Oral cancer, predominantly oral squamous cell carcinoma (OSCC), affects over 300,000 people worldwide annually. Local differences in gene/protein expression within distinct oral cavity subsites may critically affect disease diagnosis, prognosis and outcomes. The proteome reflects cellular functional status more directly than profiling DNA or RNA aberrations alone, as proteins dictate cellular phenotype, function, and regulatory processes. The objective of this study is the global proteomic analysis of tumors from diverse oral cavity subsites (tongue, floor of mouth, alveolus, hard palate, lip and buccal mucosa) in order to delineate differentially expressed proteins between anatomic sites. These proteomic findings will be correlated with our boinformatics-based analysis of TCGA RNA expression data associated with the same subsites. Differential protein expression data will be correleated with patient outcomes and mined to identify clinically relevant proteins for use as potential disease biomarkers, new drug targets or to design unique subsite-specific treatment approaches. Total proteins were extracted from patient tumor samples excised from each oral cavity site (5 independent patients/site) for mass spectroscopy-based quantitative protein identification. Bioinformatic analysis will identify differentially expressed proteins across subsites and provide insight into protein networks and pathways that may influence pathophysiology, treatment response, and patient outcomes. The long-term goal of patient tumor genomic and proteomic profiling will be to identify a set of specific biomarkers and ultimately provide tumor site-specific therapeutic approaches for oral cavity cancer.