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Pharmacogenomics of EGFR‐targeted therapies in non–small cell lung cancer: EGFR and beyond

Overview of attention for article published in Cancer Communications, April 2015
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Title
Pharmacogenomics of EGFR‐targeted therapies in non–small cell lung cancer: EGFR and beyond
Published in
Cancer Communications, April 2015
DOI 10.1186/s40880-015-0007-9
Pubmed ID
Authors

Christopher Delaney, Samuel Frank, R Stephanie Huang

Abstract

Commonly observed aberrations in epidermal growth factor receptor (EGFR) signaling have led to the development of EGFR-targeted therapies for various cancers, including non-small cell lung cancer (NSCLC). EGFR mutations and overexpression have further been shown to modulate sensitivity to these EGFR-targeted therapies in NSCLC and several other types of cancers. However, it is clear that mutations and/or genetic variations in EGFR alone cannot explain all of the variability in the responses of patients with NSCLC to EGFR-targeted therapies. For instance, in addition to EGFR genotype, genetic variations in other members of the signaling pathway downstream of EGFR or variations in parallel receptor tyrosine kinase (RTK) pathways are now recognized to have a significant impact on the efficacy of certain EGFR-targeted therapies. In this review, we highlight the mutations and genetic variations in such genes downstream of EGFR and in parallel RTK pathways. Specifically, the directional effects of these pharmacogenetic factors are discussed with a focus on two commonly prescribed EGFR inhibitors: cetuximab and erlotinib. The results of this comprehensive review can be used to optimize the treatment of NSCLC with EGFR inhibitors. Furthermore, they may provide the rationale for the design of subsequent combination therapies that involve the inhibition of EGFR.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 15%
Researcher 6 15%
Student > Bachelor 5 13%
Student > Doctoral Student 4 10%
Student > Ph. D. Student 4 10%
Other 6 15%
Unknown 8 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 26%
Agricultural and Biological Sciences 9 23%
Medicine and Dentistry 5 13%
Pharmacology, Toxicology and Pharmaceutical Science 3 8%
Nursing and Health Professions 2 5%
Other 2 5%
Unknown 8 21%