A novel tool for rapidly identifying the genetic "fingerprints" of cancer cells may enable future surgeons to more accurately remove brain tumours while a patient is in the operating room, new research reveals. Many cancer types can be identified by certain mutations and changes in the instructions encoded in the DNA of the abnormal cells.

Led by a research team from NYU Langone Health, the new study describes the development of Ultra-Rapid droplet digital PCR, or UR-ddPCR, which the team found can measure the level of tumour cells in a tissue sample in only 15 minutes while also being able to detect small numbers of cancer cells (as few as five cells per square millimetre).

The researchers say their tool is fast and accurate enough, at least in initial tests on brain tissue samples, to become the first practical tool of its kind for detecting cancer cells directly using mutations in real-time during brain surgery.

The researchers showed that UR-ddPCR had a markedly faster processing speed than standard ddPCR, short for droplet digital polymerase chain reaction. Standard ddPCR can accurately quantify tumour cells, but it typically takes several hours to produce a result, making it impractical as a surgical guide.

"For many cancers, such as tumours in the brain, the success of cancer surgery and preventing cancer's return is predicated on removing as much of the tumour and surrounding cancer cells as is safely possible," said study co-senior investigator and neurosurgeon Daniel Orringer, MD.

"With Ultra-Rapid droplet digital PCR, surgeons may now be able to determine what cells are cancerous and how many of these cancer cells are present in any particular tissue region at a level of accuracy that has never before been possible," said Orringer, an associate professor in the Departments of Neurosurgery and Pathology at NYU Grossman School of Medicine.

Publishing in the Cell Press journal Med online on Feb. 25, the study showed that UR-ddPCR produced the same results as standard ddPCR and genetic sequencing in more than 75 tissue samples from 22 patients at NYU Langone undergoing surgery to remove glioma tumours, a type of brain cancer. Results from UR-ddPCR were also checked against known samples with cancer cells and samples without any cancer.

"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 the potential to also be used for cancers outside the brain," said study co-senior investigator Gilad Evrony, MD, PhD. Evrony is a geneticist at the Center for Human Genetics and Genomics at NYU Grossman School of Medicine and also serves as an assistant professor in the Departments of Pediatrics and Neuroscience at NYU Grossman School of Medicine.

To develop UR-ddPCR, researchers looked for efficiencies in each of the steps involved in standard ddPCR. The team shortened the time needed to extract DNA from tumour samples from 30 minutes to less than five minutes in a manner that is still compatible with subsequent ddPCR. The researchers also found efficiencies by increasing the concentrations of the chemicals used in testing, reducing the overall time needed for some steps from two hours to less than three minutes. Time savings were also achieved by using reaction vessels prewarmed to each of the two temperatures required by the PCR rather than repeatedly cycling the temperature of a single reaction vessel between two temperatures.

For the study, researchers used UR-ddPCR to measure the levels of two genetic mutations, IDH1 R132H and BRAF V600E, which are prevalent in brain cancers. They combined UR-ddPCR with another technique the researchers developed earlier, called stimulated Raman histology, to calculate both the fraction and the density of tumour cells within each tissue sample.

Researchers caution that widespread use of the tool awaits further refinements and clinical trials. They say their next step is to automate UR-ddPCR to make it faster and simpler to use in the operating room. Subsequent clinical trials will be necessary to compare patient outcomes using their tool compared to current diagnostic technologies. They also plan to develop the technology to identify other common genetic mutations for other cancer types.

Besides Orringer and Evrony, other NYU Langone researchers involved in this study are lead investigator Zachary Murphy and Emilia Bianchini, and co-investigators Andrew Smith, Lisa Körner, Teresa Russell, David Reinecke, Nader Maarouf, Yuxiu Wang, John Golfinos, Alexandra Miller, and Matija Snuderl.

Orringer, Evrony, Murphy, and NYU have a patent application pending their development of UR-ddPCR.

Orringer is a shareholder in Invenio Imaging, which develops and markets imaging equipment. He has also received consulting fees from Servier, a company involved in the production of anticancer therapies. Orringer and Snuderl also have financial interests in Imagenomix. Snuderl has served as an advisor to and has financial interests in Heidelberg EPignostix and Halo Dx. He has also been a paid advisor to Arima Genomics and InnoSIGN, and received research funding support from Lilly. All of these arrangements are being managed in accordance with the policies and practices of NYU Langone Health.