Surface modification of alignment layer by ultraviolet irradiation to dramatically improve the detection limit of liquid-crystal-based immunoassay for the cancer biomarker CA125

Liquid crystal (LC)-based biosensing has attracted much attention in recent years. We focus on improving the detection limit of LC-based immunoassay techniques by surface modification of the surfactant alignment layer consisting of dimethyloctadecyl[3-(trimethoxysilyl)propyl]ammonium chloride (DMOAP...

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Veröffentlicht in:Journal of biomedical optics 2015-05, Vol.20 (5), p.057004-057004
Hauptverfasser: Su, Hui-Wen, Lee, Mon-Juan, Lee, Wei
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Sprache:eng
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Zusammenfassung:Liquid crystal (LC)-based biosensing has attracted much attention in recent years. We focus on improving the detection limit of LC-based immunoassay techniques by surface modification of the surfactant alignment layer consisting of dimethyloctadecyl[3-(trimethoxysilyl)propyl]ammonium chloride (DMOAP). The cancer biomarker CA125 was detected with an array of anti-CA125 antibodies immobilized on the ultraviolet (UV)-modified DMOAP monolayer. Compared with a pristine counterpart, UV irradiation enhanced the binding affinity of the CA125 antibody and reproducibility of immunodetection in which a detection limit of 0.01  ng/ml for the cancer biomarker CA125 was achieved. Additionally, the optical texture observed under a crossed polarized microscope was correlated with the analyte concentration. In a proof-of-concept experiment using CA125-spiked human serum as the analyte, specific binding between the CA125 antigen and the anti-CA125 antibody resulted in a distinct and concentration-dependent optical response despite the high background caused by nonspecific binding of other biomolecules in the human serum. Results from this study indicate that UV modification of the alignment layer, as well as detection with LCs of large birefringence, contributes to the enhanced performance of the label-free LC-based immunodetection, which may be considered a promising alternative to conventional label-based methods.
ISSN:1083-3668
1560-2281
DOI:10.1117/1.JBO.20.5.057004