Abstracts
2002 Digestive Disease Week

# 103690 Abstract ID: 103690 Gene Expression Profiling of Colorectal Cancer after Laser-Capture Microdissection (LCM) Using Affymetrix Genechip
Jörn Gröne, Birgit Weber, Christian Pilarsky, Irina Klaman, Heinz Buhr, Benno Mann, Andre Rosenthal, 12200 Berlin, Germany; Berlin, Germany

Purpose: Correlation of expression profiles and follow-up-data of colorectal cancer may help identifying significant determinants for the patient's prognosis (i.e. metachronous metastases, tumorfree survival, drug sensitivity or effectiveness of chemotherapy (5-FU/Leukovorin)). We applied Affymetrix GeneChip and LCM to establish transcript profiling of colorectal cancer cells as a basis for evaluation of the prognostic value of gene expression profiling. M&M: Colorectal cancer tissues, corresponding normal mucosae and clinical data were obtained prospectively with informed consent from 52 patients. Homogeneous normal colorectal epithelial cells and carcinoma cells from 16 patients were isolated by LCM. Poly(A) mRNAs were extracted, amplified and labelled with biotin. Internal quality control comprises quantitative PCR-analyses of housekeeping genes. After hybridisation of the Affymetrix GeneChip metg001A the data are analysed by Affymetrix software. Post-processing involves pairwise comparison of normal and cancerous tissue of the same patient. Results: To obtain cRNA of sufficient quantity and quality for chip-array based expression profiling more than 40mm2 of laser microdissected colorectal cells have to be isolated for each sample. RT-PCR analysis is a sufficient predictive parameter for quality of chip hybridisation. By expression profiling of 4 triplets of microdissected colorectal cancerous and normal cells, we identified by statistical analysis 74 genes that were upregulated and 48 genes that were downregulated in tumor tissue. Conclusion: Combining microarray technology and LCM in transcript profiling of colorectal cancer we can identify 122 genes with differential expression. In order to evaluate the prognostic value of gene profiles, clinical and follow-up data have to be correlated with expression data, including cluster analysis. For statistical reason we intend to analyse paired tissue samples of at least 50 patients.