Researchers at the Johns Hopkins Kimmel Cancer Center have developed a simple new blood test that can detect the presence of seven different types of cancer by spotting unique patterns in the fragmentation of DNA shed from cancer cells and circulating in the bloodstream.
In a proof-of-concept study, the test, called DELFI (DNA evaluation of fragments for early interception), accurately detected the presence of cancer DNA in 57 percent to more than 99 percent of blood samples from 208 patients with various stages of breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancers in the U.S., Denmark, and the Netherlands.
DELFI also performed well in tests of blood samples from 215 healthy individuals, falsely identifying cancer in just four cases. The test uses machine learning, a type of artificial intelligence, to identify abnormal patterns of DNA fragments in the blood of patients with cancer. By studying these patterns, the investigators said they could identify the cancers’ tissue of origin in up to 75 percent of cases.
A report on the research was published online May 29 in Nature.
Blood tests, or so-called “liquid biopsies” for cancer detection typically look for mutations, which are changes in the DNA sequence within a cancer cell, or for methylation, a chemical reaction in which a methyl group is added to DNA, says senior study author Victor E. Velculescu, MD, PhD, professor of oncology and co-director of the Cancer Biology Program at the Johns Hopkins Kimmel Cancer Center. But not all cancer patients have changes that are detectable using these methods, he says, and there is a great need for improved methods for early detection of cancer.
DELFI, he says, takes a different approach, studying the way DNA is packaged inside the nucleus of a cell by looking in the blood at the size and amount of DNA from different regions across the genome for clues to that packaging.
Alessandro Leal, MD, a lead author of the study and a PhD candidate at the Johns Hopkins University School of Medicine, explains that the nuclei of healthy cells package DNA like a well-organized suitcase in which different regions of the genome are carefully placed in various compartments. By contrast, the nuclei of cancer cells are more like disorganized suitcases, with items from across the genome thrown in haphazardly.
“For various reasons, a cancer genome is disorganized in the way it’s packaged, which means that when cancer cells die they release their DNA in a chaotic manner into the bloodstream,” says Jillian Phallen, PhD, a lead author on the study and a Johns Hopkins Kimmel Cancer Center postdoctoral fellow. “By examining this cell-free DNA (cfDNA), DELFI helps identify the presence of cancer by detecting abnormalities in the size and amount of DNA in different regions of the genome based on how it is packaged.”
The researchers caution that the test’s potential must be further validated in additional studies, but if that happens it could be used to screen for cancer by taking a tube of blood from an individual, extracting the cfDNA, studying its genetic sequences and determining the fragmentation profile of the cfDNA. The genome-wide fragmentation pattern from an individual can then be compared with reference populations to determine if the pattern is likely healthy or derived from cancer.
