Ultra-Rapid Test Helps Identify Cancerous Cells in Real Time
UR-ddPCR can measure the level of tumor cells in a tissue sample in only 15 minutes.
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Cancer is inherently a genetic disease, yet genetic information is rarely used to guide surgeries in real time. Indirect approaches – such as histology or magnetic resonance imaging – are almost always the practical choice.
Researchers from New York University (NYU) Langone Health set out to change this, developing a novel tool for rapidly identifying the genetic “fingerprints” of cancer cells that can help surgeons to more accurately remove brain tumors while a patient is in the operating room. The new technology, dubbed ultra-rapid droplet digital polymerase chain reaction (UR-ddPCR), can measure the level of tumor cells in a tissue sample in only 15 minutes. Additionally, the tool can detect small numbers of cancer cells, down to as few as five cells per square millimeter.
Technology Networks recently spoke with Dr. Gilad Evrony, an assistant professor within the Center for Human Genetics and Genomics at NYU Grossman School of Medicine, to find out more about this new technology and what it means for real-time cancer cell detection in the operating theatre.
How does UR-ddPCR compare to standard ddPCR in terms of sensitivity and specificity for detecting brain cancer cells?
Gilad Evrony, PhD (GE):
We found the sensitivity and specificity of UR-ddPCR to be extremely comparable to standard ddPCR. All the samples (i.e., tissue lysate) that we tested in the operating room using UR-ddPCR were saved and tested later that day or the next using standard ddPCR, allowing for direct comparison of the same sample. We found extremely high concordance between the methods, which gave us confidence in the UR-ddPCR technology we had developed.
IE:
What are the main technical challenges in integrating UR-ddPCR into operating room workflows?
GE:
Right now, the process (i.e., UR-ddPCR) is manual and requires a very well-trained technician to perform it. For example, we're using water baths and stainless-steel capillaries which are unlikely to be commercialized. So what we want to do is develop a much more streamlined, integrated process that can be relatively automated and parallelized for multiple samples, and perhaps even faster than what we have done so far.
Another goal is to develop more assays for UR-ddPCR analysis. Currently, we only have assays
for two mutations that are prevalent in some brain cancer types, thus being
limited in the analysis we can currently do. Of course, we would like to be
able to target other common cancer mutations and even move beyond the operating
room. We think there is potential for this technology in other point-of-care
settings, for example, in the emergency room to detect infectious diseases
accurately but also quickly.
IE:
Are there any risks associated with making real-time surgical decisions based on UR-ddPCR results?
GE:
Surgery is never usually guided by genetic information, so we are planning a clinical trial to evaluate that concept. As with any untested technology, there are always risks involved and our plan is to do that as safely as possible, including consenting patients so they are aware of the risks and further validating the UR-ddPCR sensitivity and specificity as accurately as we can before the start of the trial.
Based on our results so far, it is reasonable to assume that surgeons could safely use UR-ddPCR to make sure they are not leaving areas of the tumor containing 10–20% of cancer cells behind. The risk, of course, may be that surgeons see the assay continuing to detect tumor cells even beyond the margins they would typically cut. The question is then, what will surgeons do? For example, if they see 1% of cancer cells at the tumor margins, is cutting a little bit more out to get the margins even lower going to benefit the patient, or cause harm? We actually don't know where the boundary is between whether cutting more will help the patient without causing more harm.
There is evidence to support that patients who have more maximal brain tumor resection generally do better. But this is always balanced by the surgeon's decision-making – it has to do with where the tumor is. There are some parts of the brain where surgeons have to be less aggressive because it's up against a critical functional area of the brain. Our technology could essentially provide another input into the surgeon's decision-making to aid with maximal tumor resection.
IE:
How might UR-ddPCR be adapted for use in diagnosing and guiding surgery for other types of cancers beyond brain tumors?
GE:
We think our technology can certainly be applied to other cancer types. Many other cancer types have characteristic hot spot mutations which could be used as a marker to guide surgeons, such as melanoma. The main applications will be in cancers where surgery is a mainstay of treatment.
Our main area of focus is on situations where there is this need for ultra-rapid testing, and hopefully when the technology is available as an easy-to-use, maybe even a commercial product, then certainly it could be used in applications further afield.
IE:
What future developments to UR-ddPCR do you envisage?
GE:
The main focus right now is, how do we make this process even simpler and maybe even faster. We want this technology to be widely used, not a highly specialized method where only a very small number of surgical teams can use it. Our goal is to develop the technology to the point that you don't need a highly trained individual.
