This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Oral cancer is one of the ten most common cancers in the world. More than 30,000 cases are diagnosed each year in the United States, and South Carolina has the second highest mortality rate in the nation. Comprehensive study of the cancer pathogenesis can greatly help us to understand how oral cancer is developed and to develop novel therapeutics for oral cancer treatment. Recent studies have shown that sphingolipids may play an important role in oral cancer pathogenesis. However, testing this hypothesis requires comprehensive analysis of sphingolipidomics, genomic information and the clinical parameters of oral cancer, and new methodologies are required to integrate such complex data at the system level.We propose that object-oriented (OO) technology can be used to integrate biological information about the roles of the sphingolipid metabolic pathway in oral cancer pathogenesis. OO technology is considered the current standard for software construction, and is an excellent choice to model complex information. Our recent work has demonstrated that applying a well-defined software engineering methodology to OO technology can effectively integrate and represent biological information. We will construct a comprehensive OO model for the role of sphingolipids in oral cancer pathogenesis. Such a coherent computational model will integrate cellular components, molecular functions, biological processes, gene products, sphingolipidomic information, and clinical parameters, transforming traditional text-based descriptive biological system information into an easily updatable model. We propose to: 1) Build an OO model for studying the role of sphingolipids in oral cancer pathogenesis. 2) Expand the sphingolipid pathway model to incorporate genomic information. 3) Develop methods to analyze the constructed model and infer new knowledge about oral cancer pathogenesis.By integrating information ranging from clinical parameters to molecular mechanisms about sphingolipidomics, we will construct a comprehensive OO model about sphingolipids and their roles in oral can pathogenesis. Such integration allows us to dissect complex relationships between clinical observation, sphingolipidomics, gene expression and genome information, to gain new insight into the mechanism of oral cancer pathogenesis, and to develop new diagnostics and therapeutic measures for oral cancer.
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