systems-adme/tox: resources and network approacheserdi/ekins2.pdf · development of ht methods,...

wwwelseviercomlocatejpharmtox

Journal of Pharmacological and Toxicol

Appraisal of state-of-the art

Systems-ADMETox Resources and network approaches

Sean Ekins

GeneGo 500 Renaissance Drive Suite 106 St Joseph MI 49085 USA

School of Pharmacy Department of Pharmaceutical Sciences University of Maryland USA

Received 23 May 2005 accepted 23 May 2005

Abstract

The increasing cost of drug development is partially due to our failure to identify undesirable compounds at an early enough stage of

development The application of higher throughput screening methods have resulted in the generation of very large datasets from cells in

vitro or from in vivo experiments following the treatment with drugs or known toxins In recent years the development of systems biology

databases and pathway software has enabled the analysis of the high-throughput data in the context of the whole cell One of the latest

technology paradigms to be applied alongside the existing in vitro and computational models for absorption distribution metabolism

excretion and toxicology (ADMETox) involves the integration of complex multidimensional datasets termed toxicogenomics The goal is to

provide a more complete understanding of the effects a molecule might have on the entire biological system However due to the sheer

complexity of this data it may be necessary to apply one or more different types of computational approaches that have as yet not been fully

utilized in this field

The present review describes the data generated currently and introduces computational approaches as a component of ADMETox These

methods include network algorithms and manually curated databases of interactions that have been separately classified under systems

biology methods The integration of these disparate tools will result in systems-ADMETox and it is important to understand exactly what

data resources and technologies are available and applicable Examples of networks derived with important drug transporters and drug

metabolizing enzymes are provided to demonstrate the network technologies

D 2005 Elsevier Inc All rights reserved

Keywords Algorithms Human Microarray Mouse Networks Rat Software Toxicogenomics Toxicoproteomics

1 Introduction

Metabolism and safety assessment have witnessed some

growth in the number of new technologies and methods

that have been introduced within the last decade However

according to a recent FDA white paper there is still

considerable scope for additional new methods (FDA

2004) For example recently various reports have

described new software and methods for metabolism

prediction (Balakin et al 2004a 2004b Borodina et al

2003 Borodina et al 2004 Boyer amp Zamora 2002

Korolev et al 2003) Simultaneously the use of high

throughput (HT) methods for genomics proteomics and

metabonomics have taken off in terms of their acceptance

1056-8719$ - see front matter D 2005 Elsevier Inc All rights reserved

doi101016jvascn200505005

Corresponding author Tel +1 269 930 0974 fax +1 269 983 7654

E-mail addresses seangenegocom ekinsseanyahoocom

in the industry as they have been evaluated primarily for

toxicology and metabolism assessment (Waring et al

2003 2002 2001) with some considerable focus on

hepatotoxicity (Harris Dial amp Casciano 2004 Hartley

et al 2004 Heijne et al 2004 Huang et al 2004

Liguori et al 2005 Ulrich Rockett Gibson amp Pettit

2004) For example searching PubMed for publications in

the last 5 years with the keywords Fmicroarray and

toxicology_ or Ftoxicogenomics_ indicates that the accu-

mulation of papers describing the latter is doubling every

year (Fig 1) which perhaps is mirrored by the application

in the pharmaceutical industry for predictive toxicology

(Suter Babiss amp Wheeldon 2004)

To date toxicogenomics experiments have been carried

out under non-standardized conditions Most of the studies

have been conducted with rats less often mice using

multiple different microarray formats and statistical proce-

ogical Methods 53 (2006) 38 ndash 66

0

20

40

60

80

100

2000 2001 2002 2003 2004 2005Year

Pu

bM

edN

um

ber

of

pu

blic

atio

ns

in

Fig 1 Annual frequency of articles appearing with the words lsquolsquotoxicoge-

nomicsrsquorsquo (squares) or lsquolsquomicroarray and toxicologyrsquorsquo (diamonds)

S Ekins Journal of Pharmacological and Toxicological Methods 53 (2006) 38ndash66 39

dures (Tables 1-4) There have been relatively few cross-

platform toxicogenomics studies under controlled condi-

tions (Thompson et al 2004) Despite the suggested poor

compatibility between the different array types this latter

study demonstrated a high (90) consistency between the

expression of the genes that were shared between the

platforms The development of methods to visualize such

complex expression data has also expanded beyond the

widely used clustering methods (Eisen Spellman Brown amp

Botstein 1998) With the outcome of microarray analysis

being dependent on the widely used statistical procedures

applied to derive those genes that are significantly differ-

entially expressed (Butte 2002) newer approaches that do

not necessarily require data clustering may be an advantage

As rat and mouse are the most widely used in vivo toxicity

models it is assumed that acute and chronic toxicity shown

in animals largely coincides with human toxicity Therefore

differential expression patterns in animal models are also

assumed to be predictive of the end point toxic response in

human This is not always the case due to differences

between human and rodent physiology genetics metabo-

lism and signaling pathways For example the mechanism

of toxicity for pyrazinamide has been reconstructed

(Bugrim Nikolskaya amp Nikolsky 2004) to illustrate that

the accumulation of uric acid occurs in human but not in

mice and this results in toxicity in the former The relatively

poor understanding of such species differences may be

reflected in the relatively large number of late stage

molecules that have undergone in vivo toxicity assessment

yet have been later withdrawn due to adverse events in

humans

In recent years the appearance of systems biology which

uses the relationships of all elements of biology rather than

approaching them separately has been evident and will

likely reunite biological fields (Harrison 2004 Hood amp

Galas 2003) These systems approaches are the latest

incarnation of the importance of the Fparts vs wholes_debate (Ekins amp McGowan 2001) and interpreting ADME

Tox in this context may improve our understanding and

ultimate predictions (Bugrim et al 2004 Ekins Boulanger

Swaan amp Hupcey 2002a Kitano 2002a Werner 2003)

The perturbing effect of a molecule on the complete

biological system can be observed across all metabolic

and signaling pathways or networks and can provide some

limited insight into the binding to multiple proteins or

effects on gene expression simultaneously This requires the

collection of high-throughput data including global gene

expression protein content metabolic profiles for the same

samples as well as individual genetic clinical and pheno-

typic data However there are difficulties with such an

approach as there are likely to be differences between the

Fstimulus to effect_ durations for all the genendashprotein

relationships (Nicholson Holmes Lindon amp Wilson

2004)

We can now use either the growing number of academic

or commercially available pathway database and network

building tools with expression data These enable the

connection of interacting differentially expressed genes as

networks (Barabasi amp Oltvai 2004 Hanisch Zien Zimmer

amp Lengauer 2002 Ideker Ozier Schwikowski amp Siegal

2002 Ideker et al 2001 Segal et al 2003a Segal Wang amp

Koller 2003b Spirin amp Mirny 2003 Tornow amp Mewes

2003) as well as allowing the reverse engineering of

functional connections (Somogyi Fuhrman amp Wen 2001)

The use of such network visualizations suggests an

organized modularity in complex systems (Han et al

2004) which has also been applied to interpret the

connectivity of small molecules and their interaction with

proteins in the subfield of chemogenomics (Bredel amp Jacoby

2004 Csermely Agoston amp Pongor 2005 Parsons et al

2004 Sharom Bellows amp Tyers 2004) The parallel

development of HT methods databases ADMETox model-

ing and systems modeling is ongoing (Ekins Nikolsky amp

Nikolskaya 2005e) The present review is therefore timely

as it discusses some of the data resources limitations and

technologies that are available for Systems-ADMETox

(Fig 2) along with some illustration of their applications to

drug metabolism and drug transport which are key com-

ponents of the ADMETox process The ultimate aim of

this discussion is to provide awareness of an integrated

approach rather than a technology silo mentality represent-

ing the latest proposed research model in the field (Fig 2)

2 Data available

A recently published book provides an excellent over-

view of toxicogenomics and the reader is referred to this to

gain more insight into the applications and limitations

(Hamadeh amp Afshari 2004) The growing number of

toxicogenomic datasets derived from in vivo studies with

rat (Table 1) and mouse (Table 2) as well as in vitro cell

derived data (Table 3) highlights the different strains

microarray types and compounds that are routinely assessed

Also there are numerous instances of multiple groups testing

the same compound at similar or different doses eg well

known hepatotoxicants or nephrotoxicants such as clofibrate

Table 1

Literature toxicogenomics data derived from rat in vivo studies

Compounds Rat strain Microarray type Compound dose Microarray data

availability

Reference

Acetaminophen furan

methotrexate

methapyrilene

phenytoin

Male Spraguendash

Dawley VAF+

albino

Phase 1 Molecular

toxicology array

Acetaminophen

(4500 mgkgday)

methotrexate (1 mg

kg day)

methapyrilene (100

mgkgday) furan (40

mgkgday) or

phenytoin (300 mg

kgday)

Gene name accession

number and fold changes

are provided in a

manuscript table

(Huang et al

2004)

A-277249 3MC

Aroclor

SpraguendashDawley Affymetrix rat

toxicology U34 array

10 or 100 mgkg Gene name and

Affymetrix ID and fold

change in a manuscript

table

(Waring et al

2002)

Clofibrate paracetamol

benzoapyrene

Male Spraguendash

Dawley

Custom chip CLO at 250 mgkg

BP at 10 mgkg bw

given 3 times per

week for 2 weeks

APAP at 1000 mgkg

Gene name and fold


table

(Cunningham

Liang Fuhrman

Seilhamer amp

Somogyi 2000)

L-742694

Dexamethasone

Female

SpraguendashDawley

25K rat microarray L-742694 (50 mgkg

day) DEX (50 mg

kgday)

Tables of accession

number and gene names

only in a manuscript

table for liver and

intestine

(Hartley et al

2004)

Bromobenzene Male Wistar Custom 3000 rat gene

array

05 2 5 mmolkg Gene name accession

number and log fold

change for 3 dose levels

in a manuscript table

Supplemental data also

available

(Heijne et al

2004)

125-Dihydroxyvitamin

D3

Male Spraguendash

Dawley (small

intestine)

Affymetrix high-density

rat oligonucleotide

arrays (GeneChips

RG-U34A)

730 ngkg Gene name Genbank

accession number and

fold change in a

manuscript table

(Kutuzova amp

Deluca 2004)

Fenofibrate clofibrate

bezafibrate

gemfibrozi

ciprofibrate

beclofibrate etofibrate

Male CD Agilent arrays Dose ranging for up

to 14 days

Gene name and genbank

accession number in a

manuscript table

(Cornwell Souza

amp Ulrich 2004)

Furan Male Spraguendash

Dawley

NIEHS rat chip uml7000

clones

Exposed to 4 or 40

mgkg furan for up

to 14 days

Gene ID and gene

namemdashbinary data in a

manuscript table Dataset

also available on NIEHS

website

(Hamadeh et al

2004)

Paracetamol Male F344N Rat NIEHS tox chip

(httpdirniehsnihgov

microarraychipshtm)

0 50 150

1500 mgkg

Unigene accession

number gene name fold


table

(Heinloth et al

2004)

Carbon tetrachloride Male Spraguendash

Dawley

ADME Rat expression

bioarray (Motorola Life

Sciences) consists of

1040 single-stranded

oligonucleotide probes

Up to 14 day

treatment

Accession numbers and

binary data in a

manuscript table

(Young et al

2003)

Carbon tetrachloride and

chloroform

Male Spraguendash

Dawley

The rat CT arrays

contain sequences from

almost 700 rat genes

with known or

discovered

responsiveness to toxic

treatments

6 24 72 h high and

low doses

Gene names and fold

changes at multiple time

points in a manuscript

table

(Kier et al 2004)

(continued on next page)

S Ekins Journal of Pharmacological and Toxicological Methods 53 (2006) 38ndash6640

Table 1 (continued)


availability

Reference

Dimethylarsinic acid Female F344

(bladder

epithelium)

Rat 10K chip (MWG

Biotech Inc) containing

10000 genes

100 ppm Genbank accession

number gene name in a

manuscript table

(Wei Arnold

Cano amp Cohen

2005)

Dexamethasone

troleandomycin

miconazole

clotrimazole

isoniazid

methylclofanapate

Female Spraguendash

Dawley

Rat HepatoChip DEX (50 mgkgday)

TAO (500 mgkg

day) MIC (100 mg

kgday) CLOT (100

mgkg per day) ISN

(100 mgkgday)

MCP (75 mgkgday)

Gene name and Genbank

accession numbermdashdata

displayed as a heatmap

not readily extracted

from publication

(Meneses-Lorente

et al 2003)

TCDD PeCDF PCB126

PCB153

Female Harlan

SpraguendashDawley

Affymetrix GeneChip

Test3 arrays

Exposed for 13 weeks

to toxicologically

equivalent doses

Accession number gene

name and fold change in

a manuscript table

(Vezina Walker

amp Olson 2004)

Paclitaxel Male and female

SpraguendashDawley

Genocheck 48K cDNA 4 mgkgday male

7 mgkgday female


gene names in a

manuscript table

(Lee et al 2004)

Clofibrate gemfibrozil

phenytoin

Male Spraguendash

Dawley VAF(+)

albino

48 K cDNA microarray

in house

Treated with each

compound for 24 h

and 2 weeks

Gene name and fold


table

(Jung et al 2004)

Clofibrate

dexamethasone

phenobarbital

3-methylcholanthrene

SpraguendashDawley Merck Drug Safety Chip

1443 genes (rat human

and mouse)

30 mgkgday Gene name GenBank


relative fluorescence

levels in a manuscript

table

(Gerhold et al

2001)

Bemitradine clofibrate

doxylamine

methapyrilene

phenobarbital

tamoxifen

2-acetylaminofluorene


isoniazid

Male CD IGS Incyte RatGEM10

uml7800 rat cDNAs

Low mid and high

doses

A bar chart of 2 genes

that are affected by

compounds

(Kramer et al

2004)

PhIP Female Spraguendash

Dawley

Mouse cDNA

microarray containing

9984 cDNA clones

(National Cancer

Institute

75 mgkgday Gene names in a

manuscript table

(Shan Yu Schut

amp Snyderwine

2004)

Ethinylestradiol Male and female

SpraguendashDawley

Custom chip 3776 genes 0 001 01 and

10 ppm


name and fold change at

different exposure levels


(Kato et al 2004)

Paraquat Male Wistar 1090 genes 7 mgkgday Gene name and

expression ratio in a

manuscript table

(Satomi et al

2004)

Hexachlorobenzene Female Brown

Norway

Affymetrix rat

RGU-34A GeneChip

microarray

0 150 or 450 mgkg Accession number gene

name and fold change

data for multiple organs


(Ezendam et al

2004)

N-methyl-NV-nitro-N-nitrosoguanidine

(MNNG)

Rat pyloric muco-

sae male congenic

rat strain that has a

homozygous_LIZ

transgene of

BigBlue rat

AFFYMETRIX Rat

Genome U34A

83 mgl AFFY ID gene name

gene symbol and fold


table

(Yamashita et al

2004)


Male ACINJcI

(ACI)

Affymetrix GeneChip

Rat genome U34A

arrays

83 mgl from the age

of 8 weeks through to

40 weeks


name symbol fold change

in a manuscript table also

rat vs human stomach

cancer comparison

(Abe et al 2003)

Cisplatin SpraguendashDawley Different arrays tox

chip incyte phase 1 etc

03ndash5 mgkg over a 4 to

144 h

Unigene gene ID gene

name NIEHS ID and

data for 5 platforms in a

manuscript table

(Thompson et al

2004)


Table 1 (continued)


availability

Reference

Clofibrate Male Spraguendash

Dawley

Atlas Rat Toxicology II

arrays (Clontech Palo

Alto CA USA)

containing 465 genes

High (250 mgkgday) or

low (25 mgkgday)

Genbank accession

number and data for 3

platforms in a

manuscript table

(Baker et al

2004)

Di(2-ethylhexyl)

phthalate

Male Spraguendash

Dawleymdash(testes)

An in-house cDNA

microarray

20 or 2000 mgkg Gene names Genbank

ID and fold change in a

manuscript table

(Kijima et al

2004)

Ciprofibrate Female Fischer An in-house cDNA

microarray

50 mgkg body weight Gene names symbol

accession number mean

ratio and SD

(Yadetie et al

2003)

Methapyrilene Male Spraguendash

Dawley

Rat Tox Chip 10 10 or 100 mgkgday Gene Name accession

number and indication of

up or down regulation

original data available on

NIEHS website

(Hamadeh et al

2002b)

Ecteinascidin-743

(ET-743)

Female Wistar Custom chip cDNA

microarrays containing

approximately 4700

hybridizable mouse

expressed sequence tags

derived from IMAGE

clones obtained from

Research Genetics

(Huntsville AL) or from

the MRC Human Gene

Mapping Project

40 ugkg Data available on

laboratory websitemdashnot

available at present

(Donald et al

2002)

Clofibrate Wyeth

14643 Gemfibrozil

phenobarbital

Male Spraguendash

Dawley VAF+

NIEHS rat chip v10 Clofibrate (250

mgkgday Wyeth

14643 (250 mgkg

day) Gemfibrozil

(100 mgkgday)

Phenobarbital

(120 mgkgday)

Gene names and fold

changes in a manuscript

table

(Hamadeh et al

2002a)

Vinclozin procymidone Male Spraguendash

Dawleymdashprostate

Clontech Atlas Rat 12

Toxicology array

200 mgkg Gene name accession

number average fold

change

(Rosen Wilson

Schmid amp Gray

2005)

Cisplatin Male Spraguendash

Dawley VAF1

albino (CRL

CD(SD) BR

Rat Tox Microarrays

were purchased from

Phase-1 Molecular

Toxicology

05 or 1 mgkgday Gene name accession

number fold change in

kidney

(Huang et al

2001)

Allyl alcohol

miodarone Aroclor

1254 arsenic

carbamazepine

carbon tetrachloride

diethylnitrosamine

dimethylformamide

diquat etoposide

indomethacin

methapyrilene

methotrexate

monocrotaline


Male Spraguendash

Dawley

Affymetrix GeneChip

Test 2 Array

Allyl alcohol (40 mgkg

day) miodarone (100 mg

kgday) Aroclor 1254

(400 mgkgday) arsenic

(20 mgkgday)

carbamazepine (250 mg

kgday) carbon

tetrachloride (1000mgkg

day) diethylnitrosamine

(100 mgkgday)

dimethylformamide (1000

mgkgday) diquat (172

mgkgday) etoposide (50

mgkgday) indomethacin

(20 mgkgday)

methapyrilene (250 mg

kgday) methotrexate

(250 mgkgday)

monocrotaline (50 mgkg

day)


(100 mgkgday)

Heatmap figures and a

table of Affymetrix

names for genes

correlated with clinical

chemistry changes in a

manuscript table

(Waring et al

2001)



Table 1 (continued)


availability

Reference

Microcystin-LR (MLR)

phenobarbital (PB)

lipopolysaccharide

(LPS) carbon

tetrachloride (CT)

thioacetamide (THA)

and cyproterone

acetate (CPA)

Male Wistar Purpose-made rat DNA

microarray (Affymetrix

Santa Clara CA)

containing 1600 rat

DNA sequences

Various Accession number gene

name fold changes

shown as a heat map

table in publicationmdash

data extraction would be

laborious

(Bulera et al

2001)

