Influence of Iron Oxide Nanoparticles on Innate and Genetically Modified Secretion Profiles of Mesenchymal Stem Cells.

Mesenchymal stem cells (MSCs) have well-established paracrine effects that are proving to be therapeutically useful. This potential is based on the ability of MSCs to secrete a range of neuroprotective and anti-inflammatory molecules. Previous work in our laboratory has demonstrated that intravenous injection of MSCs, treated with superparamagnetic iron oxide nanoparticle fluidMAG-D resulted in enhanced levels of glial-derived neurotrophic factor, ciliary neurotrophic factor, hepatocyte growth factor and interleukin-10 in the dystrophic rat retina. In this present study we investigated whether the concentration of fluidMAG-D in cell culture media affects the secretion of these four molecules in vitro. In addition, we assessed the effect of fluidMAG-D concentration on retinoschisin secretion from genetically modified MSCs. ELISA-assayed secretion of these molecules was measured using escalating concentrations of fluidMAG-D which resulted in MSC iron loads of 0, 7, 120, or 274 pg iron oxide per cell respectively. Our results demonstrated glial-derived neurotrophic factor and hepatocyte growth factor secretion was significantly decreased but only at the 96 hour's time-point whereas no statistically significant effect was seen with ciliary neurotrophic factor secretion. Whereas no effect was observed on culture media concentrations of retinoschisin with increasing iron oxide load, a statistically significant increase in cell lysate retinoschisin concentration (p = 0.01) was observed suggesting that increasing fluidMAG-D concentration did increase retinoschisin production but this did not lead to greater secretion. We hypothesize that higher concentrations of iron-oxide nanoparticle fluidMAG-D have an effect on the innate ability of MSCs to secrete therapeutically useful molecules and also on secretion from genetically modified cells. Further work is required to verify these in vitro finding using in vivo model systems.