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Immunosensing of prostate cancer in human plasma samples using immobilization of antibody on the surface of mesoporous silica modified silver nanoparticles and its immunocomplex with prostate specific antigen

Abstract

An innovative screening method for the early stage diagnosis of prostate cancer in human plasma samples was proposed in this study. For this purpose, an immunoassay based on immobilization of PSA antibody on the mesoporous silica-silver nanoparticles (MSNPs-AgNPs) and it successfully designed to detection of the PSA biomarker in human plasma samples was developed. The SiO2-AgNPs provides a large surface area for the effective immobilization of PSA antibody, as well as it ascertains the bioactivity and stability of immobilized PSA antigens. Field emission scanning electron microscope (FE-SEM) was employed to monitor the sensor fabrication. The engineered immunosensor was used for the detection of PSA using differential pulse voltammetry (DPVs) and square wave voltammetry (SWVs) techniques. The proposed interface lead to enhancement of accessible surface area for immobilizing a high amount of anti-PSA antibody, increasing electrical conductivity, boosting stability, catalytic properties and biocompatibility. Under the optimized conditions, the low limit of quantitation (LLOQ) for the proposed immunosensor was recorded as 1ng/ml which this evaluation was performed at highly linear range of 0.1-0.001 µg.L-1. The proposed immunoassay was successfully applied for monitoring of the PSA in unprocessed human plasma samples.

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Supplementary files

Publication details

The article was received on 21 Sep 2019, accepted on 05 Nov 2019 and first published on 05 Nov 2019


Article type: Paper
DOI: 10.1039/C9AY02058F
Anal. Methods, 2019, Accepted Manuscript

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    Immunosensing of prostate cancer in human plasma samples using immobilization of antibody on the surface of mesoporous silica modified silver nanoparticles and its immunocomplex with prostate specific antigen

    F. Farshchi, M. Hasanzadeh and E. Solhi, Anal. Methods, 2019, Accepted Manuscript , DOI: 10.1039/C9AY02058F

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