Beyond the Identification of Transcribed Sequences: Functional and Expression Analysis

9th Annual Workshop, October 28-31, 1999

Co-sponsored by the U.S. Department of Energy


Tools for functional analysis using resources of RZPD

B. Korn1, 2, J. Boer1, P. Kioschis1,2, A. Vente3, H. Lehrach3,4 and A. Poustka1,2

1 Abteilung für Molekulare Genomanalyse, DKFZ, Heidelberg, Germany
2 RessourcenZentrum am DKFZ, Heidelberg, Germany
3 RessourcenZentrum am Max-Planck-Institut für Molekulare Genetik, Berlin-Dahlem, Germany
4 Max-Planck-Institut für Molekulare Genetik, Berlin-Dahlem, Germany

Since the launch of the German Human Genome Project (DHGP) by the Federal Ministry of Education, Science Research and Technology (BMBF) and the Deutsche Forschungsgemeinschaft (DFG) in 1995, the central unit (Resource Center) does provide standardised material and technology for genomics. In order to mimic the development in the field, we shifted our focus of product development towards functional genomics.

Collections of minimal gene sets for human, mouse and rat as well as indication-specific sets for oncology, immunology, haematology, and toxicology have been collected and characterised. These clone sets are made available as high density filter arrays, together with accompanying database information. Furthermore, we plan to provide courses to introduce the users of RZPD to different kinds of analysis tools for expression profiling using these gene sets. A genome wide project is underway to further improve the target material for expression profiling. The use of whole genome expression profiling in cancer research will be shown. Cancer cells are genetically different from normal cells, and exhibit aberrant gene expression. Knowledge of the changes in gene expression typical for certain types and stages of tumours, could give insight into the molecular changes involved in tumour development and progression, and provide molecular markers for tumour diagnosis and prognosis.

We generated gene expression profiles for kidney, breast and brain tumours and normal tissues through the complex hybridisation of high-density Nylon arrays with radioactively labelled whole tissue cDNA. Array expression data for renal clear cell carcinomas confirmed overexpression of several genes known to be upregulated in renal carcinomas, e.g. VEGF, vimentin, and haptoglobin. Other known genes that have not previously been implicated in kidney cancer were found overexpressed in the tumours, including beta-2-microglobulin, thymosin beta-4, and DNAX activation protein 12. In addition, ESTs similar to angiopoietin, and ESTs without homologies were found. Underexpressed genes in renal tumours compared to normal tissue included five members of the metallothionin family and several unknown genes (ESTs). We will compare hybridizations using whole tissue tumour and normal cDNAs with suppression subtraction cDNAs, with the aim to increase the sensitivity.

Linking the tumour hybridisation data with histopathological and clinical data in a queryable relational database will allow correlation of gene expression and tumour characteristics. By comparing at least 10 to 20 well-characterised tumour/normal pairs of the same type and stage, we expect to find significant tumour-specific expression patterns and co-ordinated changes in the expression of multiple genes.

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