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Sample records for proteomics biomarker discovery

  1. Proteomic and metabolomic approaches to biomarker discovery

    CERN Document Server

    Issaq, Haleem J

    2013-01-01

    Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

  2. Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Mass Spectrometry–Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

    Science.gov (United States)

    Hawkridge, Adam M.; Muddiman, David C.

    2011-01-01

    Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry–based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed. PMID:20636062

  4. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Larry Gold

    2010-12-01

    Full Text Available The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma. Our current assay measures 813 proteins with low limits of detection (1 pM median, 7 logs of overall dynamic range (~100 fM-1 µM, and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD. We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states.We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

  5. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Science.gov (United States)

    Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

    2010-12-07

    The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma). Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (~100 fM-1 µM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.

  6. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  7. Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

    Directory of Open Access Journals (Sweden)

    Venugopal Abhilash

    2009-01-01

    Full Text Available Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS. Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

  8. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    Science.gov (United States)

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150

  9. Proteomics for discovery of candidate colorectal cancer biomarkers

    Science.gov (United States)

    Álvarez-Chaver, Paula; Otero-Estévez, Olalla; Páez de la Cadena, María; Rodríguez-Berrocal, Francisco J; Martínez-Zorzano, Vicenta S

    2014-01-01

    Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers. PMID:24744574

  10. Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery.

    Science.gov (United States)

    Krüger, Thomas; Lautenschläger, Janin; Grosskreutz, Julian; Rhode, Heidrun

    2013-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2-5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Proteomic Approaches in Biomarker Discovery: New Perspectives in Cancer Diagnostics

    Science.gov (United States)

    Kocevar, Nina; Komel, Radovan

    2014-01-01

    Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697

  12. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Directory of Open Access Journals (Sweden)

    Debasish Paul

    2013-01-01

    Full Text Available Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

  13. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Science.gov (United States)

    Paul, Debasish; Kumar, Avinash; Gajbhiye, Akshada; Santra, Manas K.; Srikanth, Rapole

    2013-01-01

    Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches. PMID:23586059

  14. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

    DEFF Research Database (Denmark)

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn

    2016-01-01

    and Results Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFr......Background Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. Methods.......6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin. Conclusion CE-MS based urine proteome analysis served as a sensitive tool...

  15. Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

    Science.gov (United States)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John; Oller Moreno, Sergio; Irincheeva, Irina; Valsesia, Armand; Astrup, Arne; Saris, Wim H M; Hager, Jörg; Kussmann, Martin; Dayon, Loïc

    2016-02-05

    The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

  16. Proteomic biomarker discovery in 1000 human plasma samples with mass spectrometry

    DEFF Research Database (Denmark)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John

    2016-01-01

    automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked...

  17. Role of proteomics in the discovery of autism biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Ayadhi, L. A.; Halepoto, D. M. [King Saud Univ., Riyadh (Saudi Arabia). Dept. of Physiology

    2013-02-15

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  18. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

    Ayadhi, L.A.; Halepoto, D.M.

    2013-01-01

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  19. Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Ahmed, Farid E

    2009-03-01

    Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

  20. Biomarker discovery and applications for foods and beverages: proteomics to nanoproteomics.

    Science.gov (United States)

    Agrawal, Ganesh Kumar; Timperio, Anna Maria; Zolla, Lello; Bansal, Vipul; Shukla, Ravi; Rakwal, Randeep

