Abstract
e13658 Background: As a major type of liquid biopsy, circulating tumor DNA (ctDNA) provides important somatic mutation information, but the feature of rare allele frequency of mutation in ctDNA hampers its wide application. Methodology with high sensitivity, cost effectiveness, and multiplexing capability is needed for analyzing ctDNA samples. Methods: We have developed a novel methodology, termed MTEA (Multiplexed Toehold Exchange Amplification), which selectively amplifies and enriches all sequence variants (including SNV and deletion) 1000-fold over the wild-type sequence within ~20-nucleotide window. The amplified products are detected by Sanger sequencing or next-generation sequencing (NGS). This novel approach takes advantage of toehold exchange principle in which PCR amplification of wild-type rather than mutants would be greatly reduced due to the formation of a duplex of wild-type sequence with a blocker targeting to the wild-type rather than the mutant alleles. Results: Using circulating cell-free DNA (cfDNA) reference standards, we demonstrated that the major driver mutations of lung adenocarcinomas, including EGFR L858R and exon 19 deletion, KRAS G12X, and BRAF V600E, were enriched and detected simultaneously with MTEA technology at abundance as low as 0.01-0.05%. The clinical implications of MTEA technology were further validated using ctDNA from liquid biopsy specimens of 29 non-small cell lung cancer patients, and results were compared with those collected from the NGS and ddPCR analysis. Consistent results were obtained from all of the three platforms, which indicated 100% accuracy. The MTEA method has advantages over ddPCR since the later lacks the multiplexing detection ability. The MTEA technology can also save cost compared with NGS method. Conclusions: MTEA technology can enrich ctDNA from cancer patients to detect ultra-low abundance of clinically relevant mutations. Upon validation using a larger cohort, the technology may have wide application in precision medicine and guide clinicians for therapeutic decisions.
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