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Teams Publish Proof-of-Principle Studies on Targeted Mass Spec-Based Biomarker Pipelines

By Andrea Anderson

NEW YORK (GenomeWeb News) – A pair of studies appearing online in Nature Biotechnology yesterday highlight the value of targeted mass spectrometry-based pipelines for finding potential biomarkers and focusing in on those with clinical potential.

Together, the new studies demonstrate that "modern mass spectrometry methods, when properly integrated, actually deliver markers worthwhile credentialing in true clinical validation studies," Broad Institute proteomics platform Director Steven Carr, senior author on one of the papers, told GenomeWeb Daily News.

In addition, such multi-stage, targeted proteomic strategies offer an opportunity to "triage" the promising biomarkers from the long lists of candidates being discovered using "omics" approaches, "marking a substantial improvement over the current state of biomarker evaluation," Fred Hutchinson Cancer Research Center researcher Amanda Paulovich, senior author on the other new study, and her co-authors noted.

Carr's Massachusetts-based research team used targeted mass spectrometry to help find potential biomarkers for cardiovascular injury, starting with three individuals who received septal ablation — a treatment in which myocardial infarction or heart attack is induced therapeutically to destroy excess heart tissue in individuals with enlargements that interfere with normal blood flow in the heart.

Using their pipeline, the researchers used information on proteins being differentially expressed in fluid from the heart before and after this treatment to narrow in on biomarkers for cardiovascular injury in peripheral blood samples. In the process, they identified some markers that also seem to signal spontaneous heart attack.

"The first phase is non-targeted — that's the discovery — and the second two steps are targeted," Carr said, noting that the current study represents a "prioritization scheme and demonstration that the pipeline actually works."

Despite the deluge of possible biomarkers being reported, relatively few go on to be used in a clinical setting. This lack of translation has been attributed to everything from false positive results and variable effect sizes to a lack of efficient strategies for sorting through candidate markers.

In an effort to streamline this validation process, both teams employed a targeted mass spectrometry-based pipeline process stemming from a proposal by Carr and his co-authors in Nature Biotechnology in 2006.

In their current study, Carr and his colleagues first used LC-MS/MS to find candidate proteins in samples taken from the coronary sinus, a vessel that drains blood from the myocardium of the heart, in three individuals receiving planned myocardial infarction treatment.

Samples were taken from the coronary sinus vein before treatment and again 10 minutes and an hour after treatment. Researchers also took peripheral blood samples from the patients for up to 24 hours following treatment.

They then looked at whether the same possible markers found in the coronary sinus also turned up in peripheral blood samples using an approach known as "accurate inclusion mass screening," or AIMS, which finds peptides of interest in samples based on the presence or absence of a specific mass and charge profile.

"AIMS is a targeted approach that uses the same high performance mass spectrometry instrumentation that was used in the discovery phase," Carr explained. "But instead of letting the instrument decide what to analyze, we tell the instrument, 'These are the masses for peptides that we either observed from differentially abundant proteins and/or are predicted to come from proteins that we observed to be differentially abundant.'"

During the discovery phase, mass spectrometry may not see all of the potential biomarker peptides or pull out the best possible markers, he added. But by using targeted methods that also incorporate information from predictive algorithms, researchers can up the chances of finding useful candidates.

After focusing in on the most promising markers using AIMS, the team quantified levels of this subset of candidate proteins in the blood of planned and spontaneous myocardial infarction cases using both an immunoassay as well as a quantitative multiple reaction monitoring (MRM) mass spec technique that employs stable, isotope-labeled peptides as internal standards.

Overall, the researchers detected 121 proteins that were differentially expressed in the coronary sinus samples in the first phase of the study — including 40 proteins that were differentially expressed in all three individuals tested either 10 minutes and/or an hour after the treatment and 81 that were differentially expressed in at least two of the individuals following treatment.

AIMS analyses of peptides corresponding to these proteins suggest that at least 52 of these could be detected in peripheral blood samples from the same individuals — information that researchers used to design quantitative stable isotope dilution MRM-MS-based assays.

The mass spectrometry-based pipeline was more sensitive than antibody-based approaches such as western blot and enzyme-linked immunosorbent assays for detecting some of the markers, the team reported, based on their analyses of 10 proteins for which antibodies were available.

Moreover, their follow-up experiments indicated that at least some of the markers are found at elevated levels in blood samples from individuals experiencing spontaneous heart attacks, Carr noted, even several hours after the heart attack has occurred. Coupled with data from the planned myocardial infarction patients, he added, that suggests the pipeline strategy could find markers that appear quite quickly after cardiovascular damage occurs and remain elevated after the event.

"This is what would qualify as an ideal marker — something that comes up within minutes after the event and stays up and is detected in the peripheral blood of that patient," Carr said.

The study authors explained that although their findings were specific to the cardiovascular conditions tested, "analytical methods and statistical approaches used should be generalizable to biomarker discovery and verification in any other diseases, particularly in real-world clinical scenarios where individuals serve as their own controls."

"This is going to be the best way to find real biomarkers," Carr added. "There's no doubt about it."

Down the road, the team plans to continue using this pipeline approach to assess biomarkers for heart attack as well as other cardiovascular conditions, cancer, and infectious diseases such as tuberculosis, HIV, and malaria.

In another Nature Biotechnology paper, meanwhile, researchers from the Fred Hutchinson Cancer Research Center in Seattle and the University of Pennsylvania used a comparable targeted mass spectrometry that relied on AIMS and another targeted method known as selected reaction monitoring, or SRM-MS, to sift through candidate biomarkers previously reported in a mouse model of breast cancer.

"The purpose of the study wasn't to find human relevant biomarkers," Paulovich told GWDN. "The purpose was to benchmark and develop a protocol or a roadmap that can be used to do this sort of work in humans.

"Using the animal model allowed us to do a very large scale study and test a large number of candidates," she added.

That study began with more than 1,900 candidate biomarkers from tumor tissue and/or blood samples reported in more than a dozen genomic and proteomic studies of the mouse breast cancer model, they explained, including 1,144 proteins that could be targeted by AIMS.

When they assessed pooled and fractionated blood samples from mice with tumors using AIMS and chromatography MS/MS, the researchers found 572 of these candidate markers.

From there, they narrowed in on a subset of candidate markers before doing more costly semi-quantitative SRM-MS and, finally, quantitative screening using two types of de novo assays: a quantitative SRM-MS assay and quantitative, immuno-SRM-MS assay.

"The pipeline was all about stacking the deck in our favor," Paulovich explained, "so that by the end when we invested in the final set of candidates, those were highly credentialed ... so they had a high probability of actually being real biomarkers."

Indeed, when they tested another group of mice with or without tumors, they found that 30 of the 57 quantitative-SRM-tested markers and six of the 31 biomarkers assessed using the immuno-SRM strategy turned up at higher levels in the 10 mice with tumors than in the ten control animals.

Twenty-nine quantitative-SRM-based markers and one quantitative immuno-SRM-based marker also showed an uptick in mice in mice with pre-clinical tumors, suggesting that they appear early in the disease process.

Now that they have tested the pipeline approach in an animal model, Paulovich and her colleagues are turning their attention to human samples, looking for blood markers for everything from lung and breast cancer to radiation exposure.

"Although the biological variation among humans will undoubtedly be greater than that among mice, the pre-analytic and analytic variations associated with the technologies are agnostic as to what species is used," the team wrote.

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