Acetamidofluorene

aniline bromobenzene

butyl hydroxytol

dieldrin disulfiram

ethinyl estradiol

hexachlorocyclohexane

g 4-methylthiazole

nimesulide piperonyl

butoxide precocene I

pulegone tannic acid

trans-anethole

Male Spraguendash

Dawley

Custom Rat MegaA

cDNA chip 3434-gene

Acetamidofluorene (200

mgkg) aniline (200 mg

kg) bromobenzene (900

mgkg) butyl hydroxytol

(1000 mgkg) dieldrin

(30 and 45 mgkg)

disulfiram (2000 mgkg)

ethinyl estradiol (500

mgkg)


gamma (40 65 80 mg

kg) 4-methylthiazole

(120 mgkg) nimesulide

(500 mgkg) piperonyl

butoxide (4000 mgkg)

precocene I (500 mgkg)

pulegone (400 mgkg)

tannic acid (3000 mg

kg) trans-anethole

(600 mgkg)

Gene name accession

number in a manuscript

table

(McMillian et al

2004)

NIEHS website at httpdirniehsnihgovmicroarraydatasetshome-pubhtm

EDGE website at httpedgeoncologywiscedu


and cisplatin (Table 1) In the majority of cases the resulting

number of differentially expressed genes is a very small

subset of the starting number on the microarray following

clustering or other types of analysis Upon closer examina-

tion of these publications the majority of them either

provide images of a heat map andor a table listing a gene

name accession number and expression change Very few of

the published studies (Tables 1ndash3) provide the original raw

microarray data file at a freely accessible website hence

restricting further analysis by scientists using other software

Although in some cases it is possible to cut and paste the

gene expression data tables from the publication pdf files

this is not always the case In the worst case scenario one

would have to manually retype gene lists or extract them

from heatmaps as binary type data As not all computational

researchers will have a laboratory available to them to

generate such quantities of toxicogenomics data the latter

points are important if we are going to continue to see

innovation in software development for this data This will

require free unrestricted access to data published Similarly

if we are to discern lsquolsquofingerprintsrsquorsquo for molecules acting with

a similar or identical mechanism we will need databases of

many diverse chemical structures that have been tested in a

similar manner There is therefore considerable interest in

the current databases being developed by the NIEHS FDA

and other groups which should help to improve the situation

by providing freely accessible microarray and other toxicity

related data Two of these databases being developed in the

public domain are Chemical Effects in Biological Systems

(CEBS) (httpwwwniehsnihgovnctcebshtm) (Mattes

Pettit Sansone Bushel amp Waters 2004 Waters et al

2003) which will accommodate gene expression profiles

proteomics and metabolomics data and allow complex

queries (Hood 2003a Mattes et al 2004) Similar goals

are being pursued in the development of the ArrayTrack

database at the FDA (Tong et al 2003) The EDGE

database (httpedgeoncologywisceduedgephp) an

expanding public effort at The University of Wisconsin

contains mouse gene expression profiles following treat-

ment with different toxic molecules (Hayes et al 2005

Thomas et al 2001) These separate efforts if widely

adopted should make published studies describing HT data

more readily accessible although it might have been more

efficient to evolve these into a single global database instead

of fragmented repositories

Proteomics data has also been generated in a limited

number of toxicology studies (Table 4) once again this has

been produced with different strains of rats and mice using

different protein chips 2-D gel electrophoresis (2-DIGE)

and mass spectroscopy methods (eg MALDI-MS) The

proteomic data is very rarely accessible to the reader for

their own computational analysis Subsequently there have

Table 2

Literature toxicogenomics data derived from mouse in vivo studies

Compounds Mouse strain Microarray type Compound dose Microarray data

availability

Reference

Benzene Male and female P53

KO mice and

C57BL6

Affymetrix and Incyte

GEM system

300 ppm 6 h per day 5

days a week for 2 weeks

Gene name accession

number and fold change

data in a manuscript

table

(Yoon et al 2003)

Benzene Male 129SvJ Affymetrix MG-U74Av2 100 ppm 6 h per day 5


Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)

Phenobarbital CAR and wild type NIEHS Mouse tox chip

8736 genes

100 mgkg for 12 h Accession number gene


for wild type and knock

out mice in a manuscript

table

(Ueda et al 2002)

Aroclor BNF

ciprofloxacin cobalt

chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463

C57BL6J Custom array with 1200

cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)

ciprofloxacin (250 mg

kg) cobalt chloride (60

mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)

phenobarbital (100 mg

kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold

change as a heat map

Data is also available in

the EDGE database

(Thomas et al

2001)

TCPOBOP CD-1 female Custom 9000 cDNA

mouse array

1ndash3 h treatment 3 mg

kg body wt


fold change data in a

manuscript table

(Locker et al

2003)

3H-12-dithiole-3-thione

(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip

05 mmolkg Accession number gene

name fold in a

manuscript table

(Kwak et al

2003)

MDMA Male albino Swissndash

Webster (neurons)

15 K mouse cDNA clone

set

47 mgkg Gene name and fold


table

(Xie et al 2004)

Phenytoin Female C57BL6 and

LDLRMurine genome-U74Av2 300 mgl Gene name accession



(Trocho et al

2004)

Genistein (1000 Agmouseday) or

diethylstilbestrol

(DES) (50 Agmouse

day)

ICR (testes) Custom cDNA


1754 cDNA probes

Genistein (1000 Agmouseday)

diethylstilbestrol (50 Agmouseday)



a manuscript tablemdashnote

very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine

Male ICR Mouse DiscoveryArrayi

type I array containing

2688brain-derivedprobes

(Display Systems Biotech

Inc Copenhagen

Denmark)

40 mg kgmdash1 cocaine

once a day for 4 days 40

mg kgmdash1 cocaine plus

025 mg kgmdash1 BUP for

4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)

Methamphetamine Male C57BLJ6

(striatum)

Affymetrix mouse

genechip mg-U74Av2

oligonucleotides arrays

12 488 genes

40 mgkg Gene accession number

gene ID and name and

signal log ratio in a

manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate

Male C57BL6 Murine genome U74Av2

Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession

numbers gene name log

ratio data present as a bar

chart in the publication

data extraction would

take some effort

(Wong amp Gill

2002)

Diethylhexylphthalate Male PPARa null and

wild type

Custom made containing

600 tox genes

1150 mgkgday Gene names available on

a bar chartmdashquantitative

data not easily accessible

(Hasmall et al

2002)


Table 2 (continued)


availability

Reference

Acetaminophen C57B16 3 129Ola

hybrid

Test-2 Chips (Affymetrix)

then individual

oligonucleotide

microarrays (Mul1K sub

A and sub B Affymetrix)

that can detect the

expression of 11000

known genes and


(ESTs)

300 mgkg Genbank or SwissProt

ID and fold change data


(Reilly et al

2001)

Cadmium chloride

benzo(a)pyrene (BaP)

and trichloroethylene

(TCE)

Male Swiss Webster Custom Chips

containing 148 unique

genes

Various Data in table form few

genes affected for BAP

and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)


been only a very small number of studies that have

combined both transcriptomic and proteomic methods with

a single animal strain after treatment with a drug Hopefully

we will see this change in the future but this will in turn

present considerable challenges as huge amounts of

proteomic data are combined with the equally large

transcript data files

3 Network analysis and databases

From some of the early reviews of systems biology there

has been discussion of its application to drug discovery

(Kitano 2002ab) as well as the utility for ADMETox

(Ekins et al 2002a 2000b) More recently several other

journals have dedicated whole issues to the field of systems

biology However one could consider this quite a broad field

from network or pathway analysis to quantitative simulation

of organelles (Vo Greenberg amp Palsson 2004) whole cells

and organs It is apparent that we are now understanding

organisms from the perspective of computationally gener-

ated networks of protein and ligand interactions (Barabasi amp

Oltvai 2004) Network and pathway tools enable the

analysis of HT data in the context of all known interactions

when using a database as the source Individual reviews

have in some cases indicated that networks will be valuable

for understanding adverse events (Hood amp Perlmutter

2004) drug target identification or validation (Butcher

Berg amp Kunkel 2004) and complex metabolic interactions

(Nicholson et al 2004) A general schematic has been

generated in order to provide a description of the utilization

of such pathway databases and network building algorithms

from the initial parsing of high throughput data to network

comparisons and visualization (Fig 3) High throughput

data can be superimposed and visualized on the various

protein interaction databases available This is accomplished

by using either preset maps that capture current biological

knowledge or by building custom interaction networks

using many different algorithms which can be compared and

statistically evaluated as demonstrated in a very large

number of published examples (Dobrin Beg Karabasi amp

Oltvai 2004 Fiehn 2001 Han et al 2004 Hanisch et al

2002 Ideker et al 2002 Jeong Mason Barabasi amp Oltvai

2001 Jeong Tombor Albert Oltvai amp Barabasi 2000 Li

et al 2004 Milo et al 2002 Nikitin Egorov Daraselia amp

Mazo 2003 Pereira-Leal Enright amp Ouzounis 2004

Rives amp Galitski 2003 Segal et al 2003a Somogyi et al

2001 Spirin amp Mirny 2003 Tornow amp Mewes 2003

Vasquez Flammini Maritan amp Vespignani 2003 Yeger-

Lotem amp Margalit 2003 Yu Zhu Greenbaum Karro amp

Gerstein 2004)

31 Network applications

For example one group has used as an inference the

Bayesian network method for analysis of tissue toxicity from

microarray data as well as a mechanistic simulation for a

different pharmaceutically relevant molecule (Aksenov et

al 2005) Pathway tools and various resources have also

been applied to modeling the networks of nuclear hormone

receptors and their connections with other genes and small

molecules using a manually curated database MetaDrug

(Ekins Kirillov Rakmatulin amp Nikolskaya 2005d) or

MetaCore (Ekins Bugrim Nikolsky amp Nikolskaya 2005)

Transcriptional regulation of many transporters CYPs and

phase II enzymes are regulated by these receptors affecting

endogenous molecule transport metabolism cell growth

proliferation and oxidative stress (Ulrich 2003 Ulrich et al

2004) When the signaling networks and interacting ligands

for the transcriptional factors PPAR FXRRXRA ESR1

AHR HNF4A GCR-h MCR CAR-beta GCR-a LXR-a

CARRXR HNF4 FXR PXRRXR heterodimer PXR

AHRARNT heterodimer PPARaLXRa VDR PPAR-a

are visualized a very complex picture of interactions can be

created (Ekins et al 2005d) This suggests that when we

consider a molecule binding with only one nuclear receptor

we are observing only a fraction of the likely possible

feasible interactions based on the data gathered to date

Table 3

Literature toxicogenomics data derived from in vitro cell studies

Compounds Cell type Microarray type Compound dose Microarray data

availability

Reference

4-Hydroxytamoxifen

estrogen

MCF-7 breast cancer NIEHS ToxChip

microarray consisting of

1901 genes

1 uM hydroxytamoxifen

for a year 10 nM

17b-estradiol

Data available at NIEHS

website

(Hodges et al

2003)

Trovafloxacin Human hepatocytes Affymetrix U133A array 30ndash800 uM 142 genes available in

supplemental tablemdashnot

easily extracted

(Liguori et al

2005)

Estrogen MCF-7 breast cancer NIEHS ToxChip


1901 genes

10ndash10 M 17b-estradiol Data available at NIEHS

website

(Lobenhofer et al

2002)

Valproic acid NMRI mice embryo

and P19 mouse

embryocarcinoma

Custom chip including

15K mouse cDNA clone

set

600 mgkg body weight Gene symbol gene

name NIA EST log fold


table

(Kultima et al

2004)

Sulindac sulfide Human colorectal

carcinoma SW-480

and HCT-116

NIEHS human 12K chip 10 uM Genbank accession

number gene name and

fold change at various

time points in a

manuscript table data


website

(Bottone

Martinez Collins

Afshari amp Eling

2003)

17Beta-estradiol estriol

estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor

MCF-7 U95A oligonucleotide

probe arrays (Affymetrix

10 nM (E2 estriol

estrone DES) 10 AM(genistein bisphenol A

nonylphenol and

methoxychlor)

Unigene name gene


for estrogen responsive

and nonresponsive in a

manuscript table

(Terasaka et al

2004)

Ouabain lauryl sulfate

dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide

HepG2 Clontech Atlas Human

Stress Toxicology cDNA

arrays (234 genes)

Ouabain (43 uM) lauryl

sulfate (260 uM)

dimethylsulfoxide (128

M) cycloheximide (625

uM) tolbutamide (128

mM) sodium fluoride (3

mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)

potassium bromate (25

mM) sodium selenite (30

uM) alloxan (130 mM)

adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -

value in downloadable

tables at journal website

(Morgan et a l

2002)

Aflatoxin B(1) (AFB(1))


(2AAF)

dimethylnitrosamine

(DMN)

acetaminophen (APAP)

HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a

microtubule inhibitor

and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2

(Affymetrix Inc Santa

Clara CA) for all the

other chemicals a total

of 9977 probe sets

(genes or ESTs) common

to these two array

models

Low mid and high doses Accession number gene

name gene ID statistical

significance at each time

point in a manuscript

table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma

The Twin - Chip Mouse-

74K Digital Genomics

cDNA microarray

10 ngml paclitaxel 313

ugml hydroxyurea 32

ugml p-anisidine

Gene symbol and fold


table

(Lee et al 2003)

Acetaminophen

amiodarone clofibrate

erythromycin estolate

isoniazid alpha-

naphtylylisothiocyanate

beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)

A single concentration

which varied for each

compound


gene namemdashfold

changes shown as

colored heat mapmdashnote

easily extracted from

publication

(de Longueville

et al 2003)

Bleomycin and hydrogen

peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K

cDNA microarray (1185

genes)

Bleomycin (25 and 20

ugml) hydrogen peroxide

(5 and 10 ugml)

Gene names and fold

change presented as bar

charts in publication

(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin

HL-60 Agilent human cDNA

microarray

1 mM Gene name GenBank

accession number

unigene and ratio in a

manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)

Bisphenol A Mouse Sertoli TTE3 IntelliGene mouse

expression glass

microarrays (Version

10 Takara Shuzo)

which were spotted with

564 cDNA fragments of

mouse known genes and

approximately 301


(ESTs)

0ndash400 uM Gene name GenBank


fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin

Hep G2 85 human gene custom

array

10 um mitomycin C

2 um doxorubicin or

2 ethanol

Bar charts with fold

changes in publication

very few genes

(Hong Muller amp

Lai 2003)

Amphotericin B Human peripheral

blood mononuclear

and THP-1

GF211 FKnown Genes_

Genefilter cDNA array

(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene

5 ugml Accession numbers and

fold expression in a

manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid

Human-350 microarray

a glass slide with 350

spotted human cDNA

probes (Phase-1

Molecular Toxicology

0 001 010 or

10 ugml)

Gene names and fold

change at doses in a

manuscript table

(Akerman et al

2004)

Etomoxir HepG2 Clontech AtlasiHuman Stress

Toxicology cDNA arrays

(234 genes)

1 mM etomoxir Gene names and fold


table

(Merrill et al

2002)

Tetrodotoxin Human glioma cell

line HTB-138

Using Affymetrix

GeneChip (HG-U133A

10 and 20 mM Affymetrix ID Genbank

ID gene name gene

symbol and fold change


(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia

Affymetrix U133A chip Low and high dose and

combination

Data available as

supplemental data online

(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia

Affymetrix U133A chip Various Data available as


(Holleman et al

2004)



A second study has indicated how a natural language

processing method CCNet was used to show the genes

regulated by the nuclear hormone receptor FXR (Apic

Ignjatovic Boyer amp Russell 2005) These automated

methods enable a more complete understanding of the

complexity of the transcriptional factors (Ekins Mirny amp

Schueltz 2002b Plant 2004 Ulrich 2003) but ultimately

rely on the quality of the content of the underlying database

of literature interactions This is a key consideration that is

often overlooked For example the gold standard database is

one that is manually curated to ensure the fidelity of the

direct interaction and is preferable to one generated

computationally by algorithms like natural language pro-

cessing (Nikolsky Nikolskaya amp Bugrim 2005) The

advantage of interaction networks over clustering has been

demonstrated in one study using MetaCore (Nikolsky

Ekins Nikolskaya amp Bugrim 2005) by reanalysis of a

published microarray study of G0-arrested MCF-7 breast

cancer cells treated with estrogen and 4-hydroxytamoxifen

(Hodges et al 2003) After producing integrated gene

networks for each treatment strikingly different patterns

were displayed although both contained early transcriptional

factors myc jun and fos Only the estrogen network featured

induced genes essential for all cell cycle phases (Nikolsky et

al 2005) Similarly microarray data for benzene toxicity

(Yoon et al 2003) has been re-analyzed by focusing on the

genes assessed on the p53 pathway (Ekins et al 2005e) We

envisage that a database of such networks for toxic

compounds will be used for comparing between different

molecules and used in the development of predictive

algorithms for Systems-ADMETox modeling in future

Another approach to using such pathway approaches is to

visualize the results of quantitative structure activity models

for predicting molecules binding to enzymes transporters

receptors and ion channels (Ekins Andreyev et al in press

2005e)

It is also possible to simultaneously interpret high

throughput data and predictions on interaction networks

providing a novel approach to predicting and understanding

potential undesirable drugndashdrug or off target effects in the

area of systems pharmacology An example data set uses

percent inhibition data for clotrimazole and ticonazole

which were screened against many different assays at a

single concentration in a commercially available database

BioPrint (Cerep Redmond WA) as published recently

(Fliri Loging Thadejo amp VOlkman 2005) The data for

10 assays has been arbitrarily encoded as inhibitors (gt50

inhibition) or non-inhibitors (lt50 inhibition) in a text file

which was then loaded into MetaCore The analyzed

network algorithm was then used which generates a large

network and fragments it into sub-networks each with a Z-

score and p-values for ranking according to saturation with

objects from the initial gene list The Gene-ontology

processes are also mapped to the gene list and individual

networks In this example a statistically significant network

was generated for the different proteins (Fig 4

p =2838e31) This network also maps the Gene Ontology

processes for the activation of MAPK (118 of genes p

value 9143e07) signal transduction (333 1600e05)

regulation of transcription DNA-dependent (294

2786e04) regulation of inflammatory response (39

3746e04) and the regulation of blood pressure (78

4230e04) This example network indicates how molecules

of the same or different therapeutic classes could be

evaluated for their effects as a graph either together as in

this case or individually This would be useful to indicate

potential off target effects and identify structurally dissimilar

molecules with similar network patterns Such networks

could then be compared to assess network overlap or

differences between molecules and their inhibition of

multiple proteins This type of unique visualization of high

throughput screening data illustrates how the target proteins

may be connected as a network to infer the possible

downstream effects of inhibition

With the burgeoning number of freely available online

and commercial databases that can be used for pathway

construction numbering in the hundreds there have been

suggestions to impose standards for model exchange

querying and visualization (Cary Bader amp Sander 2005)

