E ditor - in - chief
editorial
William S. Hancock
Barnett Institute and Department of Chemistry Northeastern University 360 Huntington Avenue 341 Mugar Bldg. Boston, MA 02115 617-373-4881; fax 617-373-2855
[email protected] Associate E ditors Joshua LaBaer Harvard Medical School György Marko-Varga AstraZeneca and Lund University Cons u lting E ditor Jeremy Nicholson Imperial College London E ditorial adv isory board Ruedi H. Aebersold ETH Hönggerberg Leigh Anderson Plasma Proteome Institute Ettore Appella U.S. National Cancer Institute Rolf Apweiler European Bioinformatics Institute Ronald Beavis Manitoba Centre for Proteomics John J. M. Bergeron McGill University Richard Caprioli Vanderbilt University School of Medicine Christine Colvis U.S. National Institutes of Health R. Graham Cooks Purdue University Thomas E. Fehniger AstraZeneca Catherine Fenselau University of Maryland Daniel Figeys University of Ottawa Sam Hanash Fred Hutchinson Cancer Research Center Stanley Hefta Bristol-Myers Squibb Denis Hochstrasser University of Geneva Donald F. Hunt University of Virginia Barry L. Karger Northeastern University Daniel C. Liebler Vanderbilt University School of Medicine Matthias Mann Max Planck Institute of Biochemistry David Muddiman North Carolina State University Robert F. Murphy Carnegie Mellon University Gilbert S. Omenn University of Michigan Aran Paulus Bio-Rad Laboratories Jasna Peter-Katalini´c University of Muenster Ruth VanBogelen Pfizer Global Research & Development Peter Wagner Zyomyx Scot R. Weinberger GenNext Technologies Keith Williams Proteome Systems John R. Yates, III The Scripps Research Institute
© 2006 American Chemical Society
“Lewis and Clark” Proteomics
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ewis and Clark were great explorers in their time because of their ingenuity, instinct, tenacity, and willingness to take significant risks—along with the support and financial backing of the U.S. government. This is exactly the spirit that we, the scientific community, must embody when it comes to biomarker discovery. A monumental effort is under way to find predictive diagnostic and prognostic biomarkers for nearly every disease, exposure, and treatment that one could imagine. Various editorials and reports discuss how challenging and important this endeavor is, and, without question, we must pursue it! Yet the territory of proteomics is so vast—I would argue endless—that the talent required to carry out a successful biomarker exploration clearly goes beyond the boundaries of traditional expertise. Are we explorers like Lewis and Clark? Not yet, but we’ll get there! As with all editorials, this one has unstated limitations and assumptions that are never exhaustive. However, it is commonly accepted that we learn through repetition and by listening to different perspectives and making analogies based on concepts that we can grasp in a physical context. This is the motivation for this commentary.
Are we asking for too much too soon? A critical part of a biomarker discovery project is obtaining the clinical specimens on which all downstream analyses are based. Typically, an experiment has two sample groups: one for the disease under investigation and one for case controls. For example, a researcher who seeks biomarkers for early-stage ovarian cancer might have 50 case controls and 50 plasma samples from women who have early-stage ovarian cancer. This sample group is actually quite large, given the low prevalence of ovarian cancer, and thus, the biomarker discovery project seems very plausible and statistically sound. When one begins to consider each patient’s clinical data, however, far more than two groups exist within these 100 samples. Factors that might be important include the family history of cancers that affect women (e.g., ovarian, breast, uterine, and cervical cancers) and the patient’s body mass index, age, history of smoking, history of birth control and/or hormone replacement therapy, number of failed and successful pregnancies, immunization history, nutritional status, current medication, other medical conditions (e.g., diabetes), history of sexually transmitted diseases, menopausal status, and the stage of menstrual cycle when the sample was drawn (for premenopausal women). The number of factors that surely present themselves at some level in the plasma proteome is enormous. Furthermore, each sample represents only a single time point in a woman’s entire life, so no information can be derived about how the concentration of a particular biomarker changes in the short or long term. Moreover, the researcher does not know whether a candidate marker is specific for the disease under study, because it is simply not in the experimental design. Thus, regardless of which proteomics workflow is implemented, the study will be limited by the number of samples that have been analyzed. This is why the move toward national (or international) repositories with standardization is of fundamental importance. The finite resources at any single laboratory’s disposal are limiting factors in the search for biomarkers. Resources include clinicians to study a specific disease; skilled nurses to collect all of the pertinent information; pathologists to determine the stage of the disease; technologists, chemists, and biochemists to process and measure the plasma proteome; and bioinformaticians to reduce the raw data to a format that can subsequently be analyzed by statisticians. Employing this large team of highly trained professionals is a very costly endeavor—one that traditional funding mechanisms simply cannot support. We face other challenges, too: the significant number of proteomics workflows available, the inability to accurately define the weighting functions for each factor that gives rise to an individual’s plasma proteome, the paucity (often, the absence) of other disease-control samples, and the limited availability of early-stage samples for low-inJournal of Proteome Research • Vol. 5, No. 2, 2006 221
editorial cidence diseases. I think we should be thrilled and optimistic about the future of biomarker discovery, yet we also should be realistic. We have come quite far very fast, but the road ahead is steep, long, and serpentine, for sure. Researchers should be encouraged to publish new candidate biomarkers if the experiments are well designed; the details of each patient’s history are properly delineated; and the details of the sample processing, informatics, and statistical analysis are provided. To expect every study of a complex disease to be the “last word” would be highly contradictory to the scientific process itself. Even when well-defined controllable systems are studied over several decades, the last word has yet to come! Students who are interested in joining my research group have asked, “Do I need to find a new biomarker in order to graduate?” This is a very telling question. Simply put, their perception is that the expectations are too high. We risk discouraging these prospective students from entering into the field, from becoming our future explorers. My answer to these young, impressionable scientists is, “As long as you contribute new knowledge to science, you will always be viewed as significant. Finding a new biomarker for a given disease may be the ultimate goal, but you must realize that you may never actually reach it yourself. Your contributions, in some small way, will help others find a biomarker. It is not defeat to be a small part of a much larger contribution in science; it is reality!”
