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Purdue Team Develops Workflow for Measuring Glycoproteins in Extracellular Vesicles

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NEW YORK (GenomeWeb) – Purdue University researchers have developed a method for capturing and measuring glycoproteins carried by extracellular vesicles.

In a study published this week in Analytical Chemistry, the researchers used the approach to profile EV-bound glycoproteins linked to breast cancer, identifying 20 potential markers, six of which they went on to verify in a separate patient cohort.

The work indicates the approach could prove effective for discovering lower abundance glycoprotein disease markers, many of which are difficult to detect using conventional methods, said Andy Tao, professor of biochemistry at Purdue and senior author of the publication. He added that he and his colleagues are using the approach to investigate glycoprotein markers for a variety of conditions and to potentially improve the utility of existing protein markers.

Glycoproteins are among the most common kinds of protein markers in cancer, comprising, the Analytical Chemistry authors wrote, "more than half of current FDA-approved protein cancer markers."

However, as is the case with blood-based protein biomarker discovery more generally, the complexity and wide dynamic range of plasma presents challenges to the identification of glycoprotein markers and low-abundance glycoprotein markers, in particular.

To address this challenge, the Purdue researchers looked not at glycoproteins circulating in plasma but at the glycoprotein content of EVs, membrane bound-vesicles shed into the bloodstream that are known to contain genetic and protein material from their cells of origin. Because it is bound within the EV, this material is thought to represent an enriched collection of these molecules, making it possible to measure them more sensitively and at lower abundances than would be possible in an analysis of conventional plasma samples.

Given this, various researchers are exploring exosomes as potential clinical samples, and diagnostics companies like Exosome Diagnostics and NX Prenatal are using measurements of exosome-bound RNA and proteins to detect and assess conditions including prostate cancer and preterm birth.

Tao and his colleagues have previously looked at the phosphoproteomic content of EVs in breast cancer, demonstrating that they could identify a set of EV proteins more highly phosphorylated in cancer patients than controls. That work was done through a collaboration between Tao's lab at Purdue and Tymora Analytical Applications, a biotech firm he and his colleagues launched in 2010. Tymora was also involved in the recent glycoprotein work and will most likely be the company to commercialize the technology, Tao said.

EV analysis could be a particularly useful way of looking at glycoproteins given that their origins as the products of endocytic pathways or budding from cell surfaces suggest they likely harbor a large number of glycosylated cell surface proteins, Tao said. And, he noted, "compared to our previous work on phosphoproteins, glycoproteins in EVs have much higher signal on our [platform]."

In the study, the researchers used centrifugation to isolate EVs from plasma samples from 18 breast cancer patients and six healthy controls. They then lysed the EVs, digested their protein contents, enriched for glycopeptides, and analyzed them using an LTQ Orbitrap Velos Pro mass spec. In all, they identified 1,453 unique glycopeptides representing 556 glycoproteins.

This makes for one of the largest sets of glycoproteins identified from a serum or plasma sample, Tao said. According to the authors, 126 of the 556 glycoproteins they identified had not previously been reported as serum or plasma glycoproteins, and low-abundance glycoproteins were overrepresented in their EV-based dataset compared to conventional plasma analyses.

Using label-free quantitation, the researchers identified 77 glycopeptides that showed different abundance levels in the breast cancer samples compared to healthy controls. However, the researchers noted, it was unclear whether these differences were due to different levels of the proteins themselves, or changes in the percentage of these proteins that were glycosylated. To distinguish between these two phenomena, they compared the abundances of the non-glycosylated versions of the peptides in question, which make up the bulk of the total protein expression. They found that the glycopeptide levels differed more significantly between cancer and control samples than did the non-glycopeptide levels, indicating that a portion of the glycoprotein difference between cases and controls was due to cancer-specific glycosylation, as opposed to changes in protein expression.

They followed this initial analysis with a second one in a separate sample cohort consisting of 18 breast cancer patients and 10 healthy controls. This time they identified 20 glycoproteins and 21 unique glycosylation sites that differed between cancer patients and controls.

They selected for further validation six EV glycoproteins, five of which had been implicated in cancer in previous studies. For this work they used the polymer-based reverse phase glycoprotein array (polyGPA) technology developed by Tao's lab. The polyGPA platform uses arrays functionalized specifically for glycoprotein capture. Because the platform captures only glycoproteins, researchers can then probe the captured proteins using antibodies to their non-glycosylated forms, an important capability given the general lack of good glycosylation-specific antibodies.

The polyGPA platform also boosts the sensitivity of protein detection compared to a conventional reverse phase array platform due to the fact that in capturing the proteins by their glycosylations, the array leaves their epitopes more exposed to antibody detection. In previous work, Tao and his colleagues determined this led to a roughly tenfold increase in signal.

One downside of the polyGPA platform is the fact that while it captures glycosylated proteins, it does not distinguish between different glycoforms, and so researchers aren't able to determine if, for instance, a proportion of a captured protein is modified at one versus another glycosite.

"Knowing the site of glycosylation and specific glycoisoform is important, but it has been challenging," Tao noted. He said he believed there were ways to address this issue were it to be necessary from a clinical standpoint, but he did not provide specifics.

Tao said he and his colleagues are now focused on simplifying their processes for isolating the EVs and have submitted a paper describing this work. They are also using the polyGPA platform to measure existing glycomarkers, like prostate specific antigen, to determine if the performance of those markers might be improved by adding information on their glycosylation status.

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