当前位置: X-MOL 学术Nature › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Structure-based classification predicts drug response in EGFR-mutant NSCLC
Nature ( IF 50.5 ) Pub Date : 2021-09-15 , DOI: 10.1038/s41586-021-03898-1
Jacqulyne P Robichaux 1 , Xiuning Le 1 , R S K Vijayan 2 , J Kevin Hicks 3 , Simon Heeke 1 , Yasir Y Elamin 1 , Heather Y Lin 4 , Hibiki Udagawa 1 , Ferdinandos Skoulidis 1 , Hai Tran 1 , Susan Varghese 1 , Junqin He 1 , Fahao Zhang 1 , Monique B Nilsson 1 , Lemei Hu 1 , Alissa Poteete 1 , Waree Rinsurongkawong 5 , Xiaoshan Zhang 6 , Chenghui Ren 6 , Xiaoke Liu 1, 7 , Lingzhi Hong 1 , Jianjun Zhang 1 , Lixia Diao 8 , Russell Madison 9 , Alexa B Schrock 9 , Jennifer Saam 10 , Victoria Raymond 10 , Bingliang Fang 6 , Jing Wang 8 , Min Jin Ha 4 , Jason B Cross 2 , Jhanelle E Gray 11 , John V Heymach 1
Affiliation  

Epidermal growth factor receptor (EGFR) mutations typically occur in exons 18–21 and are established driver mutations in non-small cell lung cancer (NSCLC)1,2,3. Targeted therapies are approved for patients with ‘classical’ mutations and a small number of other mutations4,5,6. However, effective therapies have not been identified for additional EGFR mutations. Furthermore, the frequency and effects of atypical EGFR mutations on drug sensitivity are unknown1,3,7,8,9,10. 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.



中文翻译:

基于结构的分类预测 EGFR 突变 NSCLC 的药物反应

表皮生长因子受体 ( EGFR ) 突变通常发生在外显子 18-21 中,并且是非小细胞肺癌 (NSCLC) 中已确定的驱动突变1,2,3。靶向治疗被批准用于具有“经典”突变和少数其他突变4,5,6的患者。然而,尚未确定针对其他EGFR突变的有效疗法。此外,非典型EGFR突变对药物敏感性的频率和影响是未知的1,3,7,8,9,10。在这里,我们描述了 16,715 名EGFR突变 NSCLC 患者的突变情况,并建立了EGFR的结构-功能关系药物敏感性的突变。我们发现EGFR突变可以根据敏感性和结构变化分为四个不同的亚组,这些变化比传统的基于外显子的组更好地回顾性地预测患者接受 EGFR 抑制剂治疗后的结果。总之,这些数据描述了一种基于结构的方法来定义EGFR突变的功能组,可以有效地指导EGFR突变 NSCLC患者的治疗和临床试验选择,并表明基于结构功能的方法可以改善对药物敏感性的预测靶向治疗具有多种突变的癌基因。

更新日期:2021-09-15
down
wechat
bug