1. Toxicology Letters 140 Á/141 (2003) 145 Á/148
www.elsevier.com/locate/toxlet
Review
Toxicogenomics: challenges and opportunities
G. Orphanides *
Syngenta Central Toxicology Laboratory, Alderley Park, Macclesfield, Cheshire SK10 4TJ, UK
Received 15 September 2002; accepted 12 December 2002
Abstract
Toxicogenomics describes the measurement of global gene expression changes in biological samples exposed to
toxicants. This new technology promises to greatly facilitate research into toxicant mechanisms, with the possibility of
assisting in the detection of compounds with the potential to cause adverse health effects earlier in the development of
pharmaceutical and chemical products. In this short review, I discuss the opportunities presented by toxicogenomics,
the challenges we face in the application of these tools, and the progress we have made in realising the potential of these
new genomic approaches.
# 2003 Elsevier Science Ireland Ltd. All rights reserved.
Keywords: Toxicogenomics; Microarrays; Mechanistic toxicology; Predictive toxicology
1. Introduction these new tools to advance their discipline and a
new field was born. The application of gene
The publication of the draft sequence of the expression profiling to toxicology, termed toxico-
human genome almost 2 years ago signalled the genomics, presents us with opportunities to define,
arrival of the genomic era of the biological sciences at unprecedented levels of detail, the molecular
(International Human Genome Sequencing Con- events that precede and accompany toxicity,
sortium, 2001). This newfound knowledge accel- promising to shed light on toxic mechanisms that
erated the development of tools that allow are presently poorly understood (Afshari et al.,
biological processes to be examined on a global 1999; Farr and Dunn, 1999; Nuwasyr et al., 1999;
scale. Among these tools are those that facilitate Pennie, 2000; Pennie et al., 2000; Orphanides et al.,
the simultaneous measurement of the expression 2001; Gant, 2002; Ulrich and Friend, 2002).
levels of thousands of different genes, technologies Moreover, it is hoped that gene expression changes
known collectively as gene expression profiling induced upon chemical exposure will provide a
(Duggan et al., 1999; Brown and Botstein, 1999). means of predicting mechanisms of toxicity more
Toxicologists quickly realised the potential of rapidly.
Used in conjunction with existing tools available
* Tel.: '/44-1625-510803; fax: '/44-1625-590249.
to the toxicologist, toxicogenomics promises sig-
E-mail address: george.orphanides@syngenta.com (G. nificant advances in research and investigative
Orphanides). toxicology. These advances include:
0378-4274/03/$ - see front matter # 2003 Elsevier Science Ireland Ltd. All rights reserved.
doi:10.1016/S0378-4274(02)00500-3

2. 146 G. Orphanides / Toxicology Letters 140 Á/141 (2003) 145 Á/148
. a more detailed appreciation of molecular used successfully to predict chemical activity. The
mechanisms of toxicity. most comprehensive study of this kind involved a
. faster screens for substance toxicity. combination of chemical treatments and mutant
. enhanced extrapolation between experimental strains of the yeast Saccharomyces cerevisiae to
animals and humans in the context of risk generate a gene expression database capable of
assessment. predicting the biological effects of exogenous
compounds (Hughes et al., 2000).
In this article, I discuss the use of toxicoge- Two recent studies indicate that toxicogenomics
nomics in mechanistic and predictive toxicology. can be used to predict chemical mode of action in
In particular, I examine how far we have come toxicologically relevant species (Waring et al.,
towards realising the full potential of these tools. 2001; Hamadeh et al., 2002). These reports de-
monstrate that the liver gene expression profiles
associated with exposure of rats to different
2. Use of toxicogenomics to predict mechanisms of hepatotoxins segregate according to mechanisms
toxicity of toxicity. Thus, it appears that the assertion that
toxicogenomics has the potential to provide en-
A goal of modern toxicology is to protect the hanced methods for predicting toxicity is well
human population from exposure to harmful founded. The rodent liver is ideally suited for
substances by identifying compounds with the demonstrating proof of principle: the hepatocyte is
potential to cause toxicity. Most current testing the predominant cell type, therefore hepatotoxic
strategies measure the effects of long-term chemi- chemicals will induce mechanistically linked gene
cal exposure in experimental animals. Through the expression changes in the majority of cells that
identification of gene expression changes asso- make up the organ. However, many toxicants
ciated with chemical exposure, the hope is that target only a small proportion of cells in an organ.
toxicogenomics will facilitate the development of A challenge for the future application of toxico-
methods that predict the long-term effects of genomics in a predictive context is the identifica-
compounds using short-term assays. The under- tion of diagnostic gene expression changes
lying assumption is that compounds that induce originating from cells that represent a minority
toxicity through similar mechanisms will elicit population. Nevertheless, it appears that this
comparable changes in gene expression. It is, general approach holds much promise.
