Fig. 2. Schematic overview of toxicogenomics versus established methods in toxicology. Despite having proven the concept by properly reflecting the results generated by several established methods for toxicity testing, the question remains, whether toxicogenomics might be able to provide additional knowledge with regards to problems, which currently cannot be addressed by the traditional methods.

2. Potential added value provided by toxicogenomics

The recent withdrawal of Vioxx (rofecoxib) from the worldwide market due to safety concerns clarifies once more that there is still a need for improvement of the current industrial strategies for the evaluation of safety of new drugs during their development. Obviously, the traditionally conducted safety assessments, although well-established and undoubtedly valuable, still fail to detect some adverse drug reactions that may potentially occur in humans. In this context, the high expectations laid in the application of “-omics” technologies in toxicology become clearer. By using toxicogenomics, more sensitive and thus earlier detection of potential adverse effects of compounds seemed to be within reach, as there is strong belief that alterations in the expression of genes would precede the manifestation of toxic outcome [31]. Analysis of gene expression patterns was furthermore assumed to help identifying drug–drug interactions [32] and to provide insight into the genetical circumstances, which form the basis of idiosyncratic toxicity [31] and [33]. Additionally, the speculations about using in vitro samples, especially from human cell cultures, or even human blood samples fuelled enthusiastic prospects of gaining authentic human-relevant information. The genome-wide comparison and extrapolation of expression patterns across several species seemed also feasible after the sequencing of the human and mouse genome have been practically completed in 2001 [34] and 2002 [35], respectively. Taken together, analysis of transcriptional alterations after toxic manipulation was expected to deliver various additional information supplementing (or even outdating?) the currently employed techniques in safety evaluation. Thus, after having proven the concept, toxicogenomics now faces the question, to what extent the demand for added value can truly be fulfilled (Fig. 2).

2.1. Sensitivity of toxicogenomics versus traditional endpoints

Histopathologic examination of paraffin-embedded organ sections serves as one of the “gold-standards” for detection of organ toxicity. Integrity of organs and especially effects on cellular subpopulations are routinely investigated by experienced pathologists. Nevertheless, microscopic evaluation of hundreds of organ sections is very time-consuming and toxic lesions have to become manifested for detection. Compound-related alterations at the molecular level preceding morphological findings also remain unseen. Thus, in order to be more sensitive, toxicogenomics should facilitate prediction of toxicity either at lower doses or prior to the appearance of morphological changes. Addressing this issue, some work groups employing toxicogenomics reported the identification of a toxic outcome due to compound treatment prior to its recognition by histopathology or clinical chemistry [18], [36] and [37]. For example Kier et al. [36] first identified a subset of genes, potentially predictive for the development of kidney lesions. Subsequently, by analysis of transcriptional regulation of these genes 24 h after treatment with cyclophosphamide or ganciclovir, the nephrotoxic outcome was successfully predicted previous to tubular necrosis being apparent earliest at 72 h after treatment. Although this looks very promising, one has to bear in mind that first all these studies were conducted with well-studied model compounds, where it was already known what to look for and second that histopathology was the standard on which the predictive models were built [15]. Additionally, it seems questionable, whether toxicogenomics could really save time and costs in such short-term studies, taking into account processing of tissue samples for microarray hybridization and especially subsequent analysis of transcript profiles. In contrast, when looking at life-time carcinogenicity studies, the potential savings of time and costs might be much more distinct. The publication of Ellinger-Ziegelbauer et al. [38] exemplified that toxicogenomic profiling of genotoxic carcinogens known to produce tumors in 2-year carcinogenicity studies, revealed genes and pathways indicative for beginning tumorigenesis already in short-term in vivo studies.

In conclusion, in vivo toxicogenomics might not be able to considerably accelerate safety prediction in acute short-term studies and the detection of sub-organ-specific toxicity will also remain challenging for at least 5% of the cells in an organ homogenate need to be affected in order facilitate detection of alterations by gene expression profiling [39]. Nevertheless, there is good evidence that in terms of early detection of toxic events, which usually take time to develop, such as carcinogenesis, toxicogenomic approaches might prove very valuable. Additionally, there is still hope that toxicogenomics might facilitate the detection of toxicity already at lower doses than those leading to the development of manifest lesions visible in histopathology. This would predestine the use of toxicogenomics in very early stages of drug development, when the amount of compound is still limited. Unfortunately, published investigations addressing this issue are missing so far.

