↓ Skip to main content

Consequences of cell-to-cell P-glycoprotein transfer on acquired multidrug resistance in breast cancer: a cell population dynamics model

Overview of attention for article published in Biology Direct, January 2011
Altmetric Badge

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
52 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Consequences of cell-to-cell P-glycoprotein transfer on acquired multidrug resistance in breast cancer: a cell population dynamics model
Published in
Biology Direct, January 2011
DOI 10.1186/1745-6150-6-5
Pubmed ID
Authors

Jennifer Pasquier, Pierre Magal, Céline Boulangé-Lecomte, Glenn Webb, Frank Le Foll

Abstract

Cancer is a proliferation disease affecting a genetically unstable cell population, in which molecular alterations can be somatically inherited by genetic, epigenetic or extragenetic transmission processes, leading to a cooperation of neoplastic cells within tumoural tissue. The efflux protein P-glycoprotein (P-gp) is overexpressed in many cancer cells and has known capacity to confer multidrug resistance to cytotoxic therapies. Recently, cell-to-cell P-gp transfers have been shown. Herein, we combine experimental evidence and a mathematical model to examine the consequences of an intercellular P-gp trafficking in the extragenetic transfer of multidrug resistance from resistant to sensitive cell subpopulations.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Mexico 1 2%
United States 1 2%
Unknown 49 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 27%
Researcher 11 21%
Student > Master 4 8%
Student > Bachelor 3 6%
Student > Doctoral Student 2 4%
Other 7 13%
Unknown 11 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 23%
Biochemistry, Genetics and Molecular Biology 9 17%
Mathematics 4 8%
Medicine and Dentistry 3 6%
Chemistry 3 6%
Other 8 15%
Unknown 13 25%