Three-Dimensional DNA Hydrogel Mediated Dual-Mode Sensing Method for Quantification of Epithelial Cell Adhesion Molecule in Biological Fluid Samples

Monitoring changes in the expression of marker proteins in biological fluids is essential for biomarker-based disease diagnosis. Epithelial cell adhesion molecule (EpCAM) has been identified as a broad-spectrum biomarker for various chronic diseases and as a therapeutic target. However, the development of simple and reliable methods for quantifying EpCAM changes in biological fluids faces challenges due to the variability of its expression across different diseases, the presence of soluble forms, and matrix effects. In this paper, a surface-enhanced Raman scattering (SERS)-fluorescence (FL) dual-mode sensing method was established for quantification of trace EpCAM in biological fluids based on bimetallic Au@Ag nanoparticles and nitrogen-doped quantum dots encapsulated DNA hydrogel hybrid with graphene oxide (Au@Ag-NQDs/GO). The DNA hydrogel was constructed based on three-dimensional (3D) structure DNA-mediated strategy using an aptamer DNA (AptDNA) linker. The interaction of the AptDNA with EpCAM triggered the disassembly of the DNA hydrogel. Consequently, the release of Au@Ag nanoparticles induced an "on-off" switch in the SERS signal while the weakened FL quenching effect in Au@Ag-NQDs/GO system achieved "off-on" switch of FL signal, enabling the simultaneous SERS-FL quantification of EpCAM. The established dual-mode method exhibited outstanding sensitivity and stability in quantifying EpCAM in the range of 0.5-60.0 pg/mL, with the limits of detection (LODs) of SERS and FL as 0.17 and 0.35 pg/mL, respectively. When applied for real sample analysis, the method showed satisfactory specificity and recoveries in cancer cells lysate, serum, and urine samples with RSDs of 2.8-6.3%, 4.0-6.3%, and 2.8-5.7%, respectively. The developed SERS-FL sensing method offered a sensitive, reliable, and practical quantification strategy for trace EpCAM in diverse biological fluid samples, which would benefit the early diagnosis of disease and further health management.