Dynamics of EGFR mutations in plasma recapitulates the clinical response to EGFR-TKIs in NSCLC patients

// Liwen Xiong 1, * , Shaohua Cui 1, * , Jingyan Ding 2, * , Yun Sun 2 , Longfu Zhang 3 , Yizhuo Zhao 1 , Aiqin Gu 1 , Tianqing Chu 1 , Huimin Wang 1 , Hua Zhong 1 , Xin Ye 2 , Yi Gu 2 , Xin Zhang 3 , Min Hu 2 and Liyan Jiang 1 1 Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China 2 IMed Asia, AstraZeneca, Shanghai, China 3 Department of Pulmonary Medicine, Zhongshan Hospital, Shanghai Fudan University, Shanghai, China * These authors have contributed equally to this work Correspondence to: Liyan Jiang, email: jiang_liyan2000@126.com Min Hu, email: min-tgx.hu@AstraZeneca.com Xin Zhang, email: zhang.xin@zs-hospital.sh.cn Keywords: epidermal growth factor receptor (EGFR), EGFR tyrosine kinase inhibitors (EGFR-TKIs), circulating tumor DNA (ctDNA), droplet digital PCR (ddPCR), non-small cell lung cancer (NSCLC) Received: October 24, 2016     Accepted: June 10, 2017     Published: July 10, 2017 ABSTRACT Objectives: Genomic profiling using plasma cell-free DNA (cfDNA) represents a non-invasive alternative to tumor re-biopsy, which is challenging in clinical practice. The feasibility of dynamically monitoring epidermal growth factor receptor (EGFR) mutation status using serial plasma samples from non-small cell lung cancer (NSCLC) patients treated by tyrosine kinase inhibitors (TKIs) and its application in tracking clinical response and detection of resistance were investigated. Patients and methods: Forty-five NSCLC patients with EGFR mutation-positive pre-TKI plasma and at least two post-TKI plasma collections were recruited to this study. EGFR mutations including L858R, exon 19 deletion (19-del) and T790M were analyzed using droplet digital PCR (ddPCR) in longitudinally collected plasma samples. Results: We observed a significant reduction in plasma EGFR mutation abundance during the first two-month of TKI treatment. Acquiring of secondary T790M gatekeeper mutation or completed “loss” of EGFR mutations represented two major categories of resistance profiles. Moreover, we demonstrated that levels of plasma EGFR mutations highly correlated with changes of tumor diameter as determined by radiographic imaging, or development of new lesions. In a subset of patients, we further showed that reappearance of EGFR mutations could be detected in plasma up to 5 months ahead of progressive disease (PD), suggesting an early detection of drug resistance. Conclusions: Our findings suggest that genomic analysis using plasma cfDNA may offer an effective approach to monitor clinical response and emergence of resistance.