    2013-11-20

    Foods and beverages have been at the heart of our society for centuries, sustaining humankind - health, life, and the pleasures that go with it. The more we grow and develop as a civilization, the more we feel the need to know about the food we eat and beverages we drink. Moreover, with an ever increasing demand for food due to the growing human population food security remains a major concern. Food safety is another growing concern as the consumers prefer varied foods and beverages that are not only traded nationally but also globally. The 21st century science and technology is at a new high, especially in the field of biological sciences. The availability of genome sequences and associated high-throughput sensitive technologies means that foods are being analyzed at various levels. For example and in particular, high-throughput omics approaches are being applied to develop suitable biomarkers for foods and beverages and their applications in addressing quality, technology, authenticity, and safety issues. Proteomics are one of those technologies that are increasingly being utilized to profile expressed proteins in different foods and beverages. Acquired knowledge and protein information have now been translated to address safety of foods and beverages. Very recently, the power of proteomic technology has been integrated with another highly sensitive and miniaturized technology called nanotechnology, yielding a new term nanoproteomics. Nanoproteomics offer a real-time multiplexed analysis performed in a miniaturized assay, with low-sample consumption and high sensitivity. To name a few, nanomaterials - quantum dots, gold nanoparticles, carbon nanotubes, and nanowires - have demonstrated potential to overcome the challenges of sensitivity faced by proteomics for biomarker detection, discovery, and application. In this review, we will discuss the importance of biomarker discovery and applications for foods and beverages, the contribution of proteomic technology in

  1. Shotgun Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    W. Hayes McDonald

    2002-01-01

    Full Text Available Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC and multidimensional LC (LC/LC can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology, show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.

  2. Biomarkers: in medicine, drug discovery, and environmental health

    National Research Council Canada - National Science Library

    Vaidya, Vishal S; Bonventre, Joseph V

    2010-01-01

    ... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

  3. Mass Spectrometry-Based Biomarker Discovery.

    Science.gov (United States)

    Zhou, Weidong; Petricoin, Emanuel F; Longo, Caterina

    2017-01-01

    The discovery of candidate biomarkers within the entire proteome is one of the most important and challenging goals in proteomic research. Mass spectrometry-based proteomics is a modern and promising technology for semiquantitative and qualitative assessment of proteins, enabling protein sequencing and identification with exquisite accuracy and sensitivity. For mass spectrometry analysis, protein extractions from tissues or body fluids and subsequent protein fractionation represent an important and unavoidable step in the workflow for biomarker discovery. Following extraction of proteins, the protein mixture must be digested, reduced, alkylated, and cleaned up prior to mass spectrometry. The aim of our chapter is to provide comprehensible and practical lab procedures for sample digestion, protein fractionation, and subsequent mass spectrometry analysis.

  4. Revisiting biomarker discovery by plasma proteomics

    DEFF Research Database (Denmark)

    Geyer, Philipp E; Holdt, Lesca M; Teupser, Daniel

    2017-01-01

    slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker...

  5. Mass spectrometry for protein quantification in biomarker discovery.

    Science.gov (United States)

    Wang, Mu; You, Jinsam

    2012-01-01

    Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

  6. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction.

    Directory of Open Access Journals (Sweden)

    Kasper Rossing

    Full Text Available Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972 discriminated between HFrEF patients (N = 94, sensitivity = 93.6% and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%. Interestingly, HFrEF103 showed low sensitivity (12.6% in individuals with diastolic left ventricular dysfunction (N = 176. The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

  7. Mass spectrometry-based proteomic quest for diabetes biomarkers.

    Science.gov (United States)

    Shao, Shiying; Guo, Tiannan; Aebersold, Ruedi

    2015-06-01

    Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma.

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    Fujii, Kiyonaga; Nakamura, Haruhiko; Nishimura, Toshihide

    2017-04-01

    Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

  9. Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation.

    Science.gov (United States)

    Bhosale, Santosh D; Moulder, Robert; Kouvonen, Petri; Lahesmaa, Riitta; Goodlett, David R

    2017-01-01

    Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

  10. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

    Full Text Available The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

  11. Plasma proteomics to identify biomarkers - Application to cardiovascular diseases

    DEFF Research Database (Denmark)

    Beck, Hans Christian; Overgaard, Martin; Melholt Rasmussen, Lars

    2015-01-01

    There is an unmet need for new cardiovascular biomarkers. Despite this only few biomarkers for the diagnosis or screening of cardiovascular diseases have been implemented in the clinic. Thousands of proteins can be analysed in plasma by mass spectrometry-based proteomics technologies. Therefore......, this technology may therefore identify new biomarkers that previously have not been associated with cardiovascular diseases. In this review, we summarize the key challenges and considerations, including strategies, recent discoveries and clinical applications in cardiovascular proteomics that may lead...

