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Quantitative FRET Imaging to Visualize the Invasiveness of Live Breast Cancer Cells

Overview of attention for article published in PLOS ONE, March 2013
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Title
Quantitative FRET Imaging to Visualize the Invasiveness of Live Breast Cancer Cells
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0058569
Pubmed ID
Authors

Shaoying Lu, Yi Wang, He Huang, Yijia Pan, Eric J. Chaney, Stephen A. Boppart, Howard Ozer, Alex Y. Strongin, Yingxiao Wang

Abstract

Matrix metalloproteinases (MMPs) remodel tumor microenvironment and promote cancer metastasis. Among the MMP family proteases, the proteolytic activity of the pro-tumorigenic and pro-metastatic membrane-type 1 (MT1)-MMP constitutes a promising and targetable biomarker of aggressive cancer tumors. In this study, we systematically developed and characterized several highly sensitive and specific biosensors based on fluorescence resonant energy transfer (FRET), for visualizing MT1-MMP activity in live cells. The sensitivity of the AHLR-MT1-MMP biosensor was the highest and five times that of a reported version. Hence, the AHLR biosensor was employed to quantitatively profile the MT1-MMP activity in multiple breast cancer cell lines, and to visualize the spatiotemporal MT1-MMP activity simultaneously with the underlying collagen matrix at the single cell level. We detected a significantly higher level of MT1-MMP activity in invasive cancer cells than those in benign or non-invasive cells. Our results further show that the high MT1-MMP activity was stimulated by the adhesion of invasive cancer cells onto the extracellular matrix, which is precisely correlated with the cell's ability to degrade the collagen matrix. Thus, we systematically optimized a FRET-based biosensor, which provides a powerful tool to detect the pro-invasive MT1-MMP activity at single cell levels. This readout can be applied to profile the invasiveness of single cells from clinical samples, and to serve as an indicator for screening anti-cancer inhibitors.

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Geographical breakdown

Country Count As %
France 1 2%
Belgium 1 2%
Unknown 41 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 40%
Researcher 8 19%
Student > Master 4 9%
Student > Doctoral Student 3 7%
Student > Bachelor 2 5%
Other 4 9%
Unknown 5 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 23%
Biochemistry, Genetics and Molecular Biology 8 19%
Physics and Astronomy 4 9%
Medicine and Dentistry 3 7%
Engineering 3 7%
Other 10 23%
Unknown 5 12%