Canada Excellence Research Chair in Integrative Biology at the University of Toronto
Using lab experiments, the scientists identified interactions and then, using computer modelling, they zoomed in on proteins that ‘connect’ to one or more other cancer proteins.
“We show, really for the first time, that cancer proteins are more likely to interconnect with one another than they are to connect to randomly chosen non-cancer proteins,” says Roth, who is also a Canadian Institute for Advanced Research (CIFAR) senior fellow.
“Once you see that proteins associated to the same disease are more likely to connect to each other, you can use this network of interactions as a prediction tool to find new cancer proteins, and the genes they encode,” says Roth. For example, two known cancer genes encoded two proteins that interacted with CTBP2, a protein encoded at a location tied to prostate cancer, which can spread to nearby lymph nodes. These two proteins are implicated in lymphoid tumours, suggesting that CTBP2 plays a role in the development of lymphoid tumours.
Using their predictive method, the researchers found that 60 of their predicted cancer genes fit into a known cancer pathway. Discoveries like these are crucial for understanding how cancer and other diseases develop and ultimately, how to treat and prevent them.
Roth likens a doctor asked to treat a patient’s disease to a car mechanic. “How can we ask someone to fix a car with an incomplete list of parts and no guidance on how the parts fit together?” he says. “One major conclusion of the paper is that when you look systematically for interactions, you find them everywhere.”