美国德州大学MD安德森癌症中心John V. Heymach团队发现，基于结构的分类可预测EGFR突变型NSCLC的药物反应。相关论文于2021年9月15日在线发表在《自然》杂志上。

研究人员报道了16,715名表皮生长因子受体（EGFR突变的非小细胞肺癌（NSCLC）患者的突变情况，并建立了EGFR突变对药物敏感性的结构-功能关系。研究人员发现，根据敏感性和结构变化，可以将EGFR突变分成四个不同的亚组，这些亚组比传统的基于外显子的组别更能回顾性地预测患者接受EGFR抑制剂治疗后的结果。这些数据共同划定了一个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能改善对具有不同突变肿瘤基因的药物敏感性预测。

据介绍，EGFR突变通常发生在18-21号外显子，是NSCLC的已知驱动突变。靶向治疗被批准用于"经典"突变和少数其他突变的患者。然而，对于其他EGFR突变，尚未发现有效的治疗方法。此外，非典型表皮生长因子受体突变的频率和对药物敏感性的影响尚不清楚。

附：英文原文

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

Author: Robichaux, Jacqulyne P., Le, Xiuning, Vijayan, R. S. K., Hicks, J. Kevin, Heeke, Simon, Elamin, Yasir Y., 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, Jianjun, Diao, Lixia, Madison, Russell, Schrock, Alexa B., Saam, Jennifer, Raymond, Victoria, Fang, Bingliang, Wang, Jing, Ha, Min Jin, Cross, Jason B., Gray, Jhanelle E., Heymach, John V.

Issue&Volume: 2021-09-15

Abstract: 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.

DOI: 10.1038/s41586-021-03898-1

Source: https://www.nature.com/articles/s41586-021-03898-1