Digital PCR and Liquid Biopsy



Liquid biopsy is a noninvasive method used for the diagnosis and monitoring of disease states, including cancer. Instead of physically taking a biopsy of the affected tissue, cell-free DNA (cfDNA), circulating tumor DNA (ctDNA, a subset of cfDNA present only in tumors), or cancer cells in suspension (also known as circulating tumor cells, CTCs) are collected from blood or other fluids.

This page reviews the use of Droplet Digital™ PCR (ddPCR™) for liquid biopsies in the areas of cancer diagnosis, monitoring, evaluation of treatment modalities, and testing for reoccurrence after remission. Diabetes and organ transplantation monitoring are discussed to demonstrate other emerging uses for liquid biopsy.

What Are Liquid Biopsies?

Liquid biopsies are noninvasive tests that detect fragments of DNA or cells in blood or, occasionally, other bodily fluids. Cell-free DNA (cfDNA) refers to segments of DNA that are mainly derived from apoptotic and necrotic cells. The cfDNA circulating in the blood can be used for testing a range of diseases including cancer, diabetes, and even myocardial infarction, as well as monitoring transplanted organs in their recipients. In the case of cancer, cfDNA is often referred to as circulating tumor DNA, or ctDNA. Since tumors shed cells, circulating tumor cells (CTCs) can also be used for the detection and monitoring of cancer.

ddPCR Provides the Level of Sensitivity Required for Liquid Biopsy

ddPCR is a powerful technology that provides absolute quantification of nucleic acids with a high degree of sensitivity and precision. For more detailed information on the technique, see the ddPCR technology page and the QX200™ Droplet Digital™ PCR System product page.

In blood, the cfDNA, ctDNA, and CTCs of interest are present at low levels and found in a complex background of other components. Additionally, circulating DNA is highly fragmented, which further reduces the concentration of intact target sequence. The recent advent of more sensitive screening techniques, such as ddPCR, has permitted the detection and quantification of low abundance targets in shorter times without requiring large numbers of replicates. This has established ddPCR as a tool of choice for liquid biopsies.

Use of Liquid Biopsy for Cancer Diagnosis and Monitoring

One area of active research and development for liquid biopsy is the field of oncology. Cancer provides some unique challenges for detection and monitoring because of the number of genotype changes involved and tumor heterogeneity. Liquid biopsy is minimally intrusive compared with other methods, such as solid tissue biopsy. Samples of blood, sputum, and other fluids can be collected without the significant risk of causing harm when trying to reach affected organs that are difficult to access. Liquid biopsy also facilitates the following:

  • Monitor and determine treatment protocols — liquid biopsies can monitor effectiveness of a treatment protocol, optimize a regimen, determine whether changes in treatment regimen are beneficial, and detect if a treatment protocol loses its efficacy
  • Follow any changes in a tumor — many tumors change over time; the ability to monitor changes can provide information for changes in treatment
  • Screen for reoccurrence — screening patients in remission can detect new tumor growth before physical signs are apparent, whether a tumor is in the same location or has metastasized
  • Routinely screen for high risk patients — in cases where certain genotypes have been identified in individuals, liquid biopsies can provide early detection of cancer before there are any overt symptoms or until the cancer is detectable by conventional imaging

ddPCR in Cancer Detection and Monitoring

ddPCR has been established as a fast and accurate tool for detecting and monitoring an increasing number of different types of cancers. Several studies are described below to highlight some of the uses of ddPCR and its high level of sensitivity.

About 50% of cutaneous melanomas have a valine-to-glutamic-acid mutation in the B-Raf protooncogene serine/threonine kinase at codon 600 (BRAFV600E) and are treated with BRAF inhibitors. The level of circulating cfDNA containing the mutation is very low (<0.01% of wild-type cfDNA). ddPCR detected BRAFV600E at a fractional abundance of 0.005%, and was used to demonstrate a correlation between levels of BRAFV600E in tumors and in cfDNA (Sanmamed et al. 2015). Furthermore, in patients being treated with BRAF inhibitors, decreasing levels of BRAFV600E ctDNA paralleled destruction of tumors and increasing levels of BRAFV600E ctDNA revealed the development of a resistance to the treatment. This study demonstrated that ddPCR is an efficient tool for identifying the patients who would be responsive to BRAF inhibitor treatment, and then monitoring their treatment.

