Issue 10, 2022

A dual-signal electrochemical immunosensor for the detection of HPV16 E6 oncoprotein based on PdBP dendritic ternary nanospheres and MBSi-Chi nanocomposites

Abstract

Cervical cancer is a common cancer in women. HPV16 E6 oncoprotein is a reliable biomarker for cervical cancer. Although there are other methods for detecting E6 oncoprotein, the electrochemical method has more advantages, such as low cost, convenience and speed. In this study, a novel dual-signal electrochemical immunosensor for quick and sensitive detection of E6 oncoprotein based on a high efficiency catalyst and signal label was developed. Herein, to achieve quick detection, palladium–boron–phosphorus dendritic ternary nanospheres (PdBP NSs) not only acted as a catalyst to catalyze H2O2, but also as a support material to capture antibodies. Moreover, to realize sensitive detection, nanocomposites of mesoporous silica nanoparticles loaded with methylene blue and coated with chitosan (MBSi-Chi) were synthesized as a signal label, which can produce electrochemical signal. Under optimal conditions, the label-free immunosensor exhibited a linear range of 100 fg mL−1 to 4 ng mL−1 with a detection limit of 72.8 fg mL−1 (S/N = 3), and the sandwich-type immunosensor presented a linear range of 50 fg mL−1 to 4 ng mL−1 with a detection limit of 34.1 fg mL−1 (S/N = 3). The as-prepared dual-signal immunosensor had desirable specificity, stability and repeatability, implying its potential applications in clinical laboratory.

Graphical abstract: A dual-signal electrochemical immunosensor for the detection of HPV16 E6 oncoprotein based on PdBP dendritic ternary nanospheres and MBSi-Chi nanocomposites

Supplementary files

Article information

Article type
Paper
Submitted
24 Nov 2021
Accepted
19 Apr 2022
First published
21 Apr 2022

Analyst, 2022,147, 2272-2279

A dual-signal electrochemical immunosensor for the detection of HPV16 E6 oncoprotein based on PdBP dendritic ternary nanospheres and MBSi-Chi nanocomposites

T. Wen, C. Xia, Q. Yu, Y. Yu, S. Li, C. Zhou, K. Sun and S. Yue, Analyst, 2022, 147, 2272 DOI: 10.1039/D1AN02120F

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