Dual-Aptamer-Assisted Ratiometric SERS Biosensor for Ultrasensitive and Precise Identification of Breast Cancer Exosomes

Abstract

Due to the heterogeneity of breast cancer, its early accurate diagnosis remains a challenge. Exosomes carry abundant genetic materials and proteins and are ideal biomarkers for early cancer detection. Herein, a ratiometric surface-enhanced Raman scattering (SERS) biosensor for exosome detection was constructed using a regularly arranged Au@Ag nanoparticles/graphene oxide (Au@Ag NPs/GO) substrate with 4nitrothiophenol (4-NTP) molecules as an internal standard. Aptamers of two overexpressed proteins (epithelial cell adhesion molecule and human epidermal growth factor receptor 2) were linked by a short complementary DNA with rhodamine X modified at the 3′-terminal to form V-shaped double-stranded DNA, which attached to the surface of Au@Ag NPs/GO substrate for the selective recognition of breast cancer cell-derived exosomes. In the presence of exosomes, a competitive reaction occurred, resulting in the formation of the V-shaped double-stranded DNA/exosomes complex, and the V-shaped double-stranded DNA separated from the SERS substrate. The SERS signal of rhodamine X on the V-shaped double-stranded DNA decreased with the concentration of exosomes increasing, whereas the SERS signal of 4-NTP on the substrate remained stable. The ratiometric SERS strategy provides huge electromagnetic enhancement and abundant DNA adsorbing sites on the GO layer, achieving a wide detection range of 2.7 × 10 2 to 2.7 × 10 8 particles/mL and an ultralow limit of detection down to 1.5 × 10 2 particles/mL, without the requirement of any nucleic acid amplification. Particularly, the proposed method has significant applications in early cancer diagnosis as it can accurately identify breast cancer cell-derived exosomes in clinical serum samples and can differentiate pancreatic cancer patients and healthy individuals.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

“…Li et al also performed similar studies [ 161 ] and was also used for quantitative molecular phenotyping in a different study [ 162 ]. Recently, ratiometric SERS has been used for the identification of breast cancer using Au@Ag and GO nanostructures [ 163 ]. Cell suspensions of normal and breast cancer cells were analyzed using SERS coupled with Random Forest classifier to understand the differences.…”

Aptamers Targeting Membrane Proteins for Sensor and Diagnostic Applications

“…SERS was also applied recently for the sensitive detection of cancer biomarkers, such as carcinoembryonic antigen (CEA) [167]. In particular, Zhang et al have shown valuable improvement in the utilization of SERS through the detection of cancer cell-derived exosomes in clinical serum samples [168]. Their ratiometric SERS aptasensor (for HER2 and EpCAM), as opposed to conventional SERS, demonstrated high accuracy for target identification (considering the heterogeneity of cancer exosomes) and ultrahigh sensitivity for the early detection of cancer in patients and without any need for nucleic acid amplification.…”

Emerging Sensing and In Situ Detection Technologies for the Analysis of Extracellular Vesicle miRNAs

“…Clinical Applications EV-miRNAs are associated with the progression of many cancers, and several emerging assays have been validated in clinical samples, mostly from serum or plasma, but also from urine and some tissue fluids. These assays detect single or multiple miRNAs for the diagnosis of related diseases such as PDAC, [98] breast cancer, [99] CRC, [100] thyroid cancer, [101] and oral squamous cell carcinoma. [102] Emerging assays have shown good performance in the detection of EV-miRNAs due to their high specificity and sensitivity (Table 2).…”