Graphene-based electrochemical immunosensors for early detection of oncomarker carcinoembryonic antigen
G. Manasa, Ronald J. Mascarenhas, Shweta J. Malode and 1 more
Biosensors and Bioelectronics: X · 2022
doi:10.1016/j.biosx.2022.100189 (opens in a new tab)
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Abstract
The detection of pre-invasive tumors prior to the appearance of advanced clinical symptoms will enhance the effect of medical intervention at the earliest stage and reduce premature cancer deaths. Tumor biomarkers detection represents a powerful alternative to taking invasive biopsies; hence, biosensing technology is emphasized. Cancer diagnostics have evolved from the macroscopic detection of malignant tumors to the facile assessment of tumor biomarkers using miniaturized detection devices, such as immunosensors. Innovative immunosensors have become the most eminent candidate for analyzing oncomarkers to meet the requirements of medical diagnostics. Hence the development of highly selective immunosensors for the sensitive detection of oncomarker paves new directions for personal and medical supervision. Graphene and its derivatives are emerging carbon materials employed in developing sensors, in view of their exceptional physicochemical properties that amplify the device's sensitivity. Therefore, this review was designed to present a comprehensive interpretation of the recently developed graphene-based electrochemical immunosensors for detecting broad-spectrum oncomarker carcinoembryonic antigen (CEA). The article highlights the recent advances in signal amplification strategies accomplished utilizing graphene and its nanomaterials (2017 to mid-2022). Different electroanalytical techniques employed for CEA sensing have been discussed, and the sensor's performances are substantiated. The readers are also provided with significant statistical information on the reported immunosensors and their performance comparison: a technique used, working range, detection limit, real sample recoveries, reproducibility, and stability. Finally, the review concludes with the associated challenges and outlines the approach required to realize their successful translation into clinical settings.
Abstract licence: CC BY-NC
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