In 2016, the U.S. Food and Drug Administration approved a cell-free DNA (cfDNA) liquid biopsy for the first time (ASCO, 2016). This test, which detects mutations in cfDNA relevant to non-small cell lung cancer, marked an important step in bringing plasma-based tumor genotyping into the clinic.
Building a growing number of assays around cfDNA
Earlier that same year, the FDA also approved the first cfDNA methylation test for colorectal cancer screening (Epigenomics, 2016), and additional blood-based colorectal screening tests have seen further FDA approvals in 2024 (Chung, 2024) and 2026 (Freenome, 2026). These approvals are just examples of the growing trend in using cfDNA. Thanks to the expansion of next-generation sequencing technologies, techniques like comprehensive genomic profiling (CGP) are becoming more commonplace, which have been cataloged in OpenOnco, a curated database of cancer diagnostic tests and the research behind them (Streck is a sponsor of OpenOnco). The progression in other ‘omic methodologies and the growth in computing power has opened the doors for other techniques like fragmentomics, proteomics, and epigenetics to more widely enter the picture.
While cfDNA assays are still the foundation of liquid biopsies, the industry is clearly asking for more than cfDNA only. In research, cfDNA is increasingly evaluated alongside cell-free RNA (cfRNA), extracellular vesicles (EVs), and plasma proteins to study complementary biological signals. These additional analytes contain a wealth of information that cfDNA alone cannot provide.
The development of the wide array of methods used to analyze blood can be found in databases like Bioz, which aggregates information on products and protocols for specific assays, including a comprehensive list of citations to back up the products. The practical information found in such databases has helped scientists implement new assays into their workflows and serves as an important reference point for the future of liquid biopsy work.
Getting more from the same blood draw
Yet despite the progress in cfDNA-based assays, one challenge is the amount of DNA released in the blood. More than half of circulating plasma cfDNA in healthy people is already leukocyte-derived (Moss, 2018). Post-draw leukocyte breakdown is a separate problem, because it adds genomic DNA to the plasma pool that was never circulating at all. This is especially challenging for circulating tumor DNA (ctDNA) assays, where DNA from tumor cells represents a limited fraction of the total cfDNA. Nonetheless, researchers are pushing the limit of detection for early cancer detection or minimal residual disease testing, where disease-related signals may be far weaker than during active disease.
All of these examples point toward one thing: the need for high-quality samples that represent the blood at the time of draw. CGP requires higher DNA quality and quantity to produce a reliable result. For fragmentomic analysis, post-draw release of high molecular weight genomic DNA from leukocyte breakdown can alter the size distribution and fragment features being measured. The additional cellular DNA released can also shift the methylation signal being measured and may confound interpretation.
Greater analytical sensitivity raises the pre-analytical stakes
These methods point to a greater need to minimize any changes between the time of blood draw and processing. These pre-analytical variables, common when sending samples for analysis, become critical to control. While pre-analytical variables can be minimized by processing samples at the same site as the draw, this isn’t always practical, for example, in multi-site studies or for sites that need to outsource processing. Shipping time, storage temperature, and delayed processing can alter the measured signals, with most workflows not accounting for or controlling sample degradation.
Between collection and analysis, if not stabilized properly, white blood cells begin to break down. They release genomic DNA, and can skew readouts for methylation or fragmentomics studies or mask rare variants. cfRNA profiles can change through both degradation and the post-draw release of cellular transcripts. For extracellular vesicles, both platelet activation after the draw and residual platelets remaining in plasma can alter measured particle counts and cargo (cfRNA / protein) profiles (Bettin, 2022). Plasma protein profiles can shift through hemolysis, platelet-related effects, cellular protein release, and ongoing proteolytic activity before plasma separation.
While reducing pre-analytical variables is important for assays targeting a known mutation or a highly expressed variant, it becomes more consequential for analytes that are more sensitive to degradation and are lowly expressed. For multi-analyte analysis, a collection approach that helps limit blood cell breakdown, enzyme activity, and platelet activation is necessary so that the resultant sample maintains draw-time characteristics throughout shipping, storage, and processing.
Contaminated samples can pass standard quality checks
Here’s the part that should worry you: the checks built to catch a bad sample are often the same checks a degrading sample can pass.
Genomic DNA released from lysed white blood cells resembles high-quality, amplifiable DNA. A contaminated sample can look like a better sample, with higher DNA concentration, higher library yields and more reads, and still be less representative of the cfDNA fraction at draw time.
Fragment size analysis and the long-to-short fragment ratio can catch this where sequencing metrics can’t. Native cfDNA clusters tightly around a modal peak of about 166 base pairs, well under the length of genomic DNA fragments released from lysed cells (Snyder, 2016). But most quality checks are built to evaluate sequencing performance, not to flag this kind of contamination, so it slips through.
The result: findings may not replicate between laboratories or between runs. For cell-free DNA specifically, the National Cancer Institute’s biospecimen practices put the optimal window at two hours from venipuncture, with a delay of up to four hours at room temperature considered acceptable, and recommend a stabilizing tube when longer delays are anticipated (NCI, 2025).
Designing collection workflows for future analysis
Both the collection tube and processing method determine what reaches the freezer, and the freezer can only preserve what is there in the first place. It cannot reverse changes imparted by leukocyte breakdown, hemolysis, or platelet activation. Once you’ve chosen a collection approach, you’ve also decided what analytes are available later. This is why it’s important to accurately define the collection and processing workflows to give flexibility for future analyses. This decision shouldn’t be revisited after collection; a workflow built only around cfDNA, for example, has already ruled out other analytes.
Considering this can help prepare you for any additional analytes that may need to be revisited years from now. This would help avoid costly rework and resampling if initial data in your trial, or recently published work, points to another important biomarker worthy of further analysis.
So when you design your trial, make sure to look ahead. Define the collection tube, processing steps, and storage conditions during trial design, and document their suitability for the intended assays.
cfDNA remains the foundation of liquid biopsy work, but the numerous analytes and assays that have developed around cfDNA have tremendously moved the liquid biopsy field forward. By combining complementary plasma analytes, studies can address a broader range of biological questions. Accessing the plethora of information from one blood draw hinges on one thing: ensuring that your sample represents the blood at the time of draw.
Reading List
- FDA Approves First Liquid Biopsy Test for Use in Non-Small Cell Lung Cancer. ASCO in Action. 2016.
- Epigenomics Receives FDA Approval for Epi proColon. Epigenomics AG press release. 2016.
- Chung DC, Gray DM 2nd, Singh H, et al. A Cell-Free DNA Blood-Based Test for Colorectal Cancer Screening. N Engl J Med. 2024;390:973–983.
- FDA Approves Freenome’s SimpleScreen CRC Blood-Based Screening Test; Abbott to Commercialize in the U.S. Freenome, Inc. press release. 2026.
- Moss J, Magenheim J, Neiman D, et al. Comprehensive Human Cell-Type Methylation Atlas Reveals Origins of Circulating Cell-Free DNA in Health and Disease. Nat Commun. 2018;9:5068.
- Bettin B, Gasecka A, Li B, Dhondt B, Hendrix A, Nieuwland R, et al. Removal of Platelets from Blood Plasma to Improve the Quality of Extracellular Vesicle Research. J Thromb Haemost. 2022;20(11):2679–2685.
