New Funding to Help Set the Stage for Personalized Medicine

Oct 13, 2017
Author: 
Jovana Drinjakovic

Collaborative research receives boost from the government to build tools for predicting disease risk and tailor treatment based on genome sequence.

Brenda Andrews (centre) with Ben Blencowe, Stephane Angers, Daniel Durocher, Mikko Taipale, Tim Hughes, Charlie Boone and Jason Moffat (from top left clockwise). An inter-disciplinary team of researchers led by University Professor and Donnelly Centre Director Brenda Andrews has been awarded funding from the Canada Foundation for Innovation (CFI) to spearhead research that may one day allow scientists to predict with confidence a person’s risk of disease and tailor treatment based on their genetic makeup. The $2.76 million Innovation Fund grant will go towards building new technology for shedding light on how genes work together as part of a network to influence health of an organism.

“Our goal is to accelerate the important transition from basic cataloguing of genome sequences to functional characterization of genetic variation encoded within individual genomes,” says Andrews, who is also a professor in U of T’s Department of Molecular Genetics. “The wealth of information that our project will generate will impact our understanding of human cell function and disease and advance strategies for personalized medicine.”

Andrews’ team brings together U of T experts in diverse areas of genomics and from different research institutes and departments. On the team are Professors Ben Blencowe, Charlie Boone, Tim Hughes, Jason Moffat and Mikko Taipale from the Donnelly Centre and, as well as Professors Stephane Angers, of the Leslie Dan Faculty of Pharmacy and Daniel Durocher, of the Lunenfeld-Tanenbaum Research Institute at Sinai Health System in Toronto. All are also professors in the Department of Molecular Genetics. Through past collaborations, the team members have already developed technologies necessary for generating the first large-scale genetic network in human cells.

The funding was announced yesterday at the University of Manitoba by the Kirsty Duncan, federal minister of science, as part of an investment of more than $554 million in infrastructure projects at universities, colleges and research hospitals across Canada, according to a statement from the CFI. Overall, U of T researchers received more than $100 million for projects in diverse areas, from regenerative medicine to neuroscience and astronomy.

Learn more about other awarded research at U of T

“This funding announcement gives scientists and their students the opportunity to further their research in areas where Canada has a competitive advantage,” said Duncan. “The discoveries, innovations and skills developed in these new, state-of-the-art labs will go a long way in improving our lives, our economy and our future prosperity.”

"Our goal is to accelerate the important transition from basic cataloguing of genome sequences to functional characterization of genetic variation encoded within individual genomes" — University Professor Brenda Andrews

So far, research in human genetics has largely focused on collecting genome sequences from thousands of people in search of genetic clues of disease. But genes do not work in isolation and to understand how they impact health, it is important to study interactions between genes, which can’t be gleaned from sequence data alone.

Most diseases, such as cancer or heart disease, are caused by misspellings in dozens or even hundreds of genes, each one contributing ever so slightly to the overall risk and severity of disease. At the same time, no two genomes are the same—each person carries a unique combination of misspellings in their DNA, or genetic variants, which influence health in some ways.

“The onslaught of new genome sequence information has revealed a knowledge void – while most diseases are influenced by genetic variation, we do not understand how to properly interpret personal genome sequences to predict what genetic variation is linked to disease,” says Andrews. “And we cannot embrace the idea of personalized medicine until we make a new leap in our understanding of human genetics.”

To begin to unpick how multiple genes and their variants contribute to disease, scientists first need to understand how genes interact with each other to influence basic processes in the cell. This is usually done by systematically removing combinations of genes from cells to find those genes that work together.

A map showing interactions between all genes present in yeast cells (Michael Costanzo). In most cases, removing a single gene does little to throw a cell off balance thanks to other genes that can pick up the slack and serve as back-up. But removing two genes at a time can lead to wholly unpredictable outcomes—the cell could either die or thrive suggesting that the two genes are somehow connected.

By removing gene pairs in all possible combinations from yeast cells, Andrews and Boone’s teams have previously revealed the first complete genetic network for any cell, mapping interactions between almost all 6,000 yeast genes. With about 20,000 genes, human cells are far more complex and the team will have to analyze millions of pairwise gene combinations to find genetic interactions that cells depend on. To deal with a sheer volume of cells in experiments, the researchers are proposing to build a custom robotics platform akin to the one they had made previously for yeast work.

The researchers will remove genes from human cells using the gene editing tool CRISPR. Thanks to Moffat’s earlier work, a CRISPR library of “off switches” for every single human gene, is already available in the Donnelly Centre.

Medical implications of having the genetic interaction map for human cells are far-reaching. Knowing which genes work together can point to genetic variants that may fine-tune disease severity as opposed to merely being present in the genomes of people with that disease. These insights could help build more precise genetic tests to determine a person’s risk of cancer or heart disease. In drug discovery, genetic networks of healthy and cancer cells, for example, can reveal genetic weaknesses unique to cancer that could be targeted by drugs more precisely, avoiding harm to healthy tissue.

The prospect of personalized medicine—where one’s genome spells out diseases to come and calls for the right treatment—is poised to become a reality, said Andrews.

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