By Deborah Borfitz
July 6, 2022 | In recent years, as sequencing technology has provided a window to genetic mutations emerging in the blood, excitement has been building about the near-term likelihood of a routine method of screening for cancer. The promise extends to not only the detection of cancer but the organ from which it likely arose, based on the methylation pattern of that mutated DNA, according to Stuart S. Martin, Ph.D., professor in department of pharmacology at the University of Maryland School of Medicine as well as co-director of the Hormone-Related Cancers group within its Comprehensive Cancer Center.
Martin specializes in breast cancer metastasis, where the focus has been on circulating tumor cells (CTCs) in the blood for earlier detection than what is possible with clinical imaging. Attention is now shifting to DNA methylation patterns that appear to be important in the transition to metastatic cancer and can help pinpoint the metastasis location.
The current status in the development of DNA methylation biomarkers is a topic of several liquid biopsy talks that Martin will be moderating at the upcoming Next Generation Dx Summit. He has worked in the field for the past 12 years, paralleling the emergence of technologies for isolating CTCs as well as cell-free DNA (cfDNA) that has become a standard analyte for detecting cancers, notably metastatic disease, at an early stage.
Clinical detection as it exists today has a poor threshold for finding either primary or recurring cancer, he notes. For example, a tumor would have to be comprised of between 10 million and 100 million cells before it would be picked up by an MRI scan.
However, studies over many years have shown that using circulating tumor DNA (ctDNA) to track metastatic recurrence enables detection of a returning cancer more than a year sooner compared to MRI, says Martin. The ctDNA approach provides the opportunity to recognize earlier when a therapy isn’t working so patients can be switched to an alternate treatment or to introduce therapy to individuals with emerging evidence of disease—both of which could save an untold number of lives.
“It used to be the case that to make an effective ctDNA test you needed to have a sample of the patient’s original tumor to determine what mutations were in that tumor so you could develop a test that looks specifically for those mutations,” he says. “We now know you don’t necessarily need to do that... you can do broad sequencing of the circulating tumor DNA that is in the blood and just see the mutations emerging. You don’t need to know what the mutations are ahead of time.”
This is fueling excitement about screening tests for people who don’t yet have cancer, says Martin. The addition of DNA methylation markers on top of that further expands the diagnostic potential to the reliable detection of cancer and its tissue of origin.
Unique Patterns
A ctDNA diagnostic test measures the amount of mutated DNA relative to the ratio of normal DNA that is in the blood, Martin explains. An increasing presence of mutated DNA is indicative of a cancer that is growing. DNA methylation is the epigenetic modification that occurs to the DNA and is typically used as a mechanism to suppress transcription. “When the DNA in hyper-methylated, those genes tend not to be expressed.”
As will be discussed in some detail at the conference, the DNA methylation patterns of different tissues within the body are unique and that’s what makes it possible to use ctDNA to identify a tumor’s organ of origin, he says. DNA methylation will affect gene expression in all tissues and can be altered in multiple diseases (including muscle, bone, and neurological conditions), but cancer is both where the clinical need is great, and methylation is most easily measured in the blood.
The topics to be presented—a liquid biopsy test for triple-negative breast cancer based on the detection of DNA methylation, methylation of cfDNA as an indicator of cancer and metastasis location, and a methylation-based, multi-cancer early detection test—represent the major research avenues currently, says Martin.
Megan Barefoot, a doctoral student at Georgetown University School of Medicine, will speak on decoding cfDNA fragments from dying cells to monitor changes in tissue over time and thereby how well a therapy is working or if a cancer has spread, he says. Dynamic changes to the tumor microenvironment can likewise be monitored based on the differing characteristics of cell-free ctDNA carried by the cancer cells.
Among the big hurdles that are being overcome in this arena are signal abundance—the fraction of target cfDNA indicative of tumor-specific epigenetic changes relative to total cfDNA in patients’ blood sample—thanks largely to advances in sequencing technology, Martin says. In addition, improvements in sequencing depth and breadth have given researcher a more reliable read on those mutations and DNA methylation patterns in the ctDNA. “The ability to not only detect cancer with high sensitivity but also determine the tissue of origin is what’s providing so much promise for the early detection of cancer before a tumor has even been found in a patient with clinical imaging.”
The integration of artificial intelligence and machine learning methods has also been critical to progress, given the tremendous amount of data being collected in these sorts of studies, he adds. “It would not be possible for a single human being to read through so many DNA sequences and identify patterns, but computers are very good at doing that.”
The combination of DNA sequences and methylation patterns gives needed robustness to the data so that it applicable to diverse populations of patients whose genomes have slight variations, says Martin. Test results also might not be as misleading with the additional information on methylation patterns.
Bisulfite conversion is the most used sequencing method for recognizing methylation patterns in the DNA, he says. The biggest and best-known players in the space are Illumina, Guardant Health, and Oxford Nanopore.
Pan-Cancer Testing
Another conference session, focused on a multi-cancer early detection test to complement existing screening, will be led by Minetta C. Liu, M.D., chief medical officer at Natera. The talk is based on ongoing work, building on findings of the large Circulating Cell-free Genome Atlas study (CCGA), to develop a blood-based test utilizing cfDNA sequencing in combination with machine learning to detect cancer signals from 12 different cancers and predict their origin (
Annals of Oncology,
DOI: 10.1016/j.annonc.2021.05.806)
The methylation-based test has demonstrated high specificity, but sensitivity is optimal only at later cancer stages. However, Martin notes, sensitivity is less of a clinically relevant measure for a multi-cancer tests than positive predictive value (proportion of true positives among those with a positive test result), which the study authors pegged at 88.7%.
Major efforts are underway by several industry groups to develop a screening test for early detection of cancer, he says. Notable among these is GRAIL (a subsidiary of Illumina), which made significant contributions to the assay used in the study. GRAIL is currently marketing Galleri, a ctDNA-based blood test that can detect over 50 types of cancer with a low false-positive rate.
As reported in the Annals of Oncology, only five cancer screening tests are currently available in the U.S. (breast, colorectal, cervical, lung, and prostate) and they all have high false-positive rates. As newer, methylation-based tests enter routine use, even the false-positives could become less concerning because of the ease of repeat testing to increase clinical confidence in whether a patient is or is not suffering from cancer.
Leading a third conference session on a second-generation mDETECT liquid biopsy test for triple negative breast cancer is Christopher Mueller, Ph.D., professor of biomedical and molecular sciences at Queen’s University School of Medicine. The methylation-based blood test was clinically validated to have 93% sensitivity and 100% specificity (
Precision Oncology,
DOI: 10.1038/s41698-021-00198-9), showing potential to better monitor tumor burden in this aggressive subtype of breast cancer compared to mutation-based assays.
The test optimizes detection by looking at large numbers of highly frequent tumor-specific methylation events that occur over a small region of the genome—specifically, 53 amplicons (segments of DNA that undergo amplification) from 47 regions commonly known to be upregulated and where a tumor is likely to develop multiple copies of the genes that help it survive and grow. It is first of multiple planned mDETECT assays specific to different types of cancer based on their methylation pattern.