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Metabolomics Takes Its Place as Latest Up-and-Coming "Omic" Science

Charlie Schmidt

Since the emergence of genomics—which refers to global studies of gene expression—several other "omic" techniques have come to the fore, each promising great medical advances.

Among these latter-day omics are proteomics, global studies of protein expression, and transcriptomics, which are genome-wide studies of mRNA. But despite high expectations, an omic payoff in medicine has been slow in coming. Omic sciences are bogged down by technical limitations, database challenges, and exorbitant costs. Indeed, scientists concede that progress in these promising fields is likely to be slower and more tedious than was once expected.

Today, yet another omic science has begun to emerge: metabolomics, the study of global metabolite profiles in cells, tissues, and organisms. These profiles are typically generated with high-throughput nuclear magnetic resonance (NMR) spectroscopy and mass spectroscopy (MS). The extent to which the field is actually "new" is up for debate: Scientists have been using these analytical techniques to study metabolism for decades.

What apparently distinguishes metabolomics from these earlier efforts is a focus on complete metabolite profiles in a sample, rather than one or a few metabolites and associated pathways. These profiles are represented by analytical spectra, which are compared using statistical techniques such as pattern recognition. Ideally, metabolomic datasets will be combined with their other omic counterparts, providing complete views into the molecular pathways of systems biology.

Some scientists believe metabolomics offers more immediate clinical opportunities than its predecessors. But wary of omic promises, and already heavily vested in genomic and proteomic research, funding agencies are taking a "wait and see" approach to the field, supporting a few pilot projects before committing greater resources. The National Institutes of Health, for instance, in its new Roadmap, has an initiative devoted to metabolomics technology development, headed by the National Institute of Diabetes and Digestive and Kidney Diseases. Grants under this initiative will be funded later this year. In the meantime, unfunded scientists are working nights and weekends to produce results that could unleash greater support. "We’re working to show that metabolites in serum can be predictive for cancer and other diseases," said one scientist, Bruce Hammock, Ph.D., a professor in the Cancer Research Center at the University of California at Davis. "Once we get a few solid examples, we expect the agencies will put more money into this."

Most of the funding to date has come from the pharmaceutical industry, which supports the Consortium for Metabonomic Toxicology (COMET). This group of six major drug companies and Imperial College in London have expended tens of millions of dollars developing metabolite-based toxicity screens for drug development. (The term "metabonomics" is used at the urging of COMET’s co-director, Jeremy Nicholson, a professor at Imperial College who coined the term in the mid-1990s. Today, a debate over nomenclature simmers, with Nicholson and his colleagues publishing regularly under the "metabonomics" nomenclature. "Metabolomics," which bears greater resemblance to "metabolite," has emerged as the preferred term among NIH-affiliated scientists.)

An Emphasis on Biofluids

When discussing the clinical advantages of metabolomics, scientists point to the "real world" assessment of patient physiology that the metabolome (i.e., the collection of all metabolites in a biological system) provides. Unlike genes and proteins, which are "upstream" entities whose expression predicts cell functioning, metabolites reflect actual cellular conditions at the time of sampling.

Today, metabolomic scientists are interested chiefly in the analysis of biofluids such as urine and blood plasma. Biofluids can be obtained through noninvasive means, making them easy to sample, thus affording opportunities to study metabolites’ change over time. Researchers are hopeful that metabolite profiles will provide biomarkers for diagnostics and therapeutic monitoring. Ideally, these profiles will be linked back to their genetic origins, providing a more complete view of disease pathways.

The underlying question for cancer research is the extent to which metabolite signals produced by transformed cells and tumors are detectable in biofluids. In a now-infamous episode, ex–Harvard Medical School associate professor Eric Fossel, M.D., claimed in the mid-1980s to have identified malignant tumors based on their NMR spectra in blood plasma. However, researchers were never able to reproduce his results; Fossel himself was later shown to have falsified his data. The NIH eventually cited him for scientific misconduct in 1996.

Today, the cloud of this incident hangs over the field. But Bruce German, Ph.D., a University of California, Davis professor of food science and nutrition, suggested that technology advances have improved the outlook for biofluid analysis. "The informatic approaches are better, the NMR annotation is better, and the MS instrumentation is better," he said. "You’re still looking for a needle in a haystack with cancer, particularly early in its development. But we know that slight metabolic shifts in cancer cells have a ‘multiplier effect’ that creates an abundance of unusual metabolites. You could find some oligopolymers or conjugates that are modified on their way out of these cells."



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Dr. Bruce German

 
German said he doesn’t know if better technology will produce meaningful data. But he suggested the closer the link between the biofluid and the tissue of interest, the greater the diagnostic potential. Thus, for example, urine samples might disclose renal cancers, whereas saliva samples might disclose lung cancer.

Tumor Analysis

The keys to linking metabolic profiles to cancer lie with the sensitivity and specificity of the analytical instruments. If the sensitivity is too low, small molecules in low abundance may not be adequately detected. If the specificity is off, it may be impossible to isolate disease spectra from those produced by diet, environmental factors, and other influences. Some experts believe that despite state-of-the-art analysis, metabolic profiles in biofluids may be too far removed from solid tumors to be clinically meaningful. Natalie Serkova, Ph.D., assistant professor of anesthesiology and director of biomedical magnetic resonance imaging/magnetic resonance spectroscopy at the University of Colorado Health Sciences Center, Denver, suggested that initial metabolite explorations should focus on actual tumor biopsies. "The first thing should be a global, nonselective view of the metabolite profiles," she said. "Then, by applying the proper statistical analysis, you can distinguish the metabolites in cancerous and normal tissues. Finally, you can look for the biomarker in vivo."



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Dr. Natalie Serkova

 
Tumor analysis with solid-state NMR, once extremely challenging, is now achievable using "magic-angle spinning." This relatively new approach enables scientists to analyze small biopsy samples nondestructively; the tissues can then be histologically viewed. Metabolites linked to cancer that are identified in this way can then be assessed in patients by using magnetic resonance spectroscopy (MRS). This approach is increasingly used now, albeit with a limited number of metabolites. Levels of choline and citrate, for instance, which are metabolites that are elevated in several cancers, including prostate and brain cancer, can be analyzed in patients by using MRS.

Nonselective analysis of both tumors and biofluids may ultimately identify greater numbers of metabolites for study. Metabolite "fingerprints" generated by high-throughput analysis could provide broad contributions to the study of cancer, said Sara Nelson, Ph.D., professor of radiology at the University of California, San Francisco. Apart from diagnostics, the profiles could shed light on a tumor’s invasive potential or likelihood for metastasis. "I think the technology could provide entirely new scientific pathways that we can go off and explore," she said. "Wouldn’t it be nice to link downstream metabolic changes to genetic changes we believe are associated with cancer? We could apply this information to design in vivo spectroscopic experiments."

Database Needs

What is needed to realize this goal, experts say, are public databases that link NMR spectra to actual metabolites. Today, scientists working in genomics and proteomics consult databases such as GenBank or SwissProt to identify molecules by their physical properties. Metabolomic scientists have no such option. Rather, metabolites must be identified from spectra with a trained eye; the process can be painstaking and time-consuming. In some cases, the spectra themselves provides a fingerprint with some clinical value, particularly for toxicity screening, Nicholson said. But experts, including Nicholson, agreed that, to realize the field’s full potential, scientists must link the patterns back to biological mechanisms. Only by understanding a metabolite’s biological role can its relevance to disease—rather than a confounder such as diet or ethnicity—be conclusively determined. Furthermore, knowledge of metabolite biology is necessary to link spectrographic datasets with genomics and proteomics. This latter point emphasizes the extraordinary bioinformatic challenges associated not only with analyzing metabolomic data but also with linking it back to the greater universe of systems biology.

Today, metabolomics is in a proof-of-principle phase, said Rima Kaddurah-Daouk, Ph.D., a co-founder of Metabolon Inc. in Durham, N.C., and president of the new Metabolomics Society, a multidisciplinary group of experts promoting advances in the field. To unleash greater funding, Kaddurah-Daouk said, scientists must show that metabolomic techniques are robust, reproducible, and reliable. Furthermore, scientists must show that metabolomics can provide biomarkers that are useful for diagnosis and disease monitoring. "Metabolomics has to show it can be used to identify new therapeutic targets, streamline drug discovery, and identify the best drug candidates," she said. "We believe that metabolomics can help in all these respects, but we have to validate them one concept at a time."

If these challenges are met, the new field may ultimately prove its clinical value. But patience is a virtue; those looking for an immediate payoff are almost sure to be disappointed. Omic sciences generate vast reams of data; the computational challenge of isolating pathology from innumerable extraneous influences can hardly be underestimated. Nevertheless, the potential is there, experts say.

"I think there’s a huge potential here," said John Griffiths, MBBS, D. Phil, head of Basic Medical Sciences at St. George’s Hospital Medical School at London University. "The whole area of metabolism in cancer has been neglected in the last 30 to 40 years. There’s a great deal to be discovered by approaching metabolism in a unified way rather than focusing on individual pathways. We’re already starting to make some interesting discoveries."



             
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