Scientists have identified genetic clues to how a tumor spreads throughout the body. Understanding the genetic aberrations that enable the metastasis of cancers could help scientists design better prognostic tests and more effective treatments.
In the research, the scientists compared the genome sequence of a breast cancer patient with that of both her primary tumor and cancer cells that had spread to her brain. It is just one of two published papers comparing the genomic differences between a primary and metastatic tumor from the same patient, a challenging endeavor but one that allows scientists to track the cancer’s evolution. “A patient’s tumor is a living thing changing all the time,” says Matthew Ellis, an oncologist and scientist at Washington University, in St. Louis, and one of the study’s authors. “We’ve never been able to track that completely.”
Cancer results when healthy cells acquire a combination of genetic mutations that allow them to grow out of control. Scientists have identified a number of mutations that increase the risk of cancer, as well as predict its prognosis and its likelihood of responding to certain treatments. But much less is known about the genetic mistakes that enable tumor progression, especially metastasis. The new research, reported Wednesday in the journal Nature, “emphasizes that you can gain a lot from looking at the evolution of a cancer over time,” says Sam Aparicio, Canada Research Chair in molecular oncology, who was not involved in the study.
The researchers used sequencing technology from Illumina, a genomics company in San Diego, to analyze DNA from the patient’s healthy cells, from the primary tumor prior to treatment, and from the brain metastasis. They found 48 mutations unique to cancer cells, but very few mutations were unique to the metastatic brain tumor. Instead, the major difference between the two tumor types was the relative frequency of the individual mutations in each tissue sample. Twenty of the 48 mutations occurred occasionally in cells in the primary tumor but were quite common in the metastatic tumor, suggesting that a small cohort of cells present in the primary tumor drove the cancer’s spread. “It’s as if a small subset of cells broke off from the primary tumor, circulated through blood, found a new home in the brain, and began to grow wildly and out of control,” says Richard Wilson, director of the Genome Sequencing Center at Washington University and a senior author of the paper.
While researchers still need to determine which of these mutations are true drivers of metastasis and which are merely carrier mutations that don’t affect the cells, they have identified some interesting candidates. For example, the patient had normal versions of a gene called CTNNA1, which has been linked to cells’ ability to stick to each other. But both tumors samples had a large deletion knocking out both copies of the gene, an occurrence that was particularly common in the metastatic cells. This mutation might allow cancer cells to break free of the primary tumor and spread through the bloodstream.
In addition to studying tumor samples from the patient, researchers implanted some of her tumor tissue into a mouse with a compromised immune system. This approach, called a xenograft, is often used to study the properties of human cancers. Just as in the patient, the cancer cells quickly multiplied and spread. When the team sequenced DNA from these cells, they found it had a similar genetic profile to that of the metastatic tumor samples. “It was a big surprise to see so many similarities between the xenograft and the metastatic genome,” says Elaine Mardis, codirector of the Genome Center. Both cancers originated from the same primary tumor and seemed to evolve in similar ways, despite growing in completely different environments. “This is just one case and we need to study more, but this does look like an interesting model for studying metastatic cancer,” she says. If the findings are confirmed more broadly, drug developers can use this system to test new treatments on human tumor cells, knowing that the cells behave similarly in the mouse and in the human body.
Mardis, Wilson, and others aim to sequence hundreds of cancer genomes over the next year. “The capacity for sequencing instruments has been on a dramatic uptick,” says Mardis. “The biggest challenge now is, how do you do multigenome analysis, for example comparing 20 to 50 genomes at the same time from a carefully defined phenotype like drug resistance?” The researchers hope that studying this volume of DNA will give broader insight into cancer genomics, letting them identify key metabolic or signaling pathways that are affected in cancer and which might be good targets for new therapeutics.