4.7 Article

Fluorescence-based immunosensor using three-dimensional CNT network structure for sensitive and reproducible detection of oral squamous cell carcinoma biomarker

Journal

ANALYTICA CHIMICA ACTA
Volume 1027, Issue -, Pages 101-108

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2018.04.025

Keywords

Cyfra 21-1; Fluorescence-based immunoassay; Oral squamous cell carcinoma; 3DN-CNTs; Biosensor

Funding

  1. National Research Foundation (NRF) - Korean government (MSIP) [2012M3A7B4035286]
  2. MSIT (Ministry of Science and ICT), Korea, under ITRC (Information Technology Research Center) [IITP-2017-1711055214]
  3. NRF - Ministry of Education [2012R1A6A1029029]
  4. AFOSR/AOARD, USA [FA2386-15-1-4081]

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A hierarchical three-dimensional network of carbon nanotubes on Si pillar substrate (3DN-CNTs) was developed for the accurate detection of oral squamous cell carcinoma (OSCC) in clinical saliva samples. The 3DN-CNTs were uniformly coated with a layer of aluminum oxides to enhance structural stability during biomarker detection. Cytokeratin-19 antigen (Cyfra 21-1) was utilized as a model biomarker of OSCC for fluorescence-based immunosensor using 3DN-CNTs (3DN-CNTs sensor). The 3DN-CNTs sensor enhances the sensitivity of Cyfra 21-1 detection by increasing the density of immobilized antibody through high surface area of 3DN-CNTs and enhancing the accessibility of biomolecules through the ordered pathway of hierarchical structure. The reliable detection limit for sensing of Cyfra 21-1 was estimated as in the level of 0.5 ng/mL and the quantitative estimation of Cyfra 21-1 was analyzed by 4parameter logistic (4-PL) model for curve-fitting analysis. Clinical applicability of 3DN-CNTs sensor was evaluated through correlation with the commercially available electrochemiluminescence (ECL) detection system in the hospital. The assay results of the two systems for clinical saliva samples showed a good linear correlation. The 3DN-CNTs sensor offers great potential for accurate diagnosis of OSCC using Cyfra 21-1 biomarker in clinical fluids. (C) 2018 Elsevier B.V. All rights reserved.

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