4.2 Article

Prognostic value of matrix metalloproteinases in oral squamous cell carcinoma

Journal

BIOTECHNOLOGY & BIOTECHNOLOGICAL EQUIPMENT
Volume 28, Issue 6, Pages 1138-1149

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/13102818.2014.967510

Keywords

oropharyngeal squamous cell carcinoma; matrix metalloproteinase; tumour progression

Funding

  1. University of Bern, Institute of Anatomy, Bern, Switzerland

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The aim of this study was to investigate whether there is a correlation between the expressions of four matrix metalloproteinases (MMPs): MMP-2, MMP-7, MMP-9 and MMP-13, and the TNM (tumour-node-metastasis) stages of oral squamous cell carcinoma (OSCC); and to explore the implication of these MMPs in OSCC dissemination. Samples from 61 patients diagnosed with oropharyngeal tumour were studied by immunohistochemistry against MMP-2, MMP-7, MMP-9 and MMP-13. The assessment of immunoreactivity was semi-quantitative. The results showed that MMP-2 and MMP-9 had similar expression patterns in the tumour cells with no changes in the immunoreactivity during tumour progression. MMP-9 always had the highest expression, whereas that of MMP-2 was moderate. MMP-7 showed a significant decrease in expression levels during tumour evolution. MMP-13 had constant expression levels within stage T2 and T3, but showed a remarkable decline in immunoreactivity in stage T4. No significant differences in the MMPs immunoreactivity between tumour cells and stroma were observed. Although strong evidence for the application of MMPs as reliable predictive markers for node metastasis was not acquired, we believe that combining patients' MMPs expression intensity and clinical features may improve the diagnosis and prognosis. Strong evidence for the application of MMPs as reliable predictive markers for node metastasis was not acquired. Application of MMPs as prognostic indicators for the malignancy potential of OSCC might be considered in every case of tumour examination. We believe that combining patients' MMPs expression intensity and clinical features may improve the process of making diagnosis and prognosis.

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