Tech Digest

Research team aims to detect oral cancer earlier

A TEAM OF RESEARCHERS at the University of Minnesota is combining medical research and computer science to fight oral cancer, one of the more deadly cancers, and the sixth most common cancer worldwide. The team’s work was recently published in the journal, Molecular & Cellular Proteomics.

Computer scientists analyze cell data to aid in the early detection of diseases, and to assist in other kinds of biological research.

The research group, which includes computer science and engineering professor John Carlis and doctoral student Getiria Onsongo, is analyzing saliva and using 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 to create a method to diagnose the disease earlier.

Carlis and Onsongo are using databases and 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.

Baolin Wu, an assistant professor in the University’s School of Public Health, is responsible for the study design. Using complex statistical models, Wu will determine how many proteins—of the thousands found in human saliva—to pinpoint for study. He also analyzes data on how the proteins interact with each other to potentially lead to cancerous cells.

Studies have shown when oral cancer is diagnosed in early stages, the survival rate jumps to 80 percent. “Survival depends on early diagnoses,” Wu said. “Our study takes a novel approach to improving survival rates that haven’t changed for 30 years.”

The National Institutes of Health is funding the four-year study.