Optical biosensor based on SERS with signal calibration function for quantitative detection of carcinoembryonic antigen | Zendy

Tingyin Wang | Zendy; Youzhi Zhu | Zendy; Shuyun Weng | Zendy; Xueliang Lin | Zendy; Kien Voon Kong | Zendy; Youliang Weng | Zendy; Xianggang Jia | Zendy; Rong Chen | Zendy; Duo Lin | Zendy; Shangyuan Feng | Zendy

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Optical biosensor based on SERS with signal calibration function for quantitative detection of carcinoembryonic antigen

Author(s) -

Tingyin Wang,

Youzhi Zhu,

Shuyun Weng,

Xueliang Lin,

Kien Voon Kong,

Youliang Weng,

Xianggang Jia,

Rong Chen,

Duo Lin,

Shangyuan Feng

Publication year - 2022

Publication title -

biomedical optics express

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.362

H-Index - 86

ISSN - 2156-7085

DOI - 10.1364/boe.474273

Subject(s) - carcinoembryonic antigen , calibration , biosensor , optics , computer science , materials science , medicine , nanotechnology , physics , cancer , quantum mechanics

Monitoring the levels of cancer biomarkers is essential for cancer diagnosis and evaluation. In this study, a novel sandwich type sensing platform based on surface-enhanced Raman scattering (SERS) technology was developed for the detection of carcinoembryonic antigen (CEA), with a limit of detection (LOD) of 0.258 ng/mL. In order to achieve sensitive detection of CEA in complex samples, gold nanoparticle monolayer modified with CEA antibodies and with aptamer-functionalized probes was fabricated to target CEA. Two gold layers were integrated into the SERS platform, which greatly enhanced the signal of the probe by generating tremendous "hot spots". Meanwhile, the intensity ratio of Raman probes and the second-order peak of the silicon wafer was used to achieve dynamic calibration of the Raman probe signal. Excitingly, this sensing platform was capable of distinguishing cancer patients from healthy individuals via CEA concentrations in blood samples with the accuracy of 100%. This sandwich structure SERS sensing platform presented promising potential to be an alternative tool for clinical biomarker detection in the field of cancer diagnosis.

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