Microarray analysis and identification of novel molecules involved in insulin-like growth factor-1 receptor signaling and gene expression

Abstract

The insulin receptor (IR) and the insulin-like growth factor-1 receptor (IGF-1R) are members of the same subfamily of receptor tyrosine kinases. The two receptors phosphorylate many of the same substrates and activate the same signaling modules, including the mitogen-activated protein kinase (MAPK) and phosphatidyl inositol 3' kinase (PI3K) signaling pathways. Although the IR and IGF-1R share some redundant functions in metabolism, cell growth, differentiation, and apoptosis, they also exhibit distinct physiological roles. Some of these may be due to differences in tissue distribution, receptor structure, formation of hybrid receptors, or mechanisms of ligand binding. However, the divergent effects of insulin and IGF-1 also may be explained by specificity in the intracellular signals generated by insulin and IGF-1. In particular, the IR and IGF-1R are capable of triggering their own biological responses by using specific or preferential substrates, molecular adapters, or signaling pathways. In a recent study, we used cDNA microarray analysis to identify genes differentially regulated by insulin and IGF-1. Mouse NIH-3T3 fibroblasts expressing either the wild-type human IGF-1R or IR were stimulated with either IGF-1 or insulin, respectively. We identified 39 genes differentially regulated by insulin and IGF-1. Most of these genes had not been reported previously to be responsive to insulin or IGF-1. The genes induced by IGF-1 generally were involved in mitogenesis or differentiation, while the genes found to be induced by insulin did not conform to any particular category. In a separate study, immortalized breast epithelial cells were stimulated with IGF-1 and a cDNA microarray analysis was used to generate a profile of IGF-1-regulated genes. A number of genes known to be involved in angiogenesis were found to be regulated by IGF-1. These results strongly suggest that this technology may be extremely useful in identifying groups of genes that are specifically regulated by different ligands and their activated receptors.