NEW YORK (GenomeWeb) – Researchers at the University of Texas have developed a mass spec-based device for helping diagnose tumor margins during cancer surgery.
Named the MasSpec Pen, the instrument consists of a handheld, disposable ionization device connected to a mass spectrometer and can be used to analyze the molecular content of patient tissue in real time without destroying the tissue.
According to Livia Eberlin, assistant professor of chemistry at UT and leader of the device's development, the pen could supplement and perhaps ultimately replace the conventional pathology assays currently used to assess tumor margins during surgery.
Accurately assessing tumor margins is a key part of many cancer surgeries where the goal is to remove all cancerous tissue while leaving as much healthy tissue as possible. Margins are typically determined using pathology, which involves freezing and staining tissue and then interpreting the results during surgery. This process, Eberlin noted, can lengthen the time required for cancer surgery. Additionally, she said, the accuracy of these intra-operative pathology assays can vary significantly depending on the facility where the surgery is being performed and the experience of the pathologist analyzing the sample.
Given these challenges, researchers and clinicians are exploring a variety of technologies for more quickly and rapidly assessing tumor margins during surgery, with ambient ionization mass spec methods being one notable area of interest.
In ambient ionization mass spec, ions are generated directly from the target sample without any upfront sample preparation. This enables streamlined, rapid mass spec assays well suited to an application like profiling patient tissue during surgery, and several technologies, including Waters' iKnife instrument, are being tested for such a purpose.
Most ambient ionization techniques, however, require either damaging or destroying target tissue. (For instance, the iKnife cauterizes tissue and then analyzes the molecular content of the smoke.) The MasSpec Pen, Eberlin noted, is distinguished by its ability to extract target molecules using only water, making it well suited to in vivo analyses.
"We wanted to do something that was very gentle to the tissue," she said. "That's why we're using a single water droplet to enable chemical extraction of low molecular weight compounds like metabolites and lipids, and then from that we can get a molecular diagnosis."
The decision to use water to extract target molecules emerged from initial work in which the researchers used an ethanol-water mix, said Jialing Zhang, a postdoc in Eberlin's lab.
"In the beginning, we were using ethanol because [it is] really good at chemical extraction," he said. "Then we switched to ethanol and water, and we got pretty good results. And then we started saying, 'How about just using pure water?' Because it is completely bio-compatible with humans. And when we saw the results, we saw that we got really beautiful molecular profiles."
In a study published this week in Science Translational Medicine, the researchers used the pen for ex vivo analysis of 20 human cancer thin tissue sections and 253 human patient tissue samples consisting of normal and tumor tissue from breast, lung, thyroid, and ovary. They also used the device for analysis of mouse tumors in vivo and determined that it did not cause "any observable tissue harm or stress to the animal," the authors wrote.
Building classifiers from the molecular data they collected, Eberlin and her colleagues were able to identify cancerous tissue with a sensitivity of 96.4 percent, specificity of 96.2 percent, and overall accuracy of 96.3 percent.
The classifiers are based not on the levels of specific, targeted analytes but rather on mass spectral feature patterns analyzed using machine learning, Eberlin said, though she noted the team did identify the molecules underlying these patterns and that a number of them have been linked to cancer in past studies.
The exact composition of the profile depends on the cancer type, Zhang noted, but he said the classifiers typically consist of between 20 and 40 features.
While the accuracy numbers achieved in the STM study will need to be validated in larger sample sets and in actual surgical settings, they compare favorably with the conventional pathology methods that are currently the gold standard for assessing surgical margins, Zhang said.
For instance, he noted, recent reports put the error rate for assessing margins in gastrointestinal cancer surgery at between 20 and 30 percent, though Eberlin added that it is difficult to get solid numbers on this question given the variance between hospitals and the fact that cancer recurrence is not always due to errors in margin assessment.
In addition to potential accuracy gains, the pen instrument could also streamline analysis, Zhang said. "It's not like we have to change the methods of surgery at all."
The instrument is handheld and designed to be operated with a foot pedal. "So, in practice [the surgeon] would just need to apply it to the tissue and then trigger it with the foot pedal," Eberlin said. "There's no secret there. No specific training that is needed."
The device can return results in less than a minute, she added.
One portion of the workflow that still needs optimization for surgical use is the mass spec instrumentation. In the STM study, the researchers used a Thermo Fisher Scientific Q Exactive platform, but ideally the pen would be connected to a miniaturized mass spec better suited to a surgical suite.
Miniaturized instruments are effective for analyzing a range of small molecules like those used in the classifiers developed by the UT team, but they are lower performance machines than a research-grade system like the Q Exactive. Whether this change in power will affect the performance of the MasSpec Pen device remains to be seen, though Zhang said the researchers aim to test this in the near future.
They are also doing additional validation of the results in the STM study as well as expanding their sample types and cancer types, Eberlin said, adding that they hope to begin clinical studies using the device in early 2018.
She said that commercialization plans for the technology are still being developed and that she and her colleagues are exploring both the possibility of forming a company to sell the device and potential licensing deals.