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Proteomics to Play Important Role in Ten-Year U Penn-Led Study to Predict NSAID Risk and Response


An international group, spearheaded by the University of Pennsylvania, will spend the next decade scouring proteomic, genomic, and other data in animal models and humans to find signatures that can predict patients' response to nonsteroidal anti-inflammatory drugs for pain.

The group, titled the Personalized NSAID Therapeutics Consortium, or PENTACON, consists of 42 scientists from 22 institutions and is led by Garret FitzGerald, director of the Institute for Translational Medicine and Therapeutics at U Penn's Perelman School of Medicine. It will be funded with $18.5 million from the National Institutes of Health's National Heart, Lung, and Blood Institute.

FitzGerald told ProteoMonitor this week that proteomic and metabolomic experiments will play an important role in the project. He said the group is hoping the project's focus on the intersection of genes, proteins, and the environment will offer new insight into the biological context of NSAID effects, especially considering how much of the variance in analgesic response to the drugs, as well as patients' risk of serious cardiovascular side effects, remains unexplained by previous individual genomic or other 'omic studies.

"The hope would be to come out at the end of the day with information that could give you a profile, based on clinical information, genomic predisposition, proteomic signatures in accessible cells like monocytes perhaps, maybe epigenomic signals as well, and metabolomic response to drug exposure," he said.

"So you'd go to a doctor, and have samples taken – maybe before and after a test dose – and out of that would come information we could then slot into a predictive algorithm which would answer questions [that] patients and physicians are most interested in – whether someone should be on any of these drugs, and if so which one and how often."

The study is focused on finding ways to predict how patients will respond — either positively in terms of analgesic efficacy, or negatively in terms of dangerous side effects — to the two classes of NSAIDs, Cox-1, and Cox-2 inhibitors, and specifically the drugs naproxen and Celebrex.

Celebrex (celecoxib), a Cox-2 inhibitor marketed by Pfizer, is a cousin of the drug Vioxx, which was withdrawn from the market in 2004 due to increased risk of heart attack and stroke in some patients. Naproxen, which inhibits Cox-1, is associated with a higher risk of gastrointestinal bleeding in some patients than Celebrex, but has demonstrated no increased risk of heart attacks.

FitzGerald said the team is still making decisions about what proteomic and other technologies it plans to use in the study, which will look at five model systems — yeast, mammalian cells, mice, zebrafish, and humans — using as many 'omic approaches as are feasible in each experiment.

On the proteomics side, he said the group plans to use mass spectrometry, but he said with discussions ongoing among the investigators and potential commercial partners, there is no concrete plan to use a particular platform.

"Obviously proteomics is an absolutely intrinsic part of this across all [the model systems,]" FitzGerald said. "The main attraction being that it’s a relatively unbiased approach to signal detection."

"What we are really looking for is the convergence of the genomic information with proteomic expression data and consequent metabolomic response. It's where those things converge where we'll pay most attention," he said.

According to FitzGerald, the group will look for signatures that discriminate patient responses to Cox-2 and Cox-1 inhibition.

"We know the dominant pathways relative to analgesia and cardiovascular risk, but obviously those pathways are disrupted in the context of biological networks," he said. "The idea is that emanating from some of this 'omic data, de novo hypotheses may emerge in terms of prediction of analgesic response or cardiovascular risk. We would then test those hypotheses in the last part of the study prospectively in randomized trials in tailored populations."

The researchers plan to kick off the undertaking with a study using human samples, FitzGerald said. The group will examine retrospective samples from patients who have been on either a Cox-1 or Cox-2 inhibitor and who have or have not had a heart attack or stroke, to look for any discriminating genomic or proteomic signatures.

"It may not be particularly informative," he said, "but we may be fortunate."

At the same time, various arms of the project will begin looking at the animal model systems using pharmacological probes that preferentially inhibit Cox-2 or Cox-1, FitzGerald said. "We know a lot about the dominant pathway disturbance that occurs here … but what we really want to know is why only one to two percent of people have these [adverse] events."

"We understand how risk happens, but we want to know why it happens in some and not others – and the same on the analgesic side," he said.

According to Fitzgerald, smaller studies so far have only underscored that most of the variability in response to NSAIDs, as with drugs for many other common disorders, is likely contributed by environmental impacts on the genome or pathway intricacies that researchers do not yet understand.

"That's really the reason for having the proteomic and metabolomic readouts where you are unbiased in terms of what you might see," he said.

FitzGerald suggested that if the project is successful in identifying predictive signatures for either NSAID efficacy or risk, it may be possible to extrapolate the group's experience to other commonly used drug classes, like statins, used to treat conditions that likely represent a spectrum of molecular diseases rather than a single illness.

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