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Design and Development of Aptamer–Gold Nanoparticle Based Colorimetric Assays for In-the-field Applications
Published on: June 23, 2016
SERS-Based Quantification of Biomarker Expression at the Single Cell Level Enabled by Gold Nanostars and Truncated
Manjari Bhamidipati1, Hyeon-Yeol Cho2, Ki-Bum Lee2,3
1Department of Biomedical Engineering , Rutgers University , 599 Taylor Road , Piscataway , New Jersey 08854 , United States.
Abstract:
Surface-enhanced Raman spectroscopy (SERS)-based biosensors have been used increasingly over the past few years for cancer detection and diagnosis. SERS-based imaging offers excellent sensitivity and has advantages over other detection techniques such as fluorescence. In this study, we developed a novel biosensor to detect the cancer biomarker epithelial cell adhesion molecule (EpCAM) and quantify its expression at the single cell level. EpCAM is one of the most commonly expressed markers on a variety of cancer cells; importantly it has been suggested that reduction of its expression levels could be associated with the epithelial to mesenchymal transition (EMT) and thus to the onset of metastasis. Therefore, monitoring variations in expression levels of this membrane biomarker would improve our ability to monitor cancer progression. The described substrate-based biosensor was developed employing gold nanostars functionalized with EpCAM aptamer molecules and was able to quantify subnanomolar concentrations of EpCAM protein in solution. Importantly, we demonstrated its use to quantify EpCAM expression on the surface of two cancer cells, MCF-7 and PC-3. We also compared the binding efficiency of two EpCAM DNA aptamers of different lengths and observed a substantial improvement in the sensitivity of detection by employing the shorter aptamer sequence, probably due to the reduced number of conformations possible at room temperature with the truncated oligonucleotide. Detailed characterization of the substrates was carried out using both SERS maps and atomic force microscopy. These substrate-based diagnostic devices promise to be relevant for monitoring phenotype evolutions in cancer cells, blood, and other bodily fluids, thus improving our ability to follow in real time disease onset and progression.
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