Following the Molecular Fingerprints of Cancer with Digital PCR

For clinical researchers and scientists, the value of a biomarker depends on its accurate measurement and trackability over time. Digital PCR (dPCR) delivers both. At Tata Medical Center, Dr. Mayur Parihar, Senior Consultant in Hematology and Cytogenetics and Clinical Research Scientist at the Tata Translational Cancer Research Center, recognizes the potential of dPCR in monitoring genomic biomarkers throughout the course of diseases like cancer and using that data to guide treatments. Dr. Parihar and Dr. Poonam Das, Senior Scientific Officer at Tata Medical Center, shared how the sensitivity of dPCR is transforming cancer research through improved disease analysis and helping them address key research questions.

Qualitative and quantitative measurement in a single assay

dPCR partitions each reaction into many independent microreactions and reads out positives and negatives. Because targets distribute randomly across partitions, counts are converted to absolute copies using Poisson statistics. This offers both a yes/no call and a precise quantity without standard curves, improving accuracy at very low target levels.¹

dPCR is transforming research into cancer care by enabling the rapid and highly sensitive detection of genetic mutations and biomarkers, allowing for real-time tumor monitoring, potential early diagnosis, and informed treatment decisions. “We’ve been looking for more sensitive platforms that could help us track genomic abnormalities during the course of treatment. dPCR has provided a solution for us to analyze or track a specific genomic marker more objectively, whether it’s a transcript or a mutation, once it has been identified,” says Dr. Parihar. “Another advantage of dPCR is that it helps us to quantitatively measure a specific genomic marker.”

Longitudinal tracking that reveals relapse trends earlier

Reporting absolute copies per microliter makes it possible to plot true molecular trajectories rather than relying on isolated snapshots. In chronic myeloid leukemia (CML), dPCR has been widely explored for quantifying BCR-ABL1 target for analyzing response to therapies, MRD detection, and identifying potential candidates for treatment discontinuation.²

Solid-tumor data points in the same way. Longitudinal monitoring of circulating tumor DNA (ctDNA) using highly sensitive PCR methods can detect molecular recurrence months before radiologic relapse. For example, in breast cancer, emergent ESR1 mutations can be tracked during endocrine therapy, where residual ctDNA after curative treatment has the potential to predict early relapse.³

“dPCR lets us track genomic markers objectively over time,” says Dr. Parihar. “When we see a clear upward trend in the transcript, it can indicate an impending relapse, which helps us intervene much earlier, before overt disease returns.”

Sensitivity for rare alleles and low-copy transcripts

dPCR excels even when molecular targets are scarce. By partitioning a reaction into thousands of independent chambers, the technique isolates rare alleles or transcripts, making even a few copies detectable against background noise. This design achieves a level of precision that is particularly valuable in minimal residual disease (MRD) detection and in cancers where only trace amounts of ctDNA remain after treatment.

A recent study evaluating dPCR for BCR-ABL1 quantification in CML demonstrated that the method could reliably detect transcript levels far below conventional qPCR thresholds. The study confirmed that these ultra-low measurements improve assessment of deep molecular response and help potentially refine decisions around treatment-free remission.⁴

Similarly, multiple studies have demonstrated that dPCR has higher sensitivity than qPCR in detecting rare mutations in ctDNA from solid tumors. In one recent study, multiplex dPCR combined with melting-curve analysis improved ctDNA detection efficiency, lowered the limit of detection to below 0.2% variant allele frequency, and accurately genotyped KRAS mutations in pancreatic cancer, detecting mutations in 82.3% of patients with liver or lung metastases. These findings support dPCR’s role as an early warning tool for minimal disease burden well before clinical relapse is evident.⁵ From a research laboratory perspective, the advantages extend beyond analytical sensitivity. “We can work with very small amounts of DNA or RNA and still get consistent, reliable results. That’s critical when you’re testing samples from patients in remission, where the molecular signal is extremely low,” says Dr. Poonam Das adds.

Detecting early molecular changes at the stem-cell level

As mentioned above, one of the most valuable features of dPCR in cancer analysis is its ability to detect subtle molecular changes that arise before potential clinical relapse. These early fluctuations often originate at the stem-cell or progenitor level, where malignant clones first re-emerge. Because dPCR quantifies transcripts with high precision, it can identify these small increases long before they manifest morphologically or clinically.

“Especially when you’re looking at transcripts, some of these changes start at a stem-cell level,” explains Dr. Parihar. “You can sometimes see them even in non-malignant cells. That’s why following the trend quantitatively is so important, as it tells us when the signal is becoming significant and may indicate an overt relapse.”

Conclusions

As research into cancer diagnostics moves toward greater precision and personalization, dPCR is emerging as a pivotal tool that bridges research and routine clinical care. Its ability to combine qualitative detection with absolute quantification enables laboratories to move beyond static measurements toward potential dynamic, data-driven monitoring. By capturing early molecular changes, sometimes at the stem cell level, dPCR may be able to help the care team anticipate relapse and intervene when disease burden is still minimal. Importantly, newer multiplexing strategies in dPCR, including multi-channel readouts and melt-curve-based target discrimination, address the traditional limitation of detecting only one target per color, allowing several clinically relevant variants to be tracked in the same reaction and from the same small sample. The result enables a more sensitive, objective, and actionable approach to molecular follow-up, one that brings precision oncology research closer to potential clinical practice. For more information on how digital PCR can enhance your oncology research, click here.

References:

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