Here we have presented our method for detecting and quantifying the allelic frequency of tumor mutations in cfDNA from patient liquid biopsy. We emphasize critical steps for the success of this method, including pre-analytical sample processing, cfDNA extraction, PCR assay design, and data analysis. To limit the sample volume used, cfDNA is extracted from 1 mL of plasma but only 500 µL of CSF. When extracting from CSF, the protocol for extraction from 1 mL of urine (following the cfDNA extraction kit handbook12) is used, as per the manufacturer's recommendation. The difference in sample volume required between plasma and CSF is due to lower levels of tumor-specific cfDNA in plasma compared to CSF of patients with brain tumors, necessitating larger sample volumes for mutation detection8. If the sample is available, more than 1 mL of plasma may be extracted from to produce higher DNA yield. However, in the case of pediatric patients, it is important to minimize the amount of blood used whenever possible, as even a simple procedure such as blood draw is fatiguing to pediatric patients with cancers undergoing radiation therapies. Extracting from 1 mL aliquots of plasma also enables replicate extractions, such that the assay can be repeated (e.g., in cases of failure in DNA extraction or sample contamination).
In an effort to reduce any sample use that is not strictly necessary, cfDNA is typically not quantified. However, we have found a range of cfDNA concentrations between 0.2-2 ng/µL and 0.6-13 ng/µL in plasma and CSF, respectively. Given the low amount of cfDNA, and the fact that tumor-specific mutant alleles are present at a low frequency, a pre-amplification step using the same set of primers used for dPCR is necessary to significantly increase the amount of target DNA in the sample, aiding in mutation detection8. Diluting the pre-amplified product in DNA suspension buffer provides sufficient volume for technical replicates, which aids in distinguishing true positives. Because the number of mutant droplets can be low (for example, between 0-2 mutant droplets in a plasma sample), the inclusion of technical replicates is key for resolving mutation status. While one PCR well may yield 0 mutant droplets, the other two may yield 1-2 for a single plasma sample analyzed in triplicate; thus, the inclusion of replicates allows for greater accuracy when determining mutation status. The MAF is then calculated as the average of the replicate values.
Multiplexed pre-amplification (preamplifying wildtype and mutant alleles of two mutations of interest) increases the utility of a single sample, as the same starting material can be used to test for two mutations. Importantly, a multiplex preamplification product can be analyzed in singleplex during dPCR for greater simplicity, as described here. However, both preamplification PCR and dPCR may be multiplexed. When multiplexing, conditions must be optimized for both sets of primers and probes: primer annealing temperatures must be similar to run together in PCR amplification, and probes should be designed to generate distinct clusters (based on fluorescent signal and intensity). When validating a new set of primers and probes, run an annealing temperature gradient to determine optimum annealing temperature based on the range suggested by the manufacturer. Before testing probes on patient cfDNA specimens, validate them using synthetic DNA constructs and/or tumor tissue gDNA of different inputs (i.e., up to 10 ng).
For the detection of mutant alleles with greater specificity and reduced mismatches in the hybridization of probe to the target DNA, locked nucleic acid (LNA) probes are used. LNA is a nucleic acid analog with a methylene bridge connecting the 2'-oxygen and 4'-carbon of the ribose ring9. The methylene bridge locks the nucleic acid into a rigid bicyclic conformation that restricts flexibility, increases thermal duplex stability, and improves the specificity of probe hybridization to target DNA10,18,19. If a single base mismatch exists between LNA probe and template DNA, duplex formation between probe and target will destabilize. As such, LNA probes improve the specificity of probe binding and result in a higher signal-to-noise ratio11. Analysis of plasma and CSF from non-CNS-diseased pediatric patients has established the specificity of our assay with LNA probes targeting H3F3A p.K27M, to determine that an allelic frequency of equal to or less than 0.001% is considered a false positive8. For additional considerations for optimizing the design of probes and primers, including GC content, amplicon size, probe reporter dyes, and quenchers, refer to the dPCR manufacturer guidelines14,17. Although our method is optimized for use with the RainDance system, the protocol may be adapted for use with other dPCR platforms.
The method presented here draws strength from the high sensitivity and target enrichment achieved by dPCR, which remains the platform of choice for detecting rare tumor mutations in cfDNA. Although powerful, dPCR is limited in the number of mutations that can be tested for in a single assay. An alternative to dPCR is next generation sequencing (NGS), which may detect multiple mutations across many genes, increasing the utility of a single sample. NGS can detect mutations in CSF and plasma of patients with brainstem gliomas20, however, is currently less sensitive than dPCR at detecting tumor mutations in cfDNA, with detection limits of 0.1-10% MAF compared to 0.001% in PCR-based approaches21. dPCR also achieves faster turnaround time than NGS, enabling rapid detection of mutations of interest.The PCR approach is applicable across cancer types and can be expanded to detect hotspot mutations and methylated cfDNA22.
The liquid biopsy is indeed in its infancy and will require further development for tailoring to specific diseases. Tumor monitoring in the context of tumor evolution will be the next challenge, where a platform capable of detecting emerging mutations with high sensitivity would be required. Additionally, platforms capable of detecting a variety of biomolecules (peptides, cytokines, RNA) will be highly beneficial in assessing tumor response to treatment, as well as advancing personalized clinical interventions.