Membrane-type Matrix Metalloproteinase-1 (MT1-MMP) Is a Processing Enzyme for Human Laminin γ2 Chain*

By N. Koshikawa, Tomoko Minegishi, A. Sharabi, V. Quaranta, M. Seiki. Journal of Biological Chemistry, 2005

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Processing of the laminin-5 (Ln-5) γ2 chain by membrane-type-1 matrix metalloproteinases (MT1-MMP) promotes migration and invasion of epithelial and tumor cells. We previously demonstrated that MT1-MMP cleaves the rat γ2 chain at two sites, producing two major C-terminal fragments of 100 (γ2′) and 80 (γ2x) kDa and releasing a 30-kDa fragment containing epidermal growth factor (EGF)-like motifs (domain III (DIII) fragment). The DIII fragment bound the EGF receptor (EGF-R) and stimulated cell scattering and migration. However, it is not yet clear whether human Ln-5 is processed in a similar fashion to rat Ln-5 because one of the two MT1-MMP cleavage sites present in rat γ2 is not found in human γ2. To identify the exact cleavage site for MT1-MMP in human Ln-5, we purified both the whole molecule as well as a monomeric form of human γ2 that is frequently expressed by malignant tumor cells. Like rat Ln-5, both the monomer of γ2, as well as the γ2 derived from intact Ln-5, were cleaved by MT1-MMP in vitro, generating C-terminal γ2′ (100 kDa) and γ2x (85 kDa) fragments and releasing DIII fragments (25 and 27k Da). In addition to the conserved first cleavage site used to generate γ2′, two adjacent cleavage sites (Gly559–Asp560 and Gly579–Ser580) were found that could generate the γ2x and DIII fragments. Two of the three EGF-like motifs present in the rat DIII fragment are present in the 27-kDa human fragment, and like the rat DIII, this fragment can promote breast carcinoma cell migration by engaging the EGF-R. These results suggest that MT1-MMP processing of Ln-5 in human tumors may stimulate the EGF-R, resulting in increased tumor cell scattering and migration that could possibly increase their metastatic potential.

Subfields: Cancer Research, Immunology and Allergy, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/20b7d6a139a01c3768991faf2f0260d2cb9219f9

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