2.2. Detection and prediction of idiosyncratic toxicity

Unexpected adverse drug reactions, which do not involve any of its known pharmacological properties and which furthermore occur randomly and usually dose-independently in patients, are commonly referred to as “idiosyncratic” effects. The reasons rendering a compound liable to a high incidence of idiosyncratic reactions in patients are not yet understood. However, there have been several speculations about factors possibly increasing the likelihood of drugs to induce such reactions. Formation of reactive metabolites and induction of cellular stress or immune responses have been suggested, although none of these theories has ever been proven. Additionally, it appears that not only the properties of the compound are responsible for the development of idiosyncratic reactions, but there is also some kind of predisposition existing among susceptible individuals. Unfortunately, suitable animal models for studying idiosyncratic reactions are lacking so far [40]. Orphanides and Kimber [33] have suggested that the use of microarray-based single nucleotide polymorphism (SNP)-mapping approaches might identify the genetic circumstances associated with a high susceptibility of individuals to develop idiosyncratic adverse drug responses. Furthermore, Uetrecht [41] speculated that compounds with a high incidence of such effects might induce specific and predictive gene expression patterns even in animals or patients who do not develop idiosyncratic reactions. Despite the fact that toxicogenomics might certainly have the power to shed light on the mechanism underlying the idiosyncratic toxicity of single compounds such as trovafloxacin [42], the hope for using toxicogenomics technologies to predict the likelihood of a compound for causing these unspecific toxic reactions, must still be considered as very challenging.

2.3. Multi-chemical exposures and drug–drug interactions

In addition to adverse drug reactions exhibited by single compounds, the interaction of multiple drugs when taken by a patient in combination, remain mainly unpredictable and have been a major reason for the withdrawal of drugs from the market. Aardema and MacGregor [32] suggested the use of toxicogenomics in unveiling the effects of multi-drug exposures. Synergistic, antagonistic or additive effects might be reflected in the gene expression profiles induced by compound mixtures when compared to the profiles of the single chemicals. But taking into account the difficulties already associated with the analysis and interpretation of gene expression data derived from single compound exposures, the extraction of useful information out of multiple-chemical profiles might turn out to be even more challenging. Thus, the application of toxicogenomic approaches to successfully predict drug–drug interactions is still in its infancy.

2.4. Extrapolation of toxicity information across species

In drug development toxicologists have always been faced with the same dilemma: safety assessment of new compounds cannot be done by just testing on people. Experimental in vitro and in vivo animal models are needed as a substitute to evaluate the safety risk for humans, although only 71% of all human toxicities can be accurately predicted by using animal models [43] and [44]. At least in part this can be ascribed to species-specific differences in pharmacokinetic handling of the compounds [44]. The example of peroxisome proliferator-activating receptor agonists, which cause carcinogenicity in rats and mice, but have appeared to be “clean” in primates and humans so far [45], [46] and [47], additionally questions the suitability of animals as surrogates for humans.

With this in mind, it is not surprising that great hope was laid into toxicogenomics as a tool for reliable across-species extrapolations [32] and [48]. In 2001, sequencing of the human genome has finally been completed by the human genome project [34] soon followed by the completion of the mouse genome [35] and a first draft sequence of the rat genome [49]. These achievements additionally supported the hope for genome-wide comparisons of expression profiles across species to facilitate the explanation of species-derived differences in the response to compound treatment. Gene Logic, Inc., for example have built a rat gene expression profile database by using compounds supposed to be toxic or non-toxic in humans in order to predict human toxicity. However, considering the long development times for new drugs, the availability of this database has possibly been too short to evaluate its benefit properly.

A study conducted in our laboratories provided evidence that at least in some cases it might be possible to predict toxicity across species [37]. Three different antidiabetic compounds were investigated in short-term rat studies. Histopathology declared two of these compounds being steatotic, whereas the third one did not cause any visible signs of hepatotoxicity. In contrast, a SVM-based analysis of the rat gene expression profiles (for details regarding SVM training and optimization of parameters see [15]) classified all three compounds as steatotic. Follow-up studies truly identified the third compound as steatotic in dogs with histopathology showing liver necrosis and microsteatosis. Likewise, all three compounds produced an increase in intracellular triglyceride content of rat hepatocytes. In order to determine the human relevance of these results further confirmatory experiments are certainly needed.

