Volume 57, Issue 14 pp. 3711-3716
Communication

Combinatorial Probes for High-Throughput Electrochemical Analysis of Circulating Nucleic Acids in Clinical Samples

Dr. Jagotamoy Das

Dr. Jagotamoy Das

Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2 Canada

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Dr. Ivaylo Ivanov

Dr. Ivaylo Ivanov

Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2 Canada

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Dr. Tina S. Safaei

Dr. Tina S. Safaei

Department of Electrical and Computer Engineering, Faculty of Engineering Department, University of Toronto, Toronto, ON, Canada

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Prof. Edward H. Sargent

Prof. Edward H. Sargent

Department of Electrical and Computer Engineering, Faculty of Engineering Department, University of Toronto, Toronto, ON, Canada

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Prof. Shana O. Kelley

Corresponding Author

Prof. Shana O. Kelley

Department of Pharmaceutical Sciences, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, M5S 3M2 Canada

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First published: 01 February 2018
Citations: 67

Graphical Abstract

By our powers combined: A new strategy based on combinatorial probes immobilized on nanostructured microelectrode sensors enables the analysis of mutant sequences from circulating tumour nucleic acids.

Abstract

The analysis of circulating tumour nucleic acids (ctNAs) provides a minimally invasive way to assess the mutational spectrum of a tumour. However, effective and practical methods for analyzing this emerging class of markers are lacking. Analysis of ctNAs using a sensor-based approach has notable challenges, as it is vital to differentiate nucleic acids from normal cells from mutation-bearing sequences emerging from tumours. Moreover, many genes related to cancer have dozens of different mutations. Herein, we report an electrochemical approach that directly detects genes with mutations in patient serum by using combinatorial probes (CPs). The CPs enable detection of all of the mutant alleles derived from the same part of the gene. As a proof of concept, we analyze mutations of the EGFR gene, which has more than 40 clinically relevant alterations that include deletions, insertions, and point mutations. Our CP-based approach accurately detects mutant sequences directly in patient serum.

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