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Usage Information

Src promotes estrogen-dependent estrogen receptor α proteolysis in human breast cancer
Isabel Chu, Angel Arnaout, Sophie Loiseau, Jun Sun, Arun Seth, Chris McMahon, Kathy Chun, Bryan Hennessy, Gordon B. Mills, Zafar Nawaz, Joyce M. Slingerland
Isabel Chu, Angel Arnaout, Sophie Loiseau, Jun Sun, Arun Seth, Chris McMahon, Kathy Chun, Bryan Hennessy, Gordon B. Mills, Zafar Nawaz, Joyce M. Slingerland
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Research Article Endocrinology

Src promotes estrogen-dependent estrogen receptor α proteolysis in human breast cancer

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Abstract

Estrogen drives both transcriptional activation and proteolysis of estrogen receptor α (ERα; encoded by ESR1). Here we observed variable and overlapping ESR1 mRNA levels in 200 ERα-negative and 50 ERα-positive primary breast cancers examined, which suggests important posttranscriptional ERα regulation. Our results indicate that Src cooperates with estrogen to activate ERα proteolysis. Inducible Src stimulated ligand-activated ERα transcriptional activity and reduced ERα t1/2. Src and ERα levels were inversely correlated in primary breast cancers. ERα-negative primary breast cancers and cell lines showed increased Src levels and/or activity compared with ERα-positive cancers and cells. ERα t1/2 was reduced in ERα-negative cell lines. In both ERα-positive and -negative cell lines, both proteasome and Src inhibitors increased ERα levels. Src inhibition impaired ligand-activated ERα ubiquitylation and increased ERα levels. Src siRNA impaired ligand-activated ERα loss in BT-20 cells. Pretreatment with Src increased ERα ubiquitylation and degradation in vitro. These findings provide what we believe to be a novel link between Src activation and ERα proteolysis and support a model whereby crosstalk between liganded ERα and Src drives ERα transcriptional activity and targets ERα for ubiquitin-dependent proteolysis. Oncogenic Src activation may promote not only proliferation, but also estrogen-activated ERα loss in a subset of ERα-negative breast cancers, altering prognosis and response to therapy.

Authors

Isabel Chu, Angel Arnaout, Sophie Loiseau, Jun Sun, Arun Seth, Chris McMahon, Kathy Chun, Bryan Hennessy, Gordon B. Mills, Zafar Nawaz, Joyce M. Slingerland

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Usage data is cumulative from November 2025 through November 2026.

Usage JCI PMC
Text version 1,392 35
PDF 251 5
Figure 736 1
Supplemental data 126 1
Citation downloads 239 0
Totals 2,744 42
Total Views 2,786
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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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ISSN: 0021-9738 (print), 1558-8238 (online)

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