Clinical relevance of breast cancer-related genes as potential biomarkers for oral squamous cell carcinoma

Abstract

Background: Squamous cell carcinoma of the oral cavity (OSCC) is a common cancer form with relatively low 5-year survival rates, due partially to late detection and lack of complementary molecular markers as targets for treatment. Molecular profiling of head and neck cancer has revealed biological similarities with basal-like breast and lung carcinoma. Recently, we showed that 16 genes were consistently altered in invasive breast tumors displaying varying degrees of aggressiveness.

Methods: To extend our findings from breast cancer to another cancer type with similar characteristics, we performed an integrative analysis of transcriptomic and proteomic data to evaluate the prognostic significance of the 16 putative breast cancer-related biomarkers in OSCC using independent microarray datasets and immunohistochemistry. Predictive models for disease-specific (DSS) and/or overall survival (OS) were calculated for each marker using Cox proportional hazards models.

Results: We found that CBX2, SCUBE2, and STK32B protein expression were associated with important clinicopathological features for OSCC (peritumoral inflammatory infiltration, metastatic spread to the cervical lymph nodes, and tumor size). Consequently, SCUBE2 and STK32B are involved in the hedgehog signaling pathway which plays a pivotal role in metastasis and angiogenesis in cancer. In addition, CNTNAP2 and S100A8 protein expression were correlated with DSS and OS, respectively.

Conclusions: Taken together, these candidates and the hedgehog signaling pathway may be putative targets for drug development and clinical management of OSCC patients.

Figure 1

Prognostic potential of CNTNAP2 and S100A8 protein expression in OSCC. (A-B) Kaplan-Meier estimates of the probability of disease-specific survival and overall survival according to dichotomized protein expression for CNTNAP2 and S100A8, respectively. Patients with CNTNAP2-positive and S100A8-negative tumors had significantly shorter survival times. P-values, hazard ratios (HR), and 95% confidence intervals (95% CI) were calculated using the log-rank test and Cox proportional hazards regression, respectively. The x-axes depict Months after initial diagnosis and the y-axes depict Disease-specific survival or Overall survival. (C) Representative immunohistochemical staining showing protein expression patterns in the invasive tissue component.

Figure 2

Predictive performance of prognostic models including CNTNAP2 or S100A8. (A) The lines represent the time-dependent area under the ROC curve (AUC (t)) for disease-specific survival using established clinical variables (lymph node status and tumor size) assessed individually and in conjunction with CNTNAP2 protein expression. The estimated performance of the model including CNTNAP2 was marginally better than the model containing the established clinical variables alone, increasing the C-index from 0.941 to 0.949. (B) The lines represent the time-dependent area under the ROC curve (AUC (t)) for overall survival using established clinical variables (lymph node status, tumor size, differentiation, age) assessed individually and in conjunction with S100A8 protein expression. Combining the established clinical variables with S100A8 protein expression increased the C-index significantly from 0.605 to 0.833. The x-axes depict Survival time in months and the y-axes depict AUC (t).