
0.63
114
6.85
3.90
0.57
137
Response to DNA Damage
Stimulus
GO:0006974
6.82
4.07
0.64
103
7.12
3.79
0.84
105
6.57
3.73
0.70
124
Inflammatory Response
GO:0006954
7.61
4.64
0.86
100
8.16
3.78
0.79
132
7.15
4.03
0.49
140
BMD for cell labeling index: 4.9 ppm
BMD for tumors: 6.4 ppm
(Schlosser, Risk Anal., 2003)
Comparison Between Transcriptomic Dose
Response and Tumor Response
Critical Gene Changes
60
50
Monticello et al., 1990
40
30
20
10
0
0
0.7
2
6
Exposure Concentration (ppm)
10
15
Tumor Response (%)
Kerns et al., 1983
Conclusions:
Formaldehyde
Genomic analysis demonstrates
the need to differentiate
regions of adaptive response
from those with overt tissue
damage (> 6 ppm)
300
250
Mutation analysis demonstrates
no evidence of mutagenic
activity at clearly toxic and
tumorigenic concentrations
100
100
21
4
pp
3
m
21
54
6p
3
pm
2
1
5
4
2p
50
50
3
pm
2
1
5
0.7
4
3
pp
m
2
1
5
4
A5
A4
A3
A2
A1
10
B5
B4
B3
B2
B1
5
C5
C4
C3
C2
C1
m
D5
D4
D3
D2
D1
43
pp
E5
E4
E3
E2
E1
5
15
F5
F4
F3
F2
F1
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
150
150
con
3
tro
l
2
0.57 0.14
6. 1.29
0. 1 4
re
0. 5 7
13.
1 78. 52. 26.
posu
n of e x
o
i
t
a
r
u
D
)
(weeks
1 3 . 00
2 6 . 00
5 2 . 00
7 8 . 00
1 .2 9
6 . 00
0
Labeling index
200
200
Example 2: Genomic Analysis to Identify the Dose-Response
for Early Cellular Responses to Inorganic Arsenic
Arsenite, trivalent MMA
Normal
Epithelial
Cell
Biochemical effects
GSH/GSSG ratio
Interactions with proteins
Adaptive
State
HSP proteins
Oxidative stress
Stressed
State
Necrosis
Apoptosis
Tumors
Inflammation
Cytotoxicity
DNA damage
Proliferation
Goal of Genomic Dose-Response Studies: To identify
key elements of each state and the points of transition
Dose-Response for the In Vitro Effects of Arsenite
in Primary Cells
(Gentry et al. 2009)
Inorganic arsenic concentrations in mouse bladder
after 12 weeks of exposure to arsenic in drinking water
Gene expression changes (up/down) at weeks 1 and 12
(1.5-fold or greater, p<0.05)
1677/125
2000
1800
# of altered genes
1600
1400
831/84
1200
1000
800
490/16
19/259
600
400
0/7
200
25/294
0 17/7
0
0.5
2
10
50
Dose (ppm)
Down-regulation at week 1 changes to up-regulation at week 12
Number of Genes vs BMD
60000
20000
Week 12 Down
Week 1 Down
0
-20000
-40000
-60000
BMD (ppm)
20
18
16
14
12
10
8
6
4
Week 12 Up
2
0
Gene Count
40000
Week 1 Up
Summary of BMD Analysis
Conducted 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
GO categories (N>6) with lowest BMDs at week 1
DNA packaging
chromatin assembly or disassembly
chromatin assembly
nucleosome organization
protein-DNA complex assembly
nucleosome assembly
GO categories (N>6) with lowest BMDs at week 12
apoptotic mitochondrial changes
double-strand break repair
cellular response to oxidative stress
regulation of DNA recombination
negative regulation of gene expression, epigenetic
epidermal growth factor receptor signaling pathway
oxygen and reactive oxygen species metabolic process
response to gamma radiation
nucleotide-excision repair
positive regulation of cell division
activation of protein kinase activity
histone deacetylation
regulation of protein stability
response to ionizing radiation
response to UV
positive regulation of cell cycle
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
Oxidative stress
DNA repair inhibition
Inflammation
Cell proliferation
DNA damage
DNA mutation
Tumors
RS - As
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
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
Treatment Group
Arsenite (µM)
MMA (µM)
(trivalent)
DMA (µM)
(trivalent)
Control
0
0
0
Exposure 1
0.01
0.01
0.04
Exposure 2
0.03
0.03
0.12
Exposure 3
0.1
0.1
0.4
Exposure 4
0.3
0.3
1.2
Exposure 5
1
1
4
Results: In Vitro Exposure of Human Urothelial Cells
to Mixtures of Trivalent Arsenic Compounds
Number of Genes with Significant Change in Expression
Dose Level
1
2
3
4
5
Total Arsenic (uM)
0.06
0.18
0.6
1.8
6.0
Number of Significant Genes
0
0
0
1
36
Genomic alterations restricted to total arsenic
concentrations above 1 micromolar
The most significant genes at Dose 5 are
consistent with oxidative stress response
The inter-individual variability is much larger than the change in
expression elicited by arsenic treatment.
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
Potential Impact of Population Variability on Cancer
Dose-Response for Arsenic in Drinking Water
Average Individual Dose-Response
Sensitive / Resistant Individual Dose-Response
Population Dose-Response
0.01
0.001
Susceptibility
Factors:
Linear
0.0001
Extrapolation
0.00001
(Clewell, 2001)
0.001
0.01
- Dietary intake
- Nutritional status
- Other exposures
- selenium
- mutagens
- Genetic factors
- metabolism (GST)
- cell control (P53)
0.1
Concentration in Drinking Water (mg/L)
1.0
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)