Download - Toxicogenomics review
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
The publication of the draft sequence of the
human genome almost 2 years ago signalled the
arrival of the genomic era of the biological sciences
(International Human Genome Sequencing Con-
sortium, 2001). This newfound knowledge accel-
erated the development of tools that allow
biological processes to be examined on a global
scale. Among these tools are those that facilitate
the simultaneous measurement of the expression
levels of thousands of different genes, technologies
known collectively as gene expression profiling
(Duggan et al., 1999; Brown and Botstein, 1999).
Toxicologists quickly realised the potential of
these new tools to advance their discipline and a
new field was born. The application of gene
expression profiling to toxicology, termed toxico-
genomics, presents us with opportunities to define,
at unprecedented levels of detail, the molecular
events that precede and accompany toxicity,
promising to shed light on toxic mechanisms that
are presently poorly understood (Afshari et al.,
1999; Farr and Dunn, 1999; Nuwasyr et al., 1999;
Pennie, 2000; Pennie et al., 2000; Orphanides et al.,
2001; Gant, 2002; Ulrich and Friend, 2002).
Moreover, it is hoped that gene expression changes
induced upon chemical exposure will provide a
means of predicting mechanisms of toxicity more
rapidly.
Used in conjunction with existing tools available
to the toxicologist, toxicogenomics promises sig-
nificant advances in research and investigative
toxicology. These advances include:
* Tel.: �/44-1625-510803; fax: �/44-1625-590249.
E-mail address: [email protected] (G.
Orphanides).
Toxicology Letters 140�/141 (2003) 145�/148
www.elsevier.com/locate/toxlet
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doi:10.1016/S0378-4274(02)00500-3
. a more detailed appreciation of molecularmechanisms of toxicity.
. faster screens for substance toxicity.
. enhanced extrapolation between experimental
animals and humans in the context of risk
assessment.
In this article, I discuss the use of toxicoge-
nomics in mechanistic and predictive toxicology.
In particular, I examine how far we have come
towards realising the full potential of these tools.
2. Use of toxicogenomics to predict mechanisms of
toxicity
A goal of modern toxicology is to protect the
human population from exposure to harmfulsubstances by identifying compounds with the
potential to cause toxicity. Most current testing
strategies measure the effects of long-term chemi-
cal exposure in experimental animals. Through the
identification of gene expression changes asso-
ciated with chemical exposure, the hope is that
toxicogenomics will facilitate the development of
methods that predict the long-term effects ofcompounds using short-term assays. The under-
lying assumption is that compounds that induce
toxicity through similar mechanisms will elicit
comparable changes in gene expression. It is,
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 formultiple mechanisms of toxic insult and entered
into a database. The gene expression profile of a
suspected toxicant can then be analysed for
similarity with the expression fingerprints of
known toxicants.
The predictive capacity of gene expression
profiling has been demonstrated most compel-
lingly in a clinical setting. A number of studieshave reported the classification of tumour type
using transcript profiling (reviewed by Clarke et
al., 2001). For example, van’t Veer et al. (2002)
identified a gene expression ‘fingerprint’ capable of
distinguishing metastatic and non-metastatic
breast tumours. This approach has also been
used successfully to predict chemical activity. Themost comprehensive study of this kind involved a
combination of chemical treatments and mutant
strains of the yeast Saccharomyces cerevisiae to
generate a gene expression database capable of
predicting the biological effects of exogenous
compounds (Hughes et al., 2000).
Two recent studies indicate that toxicogenomics
can be used to predict chemical mode of action intoxicologically relevant species (Waring et al.,
2001; Hamadeh et al., 2002). These reports de-
monstrate that the liver gene expression profiles
associated with exposure of rats to different
hepatotoxins segregate according to mechanisms
of toxicity. Thus, it appears that the assertion that
toxicogenomics has the potential to provide en-
hanced methods for predicting toxicity is wellfounded. The rodent liver is ideally suited for
demonstrating proof of principle: the hepatocyte is
the predominant cell type, therefore hepatotoxic
chemicals will induce mechanistically linked gene
expression changes in the majority of cells that
make up the organ. However, many toxicants
target only a small proportion of cells in an organ.
A challenge for the future application of toxico-genomics in a predictive context is the identifica-
tion of diagnostic gene expression changes
originating from cells that represent a minority
population. Nevertheless, it appears that this
general approach holds much promise.
