| Literature DB >> 30094655 |
Samira Yazdanparast1, Ali Benvidi2, Maryam Banaei1, Habib Nikukar3,4, Marzieh Dehghan Tezerjani1, Mostafa Azimzadeh5,6.
Abstract
This paper reports on a sensitive and selective method for the detection of Michigan Cancer Foundation-7 (MCF-7) human breast cancer cells and MUC1 biomarker by using an aptamer-based sandwich assay. A biocompatible nanocomposite consisting of multiwall carbon nanotubes (MWCNT) and poly(glutamic acid) is placed on a glassy carbon electrode (GCE). The sandwich assay relies on the use of a mucin 1 (MUC1)-binding aptamer that is first immobilized on the surface of modified GCE. Another aptamer (labeled with silver nanoparticles) is applied for secondary recognition of MCF-7 cells in order to increase selectivity and produce an amplified signal. Differential pulse anodic stripping voltammetry was used to follow the electrochemical signal of the AgNPs. Under the optimal condition, the sensor responds to MCF-7 cells in the concentration range from 1.0 × 102 to 1.0 × 107 cells·mL-1 with a detection limit of 25 cells. We also demonstrate that the MUC1 tumor marker can be detected by the present biosensor. The assay is highly selective and sensitive, acceptably stable and reproducible. This warrants the applicability of the method to early diagnosis of breast cancer. Graphical abstract Schematic of the fabrication of an aptamer-based sandwich biosensor for Michigan Cancer Foundation-7 cells (MCF-7). A MWCNT-poly(glutamic acid) nanocomposite was used as a biocompatible matrix for MUC1-aptamer immobilization. Stripping voltammetry analysis of AgNPs was performed using aptamer conjugated AgNPs as signalling probe.Entities:
Keywords: Aptamer based sandwich assay; Aptamer-AgNP bioconjugates; Carbon nanotube; Differential pulse anodic stripping voltammetry; Electrochemical aptasensor; MUC1 aptamer; Michigan Cancer Foundation-7; Poly(amino acid) nanocomposite
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Year: 2018 PMID: 30094655 DOI: 10.1007/s00604-018-2918-z
Source DB: PubMed Journal: Mikrochim Acta ISSN: 0026-3672 Impact factor: 5.833