Many of the most important clues to human health and disease exist at extremely low frequencies within the human body. A handful of cancer-derived DNA fragments, a few lingering viral genomes after an infection, or a rare gene-edited cell among millions of unmodified cells can provide critical insights into early disease onset, disease recurrence, or treatment efficacy. Yet, many conventional nucleic acid detection methods fail to accurately identify and measure these rare molecular targets.1,2
Digital polymerase chain reaction (digital PCR or dPCR) has the potential to change that by precisely quantifying DNA and RNA molecules that would otherwise remain hidden beneath the detection threshold of traditionally used technologies. The most commonly used nucleic acid detection method is quantitative PCR (qPCR), which works by labeling a target molecule with a fluorescent probe and measuring its increase in fluorescence with each amplification cycle. The more molecules present in a sample, the greater the fluorescence or amplification signal at the end of the assay. The caveat is that molecules with extremely low abundance will also have extremely low fluorescence levels compared to more abundant molecules. This makes it difficult for researchers to reliably distinguish amplification signals generated by rare molecules from background noise. As such, many rare molecules, if even captured in a qPCR experiment, often go missed.1,2
Digital PCR (dPCR) circumvents these challenges by providing an absolute quantification of the number of rare molecules in a sample. The process begins by partitioning a sample into thousands to millions of droplets, each serving as its own contained PCR reaction compartment. The idea is that within each droplet, a rare target may or may not be present. dPCR machines then measure the presence or absence of these targets by detecting the presence or absence of a fluorescent signal in the droplet. The output is a binary, yes-or-no fluorescent readout from a single droplet, rather than a fluorescence amplification curve from a bulk reaction. This allows researchers to directly count individual target molecules in each partition, providing absolute quantification of rare molecules in the total sample that would otherwise be impossible to detect or measure.1,2
dPCR, originally developed in 1992 and brought to common use in the late 2000s to 2010s, is already having a major impact in cancer diagnostics.3,4 Using this technology, researchers can detect rare cancer-associated DNA or RNA biomarkers in blood and circulating tumor DNA from solid tumors that slough off into the bloodstream. It can also help researchers identify minimal residual disease (MRD), rare cancer cells that may remain after solid tumor removal that can contribute to relapse. Identifying disease through a minimally invasive blood draw offers a new, convenient avenue for detecting early cancer onset, monitoring disease recurrence, and informing precision oncology treatment strategies.4
dPCR technology applications are not limited to oncology. dPCR may also help improve infectious disease monitoring and antiviral response assessment.5 Using dPCR, researchers can detect just a few viral genomes present in a sample, rare pathogens, and trace microbial contamination in biopharmaceutical processes that could affect drug efficacy and safety.5,6 dPCR applications even extend to the fields of cell and gene therapy, where researchers are using the technology to quantify vector copy number in genetically modified cells, monitor rare engineered cell populations, and detect residual host-cell DNA in biologic products.7
The possibilities for leveraging dPCR to detect rare biological targets continue to expand as dPCR experts find new ways to innovate and advance the technology. Some of these innovations include increased multiplexing capabilities, improved workflow automation, higher throughput, and enhanced sensitivity for detecting ultra-rare targets. Some researchers are even expanding the use of dPCR beyond DNA quantification to include applications in gene expression that measure RNA transcripts and provide insights into cellular activity.8 Together, these advances push the boundaries of the technology, helping researchers and clinicians extract more information from limited samples and broadening the range of biological questions dPCR can help answer.