Issue 12, 2022

DNA self-assembled Au nanoparticle clusters on silver nanorod arrays for high-sensitive and multiplex detection of cancer-related biomarkers

Abstract

To sensitively detect multiple and cross-species disease-related targets from a single biological sample in a quick and reliable manner is of high importance in accurately diagnosing and monitoring diseases. Herein, a surface-enhanced Raman scattering (SERS) sensor based on a functionalized multiple-armed tetrahedral DNA nanostructure (FMTDN) immobilized silver nanorod (AgNR) array substrate and Au nanoparticle (AuNP) SERS tags is constructed to achieve both multiplex detection and enhanced sensitivity using a sandwich strategy. The sensor can achieve single, dual, and triple biomarker detections of three lung cancer-related nucleic acid and protein biomarkers, i.e., miRNA-21, miRNA-486 and carcinoembryonic antigen (CEA) in human serum. The enhanced SERS signals in multiplex detections are due to the DNA self-assembled AuNP clusters on the silver nanorod array during the assay, and the experimentally obtained relative enhancement factor ratios, 150 for AuNP dimers and 840 for AuNP trimers, qualitatively agree with the numerically calculated local electric field enhancements. The proposed FMTDN-functionalized AgNR SERS sensor is capable of multiplex and cross-species detection of nucleic acid and protein biomarkers with improved sensitivity, which has great potential for the screening and clinical diagnosis of cancer in the early stage.

Graphical abstract: DNA self-assembled Au nanoparticle clusters on silver nanorod arrays for high-sensitive and multiplex detection of cancer-related biomarkers

Supplementary files

Article information

Article type
Paper
Submitted
08 jan 2022
Accepted
22 fev 2022
First published
22 fev 2022

Nanoscale, 2022,14, 4538-4547

Author version available

DNA self-assembled Au nanoparticle clusters on silver nanorod arrays for high-sensitive and multiplex detection of cancer-related biomarkers

Y. Yang, C. Song, J. Zhang, J. Chao, H. M. Luong, Y. Zhao and L. Wang, Nanoscale, 2022, 14, 4538 DOI: 10.1039/D2NR00133K

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