Scientists use math to kill cancer cells

Researchers are using advanced mathematical models to engineer viruses that can infect and destroy cancer cells without affecting healthy tissue.
The technique predicts how different treatments and genetic modifications might allow cancer-killing, oncolytic viruses to overcome the natural defences that cancer cells use to stave off viral infection.
"Oncolytic viruses are special in that they specifically target cancer cells," said Dr Bell, a senior scientist at the Ottawa Hospital Research Institute and professor at the University of Ottawa's Faculty of Medicine.
"Unfortunately, cancer is a very complicated and diverse disease, and some viruses work well in some circumstances and not well in others. As a result, there has been a lot of effort in trying to modify the viruses to make them safe, so they don't target healthy tissue and yet are more efficient in eliminating cancer cells," said Bell.

Bell and co-author Mads Kaern, an assistant professor in the University of Ottawa's Faculty of Medicine led a team that used mathematical modelling to devise strategies for making cancer cells exquisitely sensitive to virus infection - killing them without affecting normal, healthy cells.
"By using these mathematical models to predict how viral modifications would actually impact cancer cells and normal cells, we are able to accelerate the pace of research," said Kaern.

Bell and Kaern have established a mathematical model that described an infection cycle, including the way a virus replicated, spread and activated cellular defence mechanisms.
They used knowledge about key physiological differences between normal cells and cancer cells to identify how modifying the genome of the virus might counter the anti-viral defences of cancer cells.

Model simulations were remarkably accurate, with the identified viral modifications efficiently eradicating cancer in a mouse model of the disease.
"What is remarkable is how well we could actually predict the experimental outcome based on computational analysis. This work creates a useful framework for developing similar types of mathematical models in the fight against cancer," said Bell.
The study was published in the journal Nature Communications.