| Literature DB >> 19190631 |
M Horsch1, C V Recktenwald, S Schädler, M Hrabé de Angelis, B Seliger, J Beckers.
Abstract
Ras acts in signalling pathways regulating the activity of multiple cellular functions including cell proliferation, differentiation, and apoptosis. Amino-acid exchanges at position 12, 13, or 61 of the Kras gene convert the proto-oncogene into an activated oncogene. Until now, a direct comparison of genome-wide expression profiling studies of Kras overexpression and different Kras mutant forms in a single assay system has not been carried out. In our study, we focused on the direct comparison of global gene expression effects caused by mutations in codon 12 or 13 of the Kras gene and Kras overexpression in murine fibroblasts. We determined Kras cellular mRNA, Ras protein and activated Ras protein levels. Further, we compared our data to the proteome analysis of the same transfected cell lines. Both overexpression and mutations of Kras lead to common altered gene expression patterns. Only two genes, Lox and Col1a1, were reversely regulated in the Kras transfectants. They may contribute to the higher aggressiveness of the Kras codon 12 mutation in tumour progression. The functional annotation of differentially expressed genes revealed a high frequency of proteins involved in tumour growth and angiogenesis. These data further support the important role of these genes in tumour-associated angiogenesis.Entities:
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Year: 2009 PMID: 19190631 PMCID: PMC2653730 DOI: 10.1038/sj.bjc.6604882
Source DB: PubMed Journal: Br J Cancer ISSN: 0007-0920 Impact factor: 7.640
Figure 1Kras transcript and protein expression levels. (A) Kras expression levels were measured by qRT–PCR. The results are given as the linear ratio of expression levels relative to the expression level of Kras expression in the non-transfected NIH3T3 cells. Numbers on the Y axis show the fold changes of gene expression levels. (B) Quantification of total Ras and activated Ras molecules by western blotting. β-actin served as loading control.
Figure 2Hierarchical cluster analysis. Hierarchical cluster analysis was performed using gene expression data from 44 probes significantly differentially expressed in at least two out of three transfected NIH3T3 cell lines. For each gene, red indicates higher expression relative to the control and green indicates lower gene expression. Grey boxes represent genes with expression levels below detection limits. Several subgroups of genes with similar expression patterns are colour coded to the left of the heat plots.
Figure 3Validation of microarray experiments. qRT–PCR from 10 regulated genes in the four transfected cell lines compared with microarray data. Results are illustrated as ratios of expression relative to the expression of the reference (non-transfected NIH3T3 cells). Black columns represent the mean linear ratio of four microarray experiments, and white columns the mean linear ratios of qRT–PCR. Numbers on the Y axis show the fold changes of gene expression levels. Data represented are : (A) Col6a1, (B) Fapb5, (C) Ftl1, (D) H3f3b, (E) Lox, (F) Prss23, (G) S100a11, (H) Sparc, (I) Sqstm1, and (J) Vim.
Gene ontology
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| Calcium–ion binding |
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| Nucleic acid binding |
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| Catalytic activity |
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| Transporter activity |
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| Structural molecule activity |
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| Enzyme regulator activity |
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| Lipid binding |
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| Oxidoreductase activity |
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| Protein binding |
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| Cell growth |
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| Development |
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| Nucleic acid metabolism |
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| Cell proliferation |
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| Protein metabolism |
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