In 2008, Dr. Timothy Ley, the Lewis T. and Rosalind B. Apple Chair in Oncology, Professor of Medicine and Genetics, and Associate Director of the McDonnell Genome Institute at Washington University, led a team that became the first to sequence an entire cancer genome using a patient’s own cancerous cells. The cancer they sequenced was called Acute Myeloid Leukemia (AML) — one of four major types leukemia.
Cancer occurs when changes in a person’s DNA cause a certain type of cell to grow unchecked. AML specifically affects the body’s blood cells, which are made in the bone marrow. There are around 13,000 new AML cases diagnosed each year in the United States. AML is a particularly aggressive and difficult cancer to treat, striking generally after the age of 60 and returning for most patients even after initial remission. The severity of the disease can depend on a number of factors such as age, blood cell count and the types of mutations within those blood cells. The treatment for AML has remained relatively unchanged for the past two decades because the genetic underpinnings of the disease have yet to be fully elucidated.
“As we were just beginning to think about how to do whole genome sequencing, it was important to us to try to work with relatively simple genomes,” says Dr. Ley, “because we knew the sequencing was going to be simpler.” AML was also a good first choice since doctors already use genomic techniques to classify the severity of an AML patient’s condition. By looking at the patient’s chromosomes and what kinds of abnormalities exist in them, doctors have been able to determine how well certain patients will do with a given treatment. This existing background knowledge of this cancer’s genetic makeup gave researchers a head start as they began sequencing it.
Unfortunately, this chromosome classification technique only works with a small group of patients. Most of the time, doctors can’t tell how an AML patient will respond to therapy such as drugs or the more radical stem cell transplants, and the majority of patients can’t be classified simply by looking at the structure of their chromosomes. This is where whole genome sequencing comes in.
In the past, researchers have looked for specific genes that were suspected of being involved in a given cancer. Looking instead at the entire genome provides an unbiased approach to searching for mutations and other changes in a patient’s DNA that lead to the cancer. “Everyone has known for a long time that we need to figure out unbiased ways to find cancer mutations,” says Dr. Ley, and here was the perfect opportunity to do that.
Dr. Ley and his colleagues began by comparing the entire sequence of DNA obtained from a patient’s AML cells with the DNA sequence from that same patient’s healthy cells. Looking at the mutations in DNA from normal versus cancerous cells allowed the researchers to understand more about the underlying genetic cause of the disease and help determine the best course of action to treat each individual. To do these whole genome comparisons, the team made use of the McDonnell Genome Institute’s advanced technology and computing power, which are key in such large-scale sequencing and data analysis.
The team sequenced two entire AML genomes and their normal cell counterparts from two separate patients. Examining the second whole cancer and normal cell AML genomes, they found two key mutations that appeared to be important in the development of AML for certain patients. One of the mutations was in a gene called IDH-1, which is important in brain cancers and turns out to be one of the most common mutations ever found in AML. This mutation could help doctors classify the severity of a patient’s cancer, since those carrying it tend to have bad outcomes. These kinds of key mutations would not have been discovered using traditional screening approaches. “We would not have found it without unbiased sequencing. No one was suspecting it,” says Dr. Ley.
The McDonnell Genome Institute has moved on to sequence dozens more AML samples, with the goal of defining all the mutations that occur in adult AML cells. This information will allow researchers to create better molecular diagnostic tools, determine which patients will benefit most from certain treatments, and identify candidate genes for new or improved targeted therapeutics. “It could immediately have an impact on patient care. That’s really why we chose AML,” says Dr. Ley. He adds: “What we wanted to do was something that would matter very quickly.”