Structure-based classification predicts drug response in EGFR-mutant NSCLC

Author:

Robichaux Jacqulyne P.,Le Xiuning,Vijayan R. S. K.,Hicks J. Kevin,Heeke SimonORCID,Elamin Yasir Y.ORCID,Lin Heather Y.,Udagawa Hibiki,Skoulidis Ferdinandos,Tran Hai,Varghese Susan,He Junqin,Zhang Fahao,Nilsson Monique B.,Hu Lemei,Poteete Alissa,Rinsurongkawong Waree,Zhang Xiaoshan,Ren Chenghui,Liu Xiaoke,Hong Lingzhi,Zhang JianjunORCID,Diao LixiaORCID,Madison Russell,Schrock Alexa B.,Saam Jennifer,Raymond Victoria,Fang Bingliang,Wang JingORCID,Ha Min Jin,Cross Jason B.,Gray Jhanelle E.,Heymach John V.ORCID

Abstract

AbstractEpidermal growth factor receptor (EGFR) mutations typically occur in exons 18–21 and are established driver mutations in non-small cell lung cancer (NSCLC)1–3. Targeted therapies are approved for patients with ‘classical’ mutations and a small number of other mutations4–6. However, effective therapies have not been identified for additional EGFR mutations. Furthermore, the frequency and effects of atypical EGFR mutations on drug sensitivity are unknown1,3,7–10. Here we characterize the mutational landscape in 16,715 patients with EGFR-mutant NSCLC, and establish the structure–function relationship of EGFR mutations on drug sensitivity. We found that EGFR mutations can be separated into four distinct subgroups on the basis of sensitivity and structural changes that retrospectively predict patient outcomes following treatment with EGFR inhibitors better than traditional exon-based groups. Together, these data delineate a structure-based approach for defining functional groups of EGFR mutations that can effectively guide treatment and clinical trial choices for patients with EGFR-mutant NSCLC and suggest that a structure–function-based approach may improve the prediction of drug sensitivity to targeted therapies in oncogenes with diverse mutations.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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