Real-time bidirectional pyrophosphorolysis-activated polymerization for quantitative detection of somatic mutations.

Detection of somatic mutations for targeted therapy is increasingly used in clinical settings. However, due to the difficulties of detecting rare mutations in excess of wild-type DNA, current methods often lack high sensitivity, require multiple procedural steps, or fail to be quantitative. We devel...

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Bibliographic Details
Main Authors: Najie Song, Xueting Zhong, Qingge Li
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4000192?pdf=render
Description
Summary:Detection of somatic mutations for targeted therapy is increasingly used in clinical settings. However, due to the difficulties of detecting rare mutations in excess of wild-type DNA, current methods often lack high sensitivity, require multiple procedural steps, or fail to be quantitative. We developed real-time bidirectional pyrophosphorolysis-activated polymerization (real-time Bi-PAP) that allows quantitative detection of somatic mutations. We applied the method to quantify seven mutations at codons 12 and 13 in KRAS, and 2 mutations (L858R, and T790M) in EGFR in clinical samples. The real-time Bi-PAP could detect 0.01% mutation in the presence of 100 ng template DNA. Of the 34 samples from the colon cancer patients, real-time Bi-PAP detected 14 KRAS mutant samples whereas the traditional real-time allele-specific PCR missed two samples with mutation abundance <1% and DNA sequencing missed nine samples with mutation abundance <10%. The detection results of the two EGFR mutations in 45 non-small cell lung cancer samples further supported the applicability of the real-time Bi-PAP. The real-time Bi-PAP also proved to be more efficient than the real-time allele-specific PCR in the detection of templates prepared from formalin-fixed paraffin-embedded samples. Thus, real-time Bi-PAP can be used for rapid and accurate quantification of somatic mutations. This flexible approach could be widely used for somatic mutation detection in clinical settings.
ISSN:1932-6203