Discovery of potential serum protein biomarkers for lymph node metastasis in oral cancer.

BACKGROUND: The purpose of our study was to identify serum protein biomarkers for node-positive oral squamous cell carcinoma (OSCC). Biomarkers indicating lymph node metastasis provides a valuable classification methodology to optimize treatment plans for patients with OSCC. METHODS: Quantitative serum proteomic analysis of OSCCs with either node-positive or node-negative disease was performed with tandem mass spectrometry and isobaric tagging for relative and absolute quantitation (iTRAQ). Immunoassays were used to validate a panel of candidate protein biomarkers and receiver operating characteristic (ROC) analysis was used to evaluate the performance of the candidate biomarkers. RESULTS: A total of 282 serum proteins were quantified between node-positive and node-negative OSCCs with the proteomic approach. Four candidate biomarkers, gelsolin, fibronectin, angiotensinogen, and haptoglobin, were validated in an independent group of patients with node-positive or node-negative OSCC. The best candidate biomarker, gelsolin, yielded a ROC value of 89% for node-positive OSCC, although the sample size for validation is relatively small. Fibronectin, gelsolin, and angiotensinogen were also found to be differentially expressed between cancer cell lines of node-positive and node-negative cancer origin. CONCLUSION: Our studies suggest that testing of serum protein biomarkers might help detect lymph node metastasis of oral cancer. Because of limited sample size in our studies, long-term longitudinal studies with large populations of individuals with oral cancer are needed to validate these potential biomarkers.

Bioinformatics advances in saliva diagnostics.

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval,integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva diagnostics made possible by the Saliva Ontology and SDxMart.

Saliva Ontology: an ontology-based framework for a Salivaomics Knowledge Base.

BACKGROUND: The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). RESULTS: We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. CONCLUSIONS: The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB.