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Lund Team Looks to Commercialize Immunoaffinity-MS Method for Tumor Grading, Discovery Proteomics

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Lund University researchers have devised an immunoaffinity-based mass spec platform for discovery proteomics that they are developing for use in histological grading of tumors and have formed a company, Immunovia, to commercialize the technology.

The platform – which they have termed global proteome survey, or GPS – relies on antibodies that target short amino acid sequences, or motifs, present in multiple proteins, allowing for highly sensitive proteomic characterization, Carl Borrebaeck, chair of the Department of Immunotechnology at Lund and one of the inventors of the method, told ProteoMonitor.

Immunoenrichment is commonly used to isolate proteins prior to mass-spec analysis in order to address issues like sensitivity, resolution, reproducibility, and dynamic range. Because antibodies are designed to bind specific proteins, though, using them for enrichment requires selecting the analytes of interest beforehand – meaning such assays are largely confined to targeted mass spec work.

Borrebaeck's team has worked around this limitation by generating antibodies that bind not to sites specific to single proteins but to short amino acid motifs present in up to several hundred different proteins.

Dubbed context-independent motif specific, or CIMS, antibodies, these reagents allow researchers to isolate proteins for mass-spec analysis in a semi-untargeted fashion, combining the enhanced sensitivity of targeted approaches with the breadth of a discovery workflow.

Borrebaeck and his colleagues published on the method last year in Molecular & Cellular Proteomics (PM 8/12/2011). Currently, he said, his team is focused on developing it to identify proteomic profiles that can be used to type breast cancers.

The researchers have just completed a 52-sample study in which they used the platform for this purpose. This effort, Borrebaeck said, "went extremely well," and the researchers have now begun a larger study involving several hundred breast cancer samples. They are also using the platform to investigate protein markers useful for grading prostate cancers.

"We are a translational cancer center, and so we always start with our clinical colleagues and ask them what problems they have," he said. "And the pathologists have a very big problem with Grade 2 breast cancer because it is very difficult to grade. Our aim is to show that, with this [proteomic technique], grading of tumors could be much more specific than just looking in a microscope."

Borrebaeck said that in the study – the results of which his lab is currently preparing for submission to a peer-reviewed journal – the researchers were able to distinguish between Grade 1, 2, and 3 breast cancers and even distinguish between two categories of Grade 2 tumors, which they termed Grade 2A and 2B.

The research, he said, "has developed into something very promising that we will try full force [through Immunovia] to see if we can offer as a tool to pathologists."

The Lund team also published last week a new study in MCP, in which they used the GPS platform to characterize the proteomes of two different yeast cultures – one grown in glucose and one in ethanol.

In the study, six different motif-specific antibodies each targeted roughly 75 different proteins, generating quantitative proteomic data that corresponded well with data generated via conventional strong-cation exchange fractionation.

Most notably, Borrebaeck said, the platform identified proteins occurring at levels as low as 50 copies per cell, demonstrating that it "can reach deep down in the proteome." The identified peptides included a number not previously reported in PeptideAtlas.

The technique also demonstrated good reproducibility, with the coefficient of variation for the entire workflow coming in at just over 10 percent.

"This study is the [platform's] first [published] application in the real world," Borrebaeck said. He added that the researchers are now working to apply it to serum, a process, he said, that still requires optimization.

Specifically, they are working to remove motifs that bind to high-abundance proteins in order to improve their sensitivity to low-abundance analytes.

"When we looked at these antibodies in serum we saw that we would probably benefit by being a little bit more sophisticated in our selection process," Borrebaeck said. "We [also] need to wash a little bit more than we did in tissue to reach the same reproducibility and sensitivity. We've done some selections where we use two different stringencies, and we see that if we are a little more stringent we perform better in serum."

The researchers used a Thermo Fisher Scientific LTQ Orbitrap XL instrument for the mass spec portion of the workflow. In the MCP paper the authors suggested that a move to MALDI mass spec could improve the technique's throughput, but, Borrebaeck said, right now he is more interested in focusing on the results obtainable with their current ESI set-up.

"I think what we may do is not so much additional technology development and looking at MALDI, but rather use bead arrays with perhaps 15 to 20 antibodies," he said. "From our experience in tissue, we could look at 2,000 or 3,000 proteins [with such a set-up]. I think looking at 3,000 proteins we'll find really interesting data in the cancer that we're looking at."

Borrebaeck said he is also collaborating with his Lund colleague Peter James on selected-reaction monitoring assays for targeted analysis of the proteins his team IDs in its discovery efforts.

"What we're doing in our continuing studies is looking at different tumors and histological gradings and so on in breast and prostate [cancer] and then following it up using SRM-MS for the proteins we've identified," he said, adding that the researchers are selecting additional antibodies for enrichment upfront of the SRM assays.

"We'll also look at the GPS antibodies," he said, "but I think it will be more sensitive using new antibodies."

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