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February 19, 2008
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| Photo by Richard Anderson |
Oral cancer is the sixth most common cancer worldwide with a long-term survival rate of 50 percent. A University of Minnesota research team is working on an interdisciplinary project to improve this statistic, using a mix of medical research and computer science.
The research group, which includes CSE professor John Carlis and doctoral student Getiria Onsongo, analyzes saliva and uses it to help identify proteins for the early detection of oral cancer. The goal is to identify the proteins that lead to oral cancer and create a method to diagnose the disease earlier.
The team's work on a new three-step process for improving this technique was published in journal, Molecular & Cellular Proteomics. This new method can detect three-to-four times more proteins than other methods, and they are working to improve this even more.
As part of the project, Carlis and Onsongo use databases and data modeling techniques to analyze the medical data. They work to find effective ways to pull out and visualize desired information from a seemingly insurmountable volume of information.
The research group is led by Timothy Griffin, an assistant professor in the University's department of Biochemistry, Molecular Biology and Biophysics, and includes researchers from medicine, dentistry, computer science and engineering, and the School of Public Health. The National Institutes of Health is funding the four-year study.
Article adapted from a story in Advances, fall 2007, a publication from the University's School of Public Health.
For more information, visit Oral Cancer Project.
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