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Usage Information

Epidermal growth factor receptor inhibits colitis-associated cancer in mice
Philip E. Dubé, Fang Yan, Shivesh Punit, Nandini Girish, Steven J. McElroy, M. Kay Washington, D. Brent Polk
Philip E. Dubé, Fang Yan, Shivesh Punit, Nandini Girish, Steven J. McElroy, M. Kay Washington, D. Brent Polk
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Research Article Oncology

Epidermal growth factor receptor inhibits colitis-associated cancer in mice

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Abstract

Inflammatory bowel disease (IBD) is a chronic illness caused by complex interactions between genetic and environmental factors that propagate inflammation and damage to the gastrointestinal epithelium. This state of chronic inflammation increases the risk for development of colitis-associated cancer in IBD patients. Thus, the development of targeted therapeutics that can disrupt the cycle of inflammation and epithelial injury is highly attractive. However, such biological therapies, including those targeting epidermal growth factor receptor pathways, pose a risk of increasing cancer rates. Using two mouse models of colitis-associated cancer, we found that epidermal growth factor receptor inactivation accelerated the incidence and progression of colorectal tumors. By modulating inflammation and epithelial regeneration, epidermal growth factor receptor optimized the response to chronic inflammation and limited subsequent tumorigenesis. These findings provide important insights into the pathogenesis of colitis-associated cancer and suggest that epidermal growth factor–based therapies for IBD may reduce long-term cancer risk.

Authors

Philip E. Dubé, Fang Yan, Shivesh Punit, Nandini Girish, Steven J. McElroy, M. Kay Washington, D. Brent Polk

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Usage data is cumulative from May 2025 through May 2026.

Usage JCI PMC
Text version 1,242 100
PDF 177 20
Figure 560 10
Table 131 0
Supplemental data 71 2
Citation downloads 123 0
Totals 2,304 132
Total Views 2,436
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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.

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