For many cancers, including brain tumors, the success of surgery and the prevention of cancer recurrence depend on removing as much of the tumor and surrounding cancerous cells as safely as possible. Surgeons, however, often lack information about the genetic mutations present in the tumors they are removing. Certain cancer types can be identified through specific mutations, which are changes in the DNA instructions of the abnormal cells. A technology that allows for the rapid and accurate quantification of mutations in the operating room could enable surgeons to tailor their approach based on the cancer's genetic profile, thereby improving the ability to remove tumor tissue more reliably. Researchers have now developed a groundbreaking technology capable of measuring mutation levels in tissues in just 15 minutes, paving the way for surgeries guided by genetic data and offering the potential for better patient outcomes. This tool for quickly identifying the genetic "fingerprints" of cancer cells could allow future surgeons to more precisely remove brain tumors while the patient is still in the operating room.

The study, led by researchers from NYU Langone Health (New York, NY, USA), presents the development of Ultra-Rapid droplet digital PCR (UR-ddPCR), which was found to measure the concentration of tumor cells in a tissue sample in only 15 minutes. The technology is capable of detecting as few as five cancer cells per square millimeter. According to the researchers, UR-ddPCR, at least in initial tests on brain tissue samples, is fast and accurate enough to be the first practical tool for detecting cancer cells in real-time during brain surgeries, directly using genetic mutations. To develop UR-ddPCR, the research team sought efficiencies in the steps of the standard droplet digital PCR (ddPCR) method. By reducing the DNA extraction time from 30 minutes to under five minutes, the team maintained compatibility with ddPCR. Further time savings were achieved by increasing the concentrations of chemicals used during testing, which shortened the time for some steps from two hours to under three minutes.

Additional efficiencies were realized by using pre-warmed reaction vessels for the two temperatures required by PCR, rather than repeatedly cycling the temperature of a single vessel. In the study, the researchers employed UR-ddPCR to measure the levels of two genetic mutations, IDH1 R132H and BRAF V600E, both commonly found in brain cancers. By combining UR-ddPCR with stimulated Raman histology—another technique the team developed earlier—the researchers could assess both the fraction and density of tumor cells within each tissue sample. The study, published in Cell Press Journal Med online, demonstrated that UR-ddPCR outperformed standard ddPCR in terms of processing speed. While standard ddPCR can accurately quantify tumor cells, it takes several hours to yield results, making it impractical for use during surgery.

With UR-ddPCR, surgeons could potentially determine the cancerous nature of cells and precisely quantify the number of cancer cells present in specific tissue areas, a level of accuracy previously unattainable. The study revealed that UR-ddPCR produced results consistent with both standard ddPCR and genetic sequencing across 75 tissue samples from 22 patients undergoing glioma tumor surgery at NYU Langone, a type of brain cancer. Results from UR-ddPCR were also verified against known cancer cell samples as well as non-cancerous samples. Although the tool has shown promising results, the researchers caution that broader use will require further refinement and clinical trials. The next step is to automate the UR-ddPCR process to simplify and speed up its application in the operating room. Clinical trials will also be necessary to evaluate patient outcomes when using this tool as compared to existing diagnostic methods. Additionally, the team plans to develop the technology to detect other genetic mutations commonly associated with various cancer types.

"Our study shows that Ultra-Rapid droplet digital PCR could be a fast and efficient tool for making a molecular diagnosis during surgery for brain cancer, and it has potential to also be used for cancers outside the brain," said study co-senior investigator Gilad Evrony, MD, PhD.

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