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  • Title: Dual-Aptamer Modified Graphene Field-Effect Transistor Nanosensor for Label-Free and Specific Detection of Hepatocellular Carcinoma-Derived Microvesicles.
    Author: Wu D, Yu Y, Jin D, Xiao MM, Zhang ZY, Zhang GJ.
    Journal: Anal Chem; 2020 Mar 03; 92(5):4006-4015. PubMed ID: 32040907.
    Abstract:
    Cancerous microvesicles (MVs), which are heterogeneous membrane-bound nanovesicles shed from the surfaces of cancer cells into the extracellular environment, have been widely recognized as promising "biofingerprints" for various cancers. High-performance identification of cancerous MVs plays a vital role in the early diagnosis of cancer, yet it is still technically challenging. Herein, we report a gold nanoparticle (AuNP)-decorated, dual-aptamer modified reduced graphene oxide (RGO) field-effect transistor (AAP-GFET) nanosensor for the label-free, specific, and sensitive quantification of HepG2 cell-derived MVs (HepG2-MVs). After GFET chips were fabricated, AuNPs were then decorated on the RGO surface. For specific capture and detection of HepG2-MVs, both sulfhydrylated HepG2 cell specific TLS11a aptamer (AptTLS11a) and epithelial cell adhesion molecule aptamer (AptEpCAM) were immobilized on the AuNP surface through an Au-S bond. This developed nanosensor delivered a broad linear dynamic range from 6 × 105 to 6 × 109 particles/mL and achieved a high sensitivity of 84 particles/μL for HepG2-MVs detection. Moreover, this AAP-GFET platform was able to distinguish HepG2-MVs from other liver cancer-related serum proteins (such as AFP and CEA) and MVs derived from human normal cells and other cancer cells of lung, pancreas, and prostate, suggesting its excellent method specificity. Compared with those modified with a single type of aptamer alone (AptTLS11a or AptEpCAM), such an AAP-GFET nanosensor showed greatly enhanced signals, suggesting that the dual-aptamer-based bio-nano interface was uniquely designed and could realize more sensitive quantification of HepG2-MVs. Using this platform to detect HepG2-MVs in clinical blood samples, we found that there were significant differences between healthy controls and hepatocellular carcinoma (HCC) patients, indicating its great potential in early HCC diagnosis.
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