Document Type

Article

Publication Date

3-2016

Publication Title

Biochimie

Volume

122

First Page

68

Last Page

76

DOI

https://doi.org/10.1016/j.biochi.2015.09.015

Abstract

Proteases are essential for normal physiology as well as multiple diseases, e.g., playing a causative role in cancer progression, including in tumor angiogenesis, invasion, and metastasis. Identification of dynamic alterations in protease activity may allow us to detect early stage cancers and to assess the efficacy of anti-cancer therapies. Despite the clinical importance of proteases in cancer progression, their functional roles individually and within the context of complex protease networks have not yet been well defined. These gaps in our understanding might be addressed with: 1) accurate and sensitive tools and methods to directly identify changes in protease activities in live cells, and 2) pathomimetic avatars for cancer that recapitulate in vitro the tumor in the context of its cellular and non-cellular microenvironment. Such avatars should be designed to facilitate mechanistic studies that can be translated to animal models and ultimately the clinic. Here, we will describe basic principles and recent applications of live-cell imaging for identification of active proteases. The avatars optimized by our laboratory are three-dimensional (3D) human breast cancer models in a matrix of reconstituted basement membrane (rBM). They are designated mammary architecture and microenvironment engineering (MAME) models as they have been designed to mimic the structural and functional interactions among cell types in the normal and cancerous human breast. We have demonstrated the usefulness of these pathomimetic avatars for following dynamic and temporal changes in cell:cell interactions and quantifying changes in protease activity associated with these interactions in real-time (4D). We also briefly describe adaptation of the avatars to custom-designed and fabricated tissue architecture and microenvironment engineering (TAME) chambers that enhance our ability to analyze concomitant changes in the malignant phenotype and the associated tumor microenvironment.

Comments

This work was supported in part by R01 CA131990 and R21 CA175931 from the National Institutes of Health to Dr. Sloane and an award from the President's Research Enhancement Program of Wayne State University to Drs. Sloane and Xu. Imaging was performed in the Microscopy, Imaging and Cytometry Resources Core, which is supported, in part, by NIH Center grant P30 CA022453 to the Karmanos Cancer Institute at Wayne State University, and the Perinatology Research Branch of the National Institutes of Child Health and Development at Wayne State University.

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