No abstract

Concerns about the potential adverse health effects of engineered nanoparticles stems in part from the possibility that some materials display unique chemical and physical properties at nanoscales which could exacerbate their biological activity. However, studies that have assessed the effect of particle size across a comprehensive set of biological responses have not been reported. Using a macrophage cell model, we demonstrate that the ability of unopsonized amorphous silica particles to stimulate inflammatory protein secretion and induce macrophage cytotoxicity scales closely with the total administered particle surface area across a wide range of particle diameters (7-500 nm). Whole genome microarray analysis of the early gene expression changes induced by 10- and 500-nm particles showed that the magnitude of change for the majority of genes affected correlated more tightly with particle surface area than either particle mass or number. Gene expression changes that were particle size-specific were also identified. However, the overall biological processes represented by all gene expression changes were nearly identical, irrespective of particle diameter. Direct comparison of the cell processes represented in the 10- and 500-nm particle gene sets using gene set enrichment analysis revealed that among 1009 total biological processes, none were statistically enriched in one particle size group over the other. The key mechanisms involved in silica nanoparticle-mediated gene regulation and cytotoxicity have yet to be established. However, our results suggest that on an equivalent nominal surface area basis, common biological modes of action are expected for nano- and supranano-sized silica particles.

We developed an ELISA in high-density microarray format to detect hepatocyte growth factor (HGF) in human serum. The microassay can detect HGF at sub-pg/mL concentrations in sample volumes of 100 microL or less. The microassay is also quantitative and was used to detect elevated HGF levels in sera from recurrent breast cancer patients. The microarray format provides the potential for high-throughput quantitation of multiple biomarkers in parallel, as demonstrated with a multiplex analysis of five biomarker proteins.