Conclusions
Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage.
Methods
We retrieved candidate biomarkers identified by proteomic analysis in OSCC from published works of literature. In training stage, immunohistochemistry (IHC) analysis was used to determine the expression of proteins and logistic regression models with stepwise variable selection were used to identify potential factors that might affect lymph node metastasis and life status. Furthermore, the prediction model was validated in validating stage.
Objective
Lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC). However, it is still controversial to define clinically negative neck (cN0) and positive neck (cN1-3).
Results
We screened eight highly expressed proteins related to lymph node metastasis in OSCC and found that the expression levels of SOD2, BST2, CAD, ITGB6, and PRDX4 were significantly elevated in patients with lymph node metastasis compared to the patients without lymph node metastasis. Furthermore, in training and validating stages, the prediction model base on the combination of CAD, SOD2 expression levels, and histopathologic grade was developed and validated in patients with OSCC. Conclusions: Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage.