Patient-Specific ddPCR Monitors ctDNA in Advanced Head and Neck Cancer

Source: Frontiers in Oncology, written by Luca Leonardo Amodio; Lea Grossmann; Stefanie Gächter; Marta Nowak; Myriam Schaufelberger; Christina Mennicke; Sepehr Rahmani-Khajouei; Martin Zoche; Holger Moch; Achim Weber; Ralph Fritsch; Tomas Brezina; Saskia Hussung (October 30, 2026). AI-generated summary by biochip.com, published November 1, 2026. Not independently reviewed.

A team at University Hospital Zurich tested personalized droplet digital PCR assays to track tumor DNA in the blood of people with recurrent or metastatic head and neck cancer. The assays tracked genetic changes first identified in each patient’s tumor tissue. In this nine-patient pilot, changes in circulating tumor DNA matched imaging results in five of six patients who had serial blood samples. The findings show that this focused monitoring approach is technically feasible, but do not establish that it can predict outcomes.

Building an assay for each patient

Circulating tumor DNA, or ctDNA, is DNA shed by a tumor into the bloodstream. Because blood can be collected repeatedly, measuring ctDNA may offer a less invasive way to follow changes in disease between imaging scans. Imaging remains essential, but inflammation and other treatment-related tissue changes can make results harder to interpret, particularly during immunotherapy.

The team used tumor genomic profiles generated through routine care to select genetic variants for personalized tests. They developed 16 single-target assays and combined them into 10 patient-specific configurations, each tracking one or more variants. The tests used droplet digital PCR, or ddPCR, a method that separates a DNA sample into many tiny reaction compartments. Like sorting a handful of marked beads among many small boxes, this partitioning helps count rare, tumor-linked DNA molecules against a much larger background of DNA.

The assays ran on the Naica Crystal Digital PCR system. Researchers analyzed 21 plasma samples from nine patients, and all samples produced technically valid measurements. Blood collection took place before or during treatment at variable times, rather than on a set research schedule. Treatment decisions were not based on the ctDNA results.

What the blood tests showed

Before treatment, samples were available for seven patients. Three of those patients, or 42.9%, had detectable ctDNA. Across all sampling time points, six of the nine patients had ctDNA detected at least once.

Six patients had serial samples that allowed the team to compare ctDNA trends with radiologic assessments. The two measures agreed descriptively in five cases. The one patient whose ctDNA increased developed progressive disease; four patients with decreasing or stable ctDNA had partial response or stable disease. The remaining patient had a mixed radiologic response.

What remains uncertain

The patient with rising ctDNA had shorter observed progression-free and overall survival than the five patients whose ctDNA decreased or remained stable. But that comparison rests on a single patient in the rising-ctDNA group, so it cannot establish that ctDNA trends predict survival. The authors characterize this observation as hypothesis-generating.

The pilot supports the feasibility of using tumor-informed ddPCR for repeated ctDNA measurements in this cancer setting. It does not compare the method’s clinical usefulness or cost with other approaches, and the small group and nonstandardized sampling schedule limit conclusions about how well the results would guide treatment. The next step is prospective evaluation to test whether this personalized monitoring adds useful information alongside imaging.

Topics: Cancer

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