Nuclear expression of metastasis-associated protein 1 (MTA1) is inversely related to progression of oral squamous cell carcinoma in Taiwan

Overexpression of metastasis-associated protein 1 (MTA1) has been demonstrated in a variety of human cancers and found to be significantly associated with the tumor size, lymph node metastasis, clinical stage, tumor invasion, and prognosis of these cancers. In this study, we examined the expression of MTA1 in 74 specimens of oral squamous cell carcinoma (OSCC), 100 specimens of oral epithelial dysplasia (OED; 33 mild, 44 moderate, and 23 severe OED cases), and 21 specimens of normal oral mucosa (NOM) by immunohistochemistry. The cytoplasmic and nuclear MTA1 labeling indices (LIs) in OSCC, OED, and NOM samples were calculated and compared among these groups. Correlations of the cytoplasmic and nuclear MTA1 LIs in OSCC with clinicopathological parameters and survival of OSCC patients were statistically analyzed. We found that the mean cytoplasmic MTA1 LIs were all over 95% for the NOM, OED, and OSCC samples. There were no significant associations of the cytoplasmic MTA1 LI with any of the clinicopathological parameters of OSCC patients. The mean nuclear MTA1 LIs significantly decreased from NOM (73% +/- 13%) to mild OED (71% +/- 16%), moderate OED (60% +/- 22%), and severe OED (46% +/- 25%) and OSCC samples (30% +/- 30%, p < 0.001). A significant correlation was found between the lower mean nuclear MTA1 LIs and OSCCs located on the buccal mucosa and tongue (p = 0.001), with larger tumor sizes (T3 and T4, p = 0.020), with regional lymph node metastases (N1, N2, and N3, p = 0.024), and with more-advanced clinical stages (stages 3 and 4, p = 0.045). Our results suggest that MTA1 is universally expressed in the cytoplasm of normal, dysplastic, and malignant oral epithelial cells. The nuclear expression of MTA1 significantly dropped from NOM through OED to OSCC samples, and was inversely related to the T status, N status, and clinical staging of OSCCs. Therefore, the nuclear MTA1 LI can be used to predict the progression of OSCCs in Taiwan.