Methylene Chloride a case study forDose-Dependent

Transitions

Raymond M. David, Ph.D.Eastman Kodak Company

©Eastman Kodak Company, 2005

Overview Methylene chloride (DCM) is a good

case study for risk assessment because it is a classic example of dose-dependent

transition in carcinogenesis there are human data for metabolism

around the inflection point example of species differences in

metabolism and genetic polymorphisms, which impact the quantitation of risk

PBPK modeling has been used for species extrapolation and risk assessment

Carcinogenic Potential National Coffee Association (NCA) study

–0, 60, 125, 185, and 250 mg/kg body in drinking water to F-344 rats and B6C3F1 mice for 2 years

National Toxicology Program (NTP) study –0, 2000, or 4000 ppm by inhalation to F-344 rats and B6C3F1 mice for 2 years

Tumor response Dose

mg/kg/dTumor

IncidenceOrgan Sex/

Strain/Species

Study

0 60125 185 250

24/125 51/20030/10031/9935/125

LiverMale

B6C3F1

NCA;Serota et

al.

0 1582 3162

3/50 16/48 40/48

LiverFemaleB6C3F1 NTP

015823162

3/45 30/4641/46

LungFemaleB6C3F1 NTP

Liver tumor response

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

10 100 1000 10000

log Dose equivalent (mg/ kg)

Perc

enta

ge

Tumor incidence summary Increased incidence of hepatocellular

adenomas and carcinomas were observed in mice (one sex) at 125 mg/kg/d.

Increased incidence of lung tumors (alveolar/bronchiolar adenomas) were observed in mice exposed to airborne concentrations of 2000 ppm.

F-344 rats showed no evidence of increased liver or lung tumors.

Mode of action At low concentrations, DCM is metabolized

primarily by cytochrome P450 (CYP). Kubic and Anders (1975) and Anders et al.

(1977) demonstrated that DCM was metabolized by CYP to carbon monoxide.

Kim and Kim (1996) later identified CYP2E1 as the isozyme associated with this pathway.

Kubic and Anders (1978) determined the Km (50.1 mM) and Vmax (5.4 nmol CO/mg prot/min).

McKenna et al. (1982) showed that CYP2E1 in laboratory animals was saturated above concentrations of 500 ppm.

Mode of action

CYP 2E1 catalyzed:

CH2Cl2 CHOHCl2 HCOCl CO + CO2

formyl chloride

COHb

Mode of action At higher concentrations, CYP pathway can

be saturated and GST pathway metabolizes DCM. Ahmed and Anders (1976) and Anders et al.

(1977) demonstrated that DCM was metabolized via a GST pathway.

Gargas et al. (1986) proposed the current metabolic scheme via GST pathway.

Blocki et al. (1994) showed that GST 5-5, a -class GST (also known as T1-1 in humans), had the highest specific activity for DCM (11,000 nmol/min/mg protein) with a Km of 300 µM.

Mode of action

GST catalyzed:

CH2Cl2 GSCH2Cl GSCH2OH HCHOchloromethylglutathione GSCHO HCOOH CO2

MOA – supporting data Reynolds and Yee (1967) and Anders et al.

(1977) showed that 14C-DCM was bound to tissue protein and lipid.

Casanova et al. (1992) demonstrated an increase of DNA-protein cross-links (DPX) in the liver and RNA-formaldehyde adducts (RFA) in the lungs.

DNA adducts may also be formed directly from the chloromethylglutathione intermediate rather than formaldehyde (Marsch et al., 2001, 2004).

MOA – supporting data Graves et al. (1994) and Thier et

al. (1993) linked mutations observed only in S. typhymurium strains TA1535 and TA100 to nascent GST activity.

Other tests for genetic toxicity generally negative.

Constructing the data set Metabolic parameters for different

species Developing human data

parameters Developing a model

Understanding the compartments Physiological parameters in different

species

Species metabolic parameters

Species

Km

(mM)

Vmax

(nmol/min/mg prot)

Km

(mM)

Vmax

(nmol/min/mg prot)

mouse 1.84 0.33

15.90 1.10 137 21 118.2 14.4

rat 1.42 0.74

5.39 0.94 nd nd

human 0.92 – 2.82

1.53 – 13.00 43.8 – 44.1 6.04 – 7.05

MFO pathway GST pathway

From Reitz et al., 1988. nd = not determined

Species metabolic parameters

Species

Tissue

MFO GST

Mouse LiverLung

1.760 ± 0.1150.732 ± 0.115

5290 ± 430727 ± 64

Rat LiverLung

0.814 ± 0.1180.111 ± 0.035

1380 ± 11077 ± 5

Human LiverLung

0.418 ± 0.1570.0006 ± 0.0003

1650 ± 480 78 ± 47

Specific activities from Lorenz et al. (1984) in nmol/min/mg protein as reported by Andersen et al. (1987)

Species metabolic parameters Glutathione transferase (GST T1-1)

catalyzes the conjugation of glutathione and DCM in mice and humans.

The gene is polymorphic in humans Non-conjugators: GST T1 (–/–) Low conjugators: GST T1 (+/–) High conjugators: GST T1 (+/+)

Distribution of the null phenotype in humans has been studied.

GSTT1 -/- DistributionGroup %

Population%

Homozygous

Asian 3.9 62

Caucasian 75.5 19.7

African-American

12.2 21.8

Mexican-American

11.4 9.7

From El-Masri et al., 1999.

Human data sets

Exposure levels (ppm)

Duration hrs

Number of

subjects

Reference

100, 350 6 6 Andersen et al. (1987)

50, 100, 150, 200

8 13 DiVincenzo et al. (1986)

250, 500, 1000

2.5 14 Astrand et al. (1975)

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10

11

12

13 A B C D E

Cle

well

(1995

)Jo

nss

on a

nd

Jo

hanso

n (

20

01)

Exp

ert

Elic

itati

on

OS

HA

Pri

or

OS

HA

Post

eri

or

Individual Values (Sweeney et al., 2004)Individual Values (Jonsson et al. (2001)

Population Values

Vm

axc/K

m (

/hr)

Human data

PBPK modeling First interspecies extrapolation

using PBPK modeling was Andersen et al. (1987).

Dose metric was blood, tissue, and exhaled DCM.

Human metabolic values were mean from subjects exposed to 100 or350 ppm for 6 hours.

GasExchange

LungMetabolism

Richly perfused

Fat

Slowly perfused

LiverGI tract

GST CYP

Blo

od

CYP

GST

Andersen model

PBPK models for DCM assessment

Citation Remarks

Reitz et al., 1988 Deterministic approach. Andersen et al. (1987) model updated with measured MFO and GST rate constants.

Andersen et al., 1991

Deterministic approach. Blood compartment added to describe carbon monoxide and carboxyhemoglobin kinetics.

Dankovic et al., 1994

Deterministic approach. Mean values for alveolar ventilation, cardiac ouput, and tissue blood flow increased.

Casanova, et al., 1996

Deterministic approach. Liver DNA-protein cross-links from formaldehyde used as the dosimeter of effect.

PBPK models for DCM assessment

Citation Remarks

Bois and Smith, 1995

Probabilistic (Bayesian) approach. Bone marrow compartment added, variance in metabolic rate constants increased.

Thomas et al., 1996

Probabilistic (Bayesian) approach. Variability from MFO induction, GST inhibition, and tissue solubility included.

El-Masri et al., 1999

Probabilistic (Bayesian) approach incorporating GST-T1 polymorphisms and estimating DPX.

Jonsson and Johanson, 2001

Probabilistic (Bayesian) approach. New fat and muscle compartments. Includes population estimates of glutathione transfersase T1 gene frequencies

Changes in unit risk over time

Source Unit risk (per µg/m3)

EPA 1985 1.0 10-6

EPA 1991 4.7 10-7

El Masri et al., 1999 1.9 10-10

Jonsson and Johanson, 2001

1.9 10-10

DCM PBPK model resultsIndividual K2, Blood Carboxyhemoglobin

0

1

2

3

4

5

6

0 10 20 30 40 50

Time (hr)

Blo

od

Carb

oxyh

em

og

lob

in (

perc

en

t)

50 ppm (model)

100 ppm (model)

200 ppm (model)

50 ppm data

100 ppm data

200 ppm data

DCM PBPK model resultsIndividual K2, Exhaled Breath DCM

0.1

1

10

100

0 5 10

Time (hr)

Ex

ha

led

bre

ath

DC

M (

pp

m)

50 ppm (model)

100 ppm (model)

200 ppm (model)

50 ppm data

100 ppm data

200 ppm data

DCM PBPK model resultsIndividual K2, Blood DCM

0.01

0.1

1

10

0 2 4 6 8 10 12

Time (hr)

Blo

od

DC

M (

mg

/L)

50 ppm (model)

100 ppm (model)

200 ppm (model)

50 ppm data

100 ppm data

200 ppm data

GasExchange

LungMetabolism

Richly perfused

Fat

Slowly perfused

LiverGI tract

GST CYP

Blo

od

CYP

GST

CYP

Sweeney model

Updating the risk assessment

Do the new human data and the model change the calculated unit risk?

Perhaps --- the unit risk is 4.8 x 10-8 using the Sweeney PBPK model compared with 4.7 x 10-7 used by the EPA.

Using probabilistic methodology and genetic polymorphisms might also impact the unit risk calculation.

Summary DCM is a good example for quantitative

risk assessment because it demonstrates a dose-dependent transition

from non-carcinogenic pathway to carcinogenic pathway

human data are available genetic polymorphisms in human

populations can be factored into the assessment

PBPK models extrapolating from animal to humans are available