Issue 3, 2024

Microfluidics-aided fabrication of 3D micro-nano hierarchical SERS substrate for rapid detection of dual hepatocellular carcinoma biomarkers

Abstract

The simultaneous analysis of trace amounts of dual biomarkers is crucial in the early diagnosis, treatment, and prognosis of hepatocellular carcinoma (HCC). In this study, we prepared SERS-active hydrogel microparticles (SAHMs) with 3D hierarchical gold nanoparticles (AuNPs) micro-nanostructures by microdroplet technology and in situ synthesis, which demonstrated high reproducibility and sensitivity. Compared with traditional 2D SERS substrates, this newly prepared 3D SERS substrate provided a high density of nano-wrinkled structures and numerous AuNPs. Furthermore, a newly designed SERS-active substrate was proposed for the simultaneous microfluidic detection of AFP and AFU. The Raman signals of sandwich immunocomplexes on the surface of the SAHMs were measured for the trace analysis of these biomarkers. The proposed microfluidic platform achieved AFP and AFU detection in the range of 0.1–100 ng mL−1 and 0.01–100 ng mL−1, respectively, which represents a good response. Indeed, this platform is easy to fabricate, of low cost and has short detection time and comparable detection limits to other methods. As far as we know, this is the first study to achieve the simultaneous detection of AFP and AFU on a microfluidic platform. Therefore, we proposed a new simultaneous detection platform for dual HCC biomarkers that shows strong potential for the early diagnosis of HCC.

Graphical abstract: Microfluidics-aided fabrication of 3D micro-nano hierarchical SERS substrate for rapid detection of dual hepatocellular carcinoma biomarkers

Supplementary files

Article information

Article type
Paper
Submitted
21 Oct 2023
Accepted
11 Dec 2023
First published
12 Dec 2023

Lab Chip, 2024,24, 528-536

Microfluidics-aided fabrication of 3D micro-nano hierarchical SERS substrate for rapid detection of dual hepatocellular carcinoma biomarkers

C. Zhan, Z. Guan, L. Yu, T. Jing, H. Jia, X. Chen and R. Gao, Lab Chip, 2024, 24, 528 DOI: 10.1039/D3LC00907F

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