Historically, five-year survival rates have been used to evaluate cancer therapeutic effectiveness in clinical trials. But time is critical for research — and for patients. Fortunately, there is a promising method for evaluating cancer therapeutic effectiveness that could potentially offer prognostic insights after just one year.

Noninvasive liquid biopsy analysis is improving researchers’ ability to detect clinical responses more rapidly. This approach includes monitoring cell-free DNA (cfDNA) — naked DNA in the bloodstream that has been released from cells — using ultra-sensitive detection tools like Droplet Digital PCR (ddPCR). cfDNA includes both DNA that has been released from normal cells and circulating tumor DNA (ctDNA), which has been released from tumor cells. Measurable residual disease (MRD) testing has already proven effective at predicting relapse and survival in hematological malignancies, and the potential for solid tumor monitoring is just getting started. Researchers and regulators alike are continuing to evaluate the potential predictive value of cfDNA biomarkers in cancer treatment. As scientists establish benchmarks, cfDNA measurements could potentially serve as early surrogate clinical trial endpoints and help critical treatments someday reach patients faster.

cfDNA Analysis is Noninvasive and Precise

ddPCR technology is advancing cancer research.

See How

Before liquid biopsy achieved widespread implementation, most patients with cancer were given a prognosis and monitored for relapse using imaging surveillance and tissue biopsy — procedures that can be time consuming, invasive, expensive, and imprecise. Liquid biopsy potentially offers a superior method for MRD detection and therapeutic monitoring because it can capture information that’s invisible via imaging, and it reduces the number of costly, invasive procedures a patient must undergo.

Accurate cfDNA Analysis Relies on Highly Sensitive Tools

Leveraging ultrasensitive molecular tools is the key to making the most of this extremely promising approach. ddPCR technology provides absolute quantification of nucleic acids with industry-leading sensitivity, accuracy, and precision. Unlike quantitative PCR (qPCR), it does not rely on standard curves, and unlike next-generation sequencing (NGS), it does not require extensive bioinformatic analysis.

ddPCR assays can robustly detect low-abundance nucleic acids in blood samples while also obtaining critical information regarding quantifiable levels of mutated DNA. This allows for the analysis of cfDNA and other key biomarkers to measure the success of therapies and monitor for post-remission relapse early, when interventions might be most effective.

MRD Detection Is Successful in Evaluating Therapies  

Scientists have used cfDNA analysis for years to assess hematological malignancies, which by nature circulate in the blood. Samples are generally taken from blood and examined for tumor-specific biomarkers — usually detectable nucleic acid mutations within cfDNA.

“In this trial, we showed that ddPCR technology is more sensitive and a better predictor…than conventional PCR.” – Jerald Radich, MD

A recent JAMA-published study assessed survival rate in patients with chronic myeloid leukemia (CML) after stopping tyrosine kinase inhibitors. The researchers, including Jerald Radich, MD, found that the level of BCR-ABL1 at time of discontinuation was highly correlated with progression-free survival (Atallah et al. 2020).

“In this trial, we showed that ddPCR technology is more sensitive and a better predictor of treatment-free remission than conventional PCR,” said Radich. “A lot of the patients we tested who had showed up negative with conventional PCR actually showed positive with ddPCR assays.”  The use of ddPCR technology could thus potentially allow physicians to determine which CML patients could safely attempt discontinuation without a fear of disease relapse or progression.

ctDNA Analysis Has Shown Promise in Solid Tumor Monitoring

Another recent study (van der Leest et al. 2021) highlighted ddPCR technology as a promising tool for monitoring ctDNA in patients receiving immune checkpoint inhibitor (ICI) therapy for advanced lung adenocarcinoma. The study measured patients’ ctDNA levels as a proxy of early tumor response to immunotherapy to determine rates of both progression-free and overall survival.

The researchers found that in patients with a PD-L1 tumor proportion score of ≥1%, changes in ctDNA levels were strongly associated with tumor response; 80% of patients with a DCB of ≥26 weeks displayed a >30% decrease in ctDNA levels at 4–6 weeks, which correlated with longer progression-free and overall survival rates. They concluded that the combination of PD-L1 expression and reduction in ctDNA is a stronger tool for monitoring ICI response than PD-L1 expression or change in ctDNA alone.

The paper cited several lung cancer studies that established the use of NGS analysis with a broad panel of biomarkers instead of a single selected marker; however, the high cost of plasma-derived cfDNA NGS was considered too cost-prohibitive for longitudinal monitoring. Therefore, monitoring ctDNA with a ddPCR assay provided these researchers with a method that was as sensitive as or more sensitive than NGS, yet more cost-effective.

Molecular Testing with ddPCR Assays Can Advance Personalized Medicine

As ultra-sensitive tools like ddPCR technology make their way from bench to bedside, they’ll continue to provide precise and absolute information — empowering clinicians to deliver precision oncology care and ensuring patients receive the care that’s best for them. Learn more about ddPCR technology in MRD monitoring.


Atallah et al. (2020). Assessment of outcomes after stopping tyrosine kinase inhibitors among patients with chronic myeloid leukemia: A nonrandomized clinical trial. JAMA Oncol 7, 42–50.

van der Leest et al. (2021). Circulating tumor DNA as a biomarker for monitoring early treatment responses of patients with advanced lung adenocarcinoma receiving immune checkpoint inhibitors. Mol Oncol 15, 2,810–2,922.

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