How to Predict Cancer: Tom Yankeelov talks to Dell Medical School about 'mathematizing' cancer for patient-specific treatment
ICES Professor Thomas Yankeelov, was already an aspiring cancer killer when, on a Florida beach five years ago, he read “The Origins of Computer Weather Prediction and Climate Modeling.”
The paper, by Peter Lynch, a professor of meteorology at University College Dublin, recounts the human failure during the last hundred or so years to predict the weather. Yankeelov, then a cancer researcher at Vanderbilt University, noticed that people’s historically weak understanding of the weather bore surprising similarity to their struggle to grasp the so-called Emperor of All Maladies.
For anyone who’s had cancer, lost someone to the disease or watched it ravage a friend or loved one — including Yankeelov, whose father died of pancreatic cancer when he was five — there’s both terror and hope in the metaphor. On one hand, humans aren’t any better at controlling the weather than we’ve ever been. When a hurricane is coming, a hurricane is coming, and there’s nothing anyone can do about it.
But when people can predict, even roughly, what’s about to happen — when you can say with 95 percent certainty, days in advance, where a hurricane is headed and who needs to get out of the way — it can save a lot of lives.
“What people call ‘cancer’ is really a group of more than 100 different diseases, and obviously every person is unique,” says Yankeelov, who received a $6 million recruitment grant from the Cancer Prevention and Research Institute of Texas and holds a joint faculty appointment at the University of Texas’ Dell Medical School and the Cockrell School of Engineering’s Department of Biomedical Engineering. “It becomes much easier to fight when we understand the mechanisms driving it — how a particular type of cancer is likely to grow in a particular person. We can only do that with patient-specific information.”
Posted: Oct. 13, 2016