3. Toxicogenomics as a mechanistic tool
The global analysis of gene expression levels has
found many diverse applications in modern biol-
ogy. A particular strength of this approach as
applied to toxicology is that it is holistic and,
therefore, provides an unbiased view of alterations
in cellular processes associated with chemical
insult. In this regard, global gene expressionprofiling is an ideal tool for hypothesis generation
in the context of mechanistic toxicology. Indivi-
dual genes, or entire pathways, implicated in a
mechanism of toxicity using this technology can be
further evaluated using more conventional ap-
proaches.
G. Orphanides / Toxicology Letters 140�/141 (2003) 145�/148146
A major challenge in the application of geneexpression technologies to mechanistic toxicology
is the identification of gene regulation events
linked directly to the mode of toxicity under
investigation. Successful application of toxicoge-
nomics in this context requires an understanding
of the link between gene expression changes and
phenotype (Smith, 2001). The simultaneous mea-
surement of changes in the expression levels of tensof thousands of genes is now becoming routine.
However, the increase in the rate at which gene
expression data can be generated has not been
accompanied by corresponding advances in our
ability to interpret them as biologically meaningful
information.
Any given toxicant is likely to induce alterations
in the expression levels of many different genes,and only some of these genes will play a role in the
mechanism of toxicity. Appropriate experimental
design can facilitate the identification of relevant
gene changes. For example, the use of animal
models in which pathways relevant to the mode of
action have been inactivated or modified can aid
the identification of gene expression changes
directly linked to the molecular mechanism of atoxicant. Transgenic ‘knock-out’ mice resistant to
the toxic effects of the compound being studied
can be used to identify genes whose regulation is
not directly related to the development of toxicity.
Changes in gene expression seen in these knock-
out mice exposed to toxicant are unlikely to be
linked to the adverse effects of the compound.
Therefore, any changes in gene expression thatoccur in a sensitive wild-type animal, but not in a
resistant knock-out animal, are more likely to be
directly associated with the mechanism of toxicity.
While, not all gene expression changes that match
this description will be directly involved in the
mode of action of a toxicant, this strategy focuses
attention on the most likely candidates. This
approach as been used to implicate the lactoferrinprotein in the mechanism of rodent non-genotoxic
hepatocarcinogenesis induced by peroxisome pro-
liferators (Hasmall et al., 2002).
Toxicant-induced gene expression changes are
often difficult to interpret in isolation. Careful
selection of compound dose and time of exposure
and the concurrent collection of conventional
toxicology data (e.g. biochemical, clinical andhistopathological data) can greatly facilitate the
interpretation of toxicogenomic data. A successful
toxicogenomic study will, therefore, be multi-
disciplinary, requiring the expert skills of the
toxicologist, pathologist and molecular biologist
(Orphanides et al., 2001).
4. Conclusions
Toxicogenomics is an evolving science. We have
witnessed many successes of the genomic sciencesin other fields of biology, and these tools are now
beginning to enhance our ability to understand
and predict mechanisms of toxicity. It is likely that
toxicogenomics, along with other global profiling
tools such as proteomics (Pandey and Mann, 2000)
and metabonomics (Nicholson et al., 2002), will
revolutionise research and investigative toxicol-
ogy, leading to a holistic appreciation of molecularresponses to toxicants. However, there is still a
long way to go before the full potential of
toxicogenomics is realised. The sheer weight of
data generated by gene expression profiling can be
overwhelming. Extraction of value from this data
will be facilitated by the development of toxicoge-
nomic databases capable of being interrogated by
expert and non-expert user alike. Moreover, theidentification of gene expression changes of pre-
dictive value or mechanistic significance often
requires the use of sophisticated computational
tools, which will evolve alongside gene expression
methodologies (Bassett et al., 1999). One thing we
can be confident about is that the tools of the
genomic era are here to stay. The toxicologist of
the future may feel equally at home with atoxicogenomic data set as with a histopathology
slide.
Acknowledgements
I thank Drs Ian Kimber and Jonathan Moggs
for critical comments on this article and apologise
to those authors whose work I have not cited due
to limitations on article length.
G. Orphanides / Toxicology Letters 140�/141 (2003) 145�/148 147
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