Issue 7, 2019

Electrochemical biosensors for autoantibodies in autoimmune and cancer diseases

Abstract

Autoantibodies (AAbs) are antibodies produced against our own cells or tissues either providing a first defense against infections or indicating the presence of pathological processes. They are not only able to inform on the evolution of diseases but also to predict some illnesses well in advance. Currently, the evaluation of the number and type of formed AAbs is employed to assess the risk, rate, severity and progression of autoimmune and cancer diseases, and to help find therapies to prevent or mitigate the impact of these illnesses. Conventional methods for the determination of AAbs generally suffer from low sensitivity, time-consuming and laborious methodologies, and need specialized technicians and well-equipped labs. Consequently, seeking new methodologies for the rapid and low-cost screening of AAbs is of great interest for global health because it would shorten the delay between sample collection and diagnosis and improve the introduction of modern diagnostics into the developing world. Electrochemical biosensors are considered as a promising alternative to conventional techniques for the determination of clinical biomarkers due to their simplicity of use, low cost, high sensitivity, multiplexing abilities or compatibility with microfabrication and point of care testing. This review is focused on the critical discussion of selected electrochemical biosensors described to date for the determination of AAbs related to autoimmune diseases and several types of cancer. An overview pointing out future directions in this field is also provided.

Graphical abstract: Electrochemical biosensors for autoantibodies in autoimmune and cancer diseases

Article information

Article type
Critical Review
Submitted
16 déc. 2018
Accepted
08 janv. 2019
First published
09 janv. 2019

Anal. Methods, 2019,11, 871-887

Electrochemical biosensors for autoantibodies in autoimmune and cancer diseases

S. Campuzano, M. Pedrero, A. González-Cortés, P. Yáñez-Sedeño and J. M. Pingarrón, Anal. Methods, 2019, 11, 871 DOI: 10.1039/C8AY02742K

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