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Cited by 703

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Mechanisms of Acquired Resistance to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer

Open access
Engelman, Jeffrey A., Jänne, Pasi A.·2008·Clinical Cancer Research

Abstract

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors gefitinib and erlotinib are effective therapies for non–small cell lung cancer patients whose tumors harbor somatic mutations in EGFR. All patients, however, ultimately develop resistance to these agents. Thus, there is a great need to understand how patients become resistant to develop effective therapies for these cancers. Studies over the last few years have identified two different EGFR tyrosine kinase inhibitor resistance mechanisms, a secondary mutation in EGFR, EGFR 790M, and amplification of the MET oncogene. These findings have led to clinical trials using newly designed targeted therapies that can overcome these resistance mechanisms and have shown promise in laboratory studies. Ongoing research efforts will likely continue to identify additional resistance mechanisms, and these findings will hopefully translate into effective therapies for non–small cell lung cancer patients.

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Registry

Crossref · 10.1158/1078-0432.ccr-07-2248

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Metadata

Authors
Engelman, J. A., & Jänne, P. A.
Venue
Clinical Cancer Research
Published
2008-05-15
Volume
14
Issue
10
Pages
2895-2899
ISSN
  • 1078-0432 (ISSN-L)
  • 1557-3265
OpenAlex
W2140334822
Cited by
703
References
8
FWCI
50.36
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Mechanisms of Acquired Resistance to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer. https://app.cochat.ai/papers/10.1158/1078-0432.ccr-07-2248
The paper
Engelman, J. A., & Jänne, P. A. (2008). Mechanisms of Acquired Resistance to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Non–Small Cell Lung Cancer. Clinical Cancer Research. https://doi.org/10.1158/1078-0432.ccr-07-2248

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.