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Danish-led Team Developing Autoantibodies against O-glycoproteins as Cancer Biomarkers


By Tony Fong

A Danish-led team of researchers has used array technology to help detect autoantibodies against abnormal glycoproteins in cancer, which could potentially provide a new source of biomarkers to detect the disease.

While other researchers have done biomarker studies looking at autoantibodies, the work described in the Feb. 2 online edition of Cancer Research may be the first pointing to autoantibodies against a protein post-translation modification as a diagnostic tool for cancer.

Classic proteomic biomarker research has focused on the upregulation of unmodified proteins, but a growing body of data has implicated protein variants and PTMs in cancer development and progression, and in particular, studies suggest glycosylation may be involved in many cancers.

So far, though, using glycosylated proteins shed by cancer cells as a biomarker has proven elusive because they are quickly filtered out by hepatocytes and other cells in the liver, making detection tricky.

"So we thought … it would be smart if we could use the patient's own immune system … to detect the presence of cancer," Hans Wandall, the first author of the Cancer Research study, told ProteoMonitor recently. Wandall is an associate professor of glycobiology at the Center for Glycomics at the University of Copenhagen.

When a cell becomes cancerous, it exposes new proteins on its surface, which become modified by glycan. When the cell becomes tumorous, the glycans change, and when that happens the body's immune system produces specific autoantibodies that react with the cancerous cells.

The strategy that Wandall and his colleagues propose is to look for these autoantibodies. "So we're combining the presence of the changed glycan structure [and a peptide motif] … on the surface of these specific molecules upregulated in cancer, and looking for an immune response specifically against molecules with or carrying these abnormal glycans," he said.

For their work, he and his colleagues focused on a type of glycoprotein called mucins. Mucins comprise a family of glycoproteins called O-glycoproteins that are found on the outer surface of cells and which have been associated with cancer. Different types and amounts of mucins have been found on tumor cells compared to normal cells. Tumors also produce mucins with altered sugar groups.

To detect cancer-associated autoantibodies, though, they needed a platform that would be able to differentiate such autoantibodies from non-cancerous antibodies. Mass specs are not suitable for the detection of antibodies, and ELISAs, while capable of detecting antibodies, are not able to distinguish antibodies that are specific to patients with cancer from patients without, Wandall said.

He and his co-researchers needed to build their own tool that would be able to detect autoantibodies that are specific to aberrant O-glycopeptide epitopes that are indicative of cancer cells.

They came up with a platform that is based on a commercially available peptide array with glass slides printed with recombinant chemoenzymatically synthesized O-glycopeptides and control structures — basically the surface of a cancer cell "but now on a specific molecule and located … on an array platform," Wandall said.

The research team chose an array format because they needed a platform that could present their antigen of interest in many different versions "because we were looking for antibodies against many different glycoforms," Wandall said. In addition, they chose a microarray format on N-hydroxysuccinimide-, or NHS, activated hydrogel slides, because prior research indicated the technology "provide[s] a remarkably low background for detection of human serum antibodies," they wrote.

The assays they created are, in effect, "a little more complex ELISAs where you bind your antigen of interest," according to Wandall, and can be printed so that different versions of the antigen can be generated.

When serum is introduced to the assay, antibodies bind to the antigen, and then are detected by a fluorescently labeled secondary antibody. The assay is then put into a microarray scanner, and Wandall and his colleagues can then check for reactivity between the antibody and the glycoprotein.

Reactivity indicates the presence of cancerous cells.

Sugary Trail of Cancer

Research into autoantibodies as a signature of cancer "is an old strategy," Wandall said, but autoantibody studies directed at PTMs and a peptide — "we can call it a combined glycopeptide epitope" — is an area of research that has, to date, been unexplored, he added.

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Using the O-glycopeptide array to detect for natural antibodies in healthy controls against newly diagnosed patients with prostate, breast, or ovarian cancers, the researchers found that the reactivity of immunoglobulin M antibodies, which are normally found in the human circulatory system, were, in essence, unchanged in healthy controls and patients with cancer.

However, "in striking contrast," IgG antibodies in the healthy control group were essentially unreactive with the glycopeptides, while IgG antibodies to three glycopeptides — Tn-MUC1, STn-MUC1, and truncated core 3 O-glycopeptides — were detected in the sera of cancer patients, the authors wrote.

Cancer-associated IgG autoantibodies to several O-glycopeptide epitopes were identified in MUC1, while IgG antibodies to peptide epitopes were not detected, suggesting that autoantibody biomarker research should include aberrant PTMs for "greatest success."

In addition, chemoenzymatic synthesis of cancer-associated O-glycopeptides in combination with a microarray platform was shown to be "a feasible strategy for broader analysis of the entire cancer O-glycopeptidome," they wrote.

While the researchers investigated prostate, breast, and ovarian cancers in the Cancer Research article, O-glycosylation has been linked to a number of other malignancies, Wandall said.

"This is one target but with numerous glycoforms, and the concept we show here is that when you add glycans, when you decorate your target, then you get your autoantibody response detected," he said. "But in the same way you can add to your array platform hundreds and hundreds of cancer-associated targets and decorate those with sugars, and then we hope that we can create patterns that are specific for each cancer form."

Because their study is a proof-of-concept, clinical use of their assay is still far off. One area of continuing work is to show that the technology "has real clinical relevance in a larger set of sera," Wandall said.

In addition to optimizing the technology, much remains unknown about PTMs and their biological consequences. That, Wandall said, is a "tremendous deal."

"You could imagine that if we had a full understanding of the combinations of the different glycan structures you can add to a backbone, the different sulfate residues, all the different PTMs, you would be able to … create a barcode that would be specific for different clinical scenarios," he said.

"And if we knew more about how and when these things were attached, we could create or recreate a specific pattern that would be specific for each clinical situation we would like to monitor," he added.

Wandall, Henrick Clausen, a professor at the Center for Glycomics, and Ola Blixt, an associate professor at the center, are developing autoantibody biomarkers based on their research using three methods. One, a so-called "intelligent design" method, is based on proteins that are known to have glycans that are upregulated in cancer, Wandall said.

A second approach is a systems biology approach based on using a random peptide library carrying various cancer-associated glycans as targets, which Wandall said is a "numbers game. … If you think about it, if you have many, many proteins with many, many glycosylation sites, you need to cover them all in the right combinations."

A final strategy combines the first two methods.

In addition to the three cancer-associated autoantibodies to defined O-glycopeptide epitopes mentioned in the study, the authors have identified other potential biomarkers for further research, though Wandall declined to describe them. The goal is to find biomarkers that can discriminate among different cancers.

The technology and method may also have therapeutic use, he said. Targets can be identified for creating cancer-specific monoclonal antibodies, which can be used to develop vaccines for cancer.

Hoping to understand how early their method can detect the disease, the researchers are also trying to discover when the immune response is initiated in a patient, which then triggers these cancer-associated autoantibodies to defined O-glycopeptide epitopes.

When a cancer-implicated protein is detectable in sera, the chance of successful treatment has already been compromised, Wandall said. "What we hope to achieve … is that by using the amplified signal from the immune system, you can detect [the disease at] a very early stage," he said.

Glycans may also be used to discriminate between healthy patients, patients with benign tumors, and patients with malignant tumors, Wandall added, and will be the subject of future research.

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