Usage Information

Signal integration: a framework for understanding the efficacy of therapeutics targeting the human EGFR family
H. Michael Shepard, … , Cathleen M. Brdlik, Hans Schreiber
H. Michael Shepard, … , Cathleen M. Brdlik, Hans Schreiber
Published November 3, 2008
Citation Information: J Clin Invest. 2008;118(11):3574-3581. https://doi.org/10.1172/JCI36049.
View: Text | PDF
Category: Review Series

Signal integration: a framework for understanding the efficacy of therapeutics targeting the human EGFR family

Abstract

The human EGFR (HER) family is essential for communication between many epithelial cancer cell types and the tumor microenvironment. Therapeutics targeting the HER family have demonstrated clinical success in the treatment of diverse epithelial cancers. Here we propose that the success of HER family–targeted monoclonal antibodies in cancer results from their ability to interfere with HER family consolidation of signals initiated by a multitude of other receptor systems. Ligand/receptor systems that initiate these signals include cytokine receptors, chemokine receptors, TLRs, GPCRs, and integrins. We further extrapolate that improvements in cancer therapeutics targeting the HER family are likely to incorporate mechanisms that block or reverse stromal support of malignant progression by isolating the HER family from autocrine and stromal influences.

Authors

H. Michael Shepard, Cathleen M. Brdlik, Hans Schreiber

×

Usage data is cumulative from October 2018 through October 2019.

Usage JCI PMC
Text version 342 56
PDF 69 49
Figure 125 0
Table 10 0
Supplemental data 0 11
Citation downloads 10 0
Totals 556 116
Total Views 672
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement