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Parallel profiling of cancer cell and protein using graphene oxide functionalized ac-EHD SERS Immunoassay

Abstract

Circulating biomarkers have emerged as promising non-invasive, real-time surrogates for cancer diagnosis, prognosis and monitoring of therapeutic response. Current bio-sensing techniques mostly involve detection of either circulating cells or proteins which are inadequate in unfolding complex pathologic transformations. Herein, we report parallel detection of cellular and molecular markers (protein) for cancer using a multiplex platform featuring i) graphene oxide (GO) functionalization that increases the active surface area and more importantly reduces the functionalization steps for rapid detection ii) alternating-current electrohydrodynamic (ac-EHD) fluid flow that provide delicate micro-mixing to enhance target-sensor interactions thereby minimize non-specific binding and iii) surface enhanced Raman scattering (SERS) for multiplex detection. We find that our platform possesses high sensitivity for detecting both proteins and cells. More importantly, this platform not only detects the cancer cells but simultaneously can monitor the heterogeneous expression of cell surface protein which could be clinically useful to determine effective patient therapy. We demonstrate the specific and sensitive detection of breast cancer cells from a mixture of non-target cells and report the heterogeneous expression of human epidermal growth factor receptor 2 (HER2) proteins on the individual cancer cell surface. Concurrently, we detect as low as 100 fg/mL HER2 and Mucin 16 proteins spiked in blood serum.

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Publication details

The article was received on 10 Apr 2018, accepted on 07 Aug 2018 and first published on 08 Aug 2018


Article type: Paper
DOI: 10.1039/C8NR02886A
Citation: Nanoscale, 2018, Accepted Manuscript
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    Parallel profiling of cancer cell and protein using graphene oxide functionalized ac-EHD SERS Immunoassay

    K. R. Khondakar, S. Dey, A. Wuethrich, A. A. I. Sina, D. Korbie, Y. Wang and M. Trau, Nanoscale, 2018, Accepted Manuscript , DOI: 10.1039/C8NR02886A

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