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Prognostic evaluation of oral squamous cell carcinoma based on pleiotrophin, urokinase plasminogen activator, and glycoprotein nonmetastatic melanoma protein B expression

This study investigated the expression of pleiotrophin (PTN), urokinase plasminogen activator (uPA), and glycoprotein nonmetastatic melanoma protein B (GPNMB) in oral squamous cell carcinoma (OSCC) tissues and their correlation with prognosis. From February 2017 to January 2020, PTN, uPA, and GPNMB...

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Detalles Bibliográficos
Autores principales: Ma, Yuxin, Liu, Yue, Meng, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637552/
https://www.ncbi.nlm.nih.gov/pubmed/37960806
http://dx.doi.org/10.1097/MD.0000000000035634
Descripción
Sumario:This study investigated the expression of pleiotrophin (PTN), urokinase plasminogen activator (uPA), and glycoprotein nonmetastatic melanoma protein B (GPNMB) in oral squamous cell carcinoma (OSCC) tissues and their correlation with prognosis. From February 2017 to January 2020, PTN, uPA, and GPNMB expression in cancer tissues and adjacent tissues of 93 patients with OSCC was determined using immunohistochemistry. The diagnostic value of the combined detection of OSCC and its relationship with clinicopathological characteristics were analyzed, as well as the prognostic potential of PTN, uPA, and GPNMB. Cancer tissues from patients with OSCC exhibited high expression of PTN, uPA, and GPNMB. The AUC for the combined detection of PTN, uPA, and GPNMB for diagnosis and prognosis was greater than that of each index alone. The rates of expression of PTN, uPA, and GPNMB were higher in the death group than in the survival group. Patients with PTN, uPA, and GPNMB expression had lower 3-year survival rates. PTN expression was a risk factor affecting the prognosis of patients with OSCC. The rate of PTN, uPA, and GPNMB expression in OSCC tissues was high, and their expression was related to clinicopathological features such as lymph node metastasis and tumor invasion depth. The combined detection of each index has a predictive value for the prognosis of patients.