CTCs were used for a comparison of ddPCR and competitive allele-specific PCR (castPCR) in the detection of the BRAFV600E and BRAFV600K mutations (Reid et al. 2014). This study demonstrates that ddPCR can be used for detecting mutations in circulating cells with a much better sensitivity than castPCR (200-fold improvement).

Non-small cell lung cancer
Non-small cell lung cancer (NSCLC) is the most common form of lung cancer. Many NSCLCs have activating epidermal growth factor receptor (EGFR) mutations and are responsive to tyrosine kinase inhibitors. There are many different EGFR-activating mutations, and after a period of treatment, the majority of NSCLCs become refractory to kinase inhibition. The most common reason for the development of resistance to treatment is a secondary EGFRT790M mutation.

Therefore, in addition to identifying EGFR mutations, there is a need to survey the appearance of secondary mutations during treatment. Use of ddPCR for analysis of ctDNA was demonstrated to increase clinical sensitivity for EGFR-activating mutations by 80% (Zhu et al. 2015). Additionally, ddPCR permitted low-level detection of the secondary EGFRT790M mutation (Oxnard et al. 2014, Watanabe et al. 2015, Zhang et al. 2015) before regrowth of a tumor due to a lack of response to the tyrosine kinase inhibitors.

Breast cancer
Since there is a significant relapse rate after surgery for breast cancer, further treatment such as radiation and/or chemotherapy is frequently prescribed to destroy any residual tumor cells. Digital PCR was used to analyze ctDNA pre- and post-surgery, and ctDNA was detected in several post-surgery samples (Beaver et al. 2014). This suggests that micro metastases were still present in these samples and that ddPCR can be used to detect residual solid tumors (Siravegna and Bardelli 2014). It may, therefore, be possible to detect low levels of ctDNA in order to predict the risk of recurrence after surgery and to guide decisions about the type of post-surgery care needed.

Detection and Monitoring of Type 1 Diabetes

In type 1 diabetes, an autoimmune reaction destroys β cells in the pancreas, resulting in reduced levels of circulating insulin. It has been suggested that progressive destruction of the β cells happens over a period of time and that there are no obvious symptoms until the majority of the β cells have been destroyed.

Cell-free β cell–derived unmethylated insulin DNA is thought to be released from β cells that have died. A study using ddPCR showed that the average levels of circulating β cell–derived unmethylated insulin DNA were higher in at-risk subjects who progressed to symptomatic diabetes than in controls (Herold et al. 2015). Additionally, the data suggested that the death of β cells can be episodic. The current testing guidelines for autoantibodies every 6 months or annually may miss periods of β cell death in some patients, not giving an accurate picture of the progression of the disease. The specificity of ddPCR for detecting β cell death (Usmani-Brown et al. 2014) may provide earlier diagnosis in high-risk patients, allowing treatment at early stages of the disease and slowing its progression.

Monitoring after Organ Transplantation

After organ transplantation, immunosuppressive drugs are used to reduce the risk of rejection. These drugs often have serious side effects causing damage to the body. Patients are monitored for both organ rejection and the deleterious effects of immunosuppression. Early detection of rejection and damage can improve quality of life and survival. Currently, testing includes biopsy of the transplanted organ and monitoring of tissue damage using markers such as creatinine kinase. Neither of these approaches can detect early damage.

Analysis of cfDNA levels from both the recipient and the donor organ can provide a more sensitive monitoring system, providing much earlier identification of problems and tailoring more effective drug regimens. Beck and coworkers (2013) combined microarrays and massive parallel sequencing with ddPCR for screening after transplantation. For ddPCR, single nucleotide polymorphisms (SNPs) from donor and recipient were used to develop an assay for monitoring the patient. The aim of the assay was to have homozygous SNPs for the recipient, and homozygous SNPs for the donor, with these SNPs being heterologous between the recipient and the donor, thereby providing personalized biomarkers. The assay was validated and the authors state that "A novel cost-effective test based on automated ddPCR with adequate same-day turnaround has been developed and used for the first time."

