Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study

Abstract

Background: Non-classical EGFR mutations demonstrate heterogeneous and attenuated responsiveness to EGFR TKIs. Non-small cell lung cancer (NSCLC) patients with atypical EGFR mutations have limited therapeutic options. A recent study established a novel structural-based classification of EGFR mutations and showed its value in predicting the response to TKI. We sought to interrogate the distribution of different structural types and to validate the predictive value in Chinese NSCLCs. Methods: A total of 837 tumor samples were retrospectively recruited from 522 patients with unresectable EGFR-mutant NSCLC. EGFR mutations were classified into four groups: classical-like, T790M-like, Ex20ins-L, and PACC. Treatment information and clinical outcomes were obtained from 436 patients. The time to treatment failure (TTF) was determined on a per-sample basis. Results: Of the 837 EGFR-mutant samples, 67.9%, 18.5%, 9.0%, and 3.1% harbored classical-like, T790M-like, PACC, and Ex20ins-L mutations, respectively. Thirteen (1.6%) samples carried mutations beyond the four types. Among the 204 samples with atypical mutations, 33.8%, 36.7%, 12.7%, and 10.3% were classical-like, PACC, Ex20ins-L, and T790M-like, respectively. In patients with PACC mutations, second-generation TKIs demonstrated a significantly longer TTF than first-generation TKIs (first-line: 15.3 vs. 6.2 months, p = 0.009; all-line: 14.7 vs. 7.1 months, p = 0.003), and a trend of longer TTF than third-generation TKIs (all-line: 14.7 vs. 5.1 months, p = 0.135). Conclusions: Our study depicted the landscape of structural types of EGFR mutations in Chinese NSCLC patients. Our results also suggest that the structural classification can serve as a predictive marker for the efficacy of various EGFR TKIs, which would guide therapeutic decision making.