Here, we present a protocol to detect tumor somatic mutations in circulating DNA present in patient biological fluids (biofluids). Our droplet digital polymerase chain reaction (dPCR)-based method enables quantification of the tumor mutation allelic frequency (MAF), facilitating a minimally invasive complement to diagnosis and temporal monitoring of tumor response.
Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular sub-classification and temporal monitoring of tumor response to therapy. Here, we describe our dPCR-based method for the detection of tumor somatic mutations in cell free DNA (cfDNA), readily available in patient biofluids. Although limited in the number of mutations that can be tested for in each assay, this method provides a high level of sensitivity and specificity. Monitoring of mutation abundance, as calculated by MAF, allows for the evaluation of tumor response to therapy, thereby providing a much-needed supplement to radiographic imaging.
Due to limitations in the availability of tumor tissue for molecular analyses, there is a need for the development of highly sensitive methods capable of detecting tumor somatic mutations in patient biofluids, including plasma, serum and cerebrospinal fluid (CSF). For example, pediatric diffuse midline gliomas (DMGs) present a challenge due to their neuroanatomical location. Over the past decade, molecular profiling of DMG tissue specimens has uncovered driver mutations in this tumor type1 and has revealed spatial and temporal heterogeneity of mutations, making biopsy necessary for characterizing a patient within a disease subgroup and promoting molecularly-targeted therapies2. As such, clinical trials advocate for integrating surgical biopsies for tumor molecular profiling at upfront diagnosis3,4,5,6. During treatment, monitoring of therapeutic response in DMGs is limited to MRI, which lacks sensitivity to detect small changes or tumor genomic evolution. MRI is also prone to detect pseudoprogression, transient inflammation at the site of the tumor that mimics true progression on imaging and may misinform interpretation of tumor response7. Thus, DMGs represent a tumor type with a high need for an alternative, minimally invasive means of detecting tumor mutations and monitoring clinical response. In order to address these needs, we developed and optimized a protocol for detecting, and quantifying the allelic frequency of, tumor mutations in cfDNA from plasma, serum and CSF of children with midline gliomas8. Given that childhood DMGs often (>80%) harbor a somatic lysine-to-methionine mutation at position 27 of histone variant H3.1 (H3.1K27M, 20% of cases) or H3.3 (H3.3K27M, 60% of cases)1, these and other mutations characteristic of DMGs (i.e., ACVR1, PIK3R1) were targeted for mutant allele quantification using cfDNA8. This assay can be tailored to detect hotspot mutations in other tumor types using sequence-specific primers and probes. The versatility of this approach makes it applicable to a variety of cancers which would benefit from the integration of cfDNA-based diagnostic tools and therapeutic monitoring.
To sensitively detect low allelic frequency mutations in cfDNA, we employ a droplet digital PCR (dPCR)-based approach. In this method, the PCR reaction mixture is partitioned into a theoretical maximum of 10 million droplets using the dPCR platform (e.g., RainDance), with 7-9 million droplets per PCR well typically seen experimentally. Due to the high degree of sample partitioning, at most only one to two DNA molecules can be present in each droplet. PCR amplification and sequence-specific fluorescent probe hybridization can occur in each droplet, such that millions of reactions take place. This maximizes the sensitivity and enables detection of rare mutant alleles, which might otherwise go undetected against a background of wildtype DNA. The utilization of locked nucleic acid (LNA) probes enhances the specificity of the assay by restricting mismatch hybridization and supporting accurate mutation detection9,10,11. Here, we describe our methods of sample processing, cfDNA extraction, preamplification of target alleles, dPCR and data analysis.
All methods described here have been approved by the Institutional Review Board of the University of California San Francisco (San Francisco, CA; IRB #14-13895) and the Children's National Health System (Washington, D.C.; IRB #1339). Specimens were collected and studied after obtaining informed consent from the patient or patient's guardian.
1. Consenting Patients Under IRB Protocol for Collection and Storage of Biological Specimens
2. Blood Collection and Separation of Plasma or Serum
3. CSF Collection and Processing
4. Extraction of cfDNA from Liquid Specimens
5. Vacuum Concentration of cfDNA
6. Design and Preparation of Primers and Probes
7. Selection of Positive Controls
8. Preamplification of Target Alleles
NOTE: Preamplification protocol is as per Jackson et al., 201613.
9. Detection and Quantification of Target DNA Using dPCR
10. Data Analysis
Figure 1 shows representative results for successful detection of H3F3A p.K27M mutation in preamplified plasma (top left panel) and CSF (top right panel) cfDNA from two children with DMG. cfDNA samples were analyzed in replicate but only one representative graph is shown for each sample type. The dPCR plots show successful droplet generation, with 7-9 million droplets per PCR well (most of which are negative droplets that do not contain target DNA). A minimum of 7 million droplets per PCR well indicates a successful dropletization, while fewer than 7 million indicate failure of the assay, in which case the user should not proceed with data analysis. Figure 1 shows a clear separation between mutant and wildtype clusters along the x and y-axes, respectively. Robust wildtype clusters indicate that the cfDNA extraction was successful because template DNA is present. Mutant clusters show a MAF of 1.60% and 39.92% for the plasma and CSF samples, respectively, demonstrating positive detection of the mutation. For these patients, dPCR results are in accordance with tumor mutation status, as confirmed by genomic analysis of biopsy tumor tissue8. The negative control (bottom left panel) shows 0 mutant and 0 wildtype droplets, indicating that there was no contamination of the PCR reaction mixture. The positive control tumor tissue gDNA (bottom right panel) shows the mutation being detected at the expected allelic frequency for the particular tumor sample selected.
