The clinical use of cell-free DNA (cfDNA), the extracellular fragments of DNA that circulate in body fluid, has gained rapid momentum in recent years. Today, analysis of cfDNA from liquid biopsies is integral to maternal health and oncology care, including early cancer detection and minimal residual disease monitoring, and applications are emerging in transplant medicine and infectious disease tracking.1
However, for clinical labs, cfDNA workflows are daunting. Highly fragmented cfDNA is present in low but variable abundance within a background of complex biological contaminants that are also characterized by incredible heterogeneity. For instance, differences in abundance and composition of cfDNA may be modulated by physiological factors, disease stage, and sample type (i.e., blood plasma, urine, cerebral spinal fluid). Differences in the abundance and composition of cfDNA contaminants can be impacted by fluid type, initial sample handling, and downstream workflow.
Historically, many labs sent their cfDNA samples out to large, specialized testing facilities, but an increasing number of clinical laboratories are now working to bring cfDNA workflows in-house in order to support their research and direct patient care. Given the complexity of these workflows, troubleshooting is an inevitable part of the process. As product developers intimately familiar with cfDNA workflows, we can share a few high-level recommendations for getting useful information from cfDNA.
Stringent upstream sample handling pays dividends
The colloquialism “garbage in, garbage out” is highly applicable to analysis of cfDNA, where success hinges on sample handling and processing. For instance, plasma, which contains cfDNA, must be separated from blood samples within two to four hours, to avoid blood cell lysis, which makes an already challenging purification problem much worse.2
Using collection tubes designed to purify and separate cfDNA from a complex biofluid matrix will make a big difference downstream. Labs developing a workflow can test various tubes by utilizing automated electrophoresis methods to visually confirm whether contaminating genomic DNA peaks have been successfully minimized in their samples. In addition, laboratories can communicate the necessary sample handling processes to medical providers through direct communication and standard operating procedures.
Clinical labs that rely on biobanks of stored cfDNA samples for their research often have less control over the initial handling of their samples. In this case, characterizing the quality of starting samples is essential, and downstream workflows may need to be adapted to compensate for more contaminated or damaged inputs.
Use sample processing methods adapted to cfDNA
Sample preparation methods, including extraction and library preparation should also be adapted to cfDNA, designed to mitigate genomic DNA contamination challenges and optimize yield. For instance, cfDNA-specific extraction kits should be specifically validated to handle complex biofluids without carrying over contaminants—such as harsh elution buffers or residual salts—that could jeopardize downstream analysis. During library prep, labs should not intentionally fragment or shear their DNA, because it will chop up any contaminating, high-molecular-weight genomic DNA, and incorporate it into the final library, skewing the data.
Additionally, while cfDNA has a characteristic size of about 167 base pairs, there are often smaller, highly clinically relevant fragments present. Labs must ensure their chosen extraction and cleanup protocols are not unintentionally washing away these critical sub-167 bp fragments.
Set realistic expectations
Even with a highly optimized method, researchers must set realistic expectations regarding the limits of their workflow. For example, it may not be possible to detect a rare mutation from one nanogram of input material. Some downstream applications may require larger input volumes, a more burdensome sample type with higher abundance of cfDNA, such as cerebrospinal fluid (CSF), or multipl01e liquid biopsies from the same patient. Labs may also benefit from implementing tools and products that are validated for end-to-end workflows and that showcase cfDNA detection data across extraction and sequencing.
Ask for help
Troubleshooting is an expected part of developing cfDNA workflows. Support from technical experts familiar with cfDNA workflow design and your specific tools is extremely helpful for optimizing challenging applications. Furthermore, collaborations between tool developers and clinical research scientists are vital for advancing diagnostic science and informing the development of future laboratory solutions.
References:
1. Bronkhorst AJ, Ungerer V, Oberhofer A, et al. New Perspectives on the Importance of Cell-Free DNA Biology. Diagnostics (Basel). 2022;12(9):2147. doi:10.3390/diagnostics12092147
2. Peng H, Pan M, Zhou Z, Chen C, Xing X, Cheng S, Zhang S, Zheng H, Qian K. The impact of preanalytical variables on the analysis of cell-free DNA from blood and urine samples. Front Cell Dev Biol. 2024 May 9;12:1385041. doi: 10.3389/fcell.2024.1385041