To date there has been little discussion with regards to

standardization of ADMETox related databases although

there has been considerable discussion relating to drug

metabolism database generation (Erhardt 2003) This is

certainly an important area to address in the future There is

already a growing literature related to ADMETox that is

partially captured in the several commercially available

databases (Ekins et al 2005e) but to date there have been

limited academic efforts to capture data for transporters

with the human membrane transporter database (Yan amp

Sadee 2000) TP-search transporter database (httpwww

ilabrisewasedaacjptp-search) drug interaction database

(httpwwwdruginteractioninfoorgDatabaseinfoaspx)

nuclear hormone receptors (Nakata Yukawa Komiyama

Nakano amp Kaminuma 2002) the ADME-AP database

(Sun Ji Chen Wang amp Chen 2002) and PharmaGKB

(Oliver et al 2002) DSStox (httpwwwepagovnheert

dsstox) TOXNET (httptoxnetnimnihgov) that are

readily accessible

In order to generate accessible pathways using any of

the available software a large enough set of object

identifiers are required to map onto the underlying data-

base To demonstrate this datasets from toxicogenomics

studies have been evaluated with both the KEGG pathway

database and a commercially available product MetaCore

(wwwgenegocom) These gene or protein lists range in

size from 21 to 1853 objects In virtually all cases more

identifiers are mapped to networks in MetaCore and this

also seems independent of the identifier type used

(Unigene Affymetrix Genbank or Locuslink Table 5)

These numbers will obviously change as more information

is added to the respective databases hence the more

objects that are mapped from a dataset The more extensive

Table 4

Literature derived toxicoproteomics data

Compounds Data source Microarray type Compound dose Microarray data

availability

Reference

Carbon

tetrachloride

Male Wistar rats Affymetrix rat chip 8799

probes+proteomics

study

6ndash24 h exposure Genbank SwissProt and

binary data in a

manuscript table

(Fountoulakis

2004)

Paracetamol CD-1 male mice Custom mouse tox blots

with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS

150 or 500 mgkg Gene name IMAGE ID

GenBank accession

number fold induction

SwissProt identifier and

protein abundance

change in manuscript

tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)

Paracetamol AP-1 male mice Affymetrix murine 11K

set+proteomics study

Up to 500 mgkg Gene names and fold

changes at multiple

doses and time points in

a manuscript tablemdash

proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643

Male B6C3F1 mice NIEHS Mouse Chip

(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)

Proteomics data in a

manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR

Proteomics 2-DIGE and

MS

250 mgkgday up to

5 days

Accession number and

protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)

Bromobenzene Male Wistar rats Proteomics 2-DIGE and

MS custom 3000 cDNA

rat chip


name fold change in a

manuscript table protein

names along with bar

charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)


the network that can be generated (as it will consist of more

nodes) then a more comprehensive understanding of the

networks is possible The data available currently in the

literature can be used to evaluate such pathway and

network generation tools Recently we have used several

of the published studies (Tables 1ndash3) with MetaCore to

visualize networks for acetaminophen furan carbon tetra-

chloride benzene and cisplatin showing genes involved in

In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS

Fig 2 The timeline for major paradigms in ADMETox

oxidative stress (Ekins Giroux Nikolsky Bugrim amp

Nikolskaya 2005c)

Other important pathwaynetwork building tools that could

potentially be applied to toxicogenomics data include

Ingenuity pathways analysis (httpwwwingenuitycom)

PathArt (httpwwwjubilantbiosyscompdhtm) Pathway

Assist (httpwwwariadnegenomicscomproctspathway

html) (Nikitin et al 2003) and several other databases

deposited at the Pathway Resource List (httpcbiiomskcc

orgprl) All of these products have unique underlying

proprietary pathway databases which are compiled manually

or automatically with text mining tools or a combination of

both We are still waiting for studies that provide a comparison

of different database tools or network building algorithms

Until then theremay be someoverlap but also some differences

between the results obtained from more than one network

method due to the database content and the algorithms used

The reader is recommended to evaluate for themselves several

technologies and select those with the most appropriate fit to

their own specialized needs

In the next Sections the further application of some

available network and database tools will be described with

Microarray or other high throughput data

Upload list of geneprotein identifiers and fold change significance etc (raw data or after selection of the differentially expressed

Genes using other statistical methods)

Parse database and generate interaction network with different algorithms or visualize on maps

Filter Networks

Access significance of the interaction networks

Determine GO processes

Compare 2 or more networks intersection overlap etc

Export gene list

Export gene list

generate interaction network with different algorithms or visualize on maps

Visualization

Fig 3 Schematic for the utilization of pathway tools for assessing high throughput data


specific detailed reference to transporters and enzymes but

these technologies can also be applied elsewhere as

described above

Fig 4 Network for high throughput screening data for clotrimazole and ticona

cholecystokinin CCR1 Choline transporter Chloride channel catechol-O-methyl

and co workers (Fliri et al 2005) Nodes highlighted with large blue circles rep

molecules showing gt50 inhibition in the assay blue circles represents both mol

inhibits gt50 and one inhibits lt50 Ligands (large) linked to transcriptional f

(wwgenegocom) (For interpretation of the references to colour in this figure leg

311 The role of transporters

A diverse array of organic solutes such as nutrients

neurotransmitters and drugs are transported by specialized

zole screened against 10 in vitro assays (Human Cannabinoid 1 Human

transferase COX2 CYP1A2 CYP2B6 CYP2C19) data published by Fliri

resent assays used in the study Red circles on these nodes represent both

ecules showing lt50 inhibition chequered circles represent one molecule

actors enzymes and transporters via edges using the MetaCorei database

end the reader is referred to the web version of this article)

Table 5

Datasets acquired from publications and other sources and used to evaluate two databasepathway tools KEGG and metaCore

Dataset Number of objects

genes proteins in list

Number of objects

mapped with KEGG

Number of objects mapped

with MetaCore on networks

Reference for microarray

data gene list

Tox Chip 10 (NIEHS) 1853 405 1498 httpsdir-appsniehsnihgov

mapsguestclonesrchcfm

4-Hydroxytamoxifen and

estrogen

1617 434 1343 (Hodges et al 2003)

Mitochondrial proteins 722 156 388 (Gaucher et al 2004

Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)

Acetaminophen 30 19 23 (Heinloth et al 2004)

Acetaminophen 84 29 64 (Huang et al 2004)

Furan 185 64 139 (Huang et al 2004)

Tetrodotoxin 116 31 86 (Raghavendra Prasad et al

2004)

Benzene 73 16 62 (Yoon et al 2003)

Benzene 76 5 53 (Faiola et al 2004)

Carbon tetrachloride 37 8 26 (Young et al 2003)

Estrogen 94 33 90 (Lobenhofer et al 2002)

Trovafloxacin 142 20 82 (Liguori et al 2005)

Phenobarbital 37 13 28 (Ueda et al 2002)

L-742694 (liver)+ 45 17 19 (Hartley et al 2004)

L-742694 (intestine)+ 23 11 10 (Hartley et al 2004)

A-277249 21 7 9 (Waring et al 2002)

All files were converted to Locuslink identifiers except as noted () unigene () Affymetrix (+) Genbank identifiers were used


proteins across cellular membranes These may function as

passive processes or active processes energized by the

hydrolysis of ATP or coupling to the co-transport of counter

ions down an electrochemical gradient such as Na+ H+ and

Cl There are many thousands of transporters which can be

classified into distinct superfamilies One of these the solute

carrier class (SLC) is rapidly expanding and contains over

30 families and 200 members The ATP-binding cassette

(ABC) contains 7 families and over 48 members including

P-glycoprotein (P-gp) and MRP subfamilies (Zhang Knipp

Ekins amp Swaan 2002a Zhang Phelps Cheng Ekins amp

Swaan 2002b) Transporters have a key role in clinical

pharmacology with many drugs specifically targeting them

Numerous drugs share transport pathways with nutrients

and transporters have a role in oral absorption drug

bioavailability drug resistance excretion and ultimately

pharmacokinetics and pharmacodynamics

Polymorphism of drug transporters may be a key factor

in drug interactions and lack of effectiveness This field has

become known as pharmacogenomics and is focused on

understanding of inherited DNA sequence variations (poly-

morphisms and mutations) revealed by xenobiotics (Evans

amp McLeod 2003 Weinshilboum 2003) Over the last few

decades many genes have been directly linked to the

mechanisms of response (Evans amp McLeod 2003 Wein-

shilboum 2003) such that 20ndash95 of variability to drug

response is inheritable (Evans amp McLeod 2003) This

phenotypical variability is mainly caused by single nucleo-

tide polymorphisms (SNPs) present in anywhere from 1 to

50 of the population resulting in either lower protein

activity incorrect folding or rapid degradation via proteo-

somes (Weinshilboum amp Wang 2004) A number of

structurally diverse molecules bind to P-gp which is

expressed in many tissues and has numerous SNPs one of

which (C3435T) affects the expression level in the

duodenum and therefore can impact the absorption of

molecules which would be substrates for this transporter

(Sakaeda Nakamura amp Okumura 2002) The human

proton-dependent dipeptide transporter (hPEPT1) can also

affect the absorption of molecules in the intestine and

recently 9 SNPs were found with only one displaying a

reduced transport capacity (Zhang et al 2004) The sodium-

dependent carnitine cotransporter OCTN2 can possess

mutations and these result in primary carnitine deficiency

which impacts fatty acid oxidation and is characterized by

many clinical manifestations (Lahjouji Mitchel amp Qureshi

2001) The organic cation transporter 1 (OCT1) is also

important in the transport of numerous xenobiotics and

endobiotics Recently 4 SNPs were identified in the

Japanese population and when functionally characterized

in vitro the uptake of cations was reduced significantly for

some of these mutations indicating that this would likely

contribute to inter-individual variations in metabolism of

drugs which were transported via OCT1 (Sakata et al

2004)

3111 Clinical relevance of transporters The pregnane

X-receptor (PXR) is a transcriptional regulator of the

enzyme human MDR1 (P-gp) MRPs and OATP (Wang amp

LeCluyse 2003) CYP3A (Bertilsson et al 1998 Blumberg

et al 1998 Kliewer et al 1998) and CYP2C89 (Synold

Dussault amp Forman 2001) as well as many other genes


involved in the transport metabolism and biosynthesis of

bile acids (Staudinger Liu Madan Habeebu amp Klaassen

2001) However the additional receptors CAR FXR LXR

and other nuclear receptors take part in a complex network

of interactions to control these and other proteins Thus

elucidation of the regulatory networks which control the

expression of these transporters is also important To date

most of the research has centered on efflux transporters but

there has been considerable interest in uptake transporters

such as the organic anion transporter polypeptide (OATP

((Kim 2003) see also later Section on OATP)

There are several specific examples of the importance of

drug transporters to the clinical development of drugs One

example is the insulin sensitizer troglitazone which was

withdrawn due to hepatotoxicity although the precise

mechanism appears to have been unclear until recently

The major metabolite is a sulfated species and is suspected

of being responsible for the observed toxicity The recent

assessment of the organic anion transporting polypeptides

OATP-C and OATP8 expressed on the hepatocyte baso-

lateral membrane indicated that sulphated troglitazone has a

high affinity for the former and possibly lower affinity for

the latter (Nozawa et al 2004) This metabolite would

therefore be expected to accumulate in hepatocytes and

inhibit the bile salt export pump and Mrp2 Because

polymorphisms have been shown for OATP-C (Tirona

Leake Merino amp Kim 2001) it is also possible that these

may result in the accumulation of the metabolite and in turn

elicit idiosyncratic toxicity A second relevant example of

the impact of transporters is the clinically significant drugndash

drug interaction between cerivastatin and cyclosporine A

which occurs via the OATP-C transporter (Shitara Itoh

Sato Li amp Sugiyama 2003) A third example are the HIV

protease inhibitors saquinavir ritonavir and indinavir which

are transported by MRP2 in vitro and other drugs such as

probenecid and sulfinpyrazone are able to enhance this

transport Transport by MRP2 suggests that these com-

pounds will have decreased bioavailability due to increased

clearance and other drugs could aggravate this situation by

further enhancing transport (Huisman et al 2002) Sim-

ilarly the rifampicin mediated induction via PXR of MRP2

and P-gp in healthy subjects was found to significantly

decrease the AUC and also correlated with intestinal

expression of these transporters This transporter is also

inducible by cisplatin 2-AAF and phenobarbital (Schrenk

et al 2001) indicating multiple mechanisms may be

involved In other species such as rat commonly used as a

toxicity model orthologs of the transporters such as OATP2

are expressed and can be induced with ligands for PXR like

PCN (Guo Choudhuri amp Klaassen 2002) This is useful

knowledge because the advent of microarray technology

allows one to dose a rat with a xenobiotic and assess

thousands of genes simultaneously in a particular tissue For

instance animals dosed with known nephrotoxins have

shown some upregulation of the NandashKndashCl transporter

however the authors suggested genomic responses are

stronger soon after exposure before declining (Fleck et

al 2003) Some transporters may therefore be specifically

targeted by drugs in one tissue such as the CNS but these

same transporters may also be expressed elsewhere in the

body hence off-target effects may result in toxicity The

serotonin transporter is one such example which is

expressed in the lungs and brain Some substrates for this

channel like fenfluramine can result in primary pulmonary

hypertension as they accumulate in pulmonary cells (Roth-

man Ayestas Dersch amp Baumann 1999) Similarly P-gp is

expressed at the blood brain barrier and intestine impacting

the efficacy and bioavailability of drugs

3112 Transporter network examples ABCA1 The

ABCA1 transporter mediates the first step of cholesterol

transport Mutations in this gene cause Tangier disease

which results in severe HDL deficiency cholesterol

accumulation in macrophages and attendant atherosclerosis

This transporter represents a drug target for upregulation

modulating cholesterol metabolism and prevention of

cardiovascular disease (Oram amp Lawn 2001) In vitro

ABCA1 can be inhibited by the sulfonylurea glybenclamide

(Field Burn amp Mathur 2004 Wang Silver Thiele amp Tall

2001) In order to illustrate the advantages of mapping drug

transporters as networks onto functional models alongside

other proteins one can consider the example of ABCA1

The query of the MetaCorei database shows that this

transporter appears on three manually curated pathway maps

representing the Fstate of the art_ knowledge derived from

reliable high quality literature sources One can also use the

individual maps as an interface to access the underlying

layers of information about the transporter including the list

of encoding genessplice variants with known SNPs In

addition to browsing MetaCorei a user can also build

custom networks around ABCA1 using the network-

construction tool (Fig 5) Such a visualization utility may

be very helpful for identification of all putative pathways

around a particular transporter or compound of interest The

ABCA1 network created by this tool shows that this

transporter at the time of writing is linked directly to

twenty-five other objects such as APOE1 and LXR Many

of its neighbors have their own SNPs that could be

important in determining interactions between transport of

a drug and normal human transport of endogenous ligands

in health or disease

3113 Transporter network examples OATP The

OATPs are key membrane bound transporters expressed in

many organs including intestine liver lung choroid plexus

blood brain barrier and other organs (Tamai et al 2000)

This family of transporters is capable of mediating the

sodium-independent transport of a diverse array of mole-

cules such as steroid conjugates organic anions and

xenobiotics by coupling uptake with efflux of bicarbonate

(Satlin Amin amp Wolkoff 1997) glutathione or its

conjugates (Hagenbuch amp Meier 2004) The inhibition of

Fig 5 The network of direct gene interactions around the ABCA1 transporter gene (centre) generated with MetaCorei The interation types between nodes are shown as small colored hexagons eg unspecified

allosteric regulation binding cleavage competition covalent modification dephosphorylation phosphorylation transcription regulation transformation When applicable interactions also have a positive or

negative effect and direction Ligands (purple) linked to other proteins (blue blobs) transfactors (red) enzymes (orange) (For interpretation of the references to colour in this figure legend the reader is referred to

the web version of this article)

SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth

ods53(2006)38ndash66

53


this transporterrsquos hepatic uptake of other compounds may be

important for reported drugndashdrug interactions (Kim 2003)

described earlier (Shitara et al 2003) as well as cerivastatin

with gemfibrozil (Shitara Hirano Sato amp Sugiyama 2004)

OATP1B1 (previous names OATP-C LST-1 OATP2

SLC21A6) represents the most studied human OATP to

date (Meier amp Stieger 2000) and is expressed on the

basolateral plasma membrane of hepatocytes Several single

nucleotide polymorphisms have been identified in the

OATP1B1 gene in European-Americans African-Americans

(Tirona et al 2001) and Japanese (Nozawa et al 2002)

dramatically impacting the transport of ligands such as

pravastatin (Mwinyi Johne Bauer Roots amp Gerloff 2004

Nishizato et al 2003) estrone-3-sulfate (Nozawa et al

2002 Tirona et al 2001) Rifampin (Tirona Leake

Wolkoff amp Kim 2003) and estradiol 17h-d-glucuronide(Tirona et al 2001)

The regulation of SLCO may be affected during

extrahepatic cholestasis bile duct ligation bile salt induced

Fig 6 Networks generated with the autoexpand algorithm in MetaCorei to illustr

be interconnected with other protein regulatory signaling information Informa

unspecified allosteric regulation binding cleavage competition covalent m

transformation When applicable interactions also have a positive or negative e

transfactors (red) enzymes (orange) (For interpretation of the references to colour

cholestatic hepatitis (Dumont et al 1997 Meier amp Stieger

2000 Rost et al 2003) and primary sclerosing cholangitis

(Oswald Kullack-Ublick Paumgarter amp Beuer 2001) In

particular OATP1B1 appears to be regulated by the liver-

enriched transcription factor hepatocyte nuclear factor 1a

(HNF1a) which binds to the promoter region of this

transporter (Jung et al 2001) Site directed mutagenesis

of this binding site resulted in inactivation suggesting the

critical nature of the interaction with HNF1a Bile acids

such as CDCA have been shown to transcriptionally repress

HNF1a in vitro via inhibition of the transactivating effect of

HNF4a on HNF1a (Jung amp Kullak-Ublick 2003) After

screening many rat and human uptake transporters in vitro

OATP1B1 was also shown to modulate the PXR response

by controlling rifampin retention in the cell and therefore

affecting the induction of CYP3A4 and other gene products

such as P-gp (Tirona et al 2003)

Some of the literature for OATP1B1 human substrate

data has been annotated into MetaCorei to illustrate the

ate how ligands for the human OATP-C (OATP1B1) transporter (centre) can

tion on the type of interaction between objects is hidden for clarity eg

odification dephosphorylation phosphorylation transcription regulation

ffect and direction Ligands (purple) linked to other proteins (blue blobs)

in this figure legend the reader is referred to the web version of this article)


visualization of the complex interconnections between this

transporter its ligands regulatory factors and signaling

molecules already in the database (Fig 6) The network was

generated with the autoexpand algorithm in the software

representing one of multiple available algorithms for

connecting genes ligands and other objects in the database

Clearly if more ligands and their connections are added to

the database the complexity of the network will increase

considerably The OATP-C (OATP1B1) gene details can be

viewed upon querying the database and links are provided

to other public databases This page can be used to highlight

the multiple synonyms for this gene as well as links to the

multiple SNPs identified to date

3114 Transporter microarray data Microarrays have

generally been limited in the number of transporters present

on them (Annereau et al 2004) however they have been used

in an attempt to correlate pharmacokinetic properties with

gene expression for valacyclovir (Landowski et al 2003) as

well as understand the expression profile in different tissues

or cell lines upon food component or xenobiotic treatment

(Anderle Huang amp Sadee 2004) This lack of transporters

on microarrays has prompted some groups to produce their

own arrays with a heavier emphasis on transporters These

arrays have for example then been used to demonstrate the

upregulation of ABC transporters and down-regulation of

GST-Pi in cell lines resistant to colchicines or 9-nitro-

camptothecin (Annereau et al 2004) The genes that were

significantly up or down-regulated in this particular study

were used to build networks with MetaCore (Fig 7A B) and

the similarities between them were assessed (Fig 7C)

