Electrochemical detection of FAM134B mutations in oesophageal cancer based on DNA-gold affinity interactions

Md Hakimul Haque, Md Nazmul Islam, Farhadul Islam, Vinod Gopalan, Nam Trung Nguyen, Alfred K. Lam, Muhammad J.A. Shiddiky

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Inexpensive, simple and rapid DNA sensors capable of accurate and sensitive detection of cancer specific point mutations in DNA biomarkers are crucial for the routine screening of genetic mutations in cancer. Conventional approaches based on sequencing, mass spectroscopy, and fluorescence are highly effective, but they are tedious, slow and require labels and expensive equipment. Recent electrochemistry based approaches mostly rely on conventional DNA biosensing using recognition and transduction layers, and hence limited by the complicated steps of sensor fabrication associated with surface cleaning, self-assembled monolayer formation, and target hybridization. Herein we report a relatively simple and inexpensive method for detecting point mutation in cancer by using the direct adsorption of purified DNA sequences onto an unmodified gold surface. The method relies on the base dependent affinity interaction of DNA with gold. Since the affinity interaction (adsorption) trend of DNA bases follows as adenine (A) > cytosine (C) > guanine (G)> thymine (T), two DNA sequences with different DNA base compositions (i. e., amplified mutated sequences will be distinctly different than its original sequence) will have different adsorption affinity towards gold. The amount of mutation sites on a DNA sequence is quantified by monitoring the electrochemical current as a function of the relative adsorption level of DNA samples onto a bare gold electrode. This method can successfully distinguish single point mutation in DNA from oesophageal cancer. We demonstrated the clinical utility of this approach by detecting different levels of mutations in tissue samples (n=9) taken from oesophageal cancer patients. Finally, the method was validated with High Resolution Melt (HRM) curve analysis and Sanger Sequencing.
Original languageEnglish
Pages (from-to)1359-1367
Number of pages9
Issue number5
Early online dateFeb 2017
Publication statusPublished - May 2017


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