Pathomimetic cancer avatars for live-cell imaging of protease activity

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.

In Vitro Models for Studying Invasive Transitions of Ductal Carcinoma In Situ

“…This interplay will vary with time and may include changes in cytokine secretion, proteolytic activity, and morphology such as formation of multicellular invasive outgrowths. Quantitative assays will be needed such as those that can be performed with cultures growing in engineered microfluidic platforms (e.g., platforms that allow regulated delivery of drugs at specific time points [136] and platforms designed for direct or indirect interactions among the cell types [111,136]).…”

“…Therefore, we have fabricated and tested microfluidic platforms that will allow us to image and quantify cell:cell and cell:matrix interactions in 3D cultures over long periods of time and over these same periods collecting conditioned media for analysis of the secretome without disturbing the cultures. The culture wells in our platforms are fabricated from polymers of acrylates [136]. We chose acrylic due to concerns about leaching and absorption in devices made of polydimethylsiloxane (for discussion, see [74,137,138], which will be of higher concern for devices intended for long-term cultures.…”

Role of tumor microenvironment in cancer progression and therapeutic strategy

“…The long‐term dynamic interactions between epithelial breast cancer cells and matrix components (lymph cells, endothelial cells, and fibroblasts) were modeled in three‐dimensional in vitro cultures, 49 which showed images of the protein hydrolysis that occurs in the TME during tumor cell invasion. The TME has important functions in mesenchymal stem cell reprogramming and tumor stems cell characteristic maintenance.…”

Interaction of prostate carcinoma-associated fibroblasts with human epithelial cell lines in vivo

“…This situation has since changed, with the development of effective three-dimensional tissue culture and co-culture approaches and advances in imaging technology to allow the development of tumor avatars that can be used to test specific paradigms (Chambers et al, 2014, Gao et al, 2014, Ji et al, 2016, Osuala et al, 2015, Sameni et al, 2012, Sameni et al, 2017, Windus et al, 2012). Such approaches also provide a valuable method of preclinical testing of potential therapeutics (Aggarwal et al, 2015, Sameni et al, 2016).…”