Diferencias entre análisis vertical y horizontal

Traditional toxicological studies, e.g. the 2-year carcinogenicity rodent study, are time consuming and expensive together with a high requirement for laboratory animals. They focus on evaluating classical endpoints like gain of body- or organ-weight, death rate, tumour incidence, serum markers or histological changes, making safety assessment one of the bottlenecks in the pharmaceutical drug developmental process. New methods and processes like genomics, proteomics, lipidomics or metabonomics are being used to improve the drug development process (Ballet, 1997; Brandon et al., 2003) and the “-omics” field is rapidly growing. Toxicogenomics is defined as a scientific sub-discipline that combines toxicology (the study of the nature and effects of poisons) with genomics (the investigation of the way that our genetic make-up, the genome, translates into biological functions). It is the study of the structure and output of the genome as it responds to adverse xenobiotic exposure and the identification of their putative mechanisms of action. The analysis of changes in gene expression caused by exposure to a test-compound together with strong bioinformatics and

profiles (Hamadeh et al., 2002a; 2002b; Zidek et al., 2007; Ellinger-Ziegelbauer et al., 2004). Several open source or commercial attempts (e.g., GENELOGIC (USA), ICONIX Biosciences Inc. (USA)) have been made to develop databases based on expression profiles of reference compounds in order to classify chemicals. It should not be forgotten that many internal databases in the pharmaceutical industry are only used for in house purposes and are not made accessible to the public (Mattes et al., 2004). There are several statistical methods to discriminate compounds on the basis of their gene expression profiles, some of which are discussed later (Page 33). In principle, they try to find single genes or gene sets that can discriminate between different treatment groups. These highly informative gene clusters can then be used to predict the class membership of a new unknown sample (Hamadeh et al., 2002a; Simon et al., 2003). The reported results are very encouraging but also show the need for large gene expression databases and effective analysis models to allow their future implementation into the drug development process.

Mechanistic studies are performed to increase the understanding of the function and regulation of genes that lead to compound specific toxicity. In most cases, the changes in gene and protein expression precede the physiological effects. This means that there is a great potential to extrapolate from changes in gene expression to long term toxicological endpoints such as liver necrosis, inflammation, steatosis or tumour neogenesis (Pennie, 2000; Burchiel et al., 2001; Fielden & Zacharewski, 2001). The detection of both the underlying mechanism of toxicity and the molecular basis of the response to exposure in an early stage of drug development will have a great impact on safety evaluation. Recent studies showed the possibility to define different toxic mechanisms, including tumour formation, inflammatory effects, oxidative stress, impairment of cellular signalling and induction of apoptosis (Bulera et al., 2001; Lettieri, 2006). Warring and his coworkers have shown a correlation between a physiological response to a toxicant and changes in the genomic profile, allowing the interpretation of gene expression data with respect to specific organotypic endpoints. This concept is referred to as “phenotypic anchoring” (Waring et al., 2001; Orphanides, 2003).

There have been numerous attempts to find new biomarkers for the early identification of hepatocarcinogenesis with the use of toxicogenomics and proteomics methods (Ellinger-Ziegelbauer et al., 2004; Fella et al., 2005). There is hope that these new methods will make it possible to detect intrinsic changes in the molecular pattern (“genetic fingerprint”) that are indicative of the pathological endpoint before he becomes histopathologically detectable (Aardema & MacGregor, 2002). Besides the improvement of the drug development process, this could also facilitate a considerable reduction in the time needed to obtain results and the number of animals used in

toxicity testing (Kroeger, 2006). Although most data is generated from in vivo liver samples, there are efforts to build databases for the screening of hepatotoxicity based on primary hepatocyte cell culture experiments by genomic and proteomic approaches. Therefore, it is necessary to carefully characterise the cell culture model used.

In order to understand the mechanisms behind any compound induced change of gene expression, it is essential to know the basal gene expression in the test system. In the case of primary hepatocytes, it is not only the individual differences but also the effects of time and the conditions of culturing which have to be taken into account. Therefore, a comprehensive analysis of gene expression changes in rat and human hepatocytes and different cell culture systems (liver slices, suspension culture, primary hepatocytes cultured on plastic surface, on collagen I ML and in SW culture as well as different cell lines) has been carried out as part of this thesis.

Not every cell culture system is appropriate for every toxicological endpoint, as liver specific functions gradually decrease over time. In vivo, they are supported by liver architecture, cell-cell and cell-matrix interactions and the complex hormonal signalling of the body. It is impossible to mimic these conditions in culture and great endeavours are being made to maintain liver specific functions and attributes for as long as possible (LeCluyse et al., 2005; Richert et al., 2004; Turncliff et al., 2006; Vinken et al., 2006). Evaluating the basal gene expression pattern will help to understand the processes of dedifferentiation and will allow the interpretation of gene expression changes caused by xenobiotics and to extrapolate to mechanisms in vivo.

However, one has to be aware of the limitations of these techniques. Some compounds directly effect cellular macromolecules causing damage without changing gene expression. Often expression changes may reflect secondary effects following after the primary direct toxicity of the compound. The dimension of changes in gene expression is also dependent on dose, duration of exposure to the toxicant and on time from dosing to sampling (Gatzidou, Zira & Theocharis, 2007). Not all changes in gene expression have a direct impact on the corresponding protein content of a cell. Due to the variety of epigenetic control mechanisms there can be significant differences in gene and protein expression. Additionally, changes in protein activity, caused for example by phosphorylation or ubiquitinylation, can not be addressed and other , proteomic techniques have to be considered (Pennie et al., 2000; Merrick &