EGFR Fragmentation for Topological Transformation Nanobarcoding. (28th May 2020)

• Record Type: Journal Article
• Authors: Kim, Jeonghun; Yoo, Changhoon; Moon, Je Hun; Um, Soong Ho
• Is Part Of: Chembiochem. Volume 21:Number 17(2020)
• Page Start: 2533
• Page End: 2539
• Publication Date: 2020-05-28
• Subjects: EGFR mutation -- fragmentation -- lung cancer -- nanobarcoding -- topological transformation; Biochemistry -- Periodicals; Molecular biology -- Periodicals; Pharmaceutical chemistry -- Periodicals; 572
• DOI: 10.1002/cbic.202000179
• Languages: English
• ISSNs: 1439-4227

Abstract

Abstract: As the market for personalized lung cancer medicine expands, the demand for molecular diagnostic tools in general, and methods of detecting multiple genes with qualitative, quantitative, and high specificity in particular, have grown. Here, we propose a system for the effective detection of lung cancer‐specific, long‐length epidermal growth factor receptor (EGFR) gene mutations by using a topological transformation nano‐barcoding technique (TNT). In former TNT studies, EGFR was successfully detected in cell environments and at test stages in the presence of a reference gene. However, because typical EGFR target concentrations are significantly lower at the clinical stage and the probe‐binding ability of long‐length targets is lower that of short targets, our system employs polymerase chain reaction (PCR) amplification, restriction, and filtering (PRF) for EGFR fragmentation to maximize performance. In a PRF system, the target is amplified by PCR, cut to a suitable size by a restriction enzyme, and filtered by a magnetic bead. With detection limits of 0.3555 % and 1.500 % for EGFR Del 19 and L858R mutations, respectively, the proposed TNT with PRF can effectively distinguish mutant cell lines and efficiently detect various lengths of genetic variations in clinical trials. Abstract : The long and short of it : Topological transformation nanobarcoding technology (TNT) has been demonstrated to be very effective in profiling important multiple gene mutations of lung cancer at once. However, it was specific for short‐length variations. To widen the use of the long‐chain lung cancer‐specific EGFR signatures, a short edit and application method to TNT is introduced here.