Four-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma

Abstract

Abstract The presence of lymph node metastasis significantly affects the survival of oral squamous cell carcinoma patients and successful detection and removal of positive lymph nodes is crucial in the treatment of this disease. Current evaluation methods still have their limitations in detecting the presence of tumor cells in the lymph nodes, where up to a third of clinically diagnosed metastasis-negative (N0) patients actually have metastasis—positive LNs in the neck. We aimed to develop a molecular signature in the primary tumor that could predict lymph node (LN) metastasis in oral squamous cell carcinoma. The expression levels of 11 proteins was evaluated using immunohistochemical analysis in a tissue microarray (TMA) consisting of 110 specimens from 32 individuals. We used receiver operating characteristic (ROC) curve to identify proteins that could significantly differentiate patients with LN metastasis from those that did not. Unsupervised hierarchical clustering analysis was used to verify the ability of chosen biomarkers in segregating LN positive patients from those with no LN involvement. Kaplan-Meier survival curve and log rank test was utilized to determine the association between LN metastasis and biomarker expression with disease-specific survival. Of the 11 biomarkers, EGFR, HER-2/neu, LAMC2 and RHOC were found to be significantly associated with LN metastasis. Unsupervised hierarchical clustering demonstrated that expression patterns of these 4 proteins could be used to differentiate the positive LN metastasis specimens from specimens that are negative. Collectively, EGFR, HER-2/neu, LAMC2 and RHOC have a specificity of 87.5% and sensitivity of 70% with a prognostic accuracy of 83.4% for LN metastasis. We also demonstrated the LN signature could independently predict disease-specific survival (p = 0.023). In summary, we developed a 4-protein LN signature that could reliably distinguish patients with lymph node metastasis from those who were metastasis free. In addition, this LN signature is also associated with disease-specific survival indicating that would be a useful prognostic tool for the management of oral cancer patients.