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A simple architecture with self-assembled monolayers to build immunosensors for detecting the pancreatic cancer biomarker CA19-9

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Abstract

The challenge of the early diagnosis of pancreatic cancer in routine clinical practice requires low-cost means of detection, and this may be achieved with immunosensors based on electrical or electrochemical principles. In this paper, we report a potentially low-cost immunosensor built with interdigitated gold electrodes coated with a self-assembled monolayer and a layer of anti-CA19-9 antibodies, which is capable of detecting the pancreatic cancer biomarker CA19-9 using electrical impedance spectroscopy. Due to specific, irreversible adsorption of CA19-9 onto its corresponding antibody, according to data from polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS), the immunosensor is highly sensitive and selective. It could detect CA19-9 in commercial samples with a limit of detection of 0.68 U mL−1, in addition to distinguishing between blood serum samples from patients with different concentrations of CA19-9. Furthermore, by treating the capacitance data with information visualization methods, we were able to verify the selectivity and robustness of the immunosensor with regard to false positives, as the samples containing higher CA19-9 concentrations, including those from tumor cells, could be distinguished from those with possible interferents.

Graphical abstract: A simple architecture with self-assembled monolayers to build immunosensors for detecting the pancreatic cancer biomarker CA19-9

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Publication details

The article was received on 07 Mar 2018, accepted on 15 Apr 2018 and first published on 19 Apr 2018


Article type: Paper
DOI: 10.1039/C8AN00430G
Citation: Analyst, 2018, Advance Article
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    A simple architecture with self-assembled monolayers to build immunosensors for detecting the pancreatic cancer biomarker CA19-9

    A. C. Soares, J. C. Soares, F. M. Shimizu, V. D. C. Rodrigues, I. T. Awan, M. E. Melendez, M. H. O. Piazzetta, A. L. Gobbi, R. M. Reis, J. H. T. G. Fregnani, A. L. Carvalho and O. N. Oliveira, Analyst, 2018, Advance Article , DOI: 10.1039/C8AN00430G

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