therefore, possible that toxicant-induced expres-
sion changes will act as sensitive and specific
indicators of toxic mechanism. In this way, gene
expression ‘fingerprints’ can be identified for 3. Toxicogenomics as a mechanistic tool
multiple mechanisms of toxic insult and entered
into a database. The gene expression profile of a The global analysis of gene expression levels has
suspected toxicant can then be analysed for found many diverse applications in modern biol-
similarity with the expression fingerprints of ogy. A particular strength of this approach as
known toxicants. applied to toxicology is that it is holistic and,
The predictive capacity of gene expression therefore, provides an unbiased view of alterations
profiling has been demonstrated most compel- in cellular processes associated with chemical
lingly in a clinical setting. A number of studies insult. In this regard, global gene expression
have reported the classification of tumour type profiling is an ideal tool for hypothesis generation
using transcript profiling (reviewed by Clarke et in the context of mechanistic toxicology. Indivi-
al., 2001). For example, van’t Veer et al. (2002) dual genes, or entire pathways, implicated in a
identified a gene expression ‘fingerprint’ capable of mechanism of toxicity using this technology can be
distinguishing metastatic and non-metastatic further evaluated using more conventional ap-
breast tumours. This approach has also been proaches.

3. G. Orphanides / Toxicology Letters 140 Á/141 (2003) 145 Á/148 147
A major challenge in the application of gene toxicology data (e.g. biochemical, clinical and
expression technologies to mechanistic toxicology histopathological data) can greatly facilitate the
is the identification of gene regulation events interpretation of toxicogenomic data. A successful
linked directly to the mode of toxicity under toxicogenomic study will, therefore, be multi-
investigation. Successful application of toxicoge- disciplinary, requiring the expert skills of the
nomics in this context requires an understanding toxicologist, pathologist and molecular biologist
of the link between gene expression changes and (Orphanides et al., 2001).
phenotype (Smith, 2001). The simultaneous mea-
surement of changes in the expression levels of tens
of thousands of genes is now becoming routine.
4. Conclusions
However, the increase in the rate at which gene
expression data can be generated has not been
Toxicogenomics is an evolving science. We have
accompanied by corresponding advances in our
witnessed many successes of the genomic sciences
ability to interpret them as biologically meaningful
in other fields of biology, and these tools are now
information.
beginning to enhance our ability to understand
Any given toxicant is likely to induce alterations
and predict mechanisms of toxicity. It is likely that
in the expression levels of many different genes,
toxicogenomics, along with other global profiling
and only some of these genes will play a role in the
tools such as proteomics (Pandey and Mann, 2000)
mechanism of toxicity. Appropriate experimental
and metabonomics (Nicholson et al., 2002), will
design can facilitate the identification of relevant
revolutionise research and investigative toxicol-
gene changes. For example, the use of animal
ogy, leading to a holistic appreciation of molecular
models in which pathways relevant to the mode of
responses to toxicants. However, there is still a
action have been inactivated or modified can aid
long way to go before the full potential of
the identification of gene expression changes
toxicogenomics is realised. The sheer weight of
directly linked to the molecular mechanism of a
data generated by gene expression profiling can be
toxicant. Transgenic ‘knock-out’ mice resistant to
overwhelming. Extraction of value from this data
the toxic effects of the compound being studied
will be facilitated by the development of toxicoge-
can be used to identify genes whose regulation is
nomic databases capable of being interrogated by
not directly related to the development of toxicity.
expert and non-expert user alike. Moreover, the
Changes in gene expression seen in these knock-
identification of gene expression changes of pre-
out mice exposed to toxicant are unlikely to be
dictive value or mechanistic significance often
linked to the adverse effects of the compound.
requires the use of sophisticated computational
Therefore, any changes in gene expression that
tools, which will evolve alongside gene expression
occur in a sensitive wild-type animal, but not in a
methodologies (Bassett et al., 1999). One thing we
resistant knock-out animal, are more likely to be
can be confident about is that the tools of the
directly associated with the mechanism of toxicity.
genomic era are here to stay. The toxicologist of
While, not all gene expression changes that match
the future may feel equally at home with a
this description will be directly involved in the
toxicogenomic data set as with a histopathology
mode of action of a toxicant, this strategy focuses
slide.
attention on the most likely candidates. This
approach as been used to implicate the lactoferrin
protein in the mechanism of rodent non-genotoxic
hepatocarcinogenesis induced by peroxisome pro- Acknowledgements
liferators (Hasmall et al., 2002).
Toxicant-induced gene expression changes are I thank Drs Ian Kimber and Jonathan Moggs
often difficult to interpret in isolation. Careful for critical comments on this article and apologise
selection of compound dose and time of exposure to those authors whose work I have not cited due
and the concurrent collection of conventional to limitations on article length.

4. 148 G. Orphanides / Toxicology Letters 140 Á/141 (2003) 145 Á/148
References Friend, S.H., 2000. Functional discovery via a compendium
of expression profiles. Cell 102, 109 Á/126.
