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Cancer is a dynamic disease with heterogenic molecular signatures and constantly evolves during the course of the disease. Single cell proteomic analysis could offer a suitable pathway to monitor cancer cell heterogeneity and deliver critical information for the diagnosis, recurrence, and drug-resistant mechanisms in cancer. Current standard techniques for proteomic analysis such as ELISA, mass spectrometry, and Western blots are time-consuming, expensive, and often require fluorescence labeling that fails to provide accurate information about the multiple protein expression changes at the single cell level. Herein, we report a surface-enhanced Raman spectroscopy-based simple microfluidic device that enables the screening of single circulating tumor cells (CTC) in a dynamic state to precisely understand the heterogeneous expression of multiple protein biomarkers in response to therapy. It further enables identifying intercellular heterogeneous expression of CTC surface proteins which would be highly informative to identify the cancer cells surviving treatment and potentially responsible for drug resistance. Using a bead and cell line-based model system, we successfully detect single bead and single cell spectra when flowed through the device. Using SK-MEL-28 melanoma cells, we demonstrate that our system is capable of monitoring heterogeneous expressions of multiple surface protein markers (MCSP, MCAM, and LNGFR) before and during drug treatment. Integrating a label-free electrochemical system with the device, we also monitor the expression of an intracellular protein (here, BRAFV600E) under drug treatment. Finally, we perform a longitudinal study with 15 samples from five different melanoma patients who underwent therapy. We find that the average expression of receptor proteins in a patient fails to determine the therapy response particularly when the disease progresses. However, single CTC analysis with our device shows a high level of intercellular heterogeneity in the receptor expression profiles of patient-derived CTCs and identifies heterogeneity within CTCs. More importantly, we find that a fraction of CTCs still shows a high expression of these receptor proteins during and after therapy, indicating the presence of resistant CTCs which may evolve after a certain time and progress the disease. We believe this automated assay will have high clinical importance in disease diagnosis and monitoring treatment and will significantly advance the understanding of cancer heterogeneity on the single cell level. |
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