Effect of glucocorticoid on insulin-like growth factor (IGF) regulation of IGF-binding protein expression in fibroblasts.

Abstract

Insulin-like growth factor (IGF)-binding proteins (IGFBPs) can determine IGF biological competence at the cellular level. IGF-I itself has been shown to be an important peptide regulator of local IGFBP availability. Glucocorticoid also has major effects on IGFBP expression. In the present study, we assessed integrated IGF-I and glucocorticoid regulation of IGFBP messenger RNA (mRNA) and protein expression in two fibroblast model systems. In bovine fibroblasts, IGF-I treatment induced IGFBP-3 and IGFBP-5 mRNA and protein secretion, and had a moderate effect on IGFBP-4 expression. Dexamethasone had little effect on the IGF-induced increase in IGFBP-3, but completely blocked the increase in IGFBP-5 expression. Basal IGFBP-4 expression was inhibited by dexamethasone, and this effect was counteracted by IGF-I. IGFBP-2 expression did not vary with IGF-I or dexamethasone treatment in these cells; IGFBP-1 mRNA was not detectable, and IGFBP-6 mRNA was low and inconsistent. In human fibroblasts, IGF-I treatment increased levels of IGFBP-3 and decreased levels of IGFBP-4 without influencing mRNA expression. IGF-I also increased steady state levels of IGFBP-5 mRNA. Dexamethasone alone decreased IGFBP-3, IGFBP-4, and IGFBP-5 mRNA, but it had no significant effect on IGFBP-3, -4, or -5 expression in the presence of IGF-I. Human fibroblast IGFBP-6 expression was stable under the different culture conditions; IGFBP-1 and -2 mRNA were not detected. These data demonstrate that IGF peptide and glucocorticoid individually modulate IGFBP expression and indicate that glucocorticoid has distinct effects on IGF regulation of IGFBP depending upon the particular IGFBP and the underlying mechanism of IGF regulation. Bovine fibroblasts may provide a useful model system to probe the molecular mechanisms of IGFBP-3, -4, and -5 gene expression and regulation by IGF-I and glucocorticoid, whereas human fibroblasts may be suitable for studying posttranscriptional interactions.