Although there were only a small number of significantly

changed genes in common (IL-8 Fos GST-Pi Calpactin and

Ubiquitin hydrolase) it is perhaps likely that there is a much

larger common gene network that is important for drug

resistance although a much larger number of cell lines and

drug treatments need to be evaluated to produce a definitive

drug resistance signature involving transporters enzymes

and transcriptional regulators

312 Applications to enzymes

As we have already described it may be particularly

valuable to visualize enzymes as networks to show

interactions with transcriptional regulators and ligands

For example a key enzyme is CYP3A4 which metabolizes

40ndash45 of all drugs and has relatively few SNPs

(Ingelman-Sundberg 2004) Using a second software suite

MetaDrugi (wwwgenegocom) it is possible to construct

a custom network around this or other drug metabolizing

enzymes (Fig 8) In this case the gene network for

CYP3A4 highlights all of the major transcriptional

regulators and several more distant linked proteins and

ligands connected on the network that may be useful for

further study (Fig 8) Substrates inhibitors as well as

regulatory factors and other enzymes can be observed

connected on this network Due to the many hundreds of

known inhibitors and substrates only a small number are

shown here for clarity We assume that if a perturbation in

a pathway (eg due to a nonfunctional enzyme) is linked

to a certain pathologic condition a similar perturbation

caused by the interference from xenobiotic metabolism

(eg competitive inhibition of the same enzyme) may

result in identical effects As microarray gene expression

data is increasingly generated the role of enzyme

regulation in toxicity of certain xenobiotics will become

more apparent from either in vivo or in vitro studies The

visualization of such signature gene networks involving

transporters and enzymes their ligands and regulatory

factors will also be important for future toxicity prediction

methods We have recently generated visualizations of

microarray data from MCF-7 cells treated with 4-hydrox-

ytamoxifen to show that some of the key genes involved in

metabolism and transport are upregulated (Ekins et al

2005d) In addition we have made predictions with various

QSAR models in MetaDrug to indicate the involvement of

PXR CYP3A4 and P-gp (Ekins et al 2005e) Therefore it

appears likely that 4-hydroxytamoxifen could increase its

own metabolism as well as efflux from cells via P-gp

which can be visualized on networks Any decrease of

function of these enzymes or transporters in a population

would likely result in changes in the metabolism and

transport of this active metabolite potentially impacting

the clinical effect This represents one example of how

both pathway tools QSAR models and network building

algorithms can be used with different types of predicted

and experimental data to allow visualization of potential

compound interactions or toxicity

313 Future network applications

As the population ages an increasing incidence and

prevalence of systemic diseases especially chronic diseases

have occurred among older adults This has resulted in an

increase in medications used concomitantly by this

population which presents challenges for drugndashdrug

interactions Physiologically elderly patients may behave

differently to the younger patients for which the drugs are

initially developed for and tested on Many pharmacoki-

netic investigations in the elderly population reveal

decreased clearance of lipophilic drugs metabolized by

the cytochrome P450 enzymes however few studies have

evaluated aging-dependent or gender-related changes in

specific P450 enzymes (Hunt Westerkam amp Slave 1992)

Age-related physiological changes such as a reduction in

liver mass hepatic metabolizing enzyme activity liver

blood flow and alterations in plasma drug binding may

account for the decreased elimination of some metabolized

drugs in the elderly It is particularly difficult to separate an

effect of aging from the variation in the rate of metabolism

due to factors such as individual metabolic phenotype

(slow or fast metabolizer due to SNPs) environmental

influences concomitant disease states and drug intake

(drugndashdrug interactions) The available data suggest that

Fig 7 Networks for drug resistant cell lines generated with the Auto expand algorithm in MetaCore A KB-3-1 vs KB-8-5 B ATC-DU-145 vs RCO1 C node overlap of A and B with initial nodes highlighted

with blue or red solid circles (Initial gene lists derived from (Annereau et al 2004)) Information on the type of interaction between objects is hidden for clarity eg unspecified allosteric regulation binding

cleavage competition covalent modification dephosphorylation phosphorylation transcription regulation transformation When applicable interactions also have a positive or negative effect and direction

Ligands (purple) linked to other proteins (blue blobs) transfactors (red) enzymes (orange) (For interpretation of the references to colour in this figure legend the reader is referred to the web version of this article)

SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)


Fig 8 The network of gene interactions around the CYP3A4 enzyme (centre) from MetaCorei Information on the type of interaction between objects is

hidden for clarity eg unspecified allosteric regulation binding cleavage competition covalent modification dephosphorylation phosphorylation

transcription regulation transformation When applicable interactions also have a positive or negative effect and direction Ligands (purple) linked to other

proteins (blue blobs) transfactors (red) enzymes (orange) (For interpretation of the references to colour in this figure legend the reader is referred to the web

version of this article)


the initial doses of drugs metabolized by these enzymes

should be reduced in older patients according to the clinical

response In most published studies the elderly appear at

least as responsive as the young to inducers or inhibitors of

P450s (Durnas Loi amp Cusack 1990) More recently there

has been some suggestion that there are age related

reductions in function of some specific P450s such as

CYP3A4 (Patki et al 2004) and this could occur at the

level of regulation However earlier studies with the same

enzyme showed no change in clearance with age (Hunt et

al 1992) To date there has been even less examination of

the transporter functions and any changes with age

(Kinirons amp OrsquoMahony 2004) so the current understand-

ing of the effects of aging on metabolism and transport is

anything but transparent This represents an extreme

challenge for the pharmaceutical industry how to predict

whether a drug has an affinity for an enzyme or transporter

and whether this may be clinically important if it shows a

decline in expression or function with aging Any decrease

of function of these enzymes or transporters in an elderly

population would result in changes in the metabolism and

transport of metabolites potentially impacting the clinical

effect This represents another example of how computa-

tional approaches may perhaps be used with different types

of predicted and experimental data to allow visualization of

potential compound interactions or toxicity in elderly

populations We may see different gene networks high-

lighted as humans age and these may be modified by drug

treatment and coadministration This represents an area

were network analysis could be applied in the future and is

in need of considerable further research

The collection of microarray data in databases such as

CEBS ArrayTrack and EDGE represents a future resource

for computational gene network analysis One could

envisage that ultimately in each case such data is converted

to one or more networks that are also displayed for the user

and can be used to compare treatments from in vivo and in

vitro experiments This would represent a different approach

to clustering the data as currently implemented in one of

these efforts (Hayes et al 2005) and may condense large

amounts of experimentally derived data into a readily

interpreted network

4 Discussion

Previously in this journal the progress of many

research groups in predicting human ADME parameters


in silico (Ekins et al 2000b) and approaches for drug

metabolism (Ekins Ring Grace McRobie-Belle amp

Wrighton 2000a) have been described Both of these

reviews commented on moving HT assays for ADME

Tox much earlier in drug discovery which had also been

indicated by other groups The initial reviews also

highlighted the likely wealth of data that would become

available and how this could be used for structure

activity relationships alongside the bioactivity data in

computational models It was noted that there was a

paucity of predictive metabolism tools at that time In

addition a growing number of efforts to model whole

cells and organs now a field called systems biology

were recognized as models that could be integrated with

the in silico ADME approaches In summary since these

past reviews virtually all pharmaceutical companies have

attempted earlier high throughput screening for ADME

Tox properties and to some extent the wider application

of computational approaches for physicochemical proper-

ties Systems biology is being quite widely acknowledged

as the new paradigm for understanding complex bio-

logical datasets derived from high throughput technolo-

gies and the accumulated knowledge on human protein

interactions (Hartwell Hopfield Leibler amp Murray 1999

Hood 2003b) Therefore systems biology can be defined

as the integration of genetic proteomic transcriptomic

and metabonomic data using computational methods

(Nicholson amp Wilson 2003) When taken together

information on molecular processes derived from different

sources represents a lsquolsquouniversersquorsquo of putative biological

functionality of which only a small fraction of it will be

realized in a cell at any given time To date systems

biology has been driven by academia and funding bodies

such as the NIH rather than the pharmaceutical compa-

nies Presently there is a great deal of interest from

scientists of all backgrounds in identifying the networks

of cellular pathways and the corresponding physically

interacting proteins

The network building software for systems biology

described in this current review will be valuable to query

high throughput data and known literature interactions in

order to predict potential toxicity in different species In the

future the compilation of published toxicogenomics data-

sets characteristic of different types of toxicity will likely

be available in these software systems to act as a reference

database It is also feasible that we will be able to generate

the annotated datasets which specifically address the

differences between human and rat networks implicated

in toxicity The identification of sub-network modules

conserved between human and rat distinct for toxicity

types or predictive for toxic end-points in human will be

possible Such signature gene networks (Nikolsky et al

2005) can then be verified with other experimentally

derived data prospectively or from preexisting databases

The combined Fhigh throughput datandashin silico network_approaches therefore represents a novel method for access-

ing complex tissue-level processes as networks integrating

all data types based on functional interactions The data-

bases developed and used in this approach will certainly

benefit from further annotation around the drug metaboliz-

ing enzymes and transporters as described herein in terms

of transcriptional regulation and the ligands associated with

them which frequently appear in the literature It will be

important to capture disparities in the assignment of ligands

to enzymes transporters and other proteins as well as

negative data

In summary although there have been numerous

toxicogenomics studies published there is presently a

relatively small number of datasets that are freely available

to perform network analysis of microarray data The

number of studies identifying large numbers of proteins

which are affected by molecule treatment are even scarcer

still while there are several examples of some published

studies that combine such data It is hoped that the

numerous database initiatives for high content and toxicol-

ogy data that are being undertaken will improve the

situation for other researchers that are not currently

equipped to do such microarray studies themselves The

addition of requirements by journals to deposit such raw

data in a freely accessible resource will aid these initiatives

ADMETox groups have seen new technologies and

approaches developed over the last decade that have all

been applied to identify poor compounds earlier (Fig 2)

The latest technologies integrate network building tools

with high content data and databases The current review

described the limited number of networks generated for

ADMETox at present and one hopes that the impact of

such analyses will be commonplace in the future Systems

biology is however more than just applying a network

approach and hence systems-ADMETox will have to

evolve due to the continual pressure to develop newer

technologies This current paradigm combining empirical

data and computational methods should integrate the

complex data already generated making it readily inter-

pretable and valuable for identifying the most promising

compounds in the future

Acknowledgements

Dr Maggie AZ Hupcey is gratefully acknowledged for

editorial assistance Dr Peter W Swaan (University of

Maryland) and Dr Cheng Chang (Ohio State University)

Dr Steve Wright (University of Arizona) Dr K Sandy

Pang (University of Toronto) and Dr Craig Giroux (Wayne

State University) are kindly acknowledged for their support

and discussions My colleagues at GeneGo Sergey

Andreyev Andy Ryabov Eugene Kirillov Eugene A

Rakhmatulin Svetlana Sorokina Andrej Bugrim Tatiana

Nikolskaya Yuri Nikolsky John Metz and Julie Bryant are

all thanked for their considerable contributions to software

development and data annotation


References

Abe M Yamashita S Kuramoto T Hirayama Y Tsukamoto T Ohta

T et al (2003) Global expression analysis of N-methyl-NV-nitro-N-nitrosoguanidine-induced rat stomach carcinomas using oligonucleotide

microarrays Carcinogenesis 24 861ndash867

Adachi T Ono Y Koh K B Takashima K Tainaka H Matsuno Y

et al (2004) Long-term alteration of gene expression without

morphological change in testis after neonatal exposure to genistein in

mice Toxicogenomic analysis using cDNA microarray Food and

Chemical Toxicology 42 445ndash452

Akerman G S Rosenzweig B A Domon O E McGarrity L J

Blankenship L R Tsai C A et al (2004) Gene expression profiles

and genetic damage in benzo(a)pyrene diol epoxide-exposed TK6 cells

Mutation Research 549 43ndash64

Aksenov S V Church B Dhiman A Georgieva A Sarangapani R

Helmlinger G et al (2005) An integrated approach for inference and

mechanistic modeling for advancing drug development FEBS Letters

579 1878ndash1883

Anderle P Huang Y amp Sadee W (2004) Intestinal membrane transport

of drugs and nutrients Genomics of membrane transporters using

expression microarrays European Journal of Pharmaceutical Sciences

21 17ndash24

Annereau J P Szakacs G Tucker C J Arciello A Cardarelli C

Collins J et al (2004) Analysis of ATP-binding cassette transporter

expression in drug-selected cell lines by a microarray dedicated to

multidrug resistance Molecular Pharmacology 66 1397ndash1405

Apic G Ignjatovic T Boyer S amp Russell R B (2005) Illuminating drug

discovery with biological pathways FEBS Letters 579 1872ndash1877

Baker V A Harries H M Waring J F Duggan C M Ni H A Jolly

R A et al (2004) Clofibrate-induced gene expression changes in rat

liver A cross-laboratory analysis using membrane cDNA arrays

Environmental Health Perspectives 112 428ndash438

Balakin K V Ekins S Bugrim A Ivanenkov Y A Korolev D amp

Nikolsky Y et al (2004a) Quantitative structurendashmetabolism relation-

ship modeling of the metabolic N-dealkylation rates Drug Metabolism

and Disposition 32 1111ndash1120


Nikolsky Y et al (2004b) Kohonen maps for prediction of binding to

human cytochrome P450 3A4 Drug Metabolism and Disposition 32

1183ndash1189

Barabasi A -L amp Oltvai Z N (2004) Network biology Under-

standing the cellrsquos functional organization Nature Reviews Genetics

5 101ndash113

Bartosiewicz M Penn S G amp Buckpitt A (2001) Applications of gene

arrays in environmental toxicology Fingerprints of gene regulation

associated with cadmium chloride benzo(a)pyrene and trichloro-

ethylene Environmental Health Perspectives 109 71ndash74

Bertilsson G Heidrich J Svensson K Asman M Jendeberg L

Sydow-Backman M et al (1998) Identification of a human nuclear

receptor defines a new signaling pathway for CYP3A induction

Proceedings of the National Academy of Sciences of the United States

of America 95 12208ndash12213

Blumberg B Sabbagh Jr W Juguilon H Bolado Jr J van Meter

C M Ong E S et al (1998) SXR a novel steroid and xenobiotic-

sensing nuclear receptor Genes and Development 12 3195ndash3205

Borodina Y Rudik A Filimonov D Kharchevnikova N Dmitriev A

Blinova V et al (2004) A new statistical approach to predicting

aromatic hydroxylation sites Comparison with model-based

approaches Journal of Chemical Information and Computer Sciences

44 1998ndash2009

Borodina Y Sadym A Filimonov D Blinova V Dmitriev A amp

Poroikov V (2003) Predicting biotransformation potential from

molecular structure Journal of Chemical Information and Computer

Sciences 43 1636ndash1646

Bottone Jr F G Martinez J M Collins J B Afshari C A amp Eling

T E (2003) Gene modulation by the cyclooxygenase inhibitor

sulindac sulfide in human colorectal carcinoma cells Possible link to

apoptosis Journal of Biological Chemistry 278 25790ndash25801

Boyer S amp Zamora I (2002) New methods in predictive metabolism

Journal of Computer-Aided Molecular Design 16 403ndash413

Bredel M amp Jacoby E (2004) Chemogenomics An emerging strategy

for rapid target and drug discovery Nature Reviews Genetics 5

262ndash275

Bugrim A Nikolskaya T amp Nikolsky Y (2004) Early prediction of drug

metabolism and toxicity Systems biology approach and modeling

Drug Discovery Today 9 127ndash135

Bulera S J Eddy S M Ferguson E Jatkoe T A Reindel J F

Bleavins M R et al (2001) RNA expression in the early character-

ization of hepatotoxicants in Wistar rats by high-density DNA micro-

arrays Hepatology 33 1239ndash1258

Butcher E C Berg E L amp Kunkel E J (2004) Systems biology in drug

discovery Nature Biotechnology 22 1253ndash1259

Butte A (2002) The use and analysis of microarray data Naturalist

Review of Drug Discovery 1 951ndash960

Cary M P Bader G D amp Sander C (2005) Pathway information for

systems biology FEBS Letters 579 1815ndash1820

Cheok M H Yang W Pui C H Downing J R Cheng C Naeve

C W et al (2003) Treatment-specific changes in gene expression

discriminate in vivo drug response in human leukemia cells Nature

Genetics 34 85ndash90

Cleary J D Rogers P D amp Chapman S W (2001) Differential

transcription factor expression in human mononuclear cells in response

to amphotericin B Identification with complementary DNA microarray

technology Pharmacotherapy 21 1046ndash1054

Coen M Ruepp S U Lindon J C Nicholson J K Pognan F Lenz

E M et al (2004) Integrated application of transcriptomics and

metabonomics yields new insight into the toxicity due to paracetamol in

the mouse Journal of Pharmaceutical and Biomedical Analysis 35

93ndash105

Cornwell P D De Souza A T amp Ulrich R G (2004) Profiling of

hepatic gene expression in rats treated with fibric acid analogs


Csermely P Agoston V amp Pongor S (2005) The efficiency of multi-

target drugs The network approach might help drug design Trends in

Pharmacological Sciences 26 178ndash182

Cunningham M J Liang S Fuhrman S Seilhamer J J amp

Somogyi R (2000) Gene expression microarray data analysis for

toxicology profiling Annals of the New York Academy of Sciences 919

52ndash67

de Longueville F Atienzar F A Marcq L Dufrane S Evrard S

Wouters L et al (2003) Use of a low density microarray for studying

gene expression patterns induced by hepatotoxicants on primary

cultures of rat hepatocytes Toxicological Sciences 75 378ndash392

Dobrin R Beg Q K Barabasi A L amp Oltvai Z N (2004)

Aggregation of topological motifs in the Escherichia coli transcriptional

regulatory network BMC Bioinformatics 5 10

Donald S Verschoyle R D Edwards R Judah D J Davies R

Riley J et al (2002) Hepatobiliary damage and changes in hepatic

gene expression caused by the antitumor drug ecteinascidin-743 (ET-

743) in the female rat Cancer Research 62 4256ndash4262

Dumont M Jacquemin E DrsquoHont C Descout C Cresteil D Haouzi

D et al (1997) Expression of the liver Na+-independent organic anion

transporting polypeptide (oatp-1) in rats with bile duct ligation Journal

of Hepatology 27 1051ndash1056

Durnas C Loi C M amp Cusack B J (1990) Hepatic drug metabolism

and aging Clinical Pharmacokinetics 19 359ndash389

Eisen M B Spellman P T Brown P O amp Botstein D (1998) Cluster

analysis and display of genome-wide expression patterns Proceedings

of the National Academy of Sciences of the United States of America

95 14863ndash14868

Ekins S Andreyev S Ryabov A Kirilov E Rakhmatulin E A

Bugrim A et al (in press) Computational Prediction of Human Drug

Metabolism Exp Opin Drug Metab Toxicol


Ekins S Boulanger B Swaan P W amp Hupcey M A Z (2002)

