Dr. Holger Sültmann
Abt. Molekulare Genomanalyse
Im Neuenheimer Feld 280
presenter: Dr. Holger Sültmann
H. Sültmann1, W. Huber1, J. Boer1,4,
F. Wilmer1, L. Füzesi3, B. Gunawan3, S.
Haas2, A. v. Heydebreck2, M. Vingron2, A. Poustka1
1Abt. Molekulare Genomanalyse, 2Theoretische Bioinformatik, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, D-69120 Heidelberg
3Zentrum Pathologie, Georg-August-Universität, Robert-Koch-Str. 40, D-37075 Göttingen
4Leiden Univ. Medical Center, Wassenarseweg 72, Leiden 2333AL, NL
Cancer cells show altered gene expression compared to normal cells. Knowledge of the changes in gene expression for certain types and stages of tumors can give insight into the molecular changes involved in tumor development and progression and provide molecular markers for tumor diagnosis and prognosis.
We use the cDNA array hybridization technology as a high throughput method to determine the expression levels of 32,000 different cDNAs spotted in duplicate onto nylon membranes. These represent known human genes and expressed sequence tags (ESTs). Normal tissue and primary tumor tissue are used to isolate poly (A)+ RNA which is reverse transcribed into 33P-labelled single stranded cDNA. The hybridization of both cDNA populations is performed on different membranes using a standardized protocol. The membranes are exposed to phosphoimage plates, and expression profiles are calculated through spotwise quantification of the signal distribution.
We have collected array expression data for 37 renal cell carcinoma samples (predominantly clear cell types) of different tumor stages and differentiation grades, and for the corresponding normal tissues of the same patients. More than 1700 genes were identified with statistical significance to be expressed at different levels between normal and tumor tissues. Among these were several genes which had been known to be differentially expressed in renal carcinoma, e.g. vimentin, VEGF, haptoglobin, metallothionein, and kininogen. This confirms the utility of the experimental approach of typing expression levels of thousands of genes simultaneously. In addition to the genes known to be associated with kidney cancer, many other genes and ESTs were found. Our data allow the definition of genes that are significantly transcribed only in certain tumor stages (e.g. in metastases). A detailed analysis of the correlation of gene expression with tumor progression is currently being performed.
The renal cell carcinoma specific genes, as well as a selection of genes which are known to have oncogenic potential in other cancer types, are being amplified by PCR and spotted on membranes or glass slides to set up a kidney tumor specific gene array. With this, we plan to conduct a further focused investigation on the differential transcription of genes in renal cell carcinoma.
A queryable database combining expression data for all genes on the array with histopathological and clinical follow-up information for the tumor material as well as tools to mine these large data sets, are under development. This database will eventually be open for the public.
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