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Quantum cytosensor for early detection of cancer
Author(s) -
Ganesh Swarna,
Venkatakrishnan Krishnan,
Tan Bo
Publication year - 2020
Publication title -
medical devices & sensors
Language(s) - English
Resource type - Journals
ISSN - 2573-802X
DOI - 10.1002/mds3.10058
Subject(s) - quantum dot , nanotechnology , cancer , graphene , cancer detection , cancer cell , quantum , biomarker , computer science , materials science , computational biology , biology , physics , biochemistry , genetics , quantum mechanics
Current use of graphene quantum dot for cancer detection is highly impeded by the low Raman cross‐section and used as a carrier for plasmonic materials. Hence, there is a need for a sensor an efficient Raman cross‐section, with maintaining the cellular homeostasis to attain accurate detection. Here, we report a SERS‐activated graphene oxide (GO) quantum Cytosensor for whole cell cancer detection capable for the early detection of cancer down to a single cellular level. On approaching quantum scale, we achieved SERS activation of GO quantum dots by introducing the functionality of quantum confinement. By altering the density of functional groups on the surface, we facilitated accelerated self‐cellular uptake resulting in increased SERS sensitivity. Here, we demonstrate cancer detection by two approaches: biomarker detection in external environment and intracellular detection using three cell lines. The quantum Cytosensor advances cancer detection to the molecular level by sensing the complex biomolecular processes transpiring intracellularly to detect and differentiate cancerous attributes of a cell. We observed a 3000‐, 2500‐ and 3500‐fold increase in enhancement of DNA, RNA and protein, respectively. Discernment of SERS spectral signatures was obtained by employing machine learning techniques which primarily identified the differences between cancer cells and normal cells. The classification and clustering techniques provided a high diagnostic sensitivity and specificity of 84.83% with unparalleled accuracy of 92.3%. Detection of cancer down to a single cellular level using quantum Cytosensor via SERS integrated with machine learning provides a new stepping stone towards adoption of SERS‐based early detection of cancer.

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