Abstract
Circulating tumor cells (CTCs) have substantial clinical implications in cancer diagnosis and monitoring. Although significant progress has been made in developing technologies for CTC detection and counting, the ability to quantitatively detect multiple surface protein markers on individual tumor cells remains very limited. In this work, we report a multiplexed method that uses magnetic multicolor surface-enhanced Raman scattering (SERS) nanotags in conjunction with a chip-based immunomagnetic separation to quantitatively and simultaneously detect four surface protein markers on individual tumor cells in whole blood. Four-color SERS nanotags were prepared using magnetic-optical iron oxide-gold core-shell nanoparticles with different Raman reporters to recognize four different cancer markers with respective antibodies. A microfluidic device was fabricated to magnetically capture the nanoparticle-bound tumor cells and to perform online negative staining and single-cell optical detection. The level of each targeted protein was obtained by signal deconvolution of the mixed SERS signals from individual tumor cells using the classic least squares regression method. The method was tested with spiked tumor cells in human whole blood with three different breast cancer cell lines and compared with the results of purified cancer cells suspended in a phosphate buffer solution. The method, with either spiked cancer cells in blood or purified cancer cells, showed a strong correlation with purified cancer cells by enzyme-linked immunosorbent assay, suggesting the potential of our method for the reliable detection of multiple surface markers on CTCs. Combining immunomagnetic enrichment with high specificity, multiplexed targeting for the capture of CTC subpopulations, multicolor SERS detection with high sensitivity and specificity, microfluidics for handling rare cells and magnetic-plasmonic nanoparticles for dual enrichment and detection, our method provides an integrated, yet a simple and an efficient platform that has the potential to more sensitively detect and monitor cancer metastasis.
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