  12. Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

    Full Text Available Abstract The field of proteomics has made leaps and bounds in the last 10 years particularly in the fields of oncology and cardiovascular medicine. In comparison, neuroproteomics is still playing catch up mainly due to the relative complexity of neurological disorders. Schizophrenia is one such disorder, believed to be the results of multiple factors both genetic and environmental. Affecting over 2 million people in the US alone, it has become a major clinical and public health concern worldwide. This paper gives an update of schizophrenia biomarker research as reviewed by Lakhan in 2006 and gives us a rundown of the progress made during the last two years. Several studies demonstrate the potential of cerebrospinal fluid as a source of neuro-specific biomarkers. Genetic association studies are making headway in identifying candidate genes for schizophrenia. In addition, metabonomics, bioinformatics, and neuroimaging techniques are aiming to complete the picture by filling in knowledge gaps. International cooperation in the form of genomics and protein databases and brain banks is facilitating research efforts. While none of the recent developments described here in qualifies as biomarker discovery, many are likely to be stepping stones towards that goal.

  13. Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

    Science.gov (United States)

    Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

    2004-01-01

    The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

  14. The application of mass-spectrometry-based protein biomarker discovery to theragnostics

    OpenAIRE

    Street, Jonathan M; Dear, James W

    2010-01-01

    Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed ‘theragnostics’). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

  15. Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

    Science.gov (United States)

    Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

    2015-11-01

    Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Exhaled Breath Condensate for Proteomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Sean W. Harshman

    2014-07-01

    Full Text Available Exhaled breath condensate (EBC has been established as a potential source of respiratory biomarkers. Compared to the numerous small molecules identified, the protein content of EBC has remained relatively unstudied due to the methodological and technical difficulties surrounding EBC analysis. In this review, we discuss the proteins identified in EBC, by mass spectrometry, focusing on the significance of those proteins identified. We will also review the limitations surrounding mass spectral EBC protein analysis emphasizing recommendations to enhance EBC protein identifications by mass spectrometry. Finally, we will provide insight into the future directions of the EBC proteomics field.

  17. Implementation of proteomic biomarkers: making it work

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John PA; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia

    2012-01-01

    While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. PMID:22519700

  18. Secreted proteins as a fundamental source for biomarker discovery

    Czech Academy of Sciences Publication Activity Database

    Šťastná, Miroslava; Van Eyk, J.E.

    2012-01-01

    Roč. 12, 4-5 (2012), s. 722-735 ISSN 1615-9853 Institutional research plan: CEZ:AV0Z40310501 Keywords : conditioned media * secreted proteins * proteomics * biomarker discovery Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 4.132, year: 2012

  19. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.

    2015-12-04

    Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.

  20. Biomarkers in Alzheimer’s Disease Analysis by Mass Spectrometry-Based Proteomics

    Directory of Open Access Journals (Sweden)

    Yahui Liu

    2014-05-01

    Full Text Available Alzheimer’s disease (AD is a common chronic and destructive disease. The early diagnosis of AD is difficult, thus the need for clinically applicable biomarkers development is growing rapidly. There are many methods to biomarker discovery and identification. In this review, we aim to summarize Mass spectrometry (MS-based proteomics studies on AD and discuss thoroughly the methods to identify candidate biomarkers in cerebrospinal fluid (CSF and blood. This review will also discuss the potential research areas on biomarkers.

  1. Implementation of proteomic biomarkers: making it work.

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John P A; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia

    2012-09-01

    While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. © 2012 The Authors. European Journal of Clinical Investigation © 2012 Stichting European Society for Clinical Investigation Journal Foundation.

  2. Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

    Science.gov (United States)

    Parker, Carol E; Borchers, Christoph H

    2014-06-01

    In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  3. A Pilot Proteomic Analysis of Salivary Biomarkers in Autism Spectrum Disorder.

