Jornal de Ensaios Clínicos
Acesso livre

Abstrato

Sensitive Detection of Epidermal Growth Factor Receptor T790M using BNAClamp Real-Time PCR

Austin Dinkel, Rachel A. Hoffmeister, Andrew Huckelby, Aaron S. Castro, Miguel M. Castro, SungKun Kim*

Mutations on Epidermal Growth Factor Receptor (EGFR) cause a variety of cancers including breast and lung cancers. The single mutation T790M on the tyrosine kinase domain of EGFR signifies the response to the cancer drugs gefitinib, which leads to the development of resistance to such a drug. Detecting the mutation thus provides effective therapeutic options for patients who are in need of cancer drug treatments. We sought to develop a facile, rapid detection method for the T790M mutation using Bridged Nucleic Acids (BNA), which has been known to enhance the hybridization affinity of oligonucleotides. Oligonucleotides containing BNA bases, called BNA-clamp and designed to block PCR reaction against wild-type genes were used to discriminate the presence of mutant genes mixed with a large number of wild-type genes. Real-time PCR in conjugation with BNA-clamping allows us to observe different degrees of PCR amplification depending on the ratio of wild-type and mutant genes. In an effort to explore the possibility, several 13-mer oligonucleotide clamps were prepared with various numbers of BNA bases. Tm value analysis suggests that the clamps containing 9 BNA bases (BNA-clamp-9) would be most effective in distinguishing the mutant from wild-type genes, and sensitivity tests using BNA-clamp-9 revealed that the clamp had the ability to detect 0.1% or lower levels of the T790M mutation among wild-type genes. Furthermore, binding structures were analyzed via Molecular Dynamics (MD) simulations, revealing that BNA-clamp-9 distorts the originally constructed BDNA structure. Additionally through umbrella sampling, binding free energies with -60 kJ/mol for the wild-type and -40 kJ/mol for the mutant gene were obtained. This BNA-clamping and real time PCR technology may offer a promising avenue to detect clinically important mutations in the future