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1.
Oncol Lett ; 10(5): 2675-2682, 2015 Nov.
Article in English | MEDLINE | ID: mdl-26722226

ABSTRACT

Regulation of the cell cycle is essential for carcinogenesis. The cell cycle is controlled by cyclin-dependent kinases (CDKs), which are upregulated by cyclins and downregulated by CDK inhibitors (CDKIs). Decreased p27Kip1 expression has been associated with survival rate, tumor size, histological differentiation and the presence of lymph node metastasis in patients with various types of cancer. The aim of the current study is to provide a literature review on the association between p27Kip1 expression and the clinical and pathological aspects of head and neck squamous cell carcinoma (HNSCC), and the expression of other CDKIs of the Cip/Kip family and cyclins. Throughout the literature, different methodologies were used to determine the immunohistochemical expression of p27Kip1; thus, results concerning p27Kip1 expression in HNSCC vary widely. However, it has now been confirmed that p27Kip1 is underexpressed in SCC cells. p27 may be a promising marker for determining the prognosis of HNSCC, despite the marked variability of the results obtained. An association between p27 expression and survival rate, time to recurrence and tumor stage has been observed. Based on the information currently available, it is premature to recommend the analysis of p27Kip1 expression in guiding HNSCC treatment planning. However, although relatively unstudied, the correlation between p27Kip1 expression and other tumor suppressor genes may turn out to be important in determining the prognosis of HNSCC. Further prospective studies utilizing standardized laboratory methodologies and statistics that facilitate meta-analyses are required to confirm this proposal.

2.
Cancer Biomark ; 15(1): 19-26, 2015.
Article in English | MEDLINE | ID: mdl-25524938

ABSTRACT

OBJECTIVES: Downregulation of p21{Waf1/CIP1} (a cyclin-dependent kinase inhibitor) has been reported for mouth cancer. The goal of this article is to quantitatively report expression of p21{Waf1/CIP1} and evaluate its relationship with the clinical and prognostic factors. MATERIALS AND METHODS: this is a retrospective study of 68 patients diagnosed with OSCC. We constructed a tissue microarray to develop an immunohistochemical assessment of p21{Waf1/CIP1} expression. A multivariate analysis using a forward-selection stepwise regression model (Cox, 1972) for predicting survival was performed. RESULTS: The quantitative expression of p21{Waf1/CIP1} showed a statistically significant relationship with the risk of lymph node metastasis, showing a higher expression in patients with homolateral single nodes of less than 3 cm (N1) (X{2}=6.58; p< 0.05). We found no statistically significant relationship with any other clinical or pathological parameters. The Cox univariate regression analysis verifies that the effect of the value of p21{Waf1/CIP1} on survival was not statistically significant (p=0.6). The best predictive multivariate Cox analysis included the covariates: recurrence, p21{Waf1/CIP1}, gender, stage, and dysplasia in the adjacent margin. All these variables showed a statistically significant relationship with survival, except p21{Waf1/CIP1}. CONCLUSION: quantitative determination of p21{Waf1/CIP1} standardizes and facilitates its analysis. Although its expression increases in patients with N1 regional metastasis, the loss of p21{WAF1/CIP1} does not seem to have any relationship with the clinical and pathological variables of the tumors.


Subject(s)
Carcinoma, Squamous Cell/metabolism , Cyclin-Dependent Kinase Inhibitor p21/biosynthesis , Head and Neck Neoplasms/metabolism , Mouth Neoplasms/metabolism , Adult , Aged , Aged, 80 and over , Carcinoma, Squamous Cell/diagnosis , Carcinoma, Squamous Cell/pathology , Cohort Studies , Female , Head and Neck Neoplasms/diagnosis , Head and Neck Neoplasms/pathology , Humans , Male , Middle Aged , Mouth Neoplasms/diagnosis , Mouth Neoplasms/pathology , Neoplasm Metastasis , Prognosis , Retrospective Studies , Squamous Cell Carcinoma of Head and Neck , Survival Analysis
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