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Phosphocaveolin-1 Enforces Tumor Growth and Chemoresistance in Rhabdomyosarcoma

Overview of attention for article published in PLOS ONE, January 2014
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Title
Phosphocaveolin-1 Enforces Tumor Growth and Chemoresistance in Rhabdomyosarcoma
Published in
PLOS ONE, January 2014
DOI 10.1371/journal.pone.0084618
Pubmed ID
Authors

Fiorella Faggi, Stefania Mitola, Guglielmo Sorci, Francesca Riuzzi, Rosario Donato, Silvia Codenotti, Pietro Luigi Poliani, Manuela Cominelli, Raffaella Vescovi, Stefania Rossi, Stefano Calza, Marina Colombi, Fabio Penna, Paola Costelli, Ilaria Perini, Maurilio Sampaolesi, Eugenio Monti, Alessandro Fanzani

Abstract

Caveolin-1 (Cav-1) can ambiguously behave as either tumor suppressor or oncogene depending on its phosphorylation state and the type of cancer. In this study we show that Cav-1 was phosphorylated on tyrosine 14 (pCav-1) by Src-kinase family members in various human cell lines and primary mouse cultures of rhabdomyosarcoma (RMS), the most frequent soft-tissue sarcoma affecting childhood. Cav-1 overexpression in the human embryonal RD or alveolar RH30 cells yielded increased pCav-1 levels and reinforced the phosphorylation state of either ERK or AKT kinase, respectively, in turn enhancing in vitro cell proliferation, migration, invasiveness and chemoresistance. In contrast, reducing the pCav-1 levels by administration of a Src-kinase inhibitor or through targeted Cav-1 silencing counteracted the malignant in vitro phenotype of RMS cells. Consistent with these results, xenotransplantation of Cav-1 overexpressing RD cells into nude mice resulted in substantial tumor growth in comparison to control cells. Taken together, these data point to pCav-1 as an important and therapeutically valuable target for overcoming the progression and multidrug resistance of RMS.

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The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 3%
Portugal 1 3%
Unknown 31 94%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 7 21%
Researcher 5 15%
Student > Ph. D. Student 5 15%
Student > Master 4 12%
Student > Bachelor 3 9%
Other 3 9%
Unknown 6 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 24%
Biochemistry, Genetics and Molecular Biology 7 21%
Medicine and Dentistry 4 12%
Psychology 2 6%
Mathematics 1 3%
Other 0 0%
Unknown 11 33%