Non-destructive and selective imaging of the functionally active, pro-invasive membrane type-1 matrix metalloproteinase (MT1-MMP) enzyme in cancer cells

对癌细胞中功能活性、促侵袭性膜型 1 基质金属蛋白酶 (MT1-MMP) 酶进行无损和选择性成像

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作者:Albert G Remacle, Sergey A Shiryaev, Vladislav S Golubkov, John N Freskos, Michael A Brown, Amolkumar S Karwa, Arati D Naik, Carol P Howard, Carolyn J Sympson, Alex Y Strongin

Abstract

Proteolytic activity of cell surface-associated MT1-matrix metalloproteinase (MMP) (MMP-14) is directly related to cell migration, invasion, and metastasis. MT1-MMP is regulated as a proteinase by activation and conversion of the latent proenzyme into the active enzyme, and also via inhibition by tissue inhibitors of MMPs (TIMPs) and self-proteolysis. MT1-MMP is also regulated as a membrane protein through its internalization and recycling. Routine immunohistochemistry, flow cytometry, reverse transcription-PCR, and immunoblotting methodologies do not allow quantitative imaging and assessment of the cell-surface levels of the active, TIMP-free MT1-MMP enzyme. Here, we developed a fluorescent reporter prototype that targets the cellular active MT1-MMP enzyme alone. The reporter (MP-3653) represents a liposome tagged with a fluorochrome and functionalized with a PEG chain spacer linked to an inhibitory hydroxamate warhead. Our studies using the MP-3653 reporter and its inactive derivative demonstrated that MP-3653 can be efficiently used not only to visualize the trafficking of MT1-MMP through the cell compartment, but also to quantify the femtomolar range amounts of the cell surface-associated active MT1-MMP enzyme in multiple cancer cell types, including breast carcinoma, fibrosarcoma, and melanoma. Thus, the levels of the naturally expressed, fully functional, active cellular MT1-MMP enzyme are roughly equal to 1 × 10(5) molecules/cell, whereas these levels are in a 1 × 10(6) range in the cells with the enforced MT1-MMP expression. We suggest that the reporter we developed will contribute to the laboratory studies of MT1-MMP and then, ultimately, to the design of novel, more efficient prognostic approaches and personalized cancer therapies.

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