CIFAR researchers used their analysis of yeast genes to identify two potential targets in humans for a new form of cancer therapy.
A representation of a genetic network. Source: University of Minnesota.
Genetic Networks Fellow Chad Myers and Senior Fellow Charles Boone identified the potential targets by looking first for mutations in yeast genes. Despite the distant relationship, yeast and humans share about 40 percent of their genes.
The team was looking for something called synthetic lethal interactions. Those occur when there are two individual mutations, neither of which will kill a cell by itself, but which taken together are lethal. The idea was to find a mutation that causes cancer in humans, and to find a mutation in another gene which is lethal when combined with the cancer-causing mutation.
Once you find the combination you can design a drug that interferes with expression of the second gene. Healthy cells will be relatively unaffected, but cells with the cancer-causing mutation will be killed.
“When we discover these interactions in human cells it can hold the key to effective, targeted cancer treatments,” Myers says.
Myers is a computational biologist at the University of Minnesota. Thanks in part to the CIFAR Genetic Networks program he works closely with Boone, who is a professor at the University of Toronto and the Canada Research Chair in Proteomics, Bioinformatics and Functional Genomics.
The researchers took a list of 125,000 synthetic lethal interactions they had found in yeast genes, and determined that 25,000 of those occurred in genes which were also found in humans. They then narrowed that list down to those involving genes that are known to contribute to cancer in humans and ended up with two candidates – each candidate consisting of a genetic mutation thought to contribute to cancer, and another mutation which combined with the first mutation is lethal to the cell.
The next step will be to try to develop a drug that could knock out the target gene, with the hope that it will kill the cancer cells and leave the healthy cells alone.
“This is a proof of concept,” Myers says. “It shows that analysis of genetic networks can provide new targets for drug treatment.”
The research is published in the journal Cancer Research. It was done in collaboration with researchers from the Mayo Clinic, the RIKEN Advance Science Institute, and the University of Wisconsin.