Genetic pathway analysis of expression microarray data

Background and Aims: mRNA expression analysis by microarrays can contribute to an enhanced diagnosis and to find altered biological pathways for explanation of the pathomechanism of the CRC. Our aim was to evaluate and interpret the chip analysis results according to the role of the differently expressed genes in genetic and biochemical pathways. Materials and Methods: Biopsy samples were taken from the pathological and routine part of the colon. Total RNA was extracted from frozen biopsy samples from 10 patients with colorectal adenocarcinoma. The mRNA fraction was amplified by T7 RNA amplification (Ambion Inc, US). RNA expression profile was evaluated by Atlas Glass 1K microarrays (BD Clontech Inc. US, 1081 genes) and the Genepix 4000B scanner (Axon Inc. SA). GenePixPro 4.1, Acuity 3.1 and SAS 6.12 softwares were used for data analysis. ANOVA, factor-, discriminant-, hierarchical cluster analysis were performed. Pathway analysis was done by Pathway Assist 2.53 software using Resnet database. Results: First the connections between differently expressed (up or downregulated) genes in CRC were explored, unlinked nodes were removed. In order to simplify the interpretation of the pathway network, 22 cell processes – that play role in the pathomechanism of colorectal carcinoma – were selected, and pathways were built and visualized. Pathways were completed with the genes from the database for getting more comprehensive overview about the processes involved in CRC. Conclusions: Atlas arrays with multivariate statistics can be used to diagnose mRNA expression profiles and to filter differences. We are able to get closer to the exploration of the background of the disease by the analysis of the role and function of the affected genes in cell pathways using Pathway Assist software.