Genotyping of common EGFR mutations in lung cancer patients by electrochemical biosensor.

J Pharm Biomed Anal

Department of Pharmaceutical Analysis, Fujian Medical University, Fuzhou, Fujian 350004, PR China. Electronic address:

Published: February 2018

AI Article Synopsis

  • Developed a sandwich-type biosensor to detect six mutations in the EGFR gene using tissue samples from non-small cell lung cancer patients.
  • Optimized the design of DNA capture probes by varying non-complementary sequences, finding that sequences in the middle improve specificity for mutation detection.
  • Introduced a grouped testing approach to streamline the identification of mutations, achieving results consistent with direct sequencing methods.

Article Abstract

In this study, we constructed a sandwich-type biosensor to identify six common types of mutations in exon 19 of the epidermal growth factor receptor (EGFR) gene, and tested them using tissue samples from patients with non-small cell lung carcinomas. Considering the characteristics that different locations of non-complementary in DNA probes resulting in different hybridization efficiency, we investigated the design of DNA capture probes with varying non-complementary sequence locations in an effort to optimize the selectivity of the biosensor. Our results revealed that non-complementary sequences located in the middle of a capture probe allow excellent hybridization specificity and achieve the strongest discrimination between mutations that differ by a single nucleotide. Based on this finding, we designed capture probes to identify six common types of EGFR mutations (del1-del6) successfully. Further, we proposed a grouped testing approach to reduce workload and rapidly identify mutation types. Subsequently, EGFR exon 19 hotspot deletion types in real samples were discriminated by this method. RT-PCR products from lung cancer patients were digested with λ-Exo and analyzed using electrochemical biosensors. The results of our grouped testing approach with optimized biosensors were consistent with that of direct sequencing, suggesting that our proposed protocol can be excellent candidate for genotyping of EGFR mutations in lung cancer patients.

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http://dx.doi.org/10.1016/j.jpba.2017.12.015DOI Listing

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