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Single-Color Digital PCR Method Shows Promise for Blood-Based Cancer Monitoring


NEW YORK (GenomeWeb) – In a recent proof-of-concept study, clinical researchers from Stanford University have described a liquid biopsy approach — using a unique single-color PCR method — which could offer a relatively simple and cost-effective platform for blood-based monitoring of cancer patients.

According to investigators, who reported on the method in the Journal of Molecular Diagnostics, single-color droplet digital PCR using Bio-Rad Technologies' platform requires only a fraction of a tube of blood and can detect as few as three mutation-bearing molecules in a single reaction.

Most cancer disease monitoring is currently limited to blood-based proteomic assays with limited accuracy, and to whole-body imaging, which can be costly, complex, and time-consuming.

As a result, the clinical field has embraced the potential of liquid biopsy, or blood-based cancer mutation tests, to serve as a more feasible and hopefully more sensitive alternative.

The Stanford team initially developed and publicized its single-color dPCR method in 2014. In short, the approach uses a double-stranded DNA intercalator dye (in this case EvaGreen), and paired allele-specific DNA primer sets to determine an absolute count of both mutated and wild-type DNA molecules present in the sample.

The interaction between the single-color dye and the PCR amplicons in droplets generated by Bio-Rad's system yields fluorescent signals that reflect the size of the amplicon product, i.e. its wild-type or mutated status.

Hanlee Ji, the study's corresponding author, said this week that as they improved the method over time, he and his colleagues saw the opportunity to apply it to circulating tumor DNA, which presents significant challenges to testing due to its highly fragmented nature, and low concentration relative to the total background of circulating nucleic acids.

In their study, the team published results from a variety of experiments with the approach, including testing primer sets that detect a single variant allele versus others that quantitate both wild-type and variant alleles, as well as integrating locked nucleic acids into the design.

To demonstrate proof of concept for the approach in ctDNA specifically, the team used colorectal cancer as a model, first designing a series of wild-type and mutation-specific assays targeted at variants that were present in the cancers of six patients — five who were previously diagnosed with colorectal cancer and one with cholangiocarcinoma.

First, the researchers designed an experiment to try and demonstrate single-base pair specificity for their method — something other commercially available probe chemistries are known to struggle with.

Using two separate paired-allele assays — one for KRAS G12D and one for the KRAS G12V mutation — the investigators tested DNA mixtures derived from two colorectal cancer cell lines, comparing the results to those obtained with a commercially available TaqMan probe.

According to the authors, the results confirm that their single-color approach can quantitatively distinguish between different variants with single-nucleotide specificity.

Ji and his colleagues then demonstrated that the single-color method could detect mutations at 0.1 percent allelic fraction. This doesn't mean that the test is limited to this frequency though, he explained.

"The way to think about it is that it has to do with input," Ji said. "If you have 1,000 genome equivalents and the allelic fraction you are describing is 0.001 percent – that's impossible. You can't have a variant that exists at a lower fraction than 1 in 1000 in that context."

"For us, the 0.1 percent number represents up to 1,000 genome equivalents. To get to 0.01 the amount of material has to be an order of magnitude greater when other groups are describing that. But we could potentially do that, too, in the same way."

After generating customized mutation detection assays for the six patients in the study, the team applied them to the six patient samples. In three patients, the assays successfully detected mutated DNA molecules, and in one, three different mutations could be distinguished.

The other three patients who were negative for circulating mutations were all undergoing active treatment at the time of sample collection, potentially explaining the failure of the approach to detect cancer DNA in their blood.

According to Ji and his coauthors, the single-color droplet PCR approach can be customized for a variety of different mutations. In clinical implementation, this would mean that patients in need of monitoring would have to be genotyped first, in order to determine which mutations to use to create primer sets for ongoing blood-based testing.

This approach is one that other groups have also been investigating in the context of cancer monitoring. For example, researcher from Johns Hopkins have published promising results using tissue sequencing results to design blood-based assays for patient monitoring, and others are now exploring a similar approach in breast cancer.

Some other groups are also hoping to advance next-gen sequencing based methods that would not require upfront knowledge of a patient's genotype. However, NGS approaches suffer in comparison to Ji and colleagues' single-color PCR in regard to simplicity and ease of use.

The study's lead author Christina Wood Bouwens of the Stanford Genome Technology Center highlighted in a statement that the single-color PCR approach is "simple enough to set up and analyze without extensive training … making it highly accessible to any laboratory."

Meanwhile, though a variety of PCR methods are being applied to liquid biopsy, the Stanford group believes that their results demonstrate important advantages over other chemistries, including the demonstrated single-base specificity, as well as relative ease in designing and testing probes and the ability to avoid specialized probe reagents.

"If you are talking about scaling this up, and you want to target the spectrum of mutation in each individual patient, that would be extraordinarily difficult with TaqMan," Ji said. "But with our system … you can use basic oligos to do this for anyone regardless of what their mutations are."

"Some of the mutations from the patients in the study represented things that you might not commonly find, but we had no trouble designing the assays," he added.

Moving forward, Ji said that he and his colleagues are seeking to improve the scalability of designing assays with highly parallel evaluation of primer candidates across tens of thousands of cancer mutations. If successful, this scalability would improve their ability to generate customized mutation primers.

He and his colleagues at Stanford plan to implement the approach in a number of longitudinal patient monitoring studies. Commercialization could also be a possibility, but so far there has not been a company interested, Ji added.