The sheer depth of the plasma proteome From a technological perspective, it is not hard to explain why this task of finding a biomarker in plasma for any disease is so difficult. Even aside from the tremendous biological variability of human beings versus the static nature of the sample being analyzed, the human plasma proteome is complex and chemically diverse and contains analytes at a wide range of concentrations. If we make an analogy between the difficulty of detecting proteins at various concentrations and distances traveled, then finding human serum albumin—the most abundant protein in plasma—is like traveling 1 mile to the grocery store or gas station. Most anyone could make this trip, and few people would question whether it was worthwhile. What is the distance one must travel to encounter the least abundant protein in plasma? This journey is very long indeed: One would have to travel around the earth at the equator about 400,000 times! How long would this quest take in a Boeing 747? About 2050 years, if we are flying at the earth’s surface and there is no need for refueling! This trip would require 65 billion gallons of fuel—equivalent to the amount of water that flows over Niagara Falls in a day. That much fuel would cost >$80 billion, which is approximately the total annual budget of the U.S. Department of Health and Human Services. Similar analogies could be made in terms of complexity and chemical diversity. Clearly, the prospect of finding biomarkers in plasma is plausible, but we must recognize that it will require significant resources and time.
location, or in the tumor itself and then work our way back into blood or urine as the final diagnostic specimen? The technology is very powerful and is advancing at a very rapid pace; but maybe we need to take the time to secure clinical materials first. Of course, they are potentially more relevant, but they also are much more difficult to obtain. Cell cultures, tissue cultures, and animal models certainly have limitations in terms of how well they represent human disease. However, their environments are significantly more homogeneous, and they can be readily studied longitudinally. In other words, we hope that these model systems, which are invaluable tools, continue to be included in the Roadmap Initiatives of the U.S. National Institutes of Health.
Concluding thoughts Exploring the terrain of proteomics is clearly a very costly and time-consuming endeavor. The elucidation of predictive biomarkers for disease is going to be a long journey for decades to come and will require highly skilled multidisciplinary teams to carefully and patiently implement fundamental new advances that are generated by a diverse range of research groups. Leaders in the field of biomarker discovery must be careful to not promise too much too soon, not overstate claims, and not create an exclusive community. More importantly, as we chart this new territory, we must continually devise standards for biomarker discovery, reward people for the significance of their findings (not for the numbers of papers published per funding cycle), and project optimism rather than frivolous hype. We need to create multidisciplinary teams that can nurture new talent—this will be the key for future success. Moreover, we should be careful to keep our expectations realistic and to test hypotheses rather than aim to prove them. The latter is far too common these days, and it should not be tolerated. It is my belief that a successful biomarker discovery platform will require significant integration of a diverse array of complex chemical and biochemical strategies to properly mine the plasma proteome. (Keep in mind that many of these strategies do not yet exist, and others have yet to be contemplated.) It goes without saying that the three keys to a truly great biomarker are validation, validation, and validation! Many newly discovered markers will fail at the validation stage, but that will not be defeat; again, it will be reality. Finally, as our toolbox for biomarker discovery gets bigger, we should lobby to have the resources that are generated in the course of our federally funded studies (e.g., novel chemistries, software, databases) made publicly available as soon as possible. A single laboratory cannot possibly develop, understand, and exploit everything de novo. Let us never forget who we are working for here: the human race—specifically, people who suffer from horrific diseases and need our help. The diverse range of scientists who direct their efforts toward biomarker discovery are blessed to have the intellect, creativity, and tax dollars to make a difference!
From cell culture to serological markers Maybe we are starting in the wrong place. What if we start our journey to discover biomarkers in cell culture, near the disease
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David C. Muddiman
