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Chinese Team Develops EV-Based Protein Assay for Early Detection of Cancer

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NEW YORK (GenomeWeb) – A team led by researchers at the University of Florida and China's National Center for Nanoscience and Technology (NCNST) has developed an aptamer-based approach for profiling the surface proteins of extracellular vesicles.

In a study published this week in Nature Biomedical Engineering, the scientists used the approach to detect extracellular vesicles (EVs) produced by cancer cells, finding that they could distinguish between stage I cancer cases and healthy controls with 95 percent sensitivity and 100 percent specificity. According to the study, the assay requires less than 1μl of serum and can return results in about three hours at a cost of roughly $1 per sample.

The researchers have patented the approach and are now working to improve its throughput and validate their findings in larger patient cohorts, said Jiashu Sun, a professor at the NCNST and author on the study.

Extracellular vesicles are membrane-bound bodies produced by cells and shed into the bloodstream and other bodily fluids. Their molecular make-up reflects that of their cell of origin, which has made them an area of growing interest in liquid biopsy research, the idea being that it might be easier to measure proteins or nucleic acids in EVs derived from, for instance, cancer cells, than to detect cancer-linked nucleic acids or proteins circulating freely in patient blood or urine.

A number of researchers and companies have identified EV-bound biomarkers linked to various diseases, with firms like Exosome DX (acquired last year by Bio-Techne) developing tests to help clinicians diagnose prostate cancer and guide therapy in lung cancer.

As the Nature Biomedical Engineering authors note, one challenge in using EVs for such purposes is the need to enrich and isolate these bodies.

Differential centrifugation has been commonly used for isolating EVs from bodily fluids, but it is a time-consuming and cumbersome process that is poorly suited to clinical work given its low reproducibility.

Researchers have developed a variety of other approaches for isolating EVs, but they typically have fairly low yields and may isolate high-abundance circulating proteins along with the target EVs, which can contaminate samples so far as protein analysis is concerned.

Sun and her colleagues developed a thermophoretic approach for isolating EVs, using heat to separate them from other analytes present in a sample. First, they incubated patient serum with fluorescing aptamers targeting cancer-linked surface proteins presented by EVs. They then used a laser to heat the microchamber containing the serum sample, which, the authors wrote, led to the "size-dependent accumulation of EVs" at the center of the laser spot, a phenomenon based on the "interplay of thermophoresis, diffusion, and convention induced by localized laser heating."

Essentially, under heating, aptamer-bound EVs were driven to the center of the well while unbound aptamers, free proteins, and other smaller molecules remained randomly distributed throughout the sample. Expression of target EV surface proteins could then be read out based on the intensity of the fluorescence of these aptamer-bound vesicles.

Sun said that she and her colleagues had determined in previous work that such an approach could be used to efficiently accumulate particles in the 100 nanometer size range. "And since EVs are also nano-sized entities, we expected that thermophoresis could enrich EVs in a size-dependent manner," she said.

The researchers used aptamers for the work because they thought the small size of these affinity reagents might allow them to better access the surface of EVs than could antibodies, Sun said, though she added that they believed antibodies would likely be compatible with the thermophoretic enrichment method and that they planned to try them in future studies.

Using the approach, the researchers measured the level of seven EV surface proteins in a set of 60 untreated cancer patients (10 each of lymphoma, breast, liver, lung, ovarian, and prostate cancer) and 10 healthy controls, finding that the cancer EVs exhibited significantly elevated levels of the target proteins compared to those from healthy controls. They then used a linear discriminant analysis algorithm to develop a model based on this data for distinguishing between cancer cases and controls. Applying the model to an independent validation cohort consisting of 19 stage I cancers, 26 stage II cancers, 23 stage III cancers, 17 stage IV cancers, and 17 healthy controls, they found that it could distinguish between the cancers and controls with sensitivity of 95 percent and specificity of 100 percent in the case of stage I cancers and with 100 percent sensitivity and specificity for stage II, III, and IV cancers.

The method was less successful in identify specific cancer types based on the EV surface protein profile, distinguishing between the six cancer types tested with an overall accuracy of 68 percent.

Testing the model in a set of cohort of 19 untreated prostate cancer patients and 14 patients with benign prostate disease — all with PSA levels above 4 ng per ml — the researchers found they were able to distinguish between the two with a sensitivity of 95 percent and specificity of 86 percent, making for an area under the curve of .94 compared to .68 for serum PSA alone. This, the authors noted, suggests the EV-based test could prove useful for determining patients with elevated PSA levels who can avoid undergoing a biopsy.

Anton Iliuk, chief technology officer of Tymora Analytical Operations, which is developing EV-based proteomic assays for clinical applications in cancer, said he thought the approach developed by Sun and her colleagues "is really promising" and called their data "certainly impressive."

In particular, Iliuk, who was not involved in the research, noted that the method's high performance in detecting early-stage cancers was "incredibly promising."

"The technology itself appears quite simple and robust, and the temperature-based accumulation is unique," he added, noting that he also liked the choice of aptamers as opposed to antibodies as the former are typically less expensive.

He said that in addition to data from larger cohorts, he would also like to see how well the approach works in plasma samples, as "serum has many exosome populations missing due to coagulation."

Broadly speaking, Iliuk said the study "produces further evidence that [EVs] are a great untapped source of new and known biomarkers for better non-invasive care."

Tymora's work has focused primarily on analysis of proteins contained within EVs, as opposed to the surface proteins targeted by Sun and her colleagues. Sun noted, though, that the researchers are now exploring new methods based on the thermophoretic approach for isolating and measuring proteins and RNA contained within EVs.

"The combination analysis of surface proteins and intravesicular markers of EVs may improve the performance," she said.

They are also looking into adding other surface proteins to their panel. In the Nature Biomedical Engineering work, the researchers measured levels of CD63, PTK7, EpCAM, LZH8, HER2, PSA, and CA125, which they chose "based on prior studies of protein overexpression in tumors … and the availability of aptamers," Sun said, adding that moving to antibodies could allow them to add more surface proteins to their analyses.

The researchers are working to multiplex the method, as well, and have since the publication of the study developed an approach that uses multiple fluorescent dyes to measure multiple EV surface proteins simultaneously, Sun said.

They are now testing the approach in larger sets of patients as well as different cancer types and are exploring whether the addition of new markers could help improve its ability to not only distinguish between cases and controls but also to identify the type of cancer detected.