Issue 43, 2024

Efficient and accurate detection of GC-associated miR-96-5p using a competitive lateral flow method based on SERS

Abstract

To facilitate rapid, efficient, and accurate detection of miR-96-5p associated with gastric cancer (GC), we developed a bioanalytical platform by integrating surface-enhanced Raman spectroscopy with lateral flow assay (SERS-LFA). With these SERS-LFA strips, miR-96-5p within the specimen competed with Au rhombic dodecahedron (AuRD) conjugated single-stranded DNA (ssDNA) to bond to the immobilized hairpin DNA (hpDNA) probe on the T line. Consequently, higher abundance of miR-96-5p led to reduced conjugation of AuRD on the T line, thereby resulting in diminished SERS intensity. The biosensor exhibited a detection time of approximately 30 min and demonstrated a low limit of detection (LOD) for miR-96-5p in PBS buffer solution, down to 3.7 fM. To validate its clinical utility for the early diagnosis of patients with different degrees of gastric lesions, we performed quantitative evaluations in cohorts that included healthy individuals, patients with mild intraepithelial neoplasia, patients with severe intraepithelial neoplasia, as well as patients diagnosed with GC. The results obtained from the SERS-LFA strips were in agreement with those obtained from the quantitative real-time polymerase chain reaction (qRT-PCR). Given the accomplishments, this biosensor has significant potential for the clinical diagnosis of GC, offering a promising avenue for timely detection and improved patient prognoses.

Graphical abstract: Efficient and accurate detection of GC-associated miR-96-5p using a competitive lateral flow method based on SERS

Supplementary files

Article information

Article type
Paper
Submitted
26 May 2024
Accepted
13 Aug 2024
First published
08 Oct 2024
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2024,14, 31809-31819

Efficient and accurate detection of GC-associated miR-96-5p using a competitive lateral flow method based on SERS

L. Jia, Y. Liu, Y. Zhang, S. Zhang, X. Cao, Y. Xu, Y. Zhao and B. Deng, RSC Adv., 2024, 14, 31809 DOI: 10.1039/D4RA03880K

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