Estimation of cell-free circulating EGFR mutation concentration predicts outcomes in NSCLC patients treated with EGFR-TKIs
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Yan-juan Zhu1, Hai-bo Zhang1, Yi-hong Liu1, Fu-li Zhang1, Ya-zhen Zhu2, Yong Li1, Jian-ping Bai1, Li-rong Liu1, Yan-chun Qu1, Xin Qu1, Xian Chen1, Yan Li1, Guang-juan Zheng2
1Oncology Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, China
2Pathology Department, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, China
Hai-bo Zhang, email: [email protected]
Keywords: droplet digital polymerase chain reaction, epidermal growth factor receptor, non-small cell lung cancer, blood biopsy
Received: October 25, 2016 Accepted: December 16, 2016 Published: January 04, 2017
Detection of circulating tumor DNA using droplet digital polymerase chain reaction (ddPCR) is a highly-sensitive, minimally invasive alternative to serial biopsies for assessment and management of cancer. We used ddPCR to assess the utility of measuring plasma concentrations of common epidermal growth factor receptor (EGFR) mutations (L858R, exon 19 deletion, and T790M) in 57 non-small cell lung cancer (NSCLC) patients treated with EGFR tyrosine kinase inhibitors (EGFR-TKIs). High baseline plasma EGFR mutation (pEGFRmut) concentrations were associated with shorter progression-free survival (8.43 months) than low baseline pEGFRmut (16.23 months; p = 0.0019). By contrast, there were no differences in tumor shrinkage or overall survival between groups. During EGFR-TKI treatment, pEGFRmut levels decreased to zero in 89.58% of patients. Twenty-five of the 27 patients who progressed had basal pEGFRmut, and 18 also had circulating T790M. All 20 patients with dramatic progression (according to a categorization system for EGFR-TKIs failure) had basal pEGFRmut, and 13 had T790M mutation at progression. These results support the use of ddPCR for analysis of plasma EGFR mutations for prediction of PFS and to monitor clinical responses to EGFR-TKIs in NSCLC patients.
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