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Overexpression of matrix-metalloproteinase-9 in human breast cancer: a potential favourable indicator in node-negative patients

A Scorilas, A Karameris, N Arnogiannaki and 4 more

British Journal of Cancer · 2001

doi:10.1054/bjoc.2001.1810

Abstract

Matrix metalloprotease-9 (MMP-9; 92 kDa type IV collaganase, gelatinase B) is regarded as, important for degradation of the basement membrane and extracellular matrix during cancer invasion and other tissue-remodelling events. In this study we evaluate the prognostic value of MMP-9, by immunoperoxidase staining in a series of 210 breast cancer tissues. The results were quantitated using the HSCORE system, which consider both staining intensity and the percentage of cells stained at given intensities. MMP-9 status was compared with the concentration of cytosolic Cathepsin-D and with other established prognostic factors, in terms of disease free survival and overall survival. The median follow-up period was 62 months. MMP-9 staining was observed primarily in cancer cells, and to a lesser degree in surrounding stromal cells. MMP-9 expression was not detected in normal breast tissue. Levels of MMP-9 expression below the cut-off point were more frequently observed in larger (P = 0.014), invasive ductal histologic (P = 0.037), progesterone receptor (PR)-negative and PR-strong positive tumours (P< 0.001), as well as samples belonging to patients with stage III-IV disease (P = 0.009) and age 45-55 years (P = 0.011). In univariate analysis, node-negative breast cancer patients with tumors positive for MMP-9 had a considerable reduction in risk for relapse (RR = 0.45;P = 0.039) or death (RR = 0.32;P = 0.009). Multivariate analysis indicated that MMP-9 status was an independent favourable predictor of OS (RR = 0.47;P = 0.034) in node-negative but not in node-positive patients. Our results suggest that MMP-9 may be an independent favourable prognostic factor in node-negative breast cancer patients. The overexpression of MMP-9 in breast cancer may be also used as a marker to subdivide node negative breast cancer patients in order to determine the optimal treatment modality.

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