Gene expression profiling to identify drug targets

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New clinical programs for treatments of rheumatoid arthritis are more and more directed on single molecular targets in the complex immune system. The choice of these drug targets have evolved from a growing knowledge of the underlying mechanism of inflammatory diseases, where most of these targets focus on candidate genes in cytokine clusters [19]. Other examples of genes that have been implicated as potential targets for treatment or disease prognosis markers are HLA and MMP-3 [20].

However, the drawback of these targets is that they all are dependent on previous knowledge of the studied molecular networks. As such, there is a deficit in identification of novel targets from previously unknown or overlooked perspectives on disease induction and perpetuation mechanisms involved in RA.

Ways to identify such a target lies in an unbiased analysis of a genetic molecular approach that precisely examines, unravels and dissects various aspects of the disease.

The first approach of choice to get a molecular insight in a complex biological system is a complete gene expression analysis including all annotated as well as yet un-annotated genes in the genome. With this approach one will detect important genes that are differentially regulated in aspect to the investigated condition for a specific tissue and time-point in the disease development. One strong aspect of this method is the large set of genes that can be analysed in the same experimental setup (on the same chip) making it possible to use the produced clustering and pathway analysis of large sets of genes in, and make use of all publicly available information of, these genes in automated analyses [21, 22].

To reach a complete understanding of the molecular regulation of arthritis one must address the complete gene expression simultaneously. To reach this goal, it is crucial to identify and quantify the genes expressed by the cells that are present and interacting in the tissue.

However, one big disadvantage with this method is that the genes of future interest must be differentially expressed at a transcriptional level to be detected by this method. Another difficulty with this method lies in the problematic choice of timepoint and tissue/cell type of interest for analysis. These kinds of experimental design are still very complex and time consuming and generate huge amounts of data. Hence, it is necessary before the experimental initiation to have a clear image of the time-point and tissue of interest for the study. A further difficulty is the need of biological replicates and the genetic heterogeneity that is involved in studies in patient material. Therefore, scepticisms to the use of gene expression profiling as a method to achieve an understanding of rheumatic diseases has been put forward [23]. However, recent analysis of gene expression fingerprints of individual patients with early rheumatoid arthritis might give hope for this still technically evolving diagnosis method [24, 25].

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