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

Jacqulyne P. Robichaux, Xiuning Le, R. S. K. Vijayan, J. Kevin Hicks, Simon Heeke, Yasir Y. Elamin, Heather Y. Lin, Hibiki Udagawa, Ferdinandos Skoulidis, Hai Tran, Susan Varghese, Junqin He, Fahao Zhang, Monique B. Nilsson, Lemei Hu, Alissa Poteete, Waree Rinsurongkawong, Xiaoshan Zhang, Chenghui Ren, Xiaoke Liu, Lingzhi Hong, Jianjun Zhang, Lixia Diao, Russell Madison, Alexa B. Schrock, Jennifer Saam, Victoria Raymond, Bingliang Fang, Jing Wang, Min Jin Ha, Jason B. Cross, Jhanelle E. Gray and John V. Heymach ()
Additional contact information
Jacqulyne P. Robichaux: MD Anderson Cancer Center
Xiuning Le: MD Anderson Cancer Center
R. S. K. Vijayan: MD Anderson Cancer Center
J. Kevin Hicks: Moffitt Cancer Center
Simon Heeke: MD Anderson Cancer Center
Yasir Y. Elamin: MD Anderson Cancer Center
Heather Y. Lin: MD Anderson Cancer Center
Hibiki Udagawa: MD Anderson Cancer Center
Ferdinandos Skoulidis: MD Anderson Cancer Center
Hai Tran: MD Anderson Cancer Center
Susan Varghese: MD Anderson Cancer Center
Junqin He: MD Anderson Cancer Center
Fahao Zhang: MD Anderson Cancer Center
Monique B. Nilsson: MD Anderson Cancer Center
Lemei Hu: MD Anderson Cancer Center
Alissa Poteete: MD Anderson Cancer Center
Waree Rinsurongkawong: MD Anderson Cancer Center
Xiaoshan Zhang: MD Anderson Cancer Center
Chenghui Ren: MD Anderson Cancer Center
Xiaoke Liu: MD Anderson Cancer Center
Lingzhi Hong: MD Anderson Cancer Center
Jianjun Zhang: MD Anderson Cancer Center
Lixia Diao: MD Anderson Cancer Center
Russell Madison: Foundation Medicine
Alexa B. Schrock: Foundation Medicine
Jennifer Saam: Guardant Health
Victoria Raymond: Guardant Health
Bingliang Fang: MD Anderson Cancer Center
Jing Wang: MD Anderson Cancer Center
Min Jin Ha: MD Anderson Cancer Center
Jason B. Cross: MD Anderson Cancer Center
Jhanelle E. Gray: Moffitt Cancer Center
John V. Heymach: MD Anderson Cancer Center

Nature, 2021, vol. 597, issue 7878, 732-737

Abstract: 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)1–3. 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.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.nature.com/articles/s41586-021-03898-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:597:y:2021:i:7878:d:10.1038_s41586-021-03898-1

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/s41586-021-03898-1

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().