NEW YORK (GenomeWeb) – Researchers from Arizona State University have developed a method for the detection of tumor-derived exosomes in circulation that could be turned into a simpler and potentially cheaper platform for cancer diagnostics development than other current approaches.
In contrast to methods that require centrifugation to gather extracellular vesicles, lyse them, and analyze their molecular contents to find signals of cancer or other disease, the Arizona team's approach uses the interaction between two nanoparticles to detect exosomes that express a particular molecular target on their surface.
In a study in Nature Biomedical Engineering this week, the team, led by Tony Hu, a researcher at Arizona's Biodesign Virginia G. Piper Center for Personalized Diagnostics, described their identification of a protein marker, EphA2, that serves to distinguish exosomes expelled by pancreatic cancers from other vesicles circulating in the blood.
They showed that their methodology for detecting EphA2-positive exosomes could very sensitively discriminate patients with pancreatic cancer from both healthy controls and individuals with pancreatitis, which poses a challenge to making a differential diagnosis of the disease.
In an interview this week, Hu said that the nanoparticle technology he and his team harnessed isn't new, but that using these methods to detect cancer-specific exosomes directly from patient samples, and showing that this can sensitively detect cancer, was a major achievement.
According to Hu, despite excitement around the potential of exosomes, the advances of a number of technologies, and even commercialization by firms like Exosome Diagnostics, the field has not seen an explosion of exosome-based tests.
Available platforms most often require time-consuming isolation and purification that is not appropriate for the development of diagnostic instruments for routine clinical use, he argued. They also usually only isolate the general population of circulating exosomes and do not capture tumor-specific vesicles.
Hu and his colleagues are hoping to advance a simpler, more direct approach, using a nanoplasmonic technique to detect tumor-specific exosomes directly from blood samples, without the need to lyse the general population and analyze their molecular components searching for cancer markers.
The method involves diluting small samples of blood (around 1 microliter) and applying them to a sensor chip that is coated with antibodies for a particular vesicle membrane protein — in this case, CD81, which the study authors wrote has been shown to be present on extracellular vesicles from most cell types.
The vesicles bound to the chip are then exposed to two different antibody-coated nanoparticles: one green nanosphere and one red nanorod.
These particles recognize two other membrane proteins. When the team first developed the method, they tested it with CD63 and CD9, which are both associated with extracellular vesicles in general. For the pancreatic cancer study, they coupled one probe for CD9 with another for a marker, EphA2, that they had identified in proteomic and bioinformatics analyses of pancreatic cancer cell lines.
Identifying this tumor-specific membrane protein as the target was in some ways the major element of the team's work, Hu said.
EphA2 was highly enriched on exosomes of pancreatic cancer cells but essentially absent on those of normal pancreas cells, the authors wrote.
In the team's assay, only vesicles that were EphA2-positive would be expected to bind both of the nanoparticles. The close contact of the two particles then causes a coupling effect that changes their color and increases the intensity of their refracted light, generating a detectable signal.
For the study, Hu and his colleagues used a dark-field microscope to detect this signal, but their goal is to adapt the readout system for fully automated, higher-throughput testing.
Most importantly for clinical development, the team was able to show, albeit in a small number of samples, that the approach could detect pancreatic cancer, including the early stages of the disease, and distinguish it from potentially confounding conditions like pancreatitis.
Overall, the investigators tested samples from 48 controls, 48 pancreatitis cases, and 49 pancreatic cancer cases from stage I to stage III. They compared results using their nanosensor method to plasma levels of CA19-9, which is a currently used, but clinically limited biomarker of pancreatic cancer.
The authors reported that the sensitivity for detecting pancreatic cancer was 94 percent versus normal controls and 89 percent when comparing to pancreatitis cases. CA19-9 was only 81 percent and 61 percent sensitive, respectively.
The EphA2 exosome assay also stayed quite sensitive when the authors looked only at stage I and II patients, showing 91 percent sensitivity in discriminating against normal controls and 86 percent against pancreatitis. This bodes well for the potential of the method for early cancer detection, the authors wrote.
The researchers also looked at EphA2-positive exosome levels in pre- and post-therapy blood samples from 23 patients treated with neoadjuvant chemotherapy or chemoradiation or both. They found that post-therapy EphA2-positive exosome levels significantly decreased in patients with good or partial therapy responses, but not in patients with poor responses. CA19-9 did not show the same association.
Hu and his colleagues believe that their approach to detecting disease-specific vesicles could also be useful for the rapid detection of other diseases. As long as researchers can identify markers that delineate disease-associated exosomes from others, the same nanoparticle-based platform should be able to read out a diagnostic signal.
The team has shown in a small number of samples that they could detect vesicles derived from tuberculosis bacteria in patient urine samples, for example.
EphA2 itself could also be applicable beyond pancreatic cancer because it is also overexpressed in the early stages of colorectal cancer and non-small-cell lung cancer, with accumulation during tumor progression.
If it were necessary to detect exosomes or other vesicles with a specific cellular origin, the probe combinations could also be tweaked, Hu and his coauthors wrote, for example by replacing the anti-CD9 nanoparticle probe with a cell-specific probe.
Hu and his team are not alone in seeing potential in an approach that allows direct detection of cancer or other disease-associated exosomes.
Exosome Diagnostics, for example, recently launched a new product it calls Shahky, which uses a label-free detection method, without upfront sample prep, to detect exosomal protein markers.
The company hasn't described details of the technology behind this detection system, however.
A group from Massachusetts General Hospital and Harvard Medical School have also described a platform for label-free, high-throughput, quantitative analysis of exosomes using transmission surface plasmon resonance through periodic nanohole arrays in a publication in Nature in 2014.
More recently, the same researchers reported what they call an integrated magneto–electrochemical sensor for exosome analysis, which they said allows highly sensitive, cell-specific exosome detection.
A team from the University of Queensland shared its own approach for the quantification of clinically relevant exosomes isolated from patient serum, also using a surface plasmon resonance platform, in Scientific Reports last year. Similar to Hu and his colleagues, the Queensland team's method uses exosome surface markers CD9 and CD63, combined with tumor-specific markers.
Moving forward, Hu and his colleagues need to validate their pancreatic cancer results in larger cohorts. He said that the team is already working on that.
Response to the team's study has already yielded potential collaborators with clinical samples the team could analyze. Hu said the group is also drafting a proposal to work with an NIH clinical trial team that has a cohort of samples, collected over 10 years.
Pancreatic cancer, because it presents such a difficult clinical puzzle, is a main target for the team, but Hu said that the group also has an ongoing study in lung cancer, with collaborators at MD Anderson.
In that study, the investigators hope to see if their exosomal approach can measure patients' response to treatment better and more cheaply than currently used PET scan imaging.
"Because PET scan is so expensive, it can only be used once a year, but clinicians really want to be able to monitor more frequently, so if we can find a better way, that will be a [significant] benefit," he said.
In preliminary data, the group has already found that it can differentiate patients with good responses at four weeks post treatment. It currently takes at least eight weeks before PET scan can see any change, Hu said.