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      Advances in mass spectrometry-based clinical biomarker discovery

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          Abstract

          The greatest unmet needs in biomarker discovery are those discoveries that lead to the development of clinical diagnostic tests. These clinical diagnostic tests can provide early intervention when a patient would present otherwise healthy (e.g., cancer or cardiovascular disease) and aid clinical decision making with improved clinical outcomes. The past two decades have seen significant technological improvements in the analytical capabilities of mass spectrometers. Mass spectrometers are unique in that they can directly analyze any biological molecule susceptible to ionization. The biological studies of human metabolites and proteins using contemporary mass spectrometry technology (metabolomics and proteomics, respectively) has been ongoing for over a decade. Some of these studies have resulted in exciting insights into human biology. However, relatively few biomarkers have been translated into clinical tests. This review will discuss some key technological developments that have occurred over this time with an emphasis on technologies that will create new avenues for biomarker discovery.

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            Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression.

            Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.
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              Proteomic analysis of post-translational modifications.

              Post-translational modifications modulate the activity of most eukaryote proteins. Analysis of these modifications presents formidable challenges but their determination generates indispensable insight into biological function. Strategies developed to characterize individual proteins are now systematically applied to protein populations. The combination of function- or structure-based purification of modified 'subproteomes', such as phosphorylated proteins or modified membrane proteins, with mass spectrometry is proving particularly successful. To map modification sites in molecular detail, novel mass spectrometric peptide sequencing and analysis technologies hold tremendous potential. Finally, stable isotope labeling strategies in combination with mass spectrometry have been applied successfully to study the dynamics of modifications.
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                Author and article information

                Contributors
                chris.crutchfield@uc.edu
                sthoma92@jhmi.edu
                lsokoll@jhmi.edu
                dchan@jhmi.edu
                Journal
                Clin Proteomics
                Clin Proteomics
                Clinical Proteomics
                BioMed Central (London )
                1542-6416
                1559-0275
                7 January 2016
                7 January 2016
                2016
                : 13
                : 1
                Affiliations
                [ ]Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, MD 21287 USA
                [ ]Department of Pathology and Laboratory Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH 45219 USA
                Article
                9102
                10.1186/s12014-015-9102-9
                4705754
                26751220
                5cdb6739-7d0f-4449-96c4-797b04081c7b
                © Crutchfield et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 1 October 2015
                : 23 December 2015
                Categories
                Review
                Custom metadata
                © The author(s) 2016

                Molecular medicine
                mass spectrometry,biomarker,proteomics,clinical performance
                Molecular medicine
                mass spectrometry, biomarker, proteomics, clinical performance

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