Publication details
cDNA Microarray Technology as a Tool for Better Understanding of Progress of Malignant Diseases
| Authors | |
|---|---|
| Year of publication | 2005 |
| Type | Article in Proceedings |
| Conference | Prague Post Genome Technology Workshop |
| MU Faculty or unit | |
| Citation | |
| Field | Genetics and molecular biology |
| Keywords | microarray |
| Description | Array technologies have made it straightforward to monitor the expression pattern of thousands of genes simultaneously. We develop new tools, not only for the analysis of gene expression, but also for better diagnostics of various types of malignances in our laboratory. The development of better diagnostic techniques requires different approach in the evaluation of obtained microarray data. The first step of microarray data processing is precise image analysis of the data obtained using scanner. The software developed in our laboratory was used. The grid was fully-automatically set up for each image and the alignment to the array of spots was checked. This software also contains normalisation methods. We learned the differences in agnostics of various types of malignances and therefore our results represent new possibilities how to validate microarray data. Human 19,008 cDNA microarrays were used to analyze gene expression profiles of 18 patients with colorectal cancer against normal colon epithelium.The transcriptome maps (TM) (Caron et al., 2001; Versteeg et al., 2003) obtained were analyzed in order to prove positional relationships between the regulated genes suggesting the influence of chromatin remodeling effects. We identified 195 prominent genes with significantly altered expression in colon cancer. A comparison of TMs showed chromosome regions with conserved changes of gene expression typical of colorectal cancer in general and patient-specific variable regions. This study proved the existence of chromosome gene clusters in which regulated genes are located in close molecular neighborhood and that belong to the conserved TM component. Comparison of TMs is suggested as a tool facilitating detailed and illustrative diagnostics and treatment planning for individual patients. Large scale expression analysis of differentiation processes of HL-60 cells into monocytes and granulocytes and K562 cells into megakaryocytes by high-density cDNA microarrays containing 19,000 genes and EST sequences was used to study the differences among various types of differentiation and the kinetics of the processes. Based on the time dependence of the level of gene expression, genes were divided into 10 groups of regulated genes (GRGs). Intersections of GRGs from three types of differentiation showed that there are subsets of genes regulated in two pathways by either the same or quite different ways. Using visualization software developed in our laboratory, the regulated genes were mapped to chromosomes. The mapping showed that genes related to differentiation are mostly localized in regions with increased gene expression where they form clusters. Changes of cluster expression profiles along chromosomes revealed, in some cases, alternating kinetics in which up-regulated genes are followed by down regulated ones and vice versa. Epigenetic mechanisms have been suggested to control this type of gene regulation. Our results demonstrate that there are not only regions of increased or decreased levels of gene expression but, in fact, in some chromosome regions we can find clustering of genes related to specific cell rocesses. The results of position clustering of genes during various types of differentiation constitute big potential in diagnostics of leukemia where we can find several combinations of changes in gene expression which lead to cessation of normal differentiation of stem cells. |
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