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Label-Free Recognition of Drug Resistance via Impedimetric Screening of Breast Cancer Cells

Overview of attention for article published in PLOS ONE, March 2013
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Title
Label-Free Recognition of Drug Resistance via Impedimetric Screening of Breast Cancer Cells
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0057423
Pubmed ID
Authors

Bilge Eker, Robert Meissner, Arnaud Bertsch, Kapil Mehta, Philippe Renaud

Abstract

We present a novel study on label-free recognition and distinction of drug resistant breast cancer cells (MCF-7 DOX) from their parental cells (MCF-7 WT) via impedimetric measurements. Drug resistant cells exhibited significant differences in their dielectric properties compared to wild-type cells, exerting much higher extracellular resistance (Rextra ). Immunostaining revealed that MCF-7 DOX cells gained a much denser F-actin network upon acquiring drug resistance indicating that remodeling of actin cytoskeleton is probably the reason behind higher Rextra , providing stronger cell architecture. Moreover, having exposed both cell types to doxorubicin, we were able to distinguish these two phenotypes based on their substantially different drug response. Interestingly, impedimetric measurements identified a concentration-dependent and reversible increase in cell stiffness in the presence of low non-lethal drug doses. Combined with a profound frequency analysis, these findings enabled distinguishing distinct cellular responses during drug exposure within four concentration ranges without using any labeling. Overall, this study highlights the possibility to differentiate drug resistant phenotypes from their parental cells and to assess their drug response by using microelectrodes, offering direct, real-time and noninvasive measurements of cell dependent parameters under drug exposure, hence providing a promising step for personalized medicine applications such as evaluation of the disease progress and optimization of the drug treatment of a patient during chemotherapy.

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The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 61 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 35%
Researcher 11 18%
Student > Master 10 16%
Student > Doctoral Student 3 5%
Student > Bachelor 3 5%
Other 8 13%
Unknown 5 8%
Readers by discipline Count As %
Engineering 19 31%
Agricultural and Biological Sciences 10 16%
Biochemistry, Genetics and Molecular Biology 9 15%
Chemistry 3 5%
Materials Science 3 5%
Other 7 11%
Unknown 11 18%