Not Just a Fine Notion
Despite countless setbacks, researchers continue to struggle to reverse cancer’s devastating mortality rates. One promising approach involves the design of treatment plans that match each cancer patient’s genetic profile.
For Canada Research Chair Igor Jurisica, the notion of custom-fitting cancer treatment lies behind much of his research. Working at the nexus of computer science and biology, he develops and uses algorithms that will help make individualized treatments a reality by making sense of the deluge of information being gleaned from cancer-related experiments.
The abundance of data comes, in part, from investigating the involvement of the relevant genes and their protein products in the biological processes related to cancer. In order to analyze the multitude of parameters and their combinations, scientists devise complex experiments in which many steps can be carried out by computers and the myriad computational algorithms (sequences of machine instructions) used to process the information.
This is where Jurisica’s work in integrative computational biology comes in. By applying his computational algorithms to the results of these experiments, Jurisica is learning about cancer at the molecular level and integrating it with disease progression and outcome. The result? Invaluable insights into how tumours are generated, how treatments can be matched to a patient's genetic profile, and how scientists can read molecular signatures so as to detect cancer at a much earlier state, even before symptoms appear.
Jurisica's work is critically important, aimed at enabling health professionals to target a single patient with individualized treatment, an approach that is guaranteed to have greater success than treating all patients the same.