Zhou, PhD, (left) and David
Schwartz, PhD, in the lab
Photo by Jeff Miller/University
of Wisconsin-Madison
A novel approach to genome analysis can provide a clearer picture of cancer genomes, according to research published in PNAS.
Investigators used this approach, which combines optical mapping and DNA sequencing, to analyze samples from a patient with multiple myeloma (MM).
They found “widespread structural variation” in the tumor genome and observed an increase in mutational burden that correlated with disease
progression.
“Cancer genomes are complicated, but we found that, using an approach like this, you can begin to understand them at every level,” said study author David Schwartz, PhD, of the University of Wisconsin-Madison.
“The approach allows an intimate view of a cancer genome. 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.”
To test the approach, the investigators obtained cancerous and noncancerous samples from a patient with MM at two different time points: while the patient was still responding to treatment and after the patient’s disease had progressed and become resistant to chemotherapy.
The team performed standard DNA sequencing to read each of the letters spelling out the genomic code of the disease. Then, isolating the individual DNA molecules, they performed optical mapping.
This involves stretching single strands of DNA and placing them in a device. The strands are given specific landmarks and marked with a fluorescent dye. An automated system takes images of each of these marked segments, cataloging the molecules into large datasets that are then pieced together to provide a larger view of the genome.
The investigators said the information provided by DNA sequencing and the “bigger picture” provided by optical mapping allowed for a comprehensive view of the patient’s MM 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,” said study author Fotis Asimakopoulos, MD, PhD, of the University of Wisconsin Carbone Cancer Center.
The approach allowed the investigators to see that, compared to the patient’s noncancerous genome, and across the two time points, the MM genome was marked by an increase in notable mutations and larger-scale changes.
The team highlighted the changes they believe are most worthy of further exploration and that yield the greatest potential for future therapies. They hope this approach could help prevent drug resistance or at least help scientists and physicians develop ways to work around it.
It could allow them to examine changes in a patient’s cancer over the progression of the illness, monitor for signs of resistance, and fine-tune treatments, Dr Schwartz said.
“To cure myeloma, we need to understand how genomes evolve with progression and treatment,” Dr Asimakopoulos added. “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.”
“Instead of [calling the disease] grade 1, we can say, ‘This is Joe’s myeloma, and, given this list of mutations and other info, this is the treatment.’ No two myeloma are alike.”
The investigators are now working toward advancing the system, making it higher-resolution, more cost-effective, and scalable. Ultimately, they would like to build a system capable of analyzing 1000 genomes in 24 hours.
