4.4 Article

Dynamic monitoring of EGFR mutations in circulating cell-free DNA for EGFR-mutant metastatic patients with lung cancer: Early detection of drug resistance and prognostic significance

Journal

ONCOLOGY LETTERS
Volume 13, Issue 6, Pages 4549-4557

Publisher

SPANDIDOS PUBL LTD
DOI: 10.3892/ol.2017.6022

Keywords

lung cancer; epidermal growth factor receptor; circulating cell-free DNA; digital polymerase chain reaction

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Funding

  1. Wu Jieping Medical Foundation [320.6750.14281]

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Detecting genetic mutations in circulating cell-free DNA (cfDNA) is a promising approach of liquid biopsy. Between June 2014 and May 2015, 168 plasma samples were collected monthly from 20 patients with metastatic lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutation receiving gefitinib therapy. Clinically relevant EGFR mutations, including exon 19 deletion, L858R and T790M, were quantified using droplet digital polymerase chain reaction. In baseline samples, 19 (95.0%) patients had the same mutation with the matched tumors, and pretreatment T790M mutations were also detected in 3 (15.0%) patients. The dynamics of EGFR mutations were generally associated with treatment response for patients with or without measurable disease. For patients with immeasurable tumor deposits, monitoring disease evolution using cfDNA-based mutation quantification appeared to be more reliable compared with measuring the diameters of target tumor lesions. In addition, molecular progressive disease, defined as a >= 20% increase of EGFR mutation concentration compared with the lowest concentration recorded during treatment, was tracked up to 8 months prior to objective progression. In survival analysis, sex (P=0.005), pretreatment T790M mutation status (P=0.006), T790M mutation status at the disease progression (P=0.043) and growth rate of EGFR mutations (P=0.023), had a significant impact on median progression-free survival. In conclusion, dynamic monitoring of EGFR mutations in cfDNA is feasible and appears to be useful in early prediction of drug resistance for patients with lung cancer receiving EGFR tyrosine kinase inhibitors.

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