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Tuning the Surface Chemistry of Gold Nanoparticles to Specifically Image Glioblastoma Cells Using Surface-Enhanced Raman Spectroscopy

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journal contribution
posted on 24.02.2020 by Floriana Burgio, Deborah Piffaretti, Felix Schmidt, Uwe Pieles, Michael Reinert, Marie-Françoise Ritz, Sina Saxer
Surface-enhanced Raman spectroscopy (SERS)-based imaging has the potential to improve the intraoperative visualization of the exact tumor borders and infiltrating foci of glioblastoma (GBM), thus achieving a more complete surgical resection. However, successful and reliable outcomes can be invalidated by the inclination of gold nanoparticles (GNPs) to aggregate or bind nonspecifically to the cells preventing discrimination between the tumor and healthy cells. Stable and specifically targeting SERS tags are achieved through application of the appropriate GNP surface chemistry and by the correct balance of inert and active targeting functionalities. This requires an in-depth characterization of the effective immobilized functionalities on the GNP surface. GNPs with varying ratios of Raman reporter, poly­(ethylene glycol) (PEG), and antibodies against epidermal growth factor receptor, which is overexpressed by GBM cells, were studied. The influence of each ratio on the GNP performance in terms of the maximal colloidal stability, sensitivity, and lowest nonspecific binding was characterized in detail both chemically and biologically. SERS tags coated with 50% Raman reporter surface coverage and conjugated to 3% antibody surface coverage showed the ideal chemistry functionalization. This allowed us to avoid GNP aggregation and to reduce nonspecific binding, while receiving enough Raman sensitivity for a fast and distinct discrimination between GBM tumor and nontumoral cell lines in vitro. Excess antibody did not improve the binding affinity of GNPs to tumor cells, but it reduced the conjugation efficiency by 35%. These findings open a stable and nonquenching alternative for GBM visualization compared to fluorescence-guided surgery, the current state-of-the-art technique for GBM imaging.