Towards a new age of virtual ADMETOX and multidimensional drug

discovery Journal of Computer-Aided Molecular Design 16 381ndash401

Ekins S Bugrim A Nikolsky Y amp Nikolskaya T (2005) Systems

biology Applications in drug discovery In S Gad (Ed) Drug

Discovery Handbook (pp 123ndash183) Hoboken NJrsquo Wiley and Sons

Ekins S Giroux C N Nikolsky Y Bugrim A amp Nikolskaya T

(2005) A signature gene network approach to toxicity The Toxoco-

logists 84

Ekins S Kirillov E Rakhmatulin E amp Nikolskaya T (2005) A novel

method for visualizing nuclear hormone receptor networks relevant to

drug metabolism Drug Metabolism and Disposition 33 474ndash481

Ekins S amp McGowan R J (2001) The limits of reductionism The

shifting genomic paradigmrsquos impact on industry and academia

Philsophy in Science 9 1ndash23

Ekins S Mirny L amp Schuetz E G (2002) A ligand-based approach to

understanding selectivity of nuclear hormone receptors PXR CAR

FXR LXRa and LXRb Pharmaceutical Research 19 1788ndash1800

Ekins S Nikolsky Y amp Nikolskaya T (2005) Techniques Application

of systems biology to absorption distribution metabolism excretion

and toxicity Trends in Pharmacological Sciences 26 202ndash209

Ekins S Ring B J Grace J McRobie-Belle D J amp Wrighton S

A (2000) Present and future in vitro approaches for drug

metabolism Journal of Pharmacological and Toxicological Methods

44 313ndash324

Ekins S Waller C L Swaan P W Cruciani G Wrighton S A amp

Wikel J H (2000) Progress in predicting human ADME parameters in

silico Journal of Pharmacological and Toxicological Methods 44

251ndash272

Erhardt P W (2003) A human drug metabolism database Potential roles

in the quantitative predictions of drug metabolism and metabolism-

related drugndashdrug interactions Current Drug Metabolism 4 411ndash422

Evans W E amp McLeod H L (2003) Pharmacogenomicsmdashdrug

disposition drug targets and side effects New England Journal of

Medicine 348 538ndash549

Ezendam J Staedtler F Pennings J Vandebriel R J Pieters R

Boffetta P et al (2004) Toxicogenomics of subchronic hexachlor-

obenzene exposure in Brown Norway rats Environmental Health

Perspectives 112 782ndash791

Faiola B Fuller E S Wong V A amp Recio L (2004) Gene expression

profile in bone marrow and hematopoietic stem cells in mice exposed to

inhaled benzene Mutation Research 549 195ndash212

FDA (2004) Innovation stagnation Challenge and opportunity on the

critical path to new medicinal products

Fiehn O (2001) Combining genomics metabolome analysis and bio-

chemical modelling to understand metabolic networks Comparative

Functional Genomics 2 155ndash168

Field F J Born E amp Mathur S N (2004) LXRRXR ligand activation

enhances basolateral efflux of beta-sitosterol in CaCo-2 cells Journal of

Lipid Research 45 905ndash913

Fleck C Sutter L Appenroth D Koch B Meinhold T Pitack M

et al (2003) Use of gene chip technology for the characterisation of

the regulation of renal transport processes and of nephrotoxicity in

rats Experimental and Toxicologic Pathology 54 401ndash410

Fliri A F Loging W T Thadeio P F amp Volkmann R A (2005)

Biological spectra analysis Linking biological activity profiles to

molecular structure Proceedings of the National Academy of Sciences

of the United States of America 102 261ndash266

Fountoulakis M (2004) Application of proteomics technologies in the

investigation of the brain Mass Spectrometry Reviews 23 231ndash258

Gaucher S P Taylor S W Fahy E Zhang B Warnock D E Ghosh

S S et al (2004) Expanded coverage of the human heart

mitochondrial proteome using multidimensional liquid chromatography

coupled with tandem mass spectrometry Journal of Proteome

Research 3 495ndash505

Gerhold D Lu M Xu J Austin C Caskey C T amp Rushmore T

(2001) Monitoring expression of genes involved in drug metabolism

and toxicology using DNA microarrays Physiological Genomics 5

161ndash170

Guo G L Choudhuri S amp Klaassen C D (2002) Induction profile of

rat organic anion transporting polypeptide 2 (oatp2) by prototypical

drug-metabolizing enzyme inducers that activate gene expression

through ligand-activated transcription factor pathways Journal of

Pharmacology and Experimental Therapeutics 300 206ndash212

Hagenbuch B amp Meier P J (2004) Organic anion transporting

polypeptides of the OATP SLC21 family Phylogenetic classification

as OATP SLCO superfamily new nomenclature and molecularfunc-

tional properties Pflugers Archiv 447 653ndash665

Hamadeh H K amp Afshari C A (2004) Toxicogenomics principles and

applications Hobokenrsquo John Wiley and Sons

Hamadeh H K Bushel P R Jayadev S Martin K DiSorbo O Sieber

S et al (2002) Gene expression analysis reveals chemical-specific

profiles Toxicological Sciences 67 219ndash231

Hamadeh H K Jayadev S Gaillard E T Huang Q Stoll R

Blanchard K et al (2004) Integration of clinical and gene expression

endpoints to explore furan-mediated hepatotoxicity Mutation Research

549 169ndash183

Hamadeh H K Knight B L Haugen A C Sieber S Amin R P

Bushel P R et al (2002) Methapyrilene toxicity Anchorage of

pathologic observations to gene expression alterations Toxicologic

Pathology 30 470ndash482

Han J D Bertin N Hao T Goldberg D S Berriz G F Zhang L V

et al (2004) Evidence for dynamically organized modularity in the

yeast proteinndashprotein interaction network Nature 430 88ndash93

Hanisch D Zien A Zimmer R amp Lengauer T (2002) Co-clustering of

biological networks and gene expression data Bioinformatics 18

S145ndashS154

Harris A J Dial S L amp Casciano D A (2004) Comparison of basal

gene expression profiles and effects of hepatocarcinogens on gene

expression in cultured primary human hepatocytes and HepG2 cells


Harrison S C (2004) Whither structural biology Nature Structural

Molecular Biology 11 12ndash15

Hartley D P Dai X He Y D Carlini E J Wang B Huskey S E

et al (2004) Activators of the rat pregnane X receptor differentially

modulate hepatic and intestinal gene expression Molecular Pharma-

cology 65 1159ndash1171

Hartwell L H Hopfield J J Leibler S amp Murray A W (1999) From

molecular to modular cell biology Nature 402 C47ndashC52

Hasmall S Orphanides G James N Pennie W Hedley K Soames

A et al (2002) Downregulation of lactoferrin by PPARalpha ligands

Role in perturbation of hepatocyte proliferation and apoptosis

Toxicology Sciences 68 304ndash313

Hayase T Yamamoto Y Yamamoto K Muso E amp Shiota K (2004)

Microarray profile analysis of toxic cocaine-induced alterations in the

expression of mouse brain gene sequences A possible rsquoprotectiversquo

effect of buprenorphine Journal of Applied Toxicology 24 15ndash20

Hayes K R Vollrath A L Zastrow G M McMillan B J Craven M

Jovanovich S et al (2005) EDGE A centralized resource for the

comparison analysis and distribution of toxicogenomic information

Molecular Pharmacology 67 1360ndash1368

Heijne W H Slitt A L van Bladeren P J Groten J P Klaassen C D

Stierum R H et al (2004) Bromobenzene-induced hepatotoxicity at

the transcriptome level Toxicology Sciences 79 411ndash422

Heijne W H Stierum R H Slijper M van Bladeren P J amp van

Ommen B (2003) Toxicogenomics of bromobenzene hepatotoxicity

A combined transcriptomics and proteomics approach Biochemical

Pharmacology 65 857ndash875

Heinloth A N Irwin R D Boorman G A Nettesheim P Fannin

R D Sieber S O et al (2004) Gene expression profiling of rat

livers reveals indicators of potential adverse effects Toxicology


Hodges L C Cook J D Lobenhofer E K Li L Bennett L Bushel

P R et al (2003) Tamoxifen functions as a molecular agonist inducing


cell cycle-associated genes in breast cancer cells Molecular Cancer


Holleman A Cheok M H den Boer M L Yang W Veerman KM

A J Kazemier et al (2004) Gene-expression patterns in drug-resistant

acute lymphoblastic leukemia cells and response to treatment New

England Journal of Medicine 351 533ndash542

Hong Y Muller U R amp Lai F (2003) Discriminating two classes of

toxicants through expression analysis of HepG2 cells with DNA arrays

Toxicology in Vitro 17 85ndash92

Hood E (2003) Proteomics Characterizing the cogs in the machinery of

life Environmental Health Perspectives 111 A816ndashA825

Hood L (2003) Systems biology Integrating technology biology and

computation Mechanism of Ageing and Development 124 9ndash16

Hood L amp Galas D (2003) The digital code of DNA Nature 421

444ndash448

Hood L amp Perlmutter R M (2004) The impact of systems approaches on

biological problems in drug discovery Nature Biotechnology 22

1215ndash1217

Hu T Gibson D P Carr G J Torontali S M Tiesman J P Chaney

J G et al (2004) Identification of a gene expression profile that

discriminates indirect-acting genotoxins from direct-acting genotoxins


Huang Q Dunn II R T Jayadev S DiSorbo O Pack F D Farr S B

et al (2001) Assessment of cisplatin-induced nephrotoxicity by

microarray technology Toxicology Sciences 63 196ndash207

Huang Q Jin X Gaillard E T Knight B L Pack F D Stoltz J H et

al (2004) Gene expression profiling reveals multiple toxicity endpoints

induced by hepatotoxicants Mutation Research 549 147ndash167

Huisman M T Smit J W Crommentuyn K M Zelcer N Wiltshire

H R Beijnen J H et al (2002) Multidrug resistance protein 2

(MRP2) transports HIV protease inhibitors and transport can be

enhanced by other drugs Aids 16 2295ndash2301

Hunt C M Westerkam W R amp Stave G M (1992) Effect of age and

gender on the activity of human hepatic CYP3A Biochemical


Ideker T Ozier O Schwikowski B amp Siegal A F (2002) Discovering

regulatory and signalling circuits in molecular interaction networks

Bioinformatics 18 S233ndashS240

Ideker T Thorsson V Ranish J A Christmas R Buhler J Eng J K

et al (2001) Integrated genomic and proteomic analyses of a system-

atically perturbed network Science 292 929ndash934

Iida M Anna C H Hartis J Bruno M Wetmore B Dubin J R et al

(2003) Changes in global gene and protein expression during early

mouse liver carcinogenesis induced by non-genotoxic model carcino-

gens oxazepam and Wyeth-14643 Carcinogenesis 24 757ndash770

Ingelman-Sundberg M (2004) Pharmacogenetics of cytochrome P450 and

its applications in drug therapy The past present and future Trends in


Jeong H Mason S P Barabasi A L amp Oltvai Z N (2001) Lethality

and centrality in protein networks Nature 411 41ndash42

Jeong H Tombor B Albert R Oltvai Z N amp Barabasi A L

(2000) The large-scale organization of metabolic networks Nature

407 651ndash654

Jung D Hagenbuch B Gresh L Pontoglio M Meier P J amp Kullak-

Ublick G A (2001) Characterization of the human OATP-C

(SLC21A6) gene promoter and regulation of liver-specific OATP genes

by hepatocyte nuclear factor 1 alpha Journal of Biological Chemistry

276 37206ndash37214

Jung D amp Kullak-Ublick G A (2003) Hepatocyte nuclear factor 1

alpha A key mediator of the effect of bile acids on gene expression

Hepatology 37 622ndash631

Jung J -W Park J -S Hwang J -W Kang K -S YS L Song B

-S et al (2004) Gene expression analysis of peroxisome prolifer-

ators- and phenytoin-induced hepatotoxicity using cDNA microarray

Journal of Veterinary Medical Science 66 1329ndash1333

Kato N Shibutani M Takagi H Uneyama C Lee K -Y Takiami S

et al (2004) Gene expression profile in the livers of rats orally

administered ethinylestradiol for 28 days using a microarray technique

Toxicology 200 179ndash192

Kier L D Neft R Tang L Suizu R Cook T Onsurez K et al

(2004) Applications of microarrays with toxicologically relevant genes

(tox genes) for the evaluation of chemical toxicants in Sprague Dawley

rats in vivo and human hepatocytes in vitro Mutation Research 549

101ndash113

Kijima K Toyosawa K Yasuba M Matsuoka N Adachi T

Komiyama M et al (2004) Gene expression analysis of the rat testis

after treatment with di(2-ethylhexyl) phthalate using cDNA microarray

and real-time RT-PCR Toxicology and Applied Pharmacology 200

103ndash110

Kim R B (2003) Organic anion-transporting polypeptide (OATP) trans-

porter family and drug disposition European Journal of Clinical

Investigation 33 1ndash5

Kinirons M T amp OrsquoMahony M S (2004) Drug metabolism and ageing

British Journal of Clinical Pharmacology 57 540ndash544

Kitano H (2002a) Computational systems biology Nature 420 206ndash210

Kitano H (2002b) Systems biology A brief overview Science 295

1662ndash1664

Kliewer S A Moore J T Wade L Staudinger J L Watson M

A Jones S A et al (1998) An orphan nuclear receptor activated

by pregnanes defines a novel steroid signalling pathway Cell 92

73ndash82

Korolev D Balakin K V Nikolsky Y Kirillov E Ivanenkov Y A

Savchuk N P et al (2003) Modeling of human cytochrome p450-

mediated drug metabolism using unsupervised machine learning

approach Journal of Medicinal Chemistry 46 3631ndash3643

Kramer J A Pettit S D Amin R P Bertram T A Car B

Cunningham M et al (2004) Overview on the application of

transcription profiling using selected nephrotoxicants for toxicology

assessment Environmental Health Perspectives 112 460ndash464

Kultima K Nystrom A -M Scholz B Gustafson A -L Dencker L

amp Stigson M (2004) Valproic acid teratogenicity A toxicogenomics

approach Environmental Health Perspectives 112 1225ndash1235

Kutuzova G D amp Deluca H F (2004) Gene expression profiles in rat

intestine identify pathways for 125-dihydroxyvitamin D(3) stimulated

calcium absorption and clarify its immunomodulatory properties

Archives of Biochemistry and Biophysics 432 152ndash166

Kwak M K Wakabayashi N Itoh K Motohashi H Yamamoto M amp

Kensler T W (2003) Modulation of gene expression by cancer

chemopreventive dithiolethiones through the Keap1-Nrf2 pathway

Identification of novel gene clusters for cell survival Journal of

Biological Chemistry 278 8135ndash8145

Lahjouji K Mitchell G A amp Qureshi I A (2001) Carnitine transport

by organic cation transporters and systemic carnitine deficiency

Molecular Genetics and Metabolism 73 287ndash297

Landowski C P Sun D Foster D R Menon S S Barnett J L

Welage L S et al (2003) Gene expression in the human intestine and

correlation with oral valacyclovir pharmacokinetic parameters Journal

of Pharmacology and Experimental Therapeutics 306 778ndash786

Lee G -J Lee W -S Jeon K -S Um C -H Kim S -J Lee C -H

et al (2004) cDNA microarray gene expression analysis and

toxicological phenotype for anticancer drug Journal of Veterinary

Medical Science 66 1339ndash1345

Lee M Kwon J Kim S N Kim J E Koh W S Kim E J et al

(2003) cDNA microarray gene expression profiling of hydroxyurea

paclitaxel and p-anisidine genotoxic compounds with differing

tumorigenicity results Environmental and Molecular Mutagenesis

42 91ndash97

Li S Armstrong C M Bertin N Ge H Milstein S Boxem M et al

(2004) A map of the interactome network of the metazoan C elegans

Science 303 540ndash543

Liguori M J Anderson L M Bukofzer S McKim J Pregenzer J F

Retief J et al (2005) Microarray analysis in human hepatocytes

suggests a mechanism for hepatotoxicity induced by trovafloxacin



Lobenhofer E K Bennett L Cable P L Li L Bushel P R amp Afshari

C A (2002) Regulation of DNA replication fork genes by 17beta-

estradiol Molecular Endocrinology 16 1215ndash1229

Locker J Tian J Carver R Concas D Cossu C Ledda-Columbano

G M et al (2003) A common set of immediate-early response genes

in liver regeneration and hyperplasia Hepatology 38 314ndash325

Mattes W B Pettit S D Sansone S A Bushel P R amp Waters M D

(2004) Database development in toxicogenomics Issues and efforts


McMillian M Nie A Y Parker J B Leone A Bryant S Kemmerer

M et al (2004) A gene expression signature for oxidant stressreactive

metabolites in rat liver Biochemical Pharmacology 68 2249ndash2261

Meier P J amp Stieger B (2000) Molecular mechanisms in bile formation

News in Physiological Sciences 15 89ndash93

Meneses-Lorente G de Longueville F Dos Santos-Mendes S Bonnert

T P Jack A Evrard S et al (2003) An evaluation of a low-density

DNA microarray using cytochrome P450 inducers Chemical Research

in Toxicology 16 1070ndash1077

Meneses-Lorente G Guest P C Lawrence J Muniappa N Knowles

M R Skynner H A et al (2004) A proteomic investigation of drug-

induced steatosis in rat liver Chemical Research in Toxicology 17

605ndash612

Merrill C L Ni H Yoon L W Tirmenstein M A Narayanan P

Benavides G R et al (2002) Etomoxir-induced oxidative stress in

HepG2 cells detected by differential gene expression is confirmed

biochemically Toxicology Sciences 68 93ndash101

Milo R Shen-Orr S Itzkovitz S Kashtan N Chklovskii D amp Alon

U (2002) Network motifs Simple building blocks of complex

networks Science 298 824ndash827

Morgan K T Ni H Brown H R Yoon L Qualls C W Crosby L

M et al (2002) Application of cDNA microarray technology to in

vitro toxicology and the selection of genes for a real-time RT-PCR-

based screen for oxidative stress in Hep-G2 cells Toxicologic


Mwinyi J Johne A Bauer S Roots I amp Gerloff T (2004) Evidence

for inverse effects of OATP-C (SLC21A6) 5 and 1b haplotypes on

pravastatin kinetics Clinical Pharmacology and Therapeutics 75

415ndash421

Nakata K Yukawa M Komiyama N Nakano T amp Kaminuma T

(2002) A nuclear receptor database that maps pathways to diseases

Genome Infomatics 13 515ndash516

Nicholson J K Holmes E Lindon J C amp Wilson I D (2004) The

challenges of modeling mammalian biocomplexity Nature Biotechnol-

ogy 22 1268ndash1274

Nicholson J K amp Wilson I D (2003) Understanding rsquoglobal systems

biology Metabonomics and the continuum of metabolism Nature

Reviews on Drug Discovery 2 668ndash676

Nikitin A Egorov S Daraselia N amp Mazo I (2003) Pathway studiomdash

the analysis and navigation of molecular networks Bioinformatics 19

2155ndash2157

Nikolsky Y Ekins S Nikolskaya T amp Bugrim A (2005) A novel

method for generation of signature networks as biomarkers from

complex high throughput data Toxicology Letters 158 20ndash29

Nikolsky Y Nikolskaya T amp Bugrim A (2005) Biological networks

and analysis of experimental data in drug discovery Drug Discovery

Today 10 653ndash662

Nishizato Y Ieiri I Suzuki H Kimura M Kawabata K Hirota T

et al (2003) Polymorphisms of OATP-C (SLC21A6) and OAT3

(SLC22A8) genes Consequences for pravastatin pharmacokinetics

Clinical Pharmacology and Therapeutics 73 554ndash565

Nozawa T Nakajima M Tamai I Noda K Nezu J Sai Y et al

(2002) Genetic polymorphisms of human organic anion transporters

OATP-C (SLC21A6) and OATP-B (SLC21A9) Allele frequencies in

the Japanese population and functional analysis Journal of Pharmacol-

ogy and Experimental Therapeutics 302 804ndash813

Nozawa T Sugiura S Nakajima M Goto A Yokoi T Nezu J et al

(2004) Involvement of organic anion transporting polypeptides in the

transport of troglitazone sulfate Implications for understanding trogli-

tazone hepatotoxicity Drug Metabolism and Disposition 32 291ndash294

Oliver D E Rubin D L Stuart J M Hewett M Klein T E amp

Altman R B (2002) Ontology development for a pharmacogenetics

knowledge base Package Symposion 88ndash99

Oram J F amp Lawn R M (2001) ABCA1 The gatekeeper for eliminating

excess tissue cholesterol Journal of Lipid Research 42 1173ndash1179

Oswald M Kullak-Ublick G A Paumgartner G amp Beuers U (2001)

