Epidermal growth factor receptor mutations in plasma DNA samples predict tumor response in Chinese patients with stages IIIB to IV non-small-cell lung cancer

Hua Bai, Li Mao, Hang Shu Wang, Jun Zhao, Lu Yang, Tong Tong An, Xin Wang, Chun Jian Duan, Na Mei Wu, Zhi Qing Guo, Yi Xu Liu, Hong Ning Liu, Ye Yu Wang, Jie Wang
Journal of Clinical Oncology 2009 June 1, 27 (16): 2653-9

PURPOSE: Mutations in the epidermal growth factor receptor (EGFR) kinase domain can predict tumor response to tyrosine kinase inhibitors (TKIs) in non-small-cell lung cancer (NSCLC). However, obtaining tumor tissues for mutation analysis is challenging. We hypothesized that plasma-based EGFR mutation analysis is feasible and has value in predicting tumor response in patients with NSCLC.

PATIENTS AND METHODS: Plasma DNA samples and matched tumors from 230 patients with stages IIIB to IV NSCLC were analyzed for EGFR mutations in exons 19 and 21 by using denaturing high-performance liquid chromatography. We compared the mutations in the plasma samples and the matched tumors and determined an association between EGFR mutation status and the patients' clinical outcomes prospectively.

RESULTS: In 230 patients, we detected 81 EGFR mutations in 79 (34.3%) of the patients' plasma samples. We detected the same mutations in 63 (79.7%) of the matched tumors. Sixteen plasma (7.0%) and fourteen tumor (6.1%) samples showed unique mutations. The mutation frequencies were significantly higher in never-smokers and in patients with adenocarcinomas (P = .012 and P = .009, respectively). In the 102 patients who failed platinum-based treatment and who were treated with gefitinib, 22 (59.5%) of the 37 with EGFR mutations in the plasma samples, whereas only 15 (23.1%) of the 65 without EGFR mutations, achieved an objective response (P = .002). Patients with EGFR mutations had a significantly longer progression-free survival time than those without mutations (P = .044) in plasma.

CONCLUSION: EGFR mutations can be reliably detected in plasma DNA of patients with stages IIIB to IV NSCLC and can be used as a biomarker to predict tumor response to TKIs.

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