Circulating cell-free DNA has a high degree of specificity to detect exon 19 deletions and the single-point substitution mutation L858R in non-small cell lung cancer
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Xin Qian1,2,*, Jia Liu3,*, Yuhui Sun4,*, Meifang Wang1,2, Huaiding Lei1,2, Guoshi Luo1,2, Xianjun Liu1,2, Chang Xiong1,2, Dan Liu1,2, Jie Liu1,2, Yijun Tang1,2
1Department of Respiratory Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, P.R. China
2Institute of Respiratory Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, P.R. China
3Department of Orthopedic, Lanzhou University First Hospital, Lanzhou, 730000, Gansu, P.R. China
4Department of Emergency Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, P.R. China
*These authors contributed equally to this work
Yijun Tang, e-mail: email@example.com
Keywords: circulating cell-free DNA, non-small cell lung cancer, sensitivity, specificity, epidermal growth factor receptor
Received: October 29, 2015 Accepted: March 28, 2016 Published: April 11, 2016
Detection of an epidermal growth factor receptor (EGFR) mutation in circulating cell-free DNA (cfDNA) is a noninvasive method to collect genetic information to guide treatment of lung cancer with tyrosine-kinase inhibitors (TKIs). However, the association between cfDNA and detection of EGFR mutations in tumor tissue remains unclear. Here, a meta-analysis was performed to determine whether cfDNA could serve as a substitute for tissue specimens for the detection of EGFR mutations. The pooled sensitivity, specificity, and areas under the curve of cfDNA were 0.60, 0.94, and 0.9208 for the detection of EGFR mutations, 0.64, 0.99, and 0.9583 for detection of the exon 19 deletion, and 0.57, 0.99, and 0.9605 for the detection of the L858R mutation, respectively. Our results showed that cfDNA has a high degree of specificity to detect exon 19 deletions and L858R mutation. Due to its high specificity and noninvasive characteristics, cfDNA analysis presents a promising method to screen for mutations in NSCLC and predict patient response to EGFR-TKI treatment, dynamically assess treatment outcome, and facilitate early detection of resistance mutations.
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