Expression of hepatic transporters OATP-C and MRP2 in primary

sclerosing cholangitis Liver 21 247ndash253

Parsons A B Brost R I Ding H Li Z Zhang C Sheikh B et al

(2004) Integration of chemical-genetic and genetic interaction data

links bioactive compounds to cellular target pathways Nature Bio-

technology 22 62ndash69

Patki K C von Moltke L L Harmatz J S Hesse L M Court M H

amp Greenblatt D J (2004) Effect of age on in vitro triazolam

biotransformation in male human liver microsomes Journal of


Pereira-Leal J B Enright A J amp Ouzounis C A (2004) Detection of

functional modules from protein interaction networks Proteins 54

49ndash57

Plant N (2004) Interaction networks Coordinating responses to xeno-

biotic exposure Toxicology 202 21ndash32

Raghavendra Prasad H S Qi Z Srinivasan K N amp Gopalakrish-

nakone P (2004) Potential effects of tetrodotoxin exposure to

human glial cells postulated using microarray approach Toxicon 44

597ndash608

Reilly T P Bourdi M Brady J N Pise-Masison C A Radonovich M

F George J W et al (2001) Expression profiling of acetaminophen

liver toxicity in mice using microarray technology Biochemical and

Biophysical Research Communications 282 321ndash328

Rives A W amp Galitski T (2003) Modular organization of cellular

networks Proceedings of the National Academy of Sciences of the

United States of America 100 1128ndash1133

Rogers P D Pearson M M Cleary J D Sullivan D C amp Chapman

S W (2002) Differential expression of genes encoding immunomodu-

latory proteins in response to amphotericin B in human mononuclear

cells identified by cDNA microarray analysis Journal of Antimicrobial

Chemotherapy 50 811ndash817

Rosen M B Wilson V S Schmid J E amp Gray L E (2005) Gene

expression analysis in the ventral prostate of rats exposed to vinclozolin

or procymidone Reproductive Toxicology 19 367ndash379

Rost D Herrmann T Sauer P Schmidts H L Stieger B Meier P J

et al (2003) Regulation of rat organic anion transporters in bile salt-

induced cholestatic hepatitis Effect of ursodeoxycholate Hepatology

38 187ndash195

Rothman R B Ayestas M A Dersch C M amp Baumann M H (1999)

Aminorex fenfluramine and chlorphentermine are serotonin transporter

substrates Implications for primary pulmonary hypertension Circula-

tion 100 869ndash875

Ruepp S U Tonge R P Shaw J Wallis N amp Pognan F (2002)

Genomics and proteomics analysis of acetaminophen toxicity in mouse

liver Toxicology Sciences 65 135ndash150

Sakaeda T Nakamura T amp Okumura K (2002) MDR1 genotype-

related pharmacokinetics and pharmacodynamics Biological amp Phar-

maceutical Bulletin 25 1391ndash1400

Sakata T Anzai N Shin H J Noshiro R Hirata T Yokoyama H

et al (2004) Novel single nucleotide polymorphisms of organic cation

transporter 1 (SLC22A1) affecting transport functions Biochemical

and Biophysical Research Communications 313 789ndash793

Satlin L M Amin V amp Wolkoff A W (1997) Organic anion

transporting polypeptide mediates organic anionHCO3-exchange

Journal of Biological Chemistry 272 26340ndash26345

Satomi Y Tsuchiya W Mihara K Ota M Kasahara Y amp Akahori F

(2004) Gene expression analysis of the lung following paraquat

administration in rats using DNA microarray Journal of Toxicological



Schrenk D Baus P R Ermel N Klein C Vorderstemann B amp

Kauffmann H M (2001) Up-regulation of transporters of the MRP

family by drugs and toxins Toxicology Letters 120 51ndash57

Segal E Shapira M Regev A Persquoer D Botstein D Koller D et al

(2003) Module networks Identifying regulatory modules and their

condition-specific regulators from gene expression data Nature


Segal E Wang H amp Koller D (2003) Discovering molecular pathways

from protein interaction and gene expression Bioinformatics 19

i264ndash i272

Seidel S D Kan H L Stott W T Schisler M R amp Gollapudi B B

(2003) Identification of transcriptome profiles for the DNA-damaging

agents bleomycin and hydrogen peroxide in L5178Y mouse lymphoma

cells Environmental and Molecular Mutagenesis 42 19ndash25

Shan L Yu Y Schut H A J amp Snyderwine E G (2004) Susceptibility

of rats to mammary gland carcinogenesis by the food-derived

carcinogen 2-Amino-1-Methyl-6-Phenylimidazo[45-b]Pyridine (PhIP)

varies with age and is associated with the induction of differential gene

expression American Journal of Pathology 165 191ndash202

Sharom J R Bellows D S amp Tyers M (2004) From large networks to

small molecules Current Opinion in Chemical Biology 8 81ndash90

Shitara Y Hirano M Sato H amp Sugiyama Y (2004) Gemfibrozil and

its glucuronide inhibit the OATP2(OATP1B1 SLC21A6)-mediated

hepatic uptake and CYP2C8-mediated metabolism of cerivastatinmdash

Analysis of the mechanism of the clinically relevant drugndashdrug

interaction between cerivastatin and gemfibrozil Journal of Pharma-

cology and Experimental Therapeutics

Shitara Y Itoh T Sato H Li A P amp Sugiyama Y (2003) Inhibition of

transporter-mediated hepatic uptake as a mechanism for drugndashdrug

interaction between cerivastatin and cyclosporin A Journal of


Somogyi R Fuhrman S amp Wen X (2001) Genetic network inference in

computational models and applications to large-scale gene expression

data In M Bower amp H Bolouri (Eds) Computational modeling of

genetic and biochemical networks (pp 119ndash157) Cambridge MArsquoThe

MIT Press

Spirin V amp Mirny L A (2003) Protein complexes and functional

modules in molecular networks Proceedings of the National Academy

of Sciences of the United States of America 100 12123ndash12128

Staudinger J Liu Y Madan A Habeebu S amp Klaassen C D

(2001) Coordinate regulation of xenobiotic and bile acid homeo-

stasis by pregnane X receptor Drug Metabolism and Disposition

29 1467ndash1472

Sun L Z Ji Z L Chen X Wang J F amp Chen Y Z (2002) ADME-

AP A database of ADME associated proteins Bioinformatics 18

1699ndash1700

Suter L Babiss L E amp Wheeldon E B (2004) Toxicogenomics in

predictive toxicology in drug development Chemistry and Biology 11

161ndash171

Synold T W Dussault I amp Forman B M (2001) The orphan nuclear

receptor SXR coordinately regulates drug metabolism and efflux

Nature Medicine 7 584ndash590

Tabuchi Y amp Kondo T (2003) cDNA microarray analysis reveals chop-

10 plays a key role in Sertoli cell injury induced by bisphenol A

Biochemical and Biophysical Research Communications 305 54ndash61

Tamai I Nezu J Uchino H Sai Y Oku A Shimane M et al (2000)

Molecular identification and characterization of novel members of the

human organic anion transporter (OATP) family Biochemical and


Taylor S W Fahy E Zhang B Glenn G M Warnock D E Wiley S

et al (2003) Characterization of the human heart mitochondrial

proteome Nature Biotechnology 21 281ndash286

Terasaka S Aita Y Inoue A Hayashi S Nishigaki M Aoyagi K

et al (2004) Using a customized DNA microarray for expression

profiling of the estrogen-responsive genes to evaluate estrogen activity

among natural estrogens and industrial chemicals Environmental

Health Perspectives 112 773ndash781

Thomas D M Francescutti-Verbeem D M Liu X amp Kuhn D M

(2004) Identification of differentially regulated transcripts in mouse

striatum following methamphetamine treatmentmdashan oligonucleotide

microarray approach Journal of Neurochemistry 88 380ndash393

Thomas R S Rank D R Penn S G Zastrow G M Hayes K R

Pande K et al (2001) Identification of toxicologically predictive

gene sets using cDNA microarrays Molecular Pharmacology 60

1189ndash1194

Thompson K L Afshari C A Amin R P Bertram T A Car B

Cunningham M et al (2004) Identification of platform-independent

gene expression markers of cisplatin nephrotoxicity Environmental


Tirona R G Leake B F Merino G amp Kim R B (2001)

Polymorphisms in OATP-C Identification of multiple allelic

variants associated with altered transport activity among European-

and African-Americans Journal of Biological Chemistry 276

35669ndash35675

Tirona R G Leake B F Wolkoff A W amp Kim R B (2003)

Human organic anion transporting polypeptide-C (SLC21A6) is a

major determinant of the rifampin-mediated pregnane X receptor

activation Journal of Pharmacology and Experimental Therapeutics

304 223ndash228

Tong W Cao X Harris S Sun H Fang H Fuscoe J et al (2003)

ArrayTrackmdashsupporting toxicogenomic research at the US Food and

Drug Administration National Center for Toxicological Research


Tornow S amp Mewes H W (2003) Functional modules by relating

protein interaction networks and gene expression Nucleic Acids


Trocho C Escola-Gil J C Ribas V Benitez S Martin-Campos J M

Rotllan N et al (2004) Phenytoin treatment reduces atherosclerosis in

mice through mechanisms independent of plasma HDL-cholesterol

concentration Atherosclerosis 174 275ndash285

Ueda A Hamadeh H K Webb H K Yamamoto Y Sueyoshi T

Afshari C A et al (2002) Diverse roles of the nuclear orphan

receptor CAR in regulating hepatic genes in response to phenobarbital


Ulrich R G (2003) The toxicogenomics of nuclear receptor agonists

Current Opinion in Chemical Biology 7 505ndash510

Ulrich R G Rockett J C Gibson G G amp Pettit S D (2004)

Overview of an interlaboratory collaboration on evaluating the effects

of model hepatotoxicants on hepatic gene expression Environmental


Unami A Shinohara Y Ichikawa T amp Baba Y (2003) Biochemical

and microarray analyses of bupivacaine-induced apoptosis Journal of

Toxicological Sciences 28 77ndash94

Vasquez A Flammini A Maritan A amp Vespignani A (2003) Global

protein function prediction from proteinndashprotein interaction networks

Nature Biotechnology 21 697ndash700

Vezina C M Walker N J amp Olson J R (2004) Subchronic Exposure to

TCDD PeCDF PCB126 and PCB153 Effect on hepatic gene

expression Environmental Health Perspectives 112 1636ndash1644

Vo T D Greenberg H J amp Palsson B O (2004) Reconstruction and

functional characterization of the human mitochondrial metabolic

network based on proteomic and biochemical data Journal of Bio-

logical Chemistry 279 39532ndash39540

Wang H amp LeCluyse E L (2003) Role of orphan nuclear receptors in

the regulation of drug-metabolising enzymes Clinical Pharmacoki-

netics 42 1331ndash1357

Wang N Silver D L Thiele C amp Tall A R (2001) ATP-

binding cassette transporter A1 (ABCA1) functions as a choles-

terol efflux regulatory protein Journal of Biological Chemistry 276

23742ndash23747

Waring J F Cavet G Jolly R A McDowell J Dai H Ciurlionis R

et al (2003) Development of a DNA Microarray for toxicology based

on hepatoxin-regulated sequences Environmental Health Perspectives

111 863ndash870


Waring J F Gum R Morfitt D Jolly R A Ciurlionis R Heindel M

et al (2002) Identifying toxic mechanisms using DNA microarrays

Evidence that an experimental inhibitor of cell adhesion molecule

expression signals through the aryl hydrocarbon nuclear receptor

Toxicology 181ndash182 537ndash550

Waring J F Jolly R A Ciurlionis R Lum P Y Praestgaard J T

Morfitt D C et al (2001) Clustering of hepatotoxins based on

mechanism of toxicity using gene expression profiles Toxicology and

Applied Pharmacology 175 28ndash42

Waters M Boorman G Bushel P Cunningham M Irwin R Merrick

A et al (2003) Systems toxicology and the Chemical Effects in

Biological Systems (CEBS) knowledge base EHP Toxicogenomics

111 15ndash28

Wei M Arnold L Cano M amp Cohen S M (2005) Effects of co-

administration of antioxidants and arsenicals on the rat urinary bladder

epithelium Toxicology Sciences 83 237ndash245

Weinshilboum R (2003) Inheritance and drug response New England

Journal of Medicine 348 529ndash537

Weinshilboum R amp Wang L (2004) Pharmacogenetics Inherited

variation in amino acid sequence and altered protein quantity Clinical

Pharmacology and Therapeutics 75 253ndash258

Werner E (2003) In silico multicellular systems biology and minimal

genomes Drug Discovery Today 8 1121ndash1127

Wong J S amp Gill S S (2002) Gene expression changes induced in

mouse liver by di(2-ethylhexyl) phthalate Toxicology and Applied


Xie T Tong L McCann U D Yuan J Becker K G Mechan A O

et al (2004) Identification and characterization of metallothionein-1

and -2 gene expression in the context of ()34-methylenedioxymetham-

phetamine-induced toxicity to brain dopaminergic neurons Journal of

Neuroscience 24 7043ndash7050

Yadetie F Laegreid A Bakke I Kusnierczyk W Komorowski J

Waldum H L et al (2003) Liver gene expression in rats in response

to the peroxisome proliferator-activated receptor-alpha agonist ciprofi-

brate Physiological Genomics 15 9ndash19

Yamashita S Nomoto T Abe M Tatematsu M Sugimura T amp

Ushijima T (2004) Persistence of gene expression changes in stomach

mucosae induced by short-term N-methyl-NV-nitro-N-nitrosoguanidinetreatment and their presence in stomach cancers Mutation Research

549 185ndash193

Yan Q amp Sadee W (2000) Human membrane transporter database A

web-accessible relational database for drug transport studies and

pharmacogenomics AAPS Pharmsci 2 E20

Yeger-Lotem E amp Margalit H (2003) Detection of regulatory circuits by

integrating the cellular networks of proteinndashprotein interactions and

transcription regulation Nucleic Acids Research 31 6053ndash6061

Yoon B I Li G -X Kitada K Kawasaki Y Igarashi K amp Kodama

Y et al (2003) Mechanisms of benzene-induced hematotoxicity and

leukemogenicity cDNA microarray analyses using mouse bone marrow

tissue Environmental Health Perspectives 111 1411ndash1420

Young M B DiSilvestro M R Sendera T J Freund J Kriete A amp

Magnuson S R (2003) Analysis of gene expression in carbon

tetrachloride-treated rat livers using a novel bioarray technology

Pharmacogenomics Journal 3 41ndash52

Yu H Zhu X Greenbaum D Karro J amp Gerstein M (2004) TopNet

A tool for comparing biological sub-networks correlating protein

properties with topological statistics Nucleic Acids Research 32

328ndash337

Zhang E Y Fu D J Pak Y A Stewart T Mukhopadhyay N

Wrighton S A et al (2004) Genetic polymorphisms in human proton-

dependent dipeptide transporter PEPT1 Implications for the functional

role of Pro586 Journal of Pharmacology and Experimental Therapeu-

tics 310 437ndash445

Zhang E Y Knipp G T Ekins S amp Swaan P W (2002)

Structural biology and function of solute transporters Implications

for identifying and designing substrates Drug Metabolism Reviews

34 709ndash750

Zhang E Y Phelps M A Cheng C Ekins S amp Swaan P W (2002)

Modeling of active transport systems Advanced Drug Delivery

Reviews 54 329ndash354


Introduction

Data available

Network analysis and databases

Network applications

The role of transporters

Clinical relevance of transporters

Transporter network examples ABCA1

Transporter network examples OATP

Transporter microarray data

Applications to enzymes

Future network applications

Discussion

Acknowledgements

References

0

20

40

60

80

100

2000 2001 2002 2003 2004 2005Year

Pu

bM

edN

um

ber

of

pu

blic

atio

ns

in

Fig 1 Annual frequency of articles appearing with the words lsquolsquotoxicoge-

nomicsrsquorsquo (squares) or lsquolsquomicroarray and toxicologyrsquorsquo (diamonds)


dures (Tables 1-4) There have been relatively few cross-

platform toxicogenomics studies under controlled condi-

tions (Thompson et al 2004) Despite the suggested poor

compatibility between the different array types this latter

study demonstrated a high (90) consistency between the

expression of the genes that were shared between the

platforms The development of methods to visualize such

complex expression data has also expanded beyond the

widely used clustering methods (Eisen Spellman Brown amp

Botstein 1998) With the outcome of microarray analysis

being dependent on the widely used statistical procedures

applied to derive those genes that are significantly differ-

entially expressed (Butte 2002) newer approaches that do

not necessarily require data clustering may be an advantage

As rat and mouse are the most widely used in vivo toxicity

models it is assumed that acute and chronic toxicity shown

in animals largely coincides with human toxicity Therefore

differential expression patterns in animal models are also

assumed to be predictive of the end point toxic response in

human This is not always the case due to differences

between human and rodent physiology genetics metabo-

lism and signaling pathways For example the mechanism

of toxicity for pyrazinamide has been reconstructed

(Bugrim Nikolskaya amp Nikolsky 2004) to illustrate that

the accumulation of uric acid occurs in human but not in

mice and this results in toxicity in the former The relatively

poor understanding of such species differences may be

reflected in the relatively large number of late stage

molecules that have undergone in vivo toxicity assessment

yet have been later withdrawn due to adverse events in

humans

In recent years the appearance of systems biology which

uses the relationships of all elements of biology rather than

approaching them separately has been evident and will

likely reunite biological fields (Harrison 2004 Hood amp

Galas 2003) These systems approaches are the latest

incarnation of the importance of the Fparts vs wholes_debate (Ekins amp McGowan 2001) and interpreting ADME