Although additional evidence for successful inter-species extrapolations is missing so far, toxicogenomics undoubtedly provides valuable information about the toxic mode of action of a compound in different species, which in the long-term automatically improves our understanding of inter-species relations.

2.5. Potential applicability of toxicogenomics to non-invasive toxicity assessment

In general, mRNA derived from of tissue or biopsy samples from animals or patients are processed and hybridized for microarray analysis. In order to assess the safety of new drug candidates much earlier in development, it is crucial to facilitate the use of non-invasive methods for sample collection. These methods would typically include the use of in vitro systems or blood samples. The use of blood samples would allow multiple sampling from the same animal and maybe even the translation of preclinical findings to a clinical setting. Employment of in vitro systems would be largely valuable especially with regard to the establishment of high-throughput toxicity screens very early in drug development. Cell culture systems offer the advantages of quick and easy handling, low cost, and may reduce the number of laboratory animals needed in early safety assessment. Additionally, the utilization of human cell lines or human primary cells might help to generate more human-relevant data. There have already been numerous approaches applying in vitro methods to toxicogenomics [50], [51] and [52], but only few addressing the correlation between in vitro and in vivo data [21] and [53].

In vitro systems are usually subject to various limitations when compared to the whole organism. Recently, a study conducted in our laboratories investigated the resemblance of gene expression profiles derived from two hepatic rat cell lines, primary rat hepatocytes cultured under different conditions, rat liver slices and rat liver [53]. The results indicated that although the cell lines showed only little comparability with whole liver expression profiles, the correlation coefficients of hepatocytes shortly after isolation versus whole liver (0.88) and of fresh liver slices versus whole liver (0.95) were quite high. In contrast, with more time elapsing between isolation of cells or preparation of slices and harvesting of RNA for microarray analysis, the correlation coefficients decreased rapidly due to dedifferentiation. On the other hand, the variation between gene expression profiles of replicate preparations was most distinct immediately after isolation, whereas after adaptation to the culture conditions the profiles became more stable.

Another study investigating the mechanisms underlying Ochratoxin A-induced nephrotoxicity in rats in vivo and in vitro [21] showed good comparability of transcriptional changes observed in vitro and in vivo. Some minor discrepancies between cell culture and rat kidney expression profiles could be traced back almost entirely to the fact that the in vitro system included only proximal tubule cells, whereas the whole kidney resembles a heterogeneous complex of various cell types, which are furthermore subject to nervous and hormonal regulation. The results of these studies strongly support the application of in vitro models to toxicogenomics; however, obtaining a profound knowledge of the limitations of the particular in vitro system is essential and must be incorporated into the interpretation of the results.

The use of blood from human donors for gene expression analysis is also highly desirable in order to investigate treatment-related transcriptional changes without invasive sample collection. The publication by Whitney et al. [54] provided strong support for the use of peripheral blood for detection of infection and disease. Additionally, Lampe et al. [55] showed that exposure to tobacco smoke is associated with specific transcriptional signatures in human blood. These observations led to the hypothesis that gene expression profiling of blood samples might also reflect compound-related organ toxicity in patients and prove highly valuable in the diagnosis of treatment-related toxicity as well as in the identification of non-responders. Additionally, the identification of surrogate markers predictive for organ toxicity seemed feasible. In order to further evaluate these hypotheses, we started to assess the potential to predict organ toxicity based on blood gene expression profiles derived from rats treated with model toxicants. A supervised learning algorithm (for details regarding SVM training and optimization of parameters see [15]) was trained with blood gene expression data derived from rats treated with 17 model hepato- or nephrotoxicants and optimized for discrimination of toxic and non-toxic profiles (unpublished data). Cross-validation of the training set revealed virtually no false positives (99% specificity), but at the expense of a relatively high rate of false negatives (56% sensitivity). Nevertheless, the accuracy of classifying samples derived from toxic treatment as “toxic” and samples derived from non-toxic treatment as “non-toxic” reached considerable 86%. The following example of Puromycin, a well-described nephrotoxicant, highlights the possible value of blood profiling in safety assessment (unpublished data).

