Medical researchers at the University of Alberta reviewed test results from thousands of patients with various types of cancer and discovered that "disorganized" cancers were more difficult to treat and consistently resulted in lower survival rates.
Principal investigator Jack Tuszynski says physicians could use a mathematical equation, or algorithm, to determine how disorganized their patients' cancer is. Once physicians determine that, then they could pinpoint which cancer treatment would be the most effective. Some cancer drugs are effective at treating simple cancers, while others are designed to attack complex cancers.
The current emphasis in cancer treatment is to inhibit "traffic systems" in cancer, says the researcher.
"Using a math equation, doctors could predict if a given therapy will be successful, which would spare the patient from suffering," says Tuszynski, who holds the Alberta Cancer Foundation-funded Allard Research Chair in Oncology with the Faculty of Medicine & Dentistry at the University of Alberta. "Instead of spending millions of dollars on clinical trials to find better cancer drugs, algorithms could be used to better pinpoint treatment instead."
The research conducted by Tuszynski, a summer student, and research colleagues in Boston, was recently published in the peer-reviewed journal Proceedings of the National Academy of Sciences (PNAS). The group looked at 14 types of cancer, including those with high survivability, like prostate cancer, and those with high death rates, such as pancreatic cancer. Each type of cancer has its own unique "metro map," says Tuszynski.
"These traffic signalling systems inside cancer cells look like transportation hubs or metro maps, so you can measure how many stations and how many lines you have," says Tuszynski, who has a joint appointment in the Department of Oncology, as well as the Department of Physics in the Faculty of Science.
|Contact: Raquel Maurier|
University of Alberta Faculty of Medicine & Dentistry