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MMP-7蛋白在肺癌患者和正常人外周血中的表达水平及临床意义

BACKGROUND AND OBJECTIVE: Matrix metalloproteinase 7 (MMP-7), also known as matrilysin, is a member of the MMP family. The objectives of this study were to test MMP-7 protein levels in the peripheral blood of lung cancer patients and healthy control subjects and to determine their corresponding clin...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 中国肺癌杂志编辑部 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6000045/
https://www.ncbi.nlm.nih.gov/pubmed/23249718
http://dx.doi.org/10.3779/j.issn.1009-3419.2012.12.06
Descripción
Sumario:BACKGROUND AND OBJECTIVE: Matrix metalloproteinase 7 (MMP-7), also known as matrilysin, is a member of the MMP family. The objectives of this study were to test MMP-7 protein levels in the peripheral blood of lung cancer patients and healthy control subjects and to determine their corresponding clinical significance. METHODS: Peripheral blood samples were obtained from 114 lung cancer patients and 100 healthy control subjects. MMP-7 protein levels in the plasma were measured by enzyme-linked immunosorbent assay. RESULTS: The plasma protein levels of MMP-7 in lung cancer patients (median=0.72 ng/mL) were significantly higher than those in healthy control subjects (median=0.30 ng/mL)(P < 0.001). When the cutoff of MMP-7 protein level was set at 0.56 ng/mL, the sensitivity and specificity of detecting lung cancer were 62.3% and 76.0%, respectively. However, the lung cancer patients and healthy control subjects did not statistically differ in age, sex, smoking status, tumor size, pathological classification, as well as lymphatic metastasis and stage (P > 0.05). CONCLUSION: The plasma protein levels of MMP-7 increase in the peripheral blood of lung cancer patients. Peripheral blood MMP-7 can be used as a tumor marker for detecting lung cancer. The fact that no significant correlation between the protein levels of MMP-7 and lung cancer clinical parameters was observed in this study warrants further analysis in larger samples.