In Bio-Rad’s droplet digital PCR workflow, reaction mixes are partitioned into droplets where a PCR reaction takes place. A reporter dye will emit a fluorescent signal to be read in a droplet if the target sequence is amplified there. Image: Bio-Rad Finding treatments for advanced stage cancer isn’t easy. Therefore, early detection methods are paramount in the fight against the disease. Motivated by the opportunity to intervene as early as possible in the course of cancer, Dr. Muneesh Tewari, a Univ. of Michigan researcher, has been studying the diagnostic potential of blood-based biomarkers. In particular, Dr. Tewari has been researching microRNA (miRNA) as an early biomarker for prostate cancer.

Tracking cancer with miRNA
miRNAs regulate the expression of thousands of genes in both normal and pathophysiological processes, including cancer, making them a hot area of biological research. Numerous studies have shown that these small, non-coding RNAs have great potential as biomarkers, as researchers are able to monitor them in samples from tissues, cells and body fluids—such as urine, cerebrospinal fluid, blood, plasma, sputum and serum.

The value of microRNA lies in the fact that unlike DNA, it’s highly responsive to environmental changes—meaning that changes in disease physiology will be reflected in miRNA levels. This may allow oncologists to track the progress of the cancer without the use of invasive CAT or PET Scans. Other blood-based biomarkers have been studied for cancer detection such as prostate-specific antigen (PSA) prostate cancer or CA-125, which is linked to ovarian cancer. Dr. Tewari believes that accurate diagnosis will depend on a combination of blood biomarker detection methods.

Quantification of low levels of miRNA using Droplet Digital PCR
Dr. Tewari recognized the potential of microRNA as an early biomarker for prostate cancer detection, and set out to test its feasibility as a diagnostic tool. During his time at the Fred Hutchinson Cancer Research Center, he found that microRNAs are released from tumors into the bloodstream in a very stable form allowing them to be detected. However, some of the microRNAs associated with cancer cells are in relatively low abundance.

The most common way to detect microRNA in blood samples is quantitative real-time PCR (qPCR). However, researchers have found that qPCR measurements of miRNAs in serum or plasma can’t be reliably compared from one day to the next, undermining the use of miRNAs as blood-based biomarkers. Therefore, Dr. Tewari’s laboratory faced the challenge of accurately and precisely quantifying microRNA for confident diagnosis of the disease and tracking response to therapy.

For years, Dr. Tewari was interested in using the digital PCR (dPCR) method to quantify miRNAs. Digital PCR is a nucleic acid molecule counting method that works by partitioning the sample into hundreds or thousands of reactions so that it can count the presence or absence of target molecules in each partition after endpoint PCR amplification. The result gives users an absolute measurement without the use of a standard curve, reducing error and improving precision. Unfortunately, Dr. Tewari couldn’t afford to run the large numbers of samples needed on available instruments at the time. That changed when Bio-Rad’s QX100 Droplet Digital PCR (ddPCR) system entered the market in 2011, providing 10-fold lower per sample costs and higher throughput, making it practical for the detection of miRNA in plasma.

Droplet digital PCR is more reliable than real-time PCR for quantifying miRNA
In a study published in the September 2013 issue of Nature Methods, Dr. Tewari showed that ddPCR standardizes the microRNA quantification process, making it feasible for results to be compared at different times and presumably across different institutions. He tested qPCR and ddPCR side-by-side to compare their reliability. First, he and his team assessed the robustness of the two techniques on cDNA from a dilution series of six different synthetic miRNAs in both water and plasma on three separate days. In comparison to qPCR, the researchers found that ddPCR demonstrated greater precision—48 to 72% lower coefficients of variation—with respect to qPCR-specific variation.

Next, Dr. Tewari and team compared the two methods for detecting miRNAs in serum. They were specifically looking for miR-141, a biomarker he discovered for advanced prostate cancer. During the study, they analyzed serum samples from 20 patients with advanced prostate cancer and 20 age-matched male controls using both qPCR and ddPCR. What the team found was remarkable: ddPCR improved day-to-day reproducibility sevenfold relative to qPCR. In addition, ddPCR was able to distinguish case vs. control specimens with higher accuracy than qPCR—just what the team had been looking for.

When conducting multi-institutional studies—patients coming in on different days at different locations—it’s crucial to have a technique that gives highly reproducible results. ddPCR allows just that. Dr. Tewari’s findings have given him and other researchers the confidence to compare data from biomarker studies conducted over a span of days within a laboratory. He’s equally confident that the technique will reliably measure miRNA across different locations, which would pave the way for miRNAs to be regularly used as biomarkers.

What the future holds for cancer biomarkers
Dr. Tewari and his laboratory will continue to study miRNAs as biomarkers of cancer. He is also interested in learning more about other types of RNA, as well as DNA biomarkers. Tewari’s laboratory operates under the belief that in order to create a comprehensive cancer detection method, various types of markers and approaches must be carefully studied and integrated. The team’s ultimate goal is to develop biofluid-based approaches for disease detection and monitoring with simplicity in mind. Dr. Tewari believes that as biomarker quantification methods evolve, they will become simpler and more automated, so that reproducibility continually improves. Droplet digital PCR will undoubtedly play an important part of that process.