Go to JCI Insight
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Alerts
  • Advertising
  • Job board
  • Subscribe
  • Contact
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Gastroenterology
    • Immunology
    • Metabolism
    • Nephrology
    • Neuroscience
    • Oncology
    • Pulmonology
    • Vascular biology
    • All ...
  • Videos
    • Conversations with Giants in Medicine
    • Author's Takes
  • Reviews
    • View all reviews ...
    • Immune Environment in Glioblastoma (Upcoming)
    • Korsmeyer Award 25th Anniversary Collection (Jan 2023)
    • Aging (Jul 2022)
    • Next-Generation Sequencing in Medicine (Jun 2022)
    • New Therapeutic Targets in Cardiovascular Diseases (Mar 2022)
    • Immunometabolism (Jan 2022)
    • Circadian Rhythm (Oct 2021)
    • View all review series ...
  • Viewpoint
  • Collections
    • In-Press Preview
    • Commentaries
    • Research letters
    • Letters to the editor
    • Editorials
    • Viewpoint
    • Top read articles
  • Clinical Medicine
  • JCI This Month
    • Current issue
    • Past issues

  • Current issue
  • Past issues
  • Specialties
  • Reviews
  • Review series
  • Conversations with Giants in Medicine
  • Author's Takes
  • In-Press Preview
  • Commentaries
  • Research letters
  • Letters to the editor
  • Editorials
  • Viewpoint
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Alerts
  • Advertising
  • Job board
  • Subscribe
  • Contact

Usage Information

Inhibition of DYRK1A destabilizes EGFR and reduces EGFR-dependent glioblastoma growth
Natividad Pozo, … , Juan M. Sepúlveda, Pilar Sánchez-Gómez
Natividad Pozo, … , Juan M. Sepúlveda, Pilar Sánchez-Gómez
Published May 1, 2013
Citation Information: J Clin Invest. 2013;123(6):2475-2487. https://doi.org/10.1172/JCI63623.
View: Text | PDF
Research Article Oncology

Inhibition of DYRK1A destabilizes EGFR and reduces EGFR-dependent glioblastoma growth

  • Text
  • PDF
Abstract

Glioblastomas (GBMs) are very aggressive tumors that are resistant to conventional chemo- and radiotherapy. New molecular therapeutic strategies are required to effectively eliminate the subpopulation of GBM tumor–initiating cells that are responsible for relapse. Since EGFR is altered in 50% of GBMs, it represents one of the most promising targets; however, EGFR kinase inhibitors have produced poor results in clinical assays, with no clear explanation for the observed resistance. We uncovered a fundamental role for the dual-specificity tyrosine phosphorylation–regulated kinase, DYRK1A, in regulating EGFR in GBMs. We found that DYRK1A was highly expressed in these tumors and that its expression was correlated with that of EGFR. Moreover, DYRK1A inhibition promoted EGFR degradation in primary GBM cell lines and neural progenitor cells, sharply reducing the self-renewal capacity of normal and tumorigenic cells. Most importantly, our data suggest that a subset of GBMs depends on high surface EGFR levels, as DYRK1A inhibition compromised their survival and produced a profound decrease in tumor burden. We propose that the recovery of EGFR stability is a key oncogenic event in a large proportion of gliomas and that pharmacological inhibition of DYRK1A could represent a promising therapeutic intervention for EGFR-dependent GBMs.

Authors

Natividad Pozo, Cristina Zahonero, Paloma Fernández, Jose M. Liñares, Angel Ayuso, Masatoshi Hagiwara, Angel Pérez, Jose R. Ricoy, Aurelio Hernández-Laín, Juan M. Sepúlveda, Pilar Sánchez-Gómez

×

Usage data is cumulative from January 2022 through January 2023.

Usage JCI PMC
Text version 711 121
PDF 116 38
Figure 160 1
Table 11 0
Supplemental data 21 2
Citation downloads 23 0
Totals 1,042 162
Total Views 1,204
(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

Copyright © 2023 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

Sign up for email alerts