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Cited by 370

The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

Targeting EGFR exon 20 insertion mutations in non-small cell lung cancer

Open access
Vyse, Simon, Huang, Paul H.·2019·Signal Transduction and Targeted Therapy

Abstract

Inframe insertions of three or more base pairs in exon 20 of the epidermal growth factor receptor (EGFR) gene were among the first EGFR mutations to be identified as oncogenic drivers in non-small cell lung cancer (NSCLC). However, unlike the classical EGFR L858R point mutation or exon 19 deletions, which represent the majority of EGFR mutations in NSCLC, low frequency EGFR exon 20 insertion mutations are associated with de novo resistance to targeted EGFR inhibitors and correlate with a poor patient prognosis. Here, we review the developments over the last 5 years in which pre-clinical studies, including elucidation of the crystal structure of an EGFR exon 20 insertion mutant kinase, have revealed a unique mechanism of kinase activation and steric conformation that define the lack of response of these EGFR mutations to clinically approved EGFR inhibitors. The recent development of several novel small molecule compounds that selectively inhibit EGFR exon 20 insertions holds promise for future therapeutic options that will be effective for patients with this molecular subtype of NSCLC.

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Metadata

Authors
Vyse, S., & Huang, P. H.
Venue
Signal Transduction and Targeted Therapy
Published
2019-03-08
Volume
4
Issue
1
Pages
5-5
ISSN
2059-3635 (ISSN-L)
OpenAlex
W2920175805
Cited by
370
References
42
FWCI
31.63
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Targeting EGFR exon 20 insertion mutations in non-small cell lung cancer. https://app.cochat.ai/papers/10.1038/s41392-019-0038-9
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Vyse, S., & Huang, P. H. (2019). Targeting EGFR exon 20 insertion mutations in non-small cell lung cancer. Signal Transduction and Targeted Therapy. https://doi.org/10.1038/s41392-019-0038-9

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.