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Plasma epidermal growth factor receptor mutation testing with a chip-based digital PCR system in patients with advanced non-small cell lung cancer.

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OBJECTIVES Epidermal growth factor receptor (EGFR) mutation testing is a companion diagnostic to determine eligibility for treatment with EGFR tyrosine kinase inhibitors (EGFR-TKIs) in non-small cell lung cancer (NSCLC). Recently,… Click to show full abstract

OBJECTIVES Epidermal growth factor receptor (EGFR) mutation testing is a companion diagnostic to determine eligibility for treatment with EGFR tyrosine kinase inhibitors (EGFR-TKIs) in non-small cell lung cancer (NSCLC). Recently, plasma-based EGFR testing by digital polymerase chain reaction (dPCR), which enables accurate quantification of target DNA, has shown promise as a minimally invasive diagnostic. Here, we aimed to evaluate the accuracy of a plasma-based EGFR mutation test developed using chip-based dPCR-based detection of 3 EGFR mutations (exon 19 deletions, L858R in exon 21, and T790M in exon 20). MATERIALS AND METHODS Forty-nine patients with NSCLC harboring EGFR-activating mutations were enrolled, and circulating free DNAs (cfDNAs) were extracted from the plasma of 21 and 28 patients before treatment and after progression following EGFR-TKI treatment, respectively. RESULTS Using reference genomic DNA containing each mutation, the detection limit of each assay was determined to be 0.1%. The sensitivity and specificity of detecting exon 19 deletions and L858R mutations, calculated by comparing the mutation status in the corresponding tumors, were 70.6% and 93.3%, and 66.7% and 100%, respectively, showing similar results compared with previous studies. T790M was detected in 43% of 28 cfDNAs after progression with EGFR-TKI treatment, but in no cfDNAs before the start of the treatment. CONCLUSION This chip-based dPCR assay can facilitate detection of EGFR mutations in cfDNA as a minimally invasive method in clinical settings.

Keywords: chip based; treatment; mutation; lung cancer

Journal Title: Lung cancer
Year Published: 2017

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