Issue 1, 2025

A simple SERS sensor based on antibody-modified Fe3O4@Au MNPs for the detection of CA19-9 in CRC patients

Abstract

This paper presents functionalized magnetic nanoparticles (Fe3O4@Au MNPs) combined with the surface-enhanced Raman spectroscopy (SERS) technique for sensitive detection of colorectal cancer (CRC) protein biomarker carbohydrate antigen 19-9 (CA19-9). Fe3O4@Au MNPs were constructed by the PEI-mediated seed growth method. Then, the signal molecule 5-5′-dithiobis (succinimidyl-2-nitrobenzoic acid) was used as a bridging agent to link CA19-9 antibody, and the SERS sensor was prepared. Using this sensor, detection of CA19-9 can be realized with only a one step sampling reaction. Fe3O4@Au MNPs combine the advantages of magnetic materials and noble metal nanoparticles, effectively amplifying the signal by creating numerous “hot spots” within the Au particle gaps and enhancing magnetic enrichment. Consequently, this approach lowers the detection limit (LOD) and enhances detection sensitivity. The ratio of characteristic peak intensities I1392/I1069 was selected for calculation, and a linear equation was constructed with a LOD as low as 0.27 U mL−1 by quantitative detections of the standard antigen. Finally, the sensor was used to analyze the clinical serum samples from CRC patients and healthy individuals, and the detection results were consistent with the actual results. This method exhibits notable advantages, including simplicity, high sensitivity, specificity, stability and reproducibility. It is expected to provide a new promising analytical method for clinical CA19-9 immunoassay.

Graphical abstract: A simple SERS sensor based on antibody-modified Fe3O4@Au MNPs for the detection of CA19-9 in CRC patients

Supplementary files

Article information

Article type
Paper
Submitted
23 Jul 2024
Accepted
30 Oct 2024
First published
01 Nov 2024

Anal. Methods, 2025,17, 84-91

A simple SERS sensor based on antibody-modified Fe3O4@Au MNPs for the detection of CA19-9 in CRC patients

M. Xu, G. Chen, Y. Huang, H. Song, Z. Wu, F. Jiang, L. Fu, C. Bi, X. Cao and W. Wei, Anal. Methods, 2025, 17, 84 DOI: 10.1039/D4AY01382D

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