Personalizing cancer treatment with 'big data'

David Skillicorn (School of Computing) has been awarded a Big Data, Big Impact Grant from the Cancer Institute of New South Wales and the Children's Hospital at Westmead in Australia to help personalize cancer treatment for children.

The grant, in its second year, will support Dr. Skillicorn and 10 other researchers for work on their project entitled Generating Actionable Knowledge from Complex Genomic Data for Personalized Clinical Decisions. The project will involve a large scale analysis of detailed data about childhood cancer patients suffering mainly from leukemia.

The project will challenge the previously defined categories that are currently used to determine cancer treatment for the patient.

"After a cancer diagnosis and some tests, patients would typically be categorized based on the risk and variance of their disease," says Dr. Skillicorn. "The category would then determine the treatment program. There were always a few patients who didn't seem to fit their category; they would do well against the odds, or poorly when they shouldn't have."

Current technology, called "high-throughput devices," collects tens of thousands of marker values for each patient. Patients are then clustered and their eventual treatment is based on their cluster. Dr. Skillicorn's research could result in a redefinition of these clusters.

"Patients don't form clusters," says Dr. Skillicorn. "The disease almost always looks different from one patient to another. We believe there must be some bottleneck that causes the wide variety of patient configurations to appear as a much smaller set of disease categories."

Provided by Queen's University