Abstract 5068: Proteomics based prognostic signature of head and neck cancer

Abstract

Abstract Introduction. Molecular cancer diagnostics is rapidly moving beyond genomics to proteomics. Clinical cancer proteomics has the potential to discover, identify, and quantify novel biomarkers for early detection, diagnosis, prediction of the clinical outcome, and to develop effective therapeutic interventions by using these biomarkers as molecular targets. Despite therapeutic interventions, the five-year survival rate of head and neck cancer patients is less than 50%, and the prognosis of advanced HNSCC cases has not improved much over the past three decades. Methods. Using high-throughput proteomics, we identified a panel of biomarkers in head and neck cancer. This panel of markers was verified in a large independent cohort of paraffin embedded head and neck cancer tissues (n=100) using immunohistochemistry (IHC). Kaplan Meier analysis and multivariate logistic regression analysis was carried out to predict the prognosis of these head and neck cancer patients. Positive and negative predictive values (PPV and NPV respectively) were calculated as function of follow-up period. Results. Our immunohistochemical analysis demonstrated overexpression of a panel of proteins including 14-3-3zeta, 14-3-3sigma, heterogeneous nuclear ribonuclear protein K (HNRNPK), S100A7 and prothymosin alpha (PTMA) in head and neck cancer patients. Kaplan Meier analysis revealed shorter disease-free survival (DFS = 4 mths.) in head and neck cancer patients showing overexpression of the panel of proteins in comparison to patient cohort not showing overexpression of this panel (DFS = 41 mths., p < 0.001). Positive predictive value (PPV) and Negative predictive value (NPV) further verified the reduced disease free survival of these patients. Logistic regression analysis clearly demonstrated the relevance of this panel as the best prognostic signature for head and neck cancer patients (p < 0.001, Hazards ratio, H.R.=19.6, 95% C.I. = 2.3 – 8.5) in comparison to combinations of 2 – 4 markers and clincopathological parameters. Conclusions. In conclusion we identified, verified and developed a proteomics-based prognostic signature for head and neck cancer patients which may find its utility in follow-up clinics to accurately predict the recurrence of the disease after primary treatment. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5068. doi:10.1158/1538-7445.AM2011-5068