MMC/VICC Partnership : Research
Identification of Serum Biomarkers in HNSCC
CO-LEADERS
- Meharry Co-leaders
Sabina P. Francis, M.D. – Assistant Professor of Surgery
Dana Marshall, M.D. – Associate Professor of Surgery
DMarshall@MMC.edu - Vanderbilt Co-leader
Wendell G. Yarbrough, M.D., FACS – Associate Professor of Otolaryngology and Cancer Biology
Wendell.Yarbrough@Vanderbilt.edu
Head and neck squamous cell carcinoma (HNSCC) remains a significant source of morbidity in the United States and worldwide. Each year, roughly 50,000 Americans are diagnosed with HNSCC making it the 5th most common tumor type in the United States. Unfortunately, the majority of patients present with advanced disease, which limits treatment options, increases treatment morbidity and adversely affects the chances of long-term survival. Additionally, treated patients must be followed closely to detect recurrences, since roughly 50% of patients with advanced disease will recur and frequently, salvage surgery is the only curative modality remaining. Despite the critical need, there are currently no clinically useful biomarkers for early detection of HNSCC. We propose to use state-of-the art analytic mass spectrometry to identify serum biomarkers for HNSCC. Mass spectrometry profiling techniques (MALDI and SELDI) have recently been used for serum analyses in HNSCC and other tumors; however, these techniques have been criticized because they are inherently biased to lower molecular weight molecules with relatively high abundance and identification of proteins or peptides that correspond to the predictive features is difficult. The approach we propose directly addresses many of these concerns. The proposed studies will use multidimensional liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to directly identify proteins and peptides present in serum from patients with and without HNSCC. Our preliminary data suggests that LC-MS/MS analyses can identify proteins of all molecular masses as well as low abundance serum proteins. The frequency of peptide identification is a semiquantitative measure of protein abundance. Here, we propose to compare identified serum proteins between patient groups to reveal proteins that distinguish patients with and without HNSCC. Once predictive proteins are identified, future studies with absolute quantitation using mass spectrometry (AQUA) of these markers on individual samples will be performed to determine variation in serum concentrations and predictive power.
