4.6 Article

EGFR-Co-Mutated Advanced NSCLC and Response to EGFR Tyrosine Kinase Inhibitors

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JOURNAL OF THORACIC ONCOLOGY
卷 12, 期 3, 页码 585-590

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ELSEVIER SCIENCE INC
DOI: 10.1016/j.jtho.2016.09.001

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EGFR; Co-mutation; Double mutation; Multiple mutation; Tyrosine kinase inhibitors

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Objectives: The evolution of EGFR tyrosine kinase inhibitors (TKIs) has changed the landscape of disease for a subset of patients with NSCLC. Most patients with an EGFR mutation respond to these drugs; however, a proportion show limited or no tumor response. We explored the impact of co-mutation (double or multiple mutation), compared with a single mutation, of the EGFR gene on response to TKIs in a series of patients with metastatic NSCLC. Methods: We retrospectively analyzed the mutation profiles of nonsquamous NSCLC tested at Royal Prince Alfred Hospital between 2012 and 2015 by MassArray using the OncoCarta v1.0 panel. Patients with metastatic disease whose tumors had sensitizing EGFR mutation(s) were included. The primary end point was progression-free survival (PFS). We used the Kaplan-Meier method for PFS and overall survival; the log rank test was used to compare groups with and without co-mutation. Multivariable analysis was done for PFS; response rate was assessed using chi-square and logistic regression analysis. Results: A total of 62 patients were included, and of these, eight (12.9%) had a co-mutation. The median PFS and overall survival times were 11.5 and 26.3 months, respectively. Patients with EGFR co-mutation had a significantly shorter median PFS than those with a single mutation (5.7 months versus 12.3 months, p = 0.02). The response rate to TKIs was significantly worse in those with co-mutation compared with in those without co-mutation (38% versus 89%, p < 0.001). Conclusions: Taking into account the small number of patients in this study, PFS in patients with EGFR co-mutation appeared significantly shorter, and response rate significantly lower, than in patients with a single mutation. Data from multipanel testing may identify subgroups of patients who are likely to respond poorly to standard treatment. Clarification of these subgroups may improve patient care. (C) 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

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