Tox in this context may improve our understanding and

ultimate predictions (Bugrim et al 2004 Ekins Boulanger

Swaan amp Hupcey 2002a Kitano 2002a Werner 2003)

The perturbing effect of a molecule on the complete

biological system can be observed across all metabolic

and signaling pathways or networks and can provide some

limited insight into the binding to multiple proteins or

effects on gene expression simultaneously This requires the

collection of high-throughput data including global gene

expression protein content metabolic profiles for the same

samples as well as individual genetic clinical and pheno-

typic data However there are difficulties with such an

approach as there are likely to be differences between the

Fstimulus to effect_ durations for all the genendashprotein

relationships (Nicholson Holmes Lindon amp Wilson

2004)

We can now use either the growing number of academic

or commercially available pathway database and network

building tools with expression data These enable the

connection of interacting differentially expressed genes as

networks (Barabasi amp Oltvai 2004 Hanisch Zien Zimmer

amp Lengauer 2002 Ideker Ozier Schwikowski amp Siegal

2002 Ideker et al 2001 Segal et al 2003a Segal Wang amp

Koller 2003b Spirin amp Mirny 2003 Tornow amp Mewes

2003) as well as allowing the reverse engineering of

functional connections (Somogyi Fuhrman amp Wen 2001)

The use of such network visualizations suggests an

organized modularity in complex systems (Han et al

2004) which has also been applied to interpret the

connectivity of small molecules and their interaction with

proteins in the subfield of chemogenomics (Bredel amp Jacoby

2004 Csermely Agoston amp Pongor 2005 Parsons et al

2004 Sharom Bellows amp Tyers 2004) The parallel

development of HT methods databases ADMETox model-

ing and systems modeling is ongoing (Ekins Nikolsky amp

Nikolskaya 2005e) The present review is therefore timely

as it discusses some of the data resources limitations and

technologies that are available for Systems-ADMETox

(Fig 2) along with some illustration of their applications to

drug metabolism and drug transport which are key com-

ponents of the ADMETox process The ultimate aim of

this discussion is to provide awareness of an integrated

approach rather than a technology silo mentality represent-

ing the latest proposed research model in the field (Fig 2)

2 Data available

A recently published book provides an excellent over-

view of toxicogenomics and the reader is referred to this to

gain more insight into the applications and limitations

(Hamadeh amp Afshari 2004) The growing number of

toxicogenomic datasets derived from in vivo studies with

rat (Table 1) and mouse (Table 2) as well as in vitro cell

derived data (Table 3) highlights the different strains

microarray types and compounds that are routinely assessed

Also there are numerous instances of multiple groups testing

the same compound at similar or different doses eg well

known hepatotoxicants or nephrotoxicants such as clofibrate

Table 1



availability

Reference

Acetaminophen furan

methotrexate

methapyrilene

phenytoin

Male Spraguendash

Dawley VAF+

albino

Phase 1 Molecular

toxicology array

Acetaminophen

(4500 mgkgday)

methotrexate (1 mg

kg day)

methapyrilene (100

mgkgday) furan (40

mgkgday) or

phenytoin (300 mg

kgday)

Gene name accession


are provided in a

manuscript table

(Huang et al

2004)

A-277249 3MC

Aroclor






table

(Waring et al

2002)


benzoapyrene

Male Spraguendash

Dawley


BP at 10 mgkg bw

given 3 times per

week for 2 weeks

APAP at 1000 mgkg

Gene name and fold


table

(Cunningham

Liang Fuhrman

Seilhamer amp

Somogyi 2000)

L-742694

Dexamethasone

Female

SpraguendashDawley


day) DEX (50 mg

kgday)

Tables of accession



table for liver and

intestine

(Hartley et al

2004)


array


number and log fold




available

(Heijne et al

2004)


D3

Male Spraguendash

Dawley (small

intestine)


rat oligonucleotide

arrays (GeneChips

RG-U34A)



fold change in a

manuscript table

(Kutuzova amp

Deluca 2004)


bezafibrate

gemfibrozi

ciprofibrate



to 14 days



manuscript table

(Cornwell Souza

amp Ulrich 2004)


Dawley


clones

Exposed to 4 or 40

mgkg furan for up

to 14 days

Gene ID and gene




website

(Hamadeh et al

2004)


(httpdirniehsnihgov

microarraychipshtm)

0 50 150

1500 mgkg

Unigene accession



table

(Heinloth et al

2004)


Dawley

ADME Rat expression





Up to 14 day

treatment


binary data in a

manuscript table

(Young et al

2003)


chloroform

Male Spraguendash

Dawley

The rat CT arrays



with known or

discovered


treatments

6 24 72 h high and

low doses

Gene names and fold



table

(Kier et al 2004)



Table 1 (continued)


availability

Reference


(bladder

epithelium)

Rat 10K chip (MWG


10000 genes



manuscript table

(Wei Arnold

Cano amp Cohen

2005)

Dexamethasone

troleandomycin

miconazole

clotrimazole

isoniazid

methylclofanapate

Female Spraguendash

Dawley


TAO (500 mgkg

day) MIC (100 mg

kgday) CLOT (100

mgkg per day) ISN

(100 mgkgday)

MCP (75 mgkgday)





from publication

(Meneses-Lorente

et al 2003)

TCDD PeCDF PCB126

PCB153

Female Harlan

SpraguendashDawley

Affymetrix GeneChip

Test3 arrays


to toxicologically

equivalent doses



a manuscript table

(Vezina Walker

amp Olson 2004)


SpraguendashDawley


7 mgkgday female


gene names in a

manuscript table

(Lee et al 2004)


phenytoin

Male Spraguendash

Dawley VAF(+)

albino


in house

Treated with each

compound for 24 h

and 2 weeks

Gene name and fold


table

(Jung et al 2004)

Clofibrate

dexamethasone

phenobarbital




and mouse)





table

(Gerhold et al

2001)


doxylamine

methapyrilene

phenobarbital

tamoxifen



isoniazid


uml7800 rat cDNAs

Low mid and high

doses



compounds

(Kramer et al

2004)


Dawley

Mouse cDNA


9984 cDNA clones

(National Cancer

Institute


manuscript table

(Shan Yu Schut

amp Snyderwine

2004)


SpraguendashDawley


10 ppm





(Kato et al 2004)



manuscript table

(Satomi et al

2004)


Norway

Affymetrix rat

RGU-34A GeneChip

microarray





(Ezendam et al

2004)


(MNNG)

Rat pyloric muco-

sae male congenic


homozygous_LIZ

transgene of

BigBlue rat

AFFYMETRIX Rat

Genome U34A




table

(Yamashita et al

2004)


Male ACINJcI

(ACI)

Affymetrix GeneChip

Rat genome U34A

arrays

83 mgl from the age


40 weeks





cancer comparison

(Abe et al 2003)




144 h


name NIEHS ID and


manuscript table

(Thompson et al

2004)


Table 1 (continued)


availability

Reference


Dawley



Alto CA USA)



low (25 mgkgday)

Genbank accession


platforms in a

manuscript table

(Baker et al

2004)

Di(2-ethylhexyl)

phthalate

Male Spraguendash

Dawleymdash(testes)

An in-house cDNA

microarray



manuscript table

(Kijima et al

2004)


microarray



ratio and SD

(Yadetie et al

2003)


Dawley





NIEHS website

(Hamadeh et al

2002b)

Ecteinascidin-743

(ET-743)



approximately 4700

hybridizable mouse


derived from IMAGE


Research Genetics


the MRC Human Gene

Mapping Project




(Donald et al

2002)

Clofibrate Wyeth

14643 Gemfibrozil

phenobarbital

Male Spraguendash

Dawley VAF+


mgkgday Wyeth

14643 (250 mgkg

day) Gemfibrozil

(100 mgkgday)

Phenobarbital

(120 mgkgday)

Gene names and fold


table

(Hamadeh et al

2002a)


Dawleymdashprostate


Toxicology array


number average fold

change

(Rosen Wilson

Schmid amp Gray

2005)


Dawley VAF1

albino (CRL

CD(SD) BR

Rat Tox Microarrays

were purchased from

Phase-1 Molecular

Toxicology



kidney

(Huang et al

2001)

Allyl alcohol

miodarone Aroclor

1254 arsenic

carbamazepine


diethylnitrosamine

dimethylformamide

diquat etoposide

indomethacin

methapyrilene

methotrexate

monocrotaline


Male Spraguendash

Dawley

Affymetrix GeneChip

Test 2 Array



kgday) Aroclor 1254


(20 mgkgday)


kgday) carbon



(100 mgkgday)





(20 mgkgday)


kgday) methotrexate

(250 mgkgday)


day)


(100 mgkgday)


table of Affymetrix

names for genes



manuscript table

(Waring et al

2001)



Table 1 (continued)


availability

Reference


phenobarbital (PB)

lipopolysaccharide

(LPS) carbon

tetrachloride (CT)

thioacetamide (THA)

and cyproterone

acetate (CPA)



Santa Clara CA)

containing 1600 rat

DNA sequences


name fold changes

shown as a heat map



laborious

(Bulera et al

2001)

Acetamidofluorene


butyl hydroxytol

dieldrin disulfiram

ethinyl estradiol


g 4-methylthiazole




trans-anethole

Male Spraguendash

Dawley

Custom Rat MegaA

cDNA chip 3434-gene






(30 and 45 mgkg)



mgkg)


gamma (40 65 80 mg






pulegone (400 mgkg)


kg) trans-anethole

(600 mgkg)

Gene name accession


table

(McMillian et al

2004)
























































Table 2



availability

Reference


KO mice and

C57BL6


GEM system



Gene name accession



table

(Yoon et al 2003)



Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)


8736 genes





table

(Ueda et al 2002)

Aroclor BNF


chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463


cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)



mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)


kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold



the EDGE database

(Thomas et al

2001)


mouse array


kg body wt



manuscript table

(Locker et al

2003)


(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip


name fold in a

manuscript table

(Kwak et al

2003)


Webster (neurons)


set



table

(Xie et al 2004)





(Trocho et al

2004)


diethylstilbestrol

(DES) (50 Agmouse

day)



1754 cDNA probes






very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine





Inc Copenhagen

Denmark)





4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)


(striatum)

Affymetrix mouse

genechip mg-U74Av2


12 488 genes




manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate


Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession





take some effort

(Wong amp Gill

2002)


wild type


600 tox genes




(Hasmall et al

2002)


Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 1



availability

Reference

Acetaminophen furan

methotrexate

methapyrilene

phenytoin

Male Spraguendash

Dawley VAF+

albino

Phase 1 Molecular

toxicology array

Acetaminophen

(4500 mgkgday)

methotrexate (1 mg

kg day)

methapyrilene (100

mgkgday) furan (40

mgkgday) or

phenytoin (300 mg

kgday)

Gene name accession


are provided in a

manuscript table

(Huang et al

2004)

A-277249 3MC

Aroclor






table

(Waring et al

2002)


benzoapyrene

Male Spraguendash

Dawley


BP at 10 mgkg bw

given 3 times per

week for 2 weeks

APAP at 1000 mgkg

Gene name and fold


table

(Cunningham

Liang Fuhrman

Seilhamer amp

Somogyi 2000)

L-742694

Dexamethasone

Female

SpraguendashDawley


day) DEX (50 mg

kgday)

Tables of accession



table for liver and

intestine

(Hartley et al

2004)


array


number and log fold




available

(Heijne et al

2004)


D3

Male Spraguendash

Dawley (small

intestine)


rat oligonucleotide

arrays (GeneChips

RG-U34A)



fold change in a

manuscript table

(Kutuzova amp

Deluca 2004)


bezafibrate

gemfibrozi

ciprofibrate



to 14 days



manuscript table

(Cornwell Souza

amp Ulrich 2004)


Dawley


clones

Exposed to 4 or 40

mgkg furan for up

to 14 days

Gene ID and gene




website

(Hamadeh et al

2004)


(httpdirniehsnihgov

microarraychipshtm)

0 50 150

1500 mgkg

Unigene accession



table

(Heinloth et al

2004)


Dawley

ADME Rat expression





Up to 14 day

treatment


binary data in a

manuscript table

(Young et al

2003)


chloroform

Male Spraguendash

Dawley

The rat CT arrays



with known or

discovered


treatments

6 24 72 h high and

low doses

Gene names and fold



table

(Kier et al 2004)



Table 1 (continued)


availability

Reference


(bladder

epithelium)

Rat 10K chip (MWG


10000 genes



manuscript table

(Wei Arnold

Cano amp Cohen

2005)

Dexamethasone

troleandomycin

miconazole

clotrimazole

isoniazid

methylclofanapate

Female Spraguendash

Dawley


TAO (500 mgkg

day) MIC (100 mg

kgday) CLOT (100

mgkg per day) ISN

(100 mgkgday)

MCP (75 mgkgday)





from publication

(Meneses-Lorente

et al 2003)

TCDD PeCDF PCB126

PCB153

Female Harlan

SpraguendashDawley

Affymetrix GeneChip

Test3 arrays


to toxicologically

equivalent doses



a manuscript table

(Vezina Walker

amp Olson 2004)


SpraguendashDawley


7 mgkgday female


gene names in a

manuscript table

(Lee et al 2004)


phenytoin

Male Spraguendash

Dawley VAF(+)

albino


in house

Treated with each

compound for 24 h

and 2 weeks

Gene name and fold


table

(Jung et al 2004)

Clofibrate

dexamethasone

phenobarbital




and mouse)





table

(Gerhold et al

2001)


doxylamine

methapyrilene

phenobarbital

tamoxifen



isoniazid


uml7800 rat cDNAs

Low mid and high

doses



compounds

(Kramer et al

2004)


Dawley

Mouse cDNA


9984 cDNA clones

(National Cancer

Institute


manuscript table

(Shan Yu Schut

amp Snyderwine

2004)


SpraguendashDawley


10 ppm





(Kato et al 2004)



manuscript table

(Satomi et al

2004)


Norway

Affymetrix rat

RGU-34A GeneChip

microarray





(Ezendam et al

2004)


(MNNG)

Rat pyloric muco-

sae male congenic


homozygous_LIZ

transgene of

BigBlue rat

AFFYMETRIX Rat

Genome U34A




table

(Yamashita et al

2004)


Male ACINJcI

(ACI)

Affymetrix GeneChip

Rat genome U34A

arrays

83 mgl from the age


40 weeks





cancer comparison

(Abe et al 2003)




144 h


name NIEHS ID and


manuscript table

(Thompson et al

2004)


Table 1 (continued)


availability

Reference


Dawley



Alto CA USA)



low (25 mgkgday)

Genbank accession


platforms in a

manuscript table

(Baker et al

2004)

Di(2-ethylhexyl)

phthalate

Male Spraguendash

Dawleymdash(testes)

An in-house cDNA

microarray



manuscript table

(Kijima et al

2004)


microarray



ratio and SD

(Yadetie et al

2003)


Dawley





NIEHS website

(Hamadeh et al

2002b)

Ecteinascidin-743

(ET-743)



approximately 4700

hybridizable mouse


derived from IMAGE


Research Genetics


the MRC Human Gene

Mapping Project




(Donald et al

2002)

Clofibrate Wyeth

14643 Gemfibrozil

phenobarbital

Male Spraguendash

Dawley VAF+


mgkgday Wyeth

14643 (250 mgkg

day) Gemfibrozil

(100 mgkgday)

Phenobarbital

(120 mgkgday)

Gene names and fold


table

(Hamadeh et al

2002a)


Dawleymdashprostate


Toxicology array


number average fold

change

(Rosen Wilson

Schmid amp Gray

2005)


Dawley VAF1

albino (CRL

CD(SD) BR

Rat Tox Microarrays

were purchased from

Phase-1 Molecular

Toxicology



kidney

(Huang et al

2001)

Allyl alcohol

miodarone Aroclor

1254 arsenic

carbamazepine


diethylnitrosamine

dimethylformamide

diquat etoposide

indomethacin

methapyrilene

methotrexate

monocrotaline


Male Spraguendash

Dawley

Affymetrix GeneChip

Test 2 Array



kgday) Aroclor 1254


(20 mgkgday)


kgday) carbon



(100 mgkgday)





(20 mgkgday)


kgday) methotrexate

(250 mgkgday)


day)


(100 mgkgday)


table of Affymetrix

names for genes



manuscript table

(Waring et al

2001)



Table 1 (continued)


availability

Reference


phenobarbital (PB)

lipopolysaccharide

(LPS) carbon

tetrachloride (CT)

thioacetamide (THA)

and cyproterone

acetate (CPA)



Santa Clara CA)

containing 1600 rat

DNA sequences


name fold changes

shown as a heat map



laborious

(Bulera et al

2001)

Acetamidofluorene


butyl hydroxytol

dieldrin disulfiram

ethinyl estradiol


g 4-methylthiazole




trans-anethole

Male Spraguendash

Dawley

Custom Rat MegaA

cDNA chip 3434-gene






(30 and 45 mgkg)



mgkg)


gamma (40 65 80 mg






pulegone (400 mgkg)


kg) trans-anethole

(600 mgkg)

Gene name accession


table

(McMillian et al

2004)
























































Table 2



availability

Reference


KO mice and

C57BL6


GEM system



Gene name accession



table

(Yoon et al 2003)



Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)


8736 genes





table

(Ueda et al 2002)

Aroclor BNF


chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463


cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)



mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)


kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold



the EDGE database

(Thomas et al

2001)


mouse array


kg body wt



manuscript table

(Locker et al

2003)


(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip


name fold in a

manuscript table

(Kwak et al

2003)


Webster (neurons)


set



table

(Xie et al 2004)





(Trocho et al

2004)


diethylstilbestrol

(DES) (50 Agmouse

day)



1754 cDNA probes






very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine





Inc Copenhagen

Denmark)





4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)


(striatum)

Affymetrix mouse

genechip mg-U74Av2


12 488 genes




manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate


Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession





take some effort

(Wong amp Gill

2002)


wild type


600 tox genes




(Hasmall et al

2002)


Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 1 (continued)


availability

Reference


(bladder

epithelium)

Rat 10K chip (MWG


10000 genes



manuscript table

(Wei Arnold

Cano amp Cohen

2005)

Dexamethasone

troleandomycin

miconazole

clotrimazole

isoniazid

methylclofanapate

Female Spraguendash

Dawley


TAO (500 mgkg

day) MIC (100 mg

kgday) CLOT (100

mgkg per day) ISN

(100 mgkgday)

MCP (75 mgkgday)





from publication

(Meneses-Lorente

et al 2003)

TCDD PeCDF PCB126

PCB153

Female Harlan

SpraguendashDawley

Affymetrix GeneChip

Test3 arrays


to toxicologically

equivalent doses



a manuscript table

(Vezina Walker

amp Olson 2004)


SpraguendashDawley


7 mgkgday female


gene names in a

manuscript table

(Lee et al 2004)


phenytoin

Male Spraguendash

Dawley VAF(+)

albino


in house

Treated with each

compound for 24 h

and 2 weeks

Gene name and fold


table

(Jung et al 2004)