Rats were treated with 10 mg/kg Puromycin and 150 mg/kg Puromycin, respectively (killing of animals 24 and 168 h thereafter). Histopathology showed only very minor findings in the livers of the 10 mg/kg groups at both time points, but major findings in livers of all animals of the high dose groups. No morphological changes were observed in any of the Puromycin-treated kidneys except in the high dose group after 168 h. Classification of the blood gene expression profiles by the previously trained SVM algorithm (high dose group at 168 h was included in the training set, whereas the other groups were used as blinded test sets) perfectly reflected the histopathological findings. Moreover, one animal was detected as outlier, which paralleled the corresponding clinical chemistry data (Fig. 3). These results are still preliminary and in order to increase sensitivity of the prediction model and to facilitate the prediction of toxicity of specific organs, a lot of additional data are required. Nevertheless, this approach comprises promising starting points for future applications of toxicogenomics including for example the identification of surrogate markers for organ toxicity in humans.

Fig. 3. SVM Analysis of blood gene expression profiles derived from rats treated with vehicle control, with 10 mg/kg Puromycin and sacrificed after 24 or 168 h, respectively, or with 150 mg/kg Puromycin and sacrificed after 24 h. In each group, the expression profiles of five rats were analyzed by employing an SVM algorithm trained and cross-validated for discrimination between toxic and non-toxic treatment using parameters described in detail in [15]. A positive discriminant value indicates toxic treatment, whereas a negative discriminant value indicates non-toxic treatment.

3. Summary and outlook

For several years toxicogenomics enjoyed the privilege of being considered an emerging new technology, which has high potential to revolutionize drug and chemical safety assessment. With growing experience gained by industrial, government and academic institutions more and more possible caveats have been uncovered and it became clear that the great hopes laid in gene expression profiling appeared overoptimistic to a certain extent. Several publications evaluated in this review have impressively corroborated the use of toxicogenomics for the prediction of toxic liabilities, for the investigation of toxic mechanisms and for the identification of biomarkers of toxicity. Compound-related changes in transcriptional activity were successfully linked to histopathological findings. Moreover, with enormous help from bioinformaticians and toxicologists, toxicogenomic approaches have settled on a sound basis for the investigation of hepatotoxicity and nephrotoxicity in rats with remarkable potential for extrapolation to humans.

Despite having proven its usefulness in reflecting existing methods for toxicity testing, the demand for providing additional knowledge (added value) has not yet been satisfied adequately. Goals included detection of toxicity earlier or at lower doses than by using traditional endpoints. Prediction of idiosyncratic toxicity or drug–drug interaction, correlation of results from in vitro to in vivo systems and especially extrapolation of toxic liabilities to humans were claimed to be within reach, but so far only few results support the practicability of these approaches. The first promising data from experiments using rat blood samples for prediction of organ toxicity raise hope that in future non-invasive sample collection would facilitate easier monitoring of patients in clinical trials and better evaluation of not only drug toxicity, but also efficacy in humans. However, this approach still suffers from several drawbacks and major efforts aim at the further development of mathematical and biological tools in order to make sense of the flood of data. With regards to the interpretation of microarray data in general, especially the diversity of platforms available on the market represents a challenge in terms of comparability of the results. First steps have been made in setting standards for design and conduct of microarray experiments (MIAME), but due to the lack of common agreement on how to analyze and interpret gene expression data, conclusions drawn from such experiments may vary tremendously. The recent release of a draft guidance on submission of pharmacogenomics data to the Food and Drug Administration (FDA; http://www.fda.gov) and several other publications discussing the regulatory view of gene expression data [56] and [57] demonstrate that “-omics” technologies have come into focus of the regulatory agencies and might influence their decision making in future. Currently, we can look back on various success stories where toxicogenomics has proven its comparability to histopathology and clinical chemistry. There is considerable evidence that gene expression profiling might even provide essential information about new drug candidates which could not be addressed by using classical endpoints so far. Thus, toxicogenomics might have the potential of leading to a paradigm-shift in safety assessment of compounds. Nevertheless, this remains challenging and much work still needs to be done.

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