Afshari, C.A., Nuwaysir, E.F., Barrett, J.C., 1999. Application International Human Genome Sequencing Consortium, Initial
of complementary DNA microarray technology to carcino- sequencing and analysis of the human genome, Nature 409
gen identification, toxicology, and drug safety evaluation. (2001) 860 Á/922.
Cancer Res. 59, 4759 Á/4760. Nicholson, J.K., Connelly, J., Lindon, J.C., Holmes, E., 2002.
Bassett, D.E., Eisen, M.B., Boguski, M.S., 1999. Gene expres- Metabonomics: a platform for studying drug toxicity and
sion informatics */it’s all in your mine. Nat. Gen. 21 gene function. Nat. Rev. Drug Disc. 1, 153 Á/161.
(supplement), 51 Á/55. Nuwasyr, E.F., Bittner, M., Trent, J., Barrett, J.C., Afshari,
Brown, P.O., Botstein, D., 1999. Exploring the new world of C.A., 1999. Microarrays and toxicology: the advent of
the genome with DNA microarrays. Nat. Gen. 21 (supple- toxicogenomics. Mol. Carcinogen. 24, 153 Á/159.
ment), 33 Á/37. Orphanides, G., Pennie, W.D., Moffat, G.J., Kimber, I., 2001.
Clarke, P.A., te Poele, R., Wooster, R., Workman, P., 2001. Toxicogenomics: theoretical and practical considerations.
Gene expression microarray analysis in cancer biology, Comm. Toxicol. 7, 333 Á/346.
pharmacology and drug development: progress and poten- Pandey, A., Mann, M., 2000. Proteomics to study genes and
tial. Biochem. Pharmacol. 62, 1311 Á/1336. genomes. Nature 405, 837 Á/846.
Duggan, D.J., Bittner, M., Chen, Y., Meltzer, P., Trent, J., Pennie, W.D., 2000. Use of cDNA microarrays to probe and
1999. Expression profiling using cDNA microarrays. Nat. understand the toxicological consequences of altered gene
Gen. 21 (supplement), 10 Á/14. expression. Toxicol. Lett. 112 Á/113, 473 Á/477.
Farr, S., Dunn, R.T., II, 1999. Concise review: gene expression Pennie, W.D., Tugwood, J.D., Oliver, G.J.A., Kimber, I., 2000.
applied to toxicology. Toxicol. Sci. 50, 1 Á/9. The principles and practice of toxicogenomics: applications
Gant, T.W., 2002. Classifying toxicity and pathology by gene- and opportunities. Toxicol. Sci. 54, 277 Á/283.
expression profile */taking a lead from studies in neoplasia. Smith, L.L., 2001. Key challenges for toxicologists in the 21st
Trends Pharm. Sci. 23, 388 Á/393. century. Trends Pharmacol. Sci. 22, 281 Á/285.
Hamadeh, H.K., Bushel, P.R., Jayadev, S., DiSorbo, O., Ulrich, R., Friend, S.H., 2002. Toxicogenomics and drug
Bennett, L., Li, L., Tennant, R., Stoll, R., Barrett, J.C., discovery: will new technologies help us produce better
Paules, R.S., Blanchard, K., Afshari, C.A., 2002. Prediction
drugs? Nat. Rev. Drug Disc. 1, 84 Á/88.
of compound signature using high density gene expression
van’t Veer, L.J., Dai, H., van de Vijver, M.J., He, Y.D., Hart,
profiling. Toxicol. Sci. 67, 232 Á/240.
A.A.M., Mao, M., Peterse, H.L., van der Kooy, K.,
Hasmall, S., Orphanides, G., James, N., Pennie, W., Hedley,
Marton, M.J., Witteveen, A.T., Schreiber, G.J., Kerkhoven,
K., Soames, A., Kimber, I., Roberts, R., 2002. Down-
R.M., Roberts, C., Linsley, P.S., Bernards, R., Friend, S.H.,
regulation of lactoferrin by PPARalpha ligands: role in
perturbation of hepatocyte proliferation and apoptosis. 2002. Gene expression profiling predicts clinical outcome of
Toxicol. Sci. 68, 304 Á/313. breast cancer. Nature 415, 530 Á/536.
Hughes, T.R., Marton, M.J., Jones, A.R., Roberts, C.J., Waring, J.F., Jolly, R.A., Ciurlionis, R., Lum, P.Y., Praes-
Stoughton, R., Armour, C.D., Bennett, H.A., Coffey, E., gaard, J.T., Morfitt, D.C., Buratto, B., Roberts, C., Schadt,
Dai, H., He, Y.D., Kidd, M.J., King, A.M., Meyer, M.R., E., Ulrich, R.G., 2001. Clustering of hepatotoxins based on
Slade, D., Lum, P.Y., Stapaniants, S.B., Shoemaker, D.D., mechanism of toxicity using gene expression profiles.
Gachotte, D., Chakraburtty, K., Simon, J., Bard, M., Toxicol. Appl. Pharmacol. 175, 28 Á/42.