MicroRNA — Potential for Liquid Biopsy

MicroRNAs (miRNAs) have been associated with a range of diseases including cancer. Since miRNAs are involved in many fundamental cell processes, it is not surprising that they are being implicated in a wide range of diseases. ddPCR has been used to demonstrate that miRNAs can be effective in the diagnosis of lung cancer using blood (Ma et al. 2013) or sputum (Li et al. 2014). miRNAs may provide another set of biomarkers for disease detection and monitoring.


The use of liquid biopsy is rapidly revolutionizing the detection and monitoring of cancer and an increasing number of diseases. The ability to detect a disease prior to the appearance of symptoms and start treatment at an early stage can reduce or slow damage and improve quality of life. Furthermore, monitoring during treatment will permit optimization of disease management at the individual level, providing effective treatment while minimizing side effects.

The unmatched sensitivity of ddPCR for detecting low abundance targets in complex backgrounds will play a major role in the use of liquid biopsies. This technology provides fast detection and accurate quantification of disease markers and accomplishes this with a minimal amount of discomfort for the patients.


Beaver JA et al. (2014). Detection of cancer DNA in plasma of patients with early-stage breast cancer. Clin Cancer Res 20, 2643–2650. PMID: 24504125

Beck J et al. (2013). Digital droplet PCR for rapid quantification of donor DNA in the circulation of transplant recipients as a potential universal biomarker of graft injury. Clin Chem 59, 1732–1741. PMID: 24061615

Herold KC et al. (2015). β Cell death and dysfunction during type 1 diabetes development in at-risk individuals. J Clin Invest 125, 1163–1173. PMID: 25642774

Li N et al. (2014). Digital PCR quantification of miRNAs in sputum for diagnosis of lung cancer. J Cancer Res Clin Oncol 140, 145–150. PMID: 24281335

Ma J et al. (2013). Quantification of plasma miRNAs by digital PCR for cancer diagnosis. Biomark Insights 8, 127–136. PMID: 24277982

Oxnard GR et al. (2014). Noninvasive detection of response and resistance in EGFR-mutant lung cancer using quantitative next-generation genotyping of cell-free plasma DNA. Clin Cancer Res 20, 1698–1705. PMID: 24429876

Reid AL et al. (2014). Detection of BRAF-V600E and V600K in melanoma circulating tumour cells by droplet digital PCR. Clin Biochem epub ahead of print. PMID: 25523300

Sanmamed MF et al. (2015). Quantitative cell-free circulating BRAFV600E mutation analysis by use of droplet digital PCR in the follow-up of patients with melanoma being treated with BRAF inhibitors. Clin Chem 61, 297–304. PMID: 25411185

Siravegna G and Bardelli A (2014). Minimal residual disease in breast cancer: in blood veritas. Clin Cancer Res 20, 2505–2507. PMID: 24658155

Usmani-Brown S et al. (2014). Analysis of β-cell death in type 1 diabetes by Droplet Digital PCR. Endocrinology 155, 3694–3698. PMID: 25004096

Watanabe M et al. (2015). Ultra-sensitive detection of the pretreatment EGFR T790M mutation in non-small cell lung cancer patients with an EGFR-activating mutation using droplet digital PCR. Clin Cancer Res epub ahead of print. PMID: 25882755

Zhang B et al. (2015). Comparison of droplet digital PCR and conventional quantitative PCR for measuring EGFR gene mutation. Exp Ther Med 9, 1383–1388. PMID: 25780439

Zhu G et al. (2015). Highly sensitive Droplet Digital PCR method for detection of EGFR-activating mutations in plasma cell-free DNA from patients with advanced non-small cell lung cancer. J Mol Diagn 17, 265–272. PMID: 25769900

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