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Een functionele genomics benadering voor de identificatie van nieuwe...

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Titel Een functionele genomics benadering voor de identificatie van nieuwe therapeutische doelen bij psoriasis
Looptijd 07 / 2002 - 07 / 2005
Status Afgesloten
Onderzoeknummer OND1297692
Leverancier gegevens Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)

Samenvatting (EN)

Background. Psoriasis is a multifactorial chronic inflammatory skin disease of unknown etiology, affecting 2-3% of the population. Immunological predisposition and abnormalities in keratinocyte growth or differentiation are key to the disease process. So far, the mediators and signaling pathways that regulate abnormal gene expression in psoriatic epidermis are largely unknown. Using conventional low throughput methods, we have previously investigated properties and regulation of differentially expressed genes in psoriasis. Recently, we have taken a functional genomic approach to make a comprehensive examination of the keratinocyte gene expression repertoire. Using Serial Analysis of Gene Expression (SAGE) we have constructed 6 libraries of cultured keratinocytes, normal epidermis, epidermal cancer and psoriatic epidermis. Over 80,000 transcripts ('tags') were sequenced, and provide a first step towards a transcriptome of human epidermis. These analyses have revealed that keratinocytes express at least 15,000 different genes, many of which represent uncharacterised new genes or genes not known to be expressed in human epidermis. We have applied noise reduction methods and two-way cluster analysis on these SAGE data. Stable and compact clusters of apparently co-regulated genes were thus identified, and clear partitions between samples were obtained. Conventional northern blot analysis and immunohistochemistry on a selection of these genes showed that SAGE data reliably correlated with findings using independent methods. To address the biological relevance and to search for meaningful interpretation of these data, we applied recently developed text-mining tools that can generate literature networks of human genes. In this way we identified a differentially expressed cluster of genes on chromosome 1q that is strongly upregulated in premalignant human epidermis. The genes identified in our SAGE libraries and expressed genes that we identified in screens using high-density oligonucleotide arrays have served as an input for medium density cDNA microarrays that we have recently constructed. These microarrays and high density cDNA microarrays will be used for expression profiling as described in this project. Bioinformatics tools and statistical techniques that we have used on the SAGE libraries are similar to those that will be used for microarray analyses as proposed in the current project. a. Overall aim and key objectives. Therapeutic treatments of psoriasis are often inadequate or limited by side-effects (corticosteroids, retinoids, cyclosporin etc). More detailed knowledge on the pathogenesis (or ideally on the etiology) of the disease will allow a more rational drug development against defined targets that are relevant for the disease. The overall aim of this project is to identify sets of genes or regulatory pathways that are critically involved in the epidermal manifestation of psoriasis ('the disease phenotype'). Obviously this is of major importance in order to identify new potential targets within these sets of genes or within the pathways that regulate their expression. The key objectives of this project are: (1) Microarray analysis of gene expression profiles in cultured keratinocytes (with and without relevant inflammatory stimuli) and biopsies from patients and controls. (2) Microarray analysis of gene expression profiles in cultured keratinocytes that are exposed to known antipsoriatic drugs. (3) Analysis of expression data obtained under (1) and (2), to identify groups of genes that are differentially expressed between patient and control samples, and to identify groups of genes that share similar regulation patterns in response to known antipsoriatic drugs. (4) Identification of functional relationships between genes identified under (1) and (2). (5) Validation of the candidate genes or pathways as a therapeutic target in psoriasis. b. Experimental approach. Objective (1) and (2): As indicated above we have constructed microarrays (up to 1000 cDNAs) at the UMCN microarray core facility. In addition to these arrays, high-density arrays (cDNA or spotted oligo-arrays of 70 nucleotides) of sufficient quality that are becoming available during the project will be used as well. mRNA of cultured keratinocytes from healthy individuals and patients will be used for comparative analysis. Skin biopsies from lesional psoriatic skin, non-lesional skin and normal skin will we used to isolate pure epidermis for mRNA isolation according to recently developed protocols, and analyzed on microarays. Cultured keratinocytes will be treated in vitro with known antipsoriatic drugs, and the resulting changes in expression profile will be examined. Objective (3): The data obtained under (1) and (2) will be subjected to data compression techniques in order to pull out informative data from a noisy background. These data will be used for cluster analysis using algorithms that have recently been applied to microarray data, and yield stable compact clusters. Objective (4): As we have experienced with the analysis of our SAGE data, large numbers of differentially expressed genes or co-regulated genes are obtained. The throughput of microarray technology is much higher than SAGE and the overwhelming amount of data cannot be examined by manual Medline searches. We will apply recently developed text-mining tools such as PubGene and MedMiner to facilitate biological interpretation of the data. Objective (5): Using in vitro systems for cultured keratinocytes we will apply pharmacological or genetic manipulation of a limited number of candidate genes involved in induction and maintenance of the psoriatic phenotype. c. Elements of innovation. The approach that we envisage has several innovative elements. The polygenic disease psoriasis has been examined extensively by whole genome screening, but this has not yet yielded causative genes or risk factors sofar, other than the known HLA class I genes. Here we take a functional genomic approach to look for deviations in gene expression levels in patient cells. In addition we will examine the overlap in transcriptional responses of cells towards established antipsoriatics. Admittedly, this will not give a direct identification of the "psoriasis gene(s)", but will rather point to aberrant signalling pathways and transcriptional programs which are amenable to therapeutic intervention. Application of transciptomic data obtained by SAGE analysis as an input for microarray technology, and data analysis via appropriate bioinformatics tools is a novel approach to identify therapeutic targets in psoriasis. d. Relevance for NWO Genomics program, contribution to national genomics infrastructure. The proposed aims and methodology comply with the objectives and definitions of the NWO genomics program: large-scale characterization of genes and gene products in order to address a clearly defined biomedical problem. Because the current application is a medium-scale project, it exploits a local network of three departments (Dermatology, Human Genetics, Center for Molecular and Biomolecular Infomatics, CMBI) rather than a nation-wide network. The major aim is to apply our existing knowledge of keratinocyte transciptome data and our experience with bioinformatics tools to address a biomedical question, rather than development of infrastructural facilities. We are engaged in national and international collaborations on application of SAGE data, and we participate in the Dutch platform for microarray research. SAGE data from two libraries are made available at our website (http://dermatology.azn.nl/) and will be deposited at the NCBI shortly. Data from four other SAGE libraries that were recently finished, will be accessible in the public domain later this year.

Betrokken organisaties

Betrokken personen

Onderzoeker Ing. G.J. de Jongh
Onderzoeker Drs. A. Pol
Projectleider Prof.dr. J. Schalkwijk

Classificatie

A34800 Geneesmiddelen en bestrijdingsmiddelen
A70000 Volksgezondheid en gezondheidszorg
C10000 Biotechnologie
D21100 Bioinformatica, biomathematica, biomechanica
D21400 Genetica
D23210 Huid- en geslachtsziekten, reumatologie, orthopedie
D23340 Biofarmaceutische wetenschappen, toxicologie

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