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

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 mutatio...

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Autores principales: Gu, Linping, Huang, Huayan, Xu, Zhangwendi, Niu, Xiaomin, Li, Ziming, Xia, Liliang, Yu, Yongfeng, Lu, Shun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821726/
https://www.ncbi.nlm.nih.gov/pubmed/36615035
http://dx.doi.org/10.3390/jcm12010236
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author Gu, Linping
Huang, Huayan
Xu, Zhangwendi
Niu, Xiaomin
Li, Ziming
Xia, Liliang
Yu, Yongfeng
Lu, Shun
author_facet Gu, Linping
Huang, Huayan
Xu, Zhangwendi
Niu, Xiaomin
Li, Ziming
Xia, Liliang
Yu, Yongfeng
Lu, Shun
author_sort Gu, Linping
collection PubMed
description 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.
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spelling pubmed-98217262023-01-07 Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study Gu, Linping Huang, Huayan Xu, Zhangwendi Niu, Xiaomin Li, Ziming Xia, Liliang Yu, Yongfeng Lu, Shun J Clin Med Article 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. MDPI 2022-12-28 /pmc/articles/PMC9821726/ /pubmed/36615035 http://dx.doi.org/10.3390/jcm12010236 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gu, Linping
Huang, Huayan
Xu, Zhangwendi
Niu, Xiaomin
Li, Ziming
Xia, Liliang
Yu, Yongfeng
Lu, Shun
Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study
title Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study
title_full Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study
title_fullStr Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study
title_full_unstemmed Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study
title_short Landscape and Predictive Significance of the Structural Classification of EGFR Mutations in Chinese NSCLCs: A Real-World Study
title_sort landscape and predictive significance of the structural classification of egfr mutations in chinese nsclcs: a real-world study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821726/
https://www.ncbi.nlm.nih.gov/pubmed/36615035
http://dx.doi.org/10.3390/jcm12010236
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