Researchers at the Johns Hopkins Kimmel Cancer Center have developed a 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 called DELFI, DNA evaluation of fragments for early interception, accurately detected the presence of cancer DNA in 57% to more than 99% 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 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% of cases.
The study was published in Nature.
Blood tests, or liquid biopsies, for cancer detection typically look for mutations or for methylation, a chemical reaction in which a methyl group is added to DNA, said senior study author Victor E. Velculescu, professor of oncology and co-director of the Cancer Biology Program at the Johns Hopkins Kimmel Cancer Center.
Not all cancer patients have changes that are detectable using these methods, Velculescu said, and there is a great need for improved methods for early detection of cancer.
DELFI studies 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, a lead author of the study, said 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,” Jillian Phallen, a lead author on the study and a Johns Hopkins Kimmel Cancer Center postdoctoral fellow, said in a statement. “By examining this cell-free DNA, 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 said the test’s potential must be further validated in additional studies. 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 to reference populations to determine if the pattern is likely healthy or derived from cancer.
Robert B. Scharpf, a senior author on the study and an associate professor of oncology, said because the genome-wide fragmentation patterns may reveal differences associated with specific tissues, these patterns, when found to be derived from cancer, can also indicate the source of the cancer, such as breast, colon, or lung.
DELFI simultaneously analyzes millions of sequences from hundreds to thousands of regions in the genome, identifying tumor-specific abnormalities from minute cfDNA amounts, said Scharpf.
Using DELFI, investigators found genome-wide cfDNA fragmentation profiles are different between cancer patients and healthy individuals.
Stephen Cristiano, a lead author on the study, said, in cancer patients, fragmentation patterns in cfDNA appear to result from mixtures of DNA released from both blood and tumor cells. It also shows multiple distinct genomic differences with increases and decreases in fragment sizes at different regions.
For the current study, the Hopkins investigators worked with colleagues from institutions in the U.S., Denmark, and the Netherlands to perform low-coverage whole genome sequencing of cfDNA from 208 patients with cancer, including 54 breast cancer patients, 27 colorectal cancer patients, 12 lung cancer patients, 28 ovarian cancer patients, 34 pancreatic cancer patients, 27 gastric cancer patients, and 26 bile duct cancer patients. They also performed whole genome sequencing to analyze cfDNA from 215 healthy individuals.
All cancer patient samples were obtained before any treatment, and the majority of the samples, 183, were from people whose disease could be treated with surgical removal of the tumors.
The researchers report the healthy individuals had similar fragmentation profiles, while patients with cancer had more variable fragmentation profiles that were less likely to match healthy profiles.
DELFI detected cancer in 73% of cancer patients overall, while misclassifying four of 215 healthy individuals (98% specificity). The test also was found to be 61%-75% accurate in identifying the tissue of origin of the cfDNA.
When DELFI and mutation-based cfDNA analyses were combined, investigators could accurately detect 91% of cancer patients.
Because the test is easy to administer and employs simple and inexpensive laboratory methods, Velculescu expects the test could ultimately be more cost-effective than other cancer screening tests, including other current cfDNA tests.
