A Mapping Service for the Cancer Genome

June 9, 2015
A Mapping Service for the Cancer Genome
Researchers have developed a technique to visualize the genome much like a mapping app, with the ability to zoom in on individual mutations and zoom out to observe large scale changes. [iStock/ymgerman]

Most of us have used a mapping app at some point, whether for driving directions, finding the best route to the closest subway stop, or just to look at places on the globe we might like to visit one day. The power of these programs is derived from their ability to zoom in on discreet locations within large cities or being able to zoom out to get an overview of how to travel from point A to point B. Imagine now that this was possible for the cancer genome.

Researchers at the University of Wisconsin-Madison are not conceptualizing this technology, as they have developed a new approach that will account for both the discreet locations and a global content of the genome at once. Ultimately, this should enable researchers and clinicians to look at the small- and large-scale genetic changes that define individual cancers.   

"Cancer genomes are complicated but we found that, using an approach like this, you can begin to understand them at every level," stated David Schwartz, Ph.D. professor of genetics and chemistry at the University of Wisconsin-Madison and senior author on the current study.

The findings from this study were published recently in PNAS through an article entitled "Single-molecule analysis reveals widespread structural variation in multiple myeloma."

While the technique and study results are still preliminary, Dr. Schwartz is excited for others to test what he and his colleagues found. Moreover, the results demonstrate the potential of the approach the investigators took, which combines a system called optical mapping with more traditional genomic tools like DNA sequencing

"The approach allows an intimate view of a cancer genome," Dr. Schwartz explained. "You get to see it, you get to measure it, and you get to see it evolve at many levels. This is what we should be doing with every cancer genome and the goal here is to make the system fast enough so this becomes a routine tool."

Specifically, Dr. Schwartz and his team isolated DNA from normal and cancerous tissue from a patient with multiple myeloma at two different stages of the illness: when the cancer was responsive to drug treatment and at a point when it had become resistant to chemotherapy.

First, the researchers performed standard DNA sequencing to obtain the zoomed in portion of the genome. Then DNA was stretched out and placed in a special device. The strands were given specific landmarks and marked with a fluorescent dye. An automated system took images of each of these marked segments, cataloging the molecules, much like a barcode, into large datasets that were then pieced together like a jigsaw puzzle to provide a zoomable view of the genome.   

"It's a rare, near-complete characterization of the complexity of a myeloma genome, from the smallest variance all the way to big chunks of chromosomal material that differ between the tumor DNA and the normal DNA of the patient," stated co-author Fotis Asimakopoulos, M.D., Ph.D., professor of medicine and a multiple myeloma researcher and physician at the UW-Madison School of Medicine and Public Health.

What they found was that across the two time points from when the samples were taken the multiple myeloma genome was marked by an increase in notable mutations and larger scale changes. Not only were there more unusual mutations as the cancer progressed, but whole sections of the genome were removed, flipped around, or even inserted.

"To cure myeloma, we need to understand how genomes evolve with progression and treatment," said Dr. Asimakopoulos. "The more we can understand the drivers in cancer in significant depth, and in each individual, the better we can tailor treatment to each patient's disease biology."

In the meantime, Dr. Schwartz and his team continue to work toward advancing the system making it higher-resolution, more cost-effective and scalable. The researchers would ultimately like to build a system capable of analyzing 1,000 genomes in 24 hours.