In Figure 2, representative results are shown for unsuccessful detection of the mutation of interest, H3F3A p.K27M, in plasma cfDNA from a child with DMG. Mutation status was confirmed by genomic analysis of tumor tissue8. Representative results from two replicate PCR wells are shown (top panels). The total number of droplets, including negative droplets, is between 7-9 million per PCR well, indicating successful dropletization. The wildtype clusters, plotted along the y-axis, show approximately 7-8,000 wildtype droplets per PCR well for the plasma cfDNA, indicating successful cfDNA extraction (as there is target wildtype DNA in the sample). However, 0 mutant droplets are detected in the plasma sample. The bottom left panel shows negative control (MB H2O) with no wildtype or mutant droplets; and the bottom right panel shows the positive control preamplified tumor tissue gDNA (0.025 ng) with positive mutation detection. As shown in this figure, the absence of mutation detection in plasma may not necessarily mean the patient is wildtype for the mutation of interest, as false negatives do occur8. In some cases, when the mutation is missed in the plasma collected at upfront biopsy, it is detected in the plasma obtained from the same patient at a later time point8.
Figure 1: Successful detection of H3F3A p.K27M mutation in preamplified plasma and CSF cfDNA from children with midline gliomas. Please click here to view a larger version of this figure.
Figure 2: False negative results obtained from analysis of a preamplified plasma cfDNA sample from a patient known to harbor the mutation of interest, H3F3A p.K27M, in the tumor. Please click here to view a larger version of this figure.
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.
The authors have nothing to disclose.
The authors would like to acknowledge the generosity of all patients and their families. This work was supported by funding from the Smashing Walnuts Foundation (Middleburg, VA), the V Foundation (Atlanta, GA), The Gabriella Miller Kids First Data Resource Center, Clinical and Translational Science Institute at Children's National (5UL1TR001876-03), Musella Foundation (Hewlett, NY), Matthew Larson Foundation (Franklin Lake, NJ), The Lilabean Foundation for Pediatric Brain Cancer Research (Silver Spring, MD), the Childhood Brain Tumor Foundation (Germantown, MD), the Children's Brain Tumor Tissue Consortium (Philadelphia, PA), and Rally Foundation for Childhood Cancer Research (Atlanta, GA).
10mM Tris-HCl, 0.1mM EDTA DNA Suspension Buffer (pH 8.0) | Teknova | T0227 | |
BD Vacutainer K2-EDTA 7.2mg Blood Collection Tubes (10mL) | Becton Dickinson Diagnostics | 367525 | For plasma collection |
BD Vacutainer Plastic Serum tube with Red BD Hemogard Closure (10mL) | Becton Dickinson Diagnostics | 367895 | For serum collection |
Bleach | General Lab Supplier | ||
Buffer ATL | Qiagen | 19076 | |
Cell-Free DNA Blood Collection Tubes | Streck | 218961 | cfDNA blood collection tubes (optional) |
CentriVap Concentrator | Labconco | 7810010 | |
Forward Primer | Integrated DNA Technologies, Inc. | Custom design | |
MiniAmp Thermal Cycler | Thermofisher Scientific | A37834 | |
Molecular Biology Grade Absolute Ethanol (200 proof) | General Lab Supplier | ||
Mutant Probe | Integrated DNA Technologies, Inc. | Custom design | |
PAXgene Blood ccfDNA tubes | PreAnalytiX | 768115 | cfDNA blood collection tubes (optional) |
PCR 8 well strip tube caps | VWR | 10011-786 | |
PCR 8 well strip tubes | Axygen | PCR-0208-C | |
Pipette (p20, p200, p1000) | General Lab Supplier | ||
Pipette filter tips (p20, p200, p1000) | General Lab Supplier | ||
Q5 Hot Start High-Fidelity 2X Master Mix | New England Biolabs Inc | M0494S | |
QIAamp Circulating Nucleic Acid HandBook | Qiagen | cfDNA extraction kit handbook (2013 edition) | |
QIAamp Circulating Nucleic Acid Kit | Qiagen | 55114 | cfDNA extraction kit (Protocol Step 4) |
QIAamp MinElute Virus Spin Kit | Qiagen | 57704 | Optional kit for DNA extraction from small (< or =200µL) sample volumes |
Qiavac 24 Plus | Qiagen | 19413 | For use with QIAamp Circulating Nucleic Acids kit |
Raindance Consumable Kit | Bio-Rad | 20-04411 | Contains droplet-generating instrument chips, quantification instrument chips, PCR strip caps including high-speed caps, and droplet stabilizing oil |
Raindance Sense Instrument | Bio-Rad | Quantification instrument (used in Protocol Step 9) | |
Raindance Source Instrument | Bio-Rad | Droplet-generating instrument (used in Protocol Step 9) | |
RainDrop Analyst II Software | RainDance Technologies | Analyst software used for Data Analysis (Protocol Step 10) | |
Refrigerated Vapor Trap | Savant | RVT5105-115 | |
Reverse Primer | Integrated DNA Technologies, Inc. | Custom design | |
Smartblock 2mL | Eppendorf | 05 412 506 | |
TaqMan Genotyping Master Mix | Thermofisher Scientific | 4371353 | |
Thermomixer C | Eppendorf | 14 285 562PM | |
WT Probe | Integrated DNA Technologies, Inc. | Custom design |