Clofibrate

dexamethasone

phenobarbital




and mouse)





table

(Gerhold et al

2001)


doxylamine

methapyrilene

phenobarbital

tamoxifen



isoniazid


uml7800 rat cDNAs

Low mid and high

doses



compounds

(Kramer et al

2004)


Dawley

Mouse cDNA


9984 cDNA clones

(National Cancer

Institute


manuscript table

(Shan Yu Schut

amp Snyderwine

2004)


SpraguendashDawley


10 ppm





(Kato et al 2004)



manuscript table

(Satomi et al

2004)


Norway

Affymetrix rat

RGU-34A GeneChip

microarray





(Ezendam et al

2004)


(MNNG)

Rat pyloric muco-

sae male congenic


homozygous_LIZ

transgene of

BigBlue rat

AFFYMETRIX Rat

Genome U34A




table

(Yamashita et al

2004)


Male ACINJcI

(ACI)

Affymetrix GeneChip

Rat genome U34A

arrays

83 mgl from the age


40 weeks





cancer comparison

(Abe et al 2003)




144 h


name NIEHS ID and


manuscript table

(Thompson et al

2004)


Table 1 (continued)


availability

Reference


Dawley



Alto CA USA)



low (25 mgkgday)

Genbank accession


platforms in a

manuscript table

(Baker et al

2004)

Di(2-ethylhexyl)

phthalate

Male Spraguendash

Dawleymdash(testes)

An in-house cDNA

microarray



manuscript table

(Kijima et al

2004)


microarray



ratio and SD

(Yadetie et al

2003)


Dawley





NIEHS website

(Hamadeh et al

2002b)

Ecteinascidin-743

(ET-743)



approximately 4700

hybridizable mouse


derived from IMAGE


Research Genetics


the MRC Human Gene

Mapping Project




(Donald et al

2002)

Clofibrate Wyeth

14643 Gemfibrozil

phenobarbital

Male Spraguendash

Dawley VAF+


mgkgday Wyeth

14643 (250 mgkg

day) Gemfibrozil

(100 mgkgday)

Phenobarbital

(120 mgkgday)

Gene names and fold


table

(Hamadeh et al

2002a)


Dawleymdashprostate


Toxicology array


number average fold

change

(Rosen Wilson

Schmid amp Gray

2005)


Dawley VAF1

albino (CRL

CD(SD) BR

Rat Tox Microarrays

were purchased from

Phase-1 Molecular

Toxicology



kidney

(Huang et al

2001)

Allyl alcohol

miodarone Aroclor

1254 arsenic

carbamazepine


diethylnitrosamine

dimethylformamide

diquat etoposide

indomethacin

methapyrilene

methotrexate

monocrotaline


Male Spraguendash

Dawley

Affymetrix GeneChip

Test 2 Array



kgday) Aroclor 1254


(20 mgkgday)


kgday) carbon



(100 mgkgday)





(20 mgkgday)


kgday) methotrexate

(250 mgkgday)


day)


(100 mgkgday)


table of Affymetrix

names for genes



manuscript table

(Waring et al

2001)



Table 1 (continued)


availability

Reference


phenobarbital (PB)

lipopolysaccharide

(LPS) carbon

tetrachloride (CT)

thioacetamide (THA)

and cyproterone

acetate (CPA)



Santa Clara CA)

containing 1600 rat

DNA sequences


name fold changes

shown as a heat map



laborious

(Bulera et al

2001)

Acetamidofluorene


butyl hydroxytol

dieldrin disulfiram

ethinyl estradiol


g 4-methylthiazole




trans-anethole

Male Spraguendash

Dawley

Custom Rat MegaA

cDNA chip 3434-gene






(30 and 45 mgkg)



mgkg)


gamma (40 65 80 mg






pulegone (400 mgkg)


kg) trans-anethole

(600 mgkg)

Gene name accession


table

(McMillian et al

2004)
























































Table 2



availability

Reference


KO mice and

C57BL6


GEM system



Gene name accession



table

(Yoon et al 2003)



Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)


8736 genes





table

(Ueda et al 2002)

Aroclor BNF


chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463


cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)



mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)


kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold



the EDGE database

(Thomas et al

2001)


mouse array


kg body wt



manuscript table

(Locker et al

2003)


(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip


name fold in a

manuscript table

(Kwak et al

2003)


Webster (neurons)


set



table

(Xie et al 2004)





(Trocho et al

2004)


diethylstilbestrol

(DES) (50 Agmouse

day)



1754 cDNA probes






very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine





Inc Copenhagen

Denmark)





4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)


(striatum)

Affymetrix mouse

genechip mg-U74Av2


12 488 genes




manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate


Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession





take some effort

(Wong amp Gill

2002)


wild type


600 tox genes




(Hasmall et al

2002)


Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 1 (continued)


availability

Reference


Dawley



Alto CA USA)



low (25 mgkgday)

Genbank accession


platforms in a

manuscript table

(Baker et al

2004)

Di(2-ethylhexyl)

phthalate

Male Spraguendash

Dawleymdash(testes)

An in-house cDNA

microarray



manuscript table

(Kijima et al

2004)


microarray



ratio and SD

(Yadetie et al

2003)


Dawley





NIEHS website

(Hamadeh et al

2002b)

Ecteinascidin-743

(ET-743)



approximately 4700

hybridizable mouse


derived from IMAGE


Research Genetics


the MRC Human Gene

Mapping Project




(Donald et al

2002)

Clofibrate Wyeth

14643 Gemfibrozil

phenobarbital

Male Spraguendash

Dawley VAF+


mgkgday Wyeth

14643 (250 mgkg

day) Gemfibrozil

(100 mgkgday)

Phenobarbital

(120 mgkgday)

Gene names and fold


table

(Hamadeh et al

2002a)


Dawleymdashprostate


Toxicology array


number average fold

change

(Rosen Wilson

Schmid amp Gray

2005)


Dawley VAF1

albino (CRL

CD(SD) BR

Rat Tox Microarrays

were purchased from

Phase-1 Molecular

Toxicology



kidney

(Huang et al

2001)

Allyl alcohol

miodarone Aroclor

1254 arsenic

carbamazepine


diethylnitrosamine

dimethylformamide

diquat etoposide

indomethacin

methapyrilene

methotrexate

monocrotaline


Male Spraguendash

Dawley

Affymetrix GeneChip

Test 2 Array



kgday) Aroclor 1254


(20 mgkgday)


kgday) carbon



(100 mgkgday)





(20 mgkgday)


kgday) methotrexate

(250 mgkgday)


day)


(100 mgkgday)


table of Affymetrix

names for genes



manuscript table

(Waring et al

2001)



Table 1 (continued)


availability

Reference


phenobarbital (PB)

lipopolysaccharide

(LPS) carbon

tetrachloride (CT)

thioacetamide (THA)

and cyproterone

acetate (CPA)



Santa Clara CA)

containing 1600 rat

DNA sequences


name fold changes

shown as a heat map



laborious

(Bulera et al

2001)

Acetamidofluorene


butyl hydroxytol

dieldrin disulfiram

ethinyl estradiol


g 4-methylthiazole




trans-anethole

Male Spraguendash

Dawley

Custom Rat MegaA

cDNA chip 3434-gene






(30 and 45 mgkg)



mgkg)


gamma (40 65 80 mg






pulegone (400 mgkg)


kg) trans-anethole

(600 mgkg)

Gene name accession


table

(McMillian et al

2004)
























































Table 2



availability

Reference


KO mice and

C57BL6


GEM system



Gene name accession



table

(Yoon et al 2003)



Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)


8736 genes





table

(Ueda et al 2002)

Aroclor BNF


chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463


cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)



mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)


kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold



the EDGE database

(Thomas et al

2001)


mouse array


kg body wt



manuscript table

(Locker et al

2003)


(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip


name fold in a

manuscript table

(Kwak et al

2003)


Webster (neurons)


set



table

(Xie et al 2004)





(Trocho et al

2004)


diethylstilbestrol

(DES) (50 Agmouse

day)



1754 cDNA probes






very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine





Inc Copenhagen

Denmark)





4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)


(striatum)

Affymetrix mouse

genechip mg-U74Av2


12 488 genes




manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate


Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession





take some effort

(Wong amp Gill

2002)


wild type


600 tox genes




(Hasmall et al

2002)


Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 1 (continued)


availability

Reference


phenobarbital (PB)

lipopolysaccharide

(LPS) carbon

tetrachloride (CT)

thioacetamide (THA)

and cyproterone

acetate (CPA)



Santa Clara CA)

containing 1600 rat

DNA sequences


name fold changes

shown as a heat map



laborious

(Bulera et al

2001)

Acetamidofluorene


butyl hydroxytol

dieldrin disulfiram

ethinyl estradiol


g 4-methylthiazole




trans-anethole

Male Spraguendash

Dawley

Custom Rat MegaA

cDNA chip 3434-gene






(30 and 45 mgkg)



mgkg)


gamma (40 65 80 mg






pulegone (400 mgkg)


kg) trans-anethole

(600 mgkg)

Gene name accession


table

(McMillian et al

2004)
























































Table 2



availability

Reference


KO mice and

C57BL6


GEM system



Gene name accession



table

(Yoon et al 2003)



Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)


8736 genes





table

(Ueda et al 2002)

Aroclor BNF


chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463


cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)



mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)


kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold



the EDGE database

(Thomas et al

2001)


mouse array


kg body wt



manuscript table

(Locker et al

2003)


(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip


name fold in a

manuscript table

(Kwak et al

2003)


Webster (neurons)


set



table

(Xie et al 2004)





(Trocho et al

2004)


diethylstilbestrol

(DES) (50 Agmouse

day)



1754 cDNA probes






very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine





Inc Copenhagen

Denmark)





4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)


(striatum)

Affymetrix mouse

genechip mg-U74Av2


12 488 genes




manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate


Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession





take some effort

(Wong amp Gill

2002)


wild type


600 tox genes




(Hasmall et al

2002)


Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 2



availability

Reference


KO mice and

C57BL6


GEM system



Gene name accession



table

(Yoon et al 2003)



Gene name accession



table

(Faiola Fuller

Wong amp Recio

2004)


8736 genes





table

(Ueda et al 2002)

Aroclor BNF


chloride TCDD IL-6

LPS PCB-153

phenobarbital

phenylhyrzn TNFa

WY-16463


cDNAs

Aroclor (200 mgkg)

BNF (5 mgkg)



mgkg) TCDD (10 ug

kg) IL-6 (25 ugkg)

LPS (1 mgkg)

PCB-153 (80 mgkg)


kgday) 3 days

phenylhyrzn (100 mg

kg) TNFa (50 ugkg)

WY-16463 (0125wv)

Gene names and fold



the EDGE database

(Thomas et al

2001)


mouse array


kg body wt



manuscript table

(Locker et al

2003)


(D3T)

Male wild-type and

nrf2-disrupted

Affymetrix murine

genome U74Av2

GeneChip


name fold in a

manuscript table

(Kwak et al

2003)


Webster (neurons)


set



table

(Xie et al 2004)





(Trocho et al

2004)


diethylstilbestrol

(DES) (50 Agmouse

day)



1754 cDNA probes






very few genes

(Adachi et al

2004)

Cocaine and

buprenorphine





Inc Copenhagen

Denmark)





4 days

Data apparently not

available

(Hayase

Yamamoto

Yamamoto Muso

amp Shiota 2004)


(striatum)

Affymetrix mouse

genechip mg-U74Av2


12 488 genes




manuscript table

(Thomas

Francescutti-

Verbeem Liu amp

Kuhn 2004)

Di(2-ethylhexyl)

phthalate


Arrays (MGU74Av2)

10 dietary DEHP for

13 weeks

Genbank accession





take some effort

(Wong amp Gill

2002)


wild type


600 tox genes




(Hasmall et al

2002)


Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 2 (continued)


availability

Reference


hybrid


then individual

oligonucleotide



that can detect the

expression of 11000

known genes and


(ESTs)




(Reilly et al

2001)

Cadmium chloride



(TCE)



genes



and TCE

(Bartosiewicz

Penn amp Buckpitt

2001)

















































Gerstein 2004)


























Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 3



availability

Reference

4-Hydroxytamoxifen

estrogen



1901 genes


for a year 10 nM

17b-estradiol


website

(Hodges et al

2003)



easily extracted

(Liguori et al

2005)



1901 genes


website

(Lobenhofer et al

2002)


and P19 mouse

embryocarcinoma



set




table

(Kultima et al

2004)


carcinoma SW-480

and HCT-116




time points in a



website

(Bottone

Martinez Collins

Afshari amp Eling

2003)


estrone genistein

diethylstilbestrol

bisphenol A

nonylphenol

methoxychlor



10 nM (E2 estriol


nonylphenol and

methoxychlor)

Unigene name gene




manuscript table

(Terasaka et al

2004)


dimethylsulfoxide

cycloheximide

tolbutamide sodium

fluoride diethyl

maleate buthionine

sulfoxamine

potassium bromate

sodium selenite

alloxan adriamycin

hydrogen peroxide



arrays (234 genes)


sulfate (260 uM)





mM) diethyl maleate

(125 mM) buthionine

sulfoxamine (30 mM)




adriamycin (40 uM)

hydrogen peroxide

(4 mM)

Gene name ratio p -



(Morgan et a l

2002)



(2AAF)

dimethylnitrosamine

(DMN)


HepG2 and primary

hepatocytes

Gene filter arrays


10 uM aflatoxin B1

40 mM acetaminophen

100 uM

dimethylnitrosamine

10 uM


None (Harris et al

2004)

Mitomycin C (MMC)

and cisplatin (CIS)

and an alkylating

agent methyl

methanesulfonate

(MMS)

indirect-acting

genotoxins included

hydroxyurea (HU) a

ribonucleotide

reductase inhibitor

taxol (TXL) a


and etoposide

(ETOP)

L5178Y TK(+-)

mouse lymphoma

Affymetrix mouse

MG-U74A for MMC

and MG-U745Av2




of 9977 probe sets


to these two array

models





table

(Hu et al 2004)


Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 3 (continued)


availability

Reference

Hydroxyurea

(a carcinogen)

p-anisidine

(a noncarcinogen)

and paclitaxel

L5178Y Tk_-mouse

lymphoma



cDNA microarray


ugml hydroxyurea 32

ugml p-anisidine



table

(Lee et al 2003)

Acetaminophen



isoniazid alpha-


beta-naphtoflavone

4-pentenoic acid

phenobarbital

tetracycline and

zileuton

Wistar Rat

hepatocytes

DualChip rat hepato

(Eppendorf Hamburg

Germany)



compound


gene namemdashfold

changes shown as



publication

(de Longueville

et al 2003)


peroxide

Mouse lymphoma

L5178Y TK(+ -)

Clontech Mouse 12K


genes)



(5 and 10 ugml)

Gene names and fold



(Seidel Kan

Stott Schisler amp

Gollapudi 2003)

Bupivicaine

camptothecin


microarray


accession number


manuscript table

(Unami

Shinohara

Ichikawa amp Baba

2003)


expression glass


10 Takara Shuzo)




approximately 301


(ESTs)



fold change at time


table

(Tabuchi amp

Kondo 2003)

Mitomycin C or

doxorubicin


array

10 um mitomycin C

2 um doxorubicin or

2 ethanol



very few genes

(Hong Muller amp

Lai 2003)


blood mononuclear

and THP-1

GF211 FKnown Genes_


(ResGen) this array

consists of gt4000

individual elements

each representing a

known human gene



manuscript table

(Cleary Rogers amp

Chapman 2001

Rogers Pearson

Cleary Sullivan

amp Chapman

2002)

Benzo(a)pyrene diol

epoxide

TK6 human

lymphoblastoid



spotted human cDNA

probes (Phase-1


0 001 010 or

10 ugml)

Gene names and fold


manuscript table

(Akerman et al

2004)



(234 genes)



table

(Merrill et al

2002)


line HTB-138

Using Affymetrix

GeneChip (HG-U133A


ID gene name gene



(Raghavendra

Prasad Qi

Srinivasan amp

Gopalakrishnakone

2004)

Methotrexate

mercaptopurine

Human acute

lymphoblastic

leukemia


combination

Data available as


(Cheok et al 2003)

Prednisolone

vincristine

asparaginase

daunorubicin

Human acute

lymphoblastic

leukemia



(Holleman et al

2004)






































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References





































2005e)






























































readily accessible















Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 4



availability

Reference

Carbon

tetrachloride


probes+proteomics

study


binary data in a

manuscript table

(Fountoulakis

2004)


with 450 genes

RTQ-PCR+proteomics

study 2-DIGE+

MALDI-MS


GenBank accession



protein abundance


tables

(Ruepp Tonge

Shaw Wallis amp

Pognan 2002)




changes at multiple



proteomics data not

accessible

(Coen et al 2004)

Oxazepam or

Wy-14643


(8700 genes) 2-DIGE

and MS

Oxazepam (2500 ppm)

Wyeth (Wy)-14643

(500 ppm)


manuscript table

Genbank accession


fold change in a


also available to

download from NIEHS

website

(Iida et al 2003)

Compound A

(PPAR gamma

ligand)

Female rats CrlCD

(SD)IGS BR


MS

250 mgkgday up to

5 days


protein name and

average ratio in a

manuscript table

(Meneses-Lorente

et al 2004)


MS custom 3000 cDNA

rat chip





charts

(Heijne Stierum

Slijper van

Bladeren amp van

Ommen 2003)










In vivo

In vitro

In Silico

1970s 1980s 1990s 2000s

Systems Biology ()

OMICS



Nikolskaya 2005c)

























Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References





Filter Networks




Export gene list

Export gene list


Visualization





described above
















Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Table 5




Number of objects

mapped with KEGG




data gene list




estrogen

1617 434 1343 (Hodges et al 2003)


Taylor et al 2003)

Bromobenzene

(24 and 48 h)

130 41 89 (Heijne et al 2004)





2004)









A-277249 21 7 9 (Waring et al 2002)

























































2004)


























































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References




















































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


53



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References



































































































































































SEkin

sJournalofPharm

acologica

landToxico

logica

lMeth


56

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Fig7(continued)


Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

Fig7(continued)

















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References
















































interpreted network

4 Discussion




































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References


































































negative data































Acknowledgements














References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References


References
















579 1878ndash1883




21 17ndash24


















1183ndash1189



5 101ndash113

















44 1998ndash2009













262ndash275


























93ndash105










52ndash67





















95 14863ndash14868













logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References










logists 84
















44 313ndash324




251ndash272








































161ndash170


















549 169ndash183










S145ndashS154





















































444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References
















444ndash448



1215ndash1217



































407 651ndash654





276 37206ndash37214
















101ndash113





103ndash110








1662ndash1664




73ndash82




































42 91ndash97






























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References























605ndash612
















415ndash421












2155ndash2157






































49ndash57






597ndash608



















38 187ndash195
































i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References











i264ndash i272


























MIT Press







29 1467ndash1472



1699ndash1700



161ndash171


























1189ndash1194









35669ndash35675





304 223ndash228









































23742ndash23747




111 863ndash870














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References














111 15ndash28


























549 185ndash193


















328ndash337









34 709ndash750





Introduction

Data available










Discussion

Acknowledgements

References

systems-adme/tox: resources and network approacheserdi/ekins2.pdf · development of ht methods,...

Documents