I have blogged extensively about the progress that is being made with liquid biopsy research (see, for example: Grail Picks Specific Method for Liquid Biopsy Clinical Trials). The test is based on the correlation that can be made between cell-free DNA (cfDNA) fragments circulating in the blood with a malignant tumor that may be growing in the patient. A recent article addressed some new science for assessing fragments of DNA in the circulation based on a machine learning model (see: Genome-wide cell-free DNA fragmentation in patients with cancer). Below is an excerpt from the summary of the article:
Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles....A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.
I first blogged about liquid biopsies in October, 2010 (see: Does the New Term "Liquid Biopsy" Make Any Sense?), complaining that I did not like the term. It has persisted so we are stuck with it. In those early years, the test involved isolating the very rare cancer cells in the peripheral blood and then genotyping them. There was major questions about this technology including questions like the extent to which malignant neoplasms shed cells into the peripheral blood stream. The science and technology then evolved over the years to the far easier task of isolating cell-free DNA (cfDNA) from the blood stream.
For patients with known cancers subject to recurrence, the correlation between circulating cfDNA and a known, preexisting primary tumor will be relatively obvious. However, such knowledge does not exist if and when a liquid biopsy is used for cancer screening in the general population. Such screening will probably be the norm in several years for patients with known high cancer risk such as chronic smokers. The ability to analyze and make sense of circulating DNA fragments, an obviously daunting task, has now apparently been solved using machine learning technology. Very interesting is the point made above that DNA fragments in normal individuals were found to be related to the nucleosomal patterns of white blood cells.
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