    Science.gov (United States)

    Ngounou Wetie, Armand G; Wormwood, Kelly L; Russell, Stefanie; Ryan, Jeanne P; Darie, Costel C; Woods, Alisa G

    2015-06-01

    Autism spectrum disorder (ASD) prevalence is increasing, with current estimates at 1/68-1/50 individuals diagnosed with an ASD. Diagnosis is based on behavioral assessments. Early diagnosis and intervention is known to greatly improve functional outcomes in people with ASD. Diagnosis, treatment monitoring and prognosis of ASD symptoms could be facilitated with biomarkers to complement behavioral assessments. Mass spectrometry (MS) based proteomics may help reveal biomarkers for ASD. In this pilot study, we have analyzed the salivary proteome in individuals with ASD compared to neurotypical control subjects, using MS-based proteomics. Our goal is to optimize methods for salivary proteomic biomarker discovery and to identify initial putative biomarkers in people with ASDs. The salivary proteome is virtually unstudied in ASD, and saliva could provide an easily accessible biomaterial for analysis. Using nano liquid chromatography-tandem mass spectrometry, we found statistically significant differences in several salivary proteins, including elevated prolactin-inducible protein, lactotransferrin, Ig kappa chain C region, Ig gamma-1 chain C region, Ig lambda-2 chain C regions, neutrophil elastase, polymeric immunoglobulin receptor and deleted in malignant brain tumors 1. Our results indicate that this is an effective method for identification of salivary protein biomarkers, support the concept that immune system and gastrointestinal disturbances may be present in individuals with ASDs and point toward the need for larger studies in behaviorally-characterized individuals. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  4. Discovery of prognostic biomarker candidates of lacunar infarction by quantitative proteomics of microvesicles enriched plasma.

    Directory of Open Access Journals (Sweden)

    Arnab Datta

    Full Text Available Lacunar infarction (LACI is a subtype of acute ischemic stroke affecting around 25% of all ischemic stroke cases. Despite having an excellent recovery during acute phase, certain LACI patients have poor mid- to long-term prognosis due to the recurrence of vascular events or a decline in cognitive functions. Hence, blood-based biomarkers could be complementary prognostic and research tools.Plasma was collected from forty five patients following a non-disabling LACI along with seventeen matched control subjects. The LACI patients were monitored prospectively for up to five years for the occurrence of adverse outcomes and grouped accordingly (i.e., LACI-no adverse outcome, LACI-recurrent vascular event, and LACI-cognitive decline without any recurrence of vascular events. Microvesicles-enriched fractions isolated from the pooled plasma of four groups were profiled by an iTRAQ-guided discovery approach to quantify the differential proteome. The data have been deposited to the ProteomeXchange with identifier PXD000748. Bioinformatics analysis and data mining revealed up-regulation of brain-specific proteins including myelin basic protein, proteins of coagulation cascade (e.g., fibrinogen alpha chain, fibrinogen beta chain and focal adhesion (e.g., integrin alpha-IIb, talin-1, and filamin-A while albumin was down-regulated in both groups of patients with adverse outcome.This data set may offer important insight into the mechanisms of poor prognosis and provide candidate prognostic biomarkers for validation on larger cohort of individual LACI patients.

  5. Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

    DEFF Research Database (Denmark)

    Kristiansen, Troels Zakarias; Harsha, H C; Grønborg, Mads

    2008-01-01

    Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based...

  6. Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue

    NARCIS (Netherlands)

    N.Q. Liu (Ning Qing); R.B.H. Braakman (René); C. Stingl (Christoph); T.M. Luider (Theo); J.W.M. Martens (John); J.A. Foekens (John); A. Umar (Arzu)

    2012-01-01

    textabstractMass spectrometry (MS)-based label-free proteomics offers an unbiased approach to screen biomarkers related to disease progression and therapy-resistance of breast cancer on the global scale. However, multi-step sample preparation can introduce large variation in generated data, while

  7. Novel TIA biomarkers identified by mass spectrometry-based proteomics.

    Science.gov (United States)

    George, Paul M; Mlynash, Michael; Adams, Christopher M; Kuo, Calvin J; Albers, Gregory W; Olivot, Jean-Marc

    2015-12-01

    Transient ischemic attacks remain a clinical diagnosis with significant variability between physicians. Finding reliable biomarkers to identify transient ischemic attacks would improve patient care and optimize treatment. Our aim is to identify novel serum TIA biomarkers through the use of mass spectroscopy-based proteomics. Patients with transient neurologic symptoms were prospectively enrolled. Mass spectrometry-based proteomics, an unbiased method to identify candidate proteins, was used to test the serum of the patients for biomarkers of cerebral ischemia. Three candidate proteins were found, and serum concentrations of these proteins were measured by enzyme-linked immunosorbent assay in a second cohort of prospectively enrolled patients. The Student's t-test was used for comparison. The Benjamini-Hochberg false discovery rate controlling procedure for multiple comparison adjustments determined significance for the proteomic screen. Patients with transient ischemic attacks (n = 20), minor strokes (n = 15), and controls (i.e. migraine, seizure, n = 12) were enrolled in the first cohort. Ceruloplasmin, complement component C8 gamma (C8γ), and platelet basic protein were significantly different between the ischemic group (transient ischemic attack and minor stroke) and the controls (P = 0·0001, P = 0·00027, P = 0·00105, respectively). A second cohort of patients with transient ischemic attack (n = 22), minor stroke (n = 20), and controls' (n = 12) serum was enrolled. Platelet basic protein serum concentrations were increased in the ischemic samples compared with control (for transient ischemic attack alone, P = 0·019, for the ischemic group, P = 0·046). Ceruloplasmin trended towards increased concentrations in the ischemic group (P = 0·127); no significant difference in C8γ (P = 0·44) was found. Utilizing mass spectrometry-based proteomics, platelet basic protein has been identified as a candidate serum

  8. Novel ageing-biomarker discovery using data-intensive technologies.

    Science.gov (United States)

    Griffiths, H R; Augustyniak, E M; Bennett, S J; Debacq-Chainiaux, F; Dunston, C R; Kristensen, P; Melchjorsen, C J; Navarrete, Santos A; Simm, A; Toussaint, O

    2015-11-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for biomarker discovery; (1) microarray analyses and/or proteomics in cell systems e.g. endothelial progenitor cells or T cell ageing including a stress model; and (2) investigation of cellular material and plasma directly from tightly-defined proband subsets of different ages using proteomic, transcriptomic and miR array. The first approach provided longitudinal insight into endothelial progenitor and T cell ageing. This review describes the strategy and use of hypothesis-free, data-intensive approaches to explore cellular proteins, miR, mRNA and plasma proteins as healthy ageing biomarkers, using ageing models and directly within samples from adults of different ages. It considers the challenges associated with integrating multiple models and pilot studies as rational biomarkers for a large cohort study. From this approach, a number of high-throughput methods were developed to evaluate novel, putative biomarkers of ageing in the MARK-AGE cohort. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

  9. Proteomic Biomarkers for Spontaneous Preterm Birth

    DEFF Research Database (Denmark)

    Kacerovsky, Marian; Lenco, Juraj; Musilova, Ivana

    2014-01-01

    This review aimed to identify, synthesize, and analyze the findings of studies on proteomic biomarkers for spontaneous preterm birth (PTB). Three electronic databases (Medline, Embase, and Scopus) were searched for studies in any language reporting the use of proteomic biomarkers for PTB published...

  10. Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers

    LENUS (Irish Health Repository)

    Dakna, Mohammed

    2010-12-10

    Abstract Background The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of sets of clinically relevant biomarkers. As tractable example we define the measurable proteomic differences between apparently healthy adult males and females. We choose urine as body-fluid of interest and CE-MS, a thoroughly validated platform technology, allowing for routine analysis of a large number of samples. The second urine of the morning was collected from apparently healthy male and female volunteers (aged 21-40) in the course of the routine medical check-up before recruitment at the Hannover Medical School. Results We found that the Wilcoxon-test is best suited for the definition of potential biomarkers. Adjustment for multiple testing is necessary. Sample size estimation can be performed based on a small number of observations via resampling from pilot data. Machine learning algorithms appear ideally suited to generate classifiers. Assessment of any results in an independent test-set is essential. Conclusions Valid proteomic biomarkers for diagnosis and prognosis only can be defined by applying proper statistical data mining procedures. In particular