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Inhibition of Specific NF-κB Activity Contributes to the Tumor Suppressor Function of 14-3-3σ in Breast Cancer

Overview of attention for article published in PLOS ONE, May 2012
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Title
Inhibition of Specific NF-κB Activity Contributes to the Tumor Suppressor Function of 14-3-3σ in Breast Cancer
Published in
PLOS ONE, May 2012
DOI 10.1371/journal.pone.0038347
Pubmed ID
Authors

Julia Inglés-Esteve, Mònica Morales, Alba Dalmases, Ricard Garcia-Carbonell, Alba Jené-Sanz, Núria López-Bigas, Mar Iglesias, Cristina Ruiz-Herguido, Ana Rovira, Federico Rojo, Joan Albanell, Roger R. Gomis, Anna Bigas, Lluís Espinosa

Abstract

14-3-3σ is frequently lost in human breast cancers by genetic deletion or promoter methylation. We have now investigated the involvement of 14-3-3σ in the termination of NF-κB signal in mammary cells and its putative role in cancer relapse and metastasis. Our results show that 14-3-3σ regulates nuclear export of p65-NF-κB following chronic TNFα stimulation. Restoration of 14-3-3σ in breast cancer cells reduces migration capacity and metastatic abilities in vivo. By microarray analysis, we have identified a genetic signature that responds to TNFα in a 14-3-3σ-dependent manner and significantly associates with different breast and other types of cancer. By interrogating public databases, we have found that over-expression of this signature correlates with poor relapse-free survival in breast cancer patients. Finally, screening of 96 human breast tumors showed that NF-κB activation strictly correlates with the absence of 14-3-3σ and it is significantly associated with worse prognosis in the multivariate analysis. Our findings identify a genetic signature that is important for breast cancer prognosis and for future personalized treatments based on NF-κB targeting.

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The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
Germany 1 2%
Brazil 1 2%
Unknown 42 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 17%
Student > Master 8 17%
Researcher 7 15%
Student > Bachelor 5 11%
Student > Doctoral Student 3 7%
Other 8 17%
Unknown 7 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 26%
Medicine and Dentistry 10 22%
Biochemistry, Genetics and Molecular Biology 7 15%
Chemistry 4 9%
Computer Science 2 4%
Other 2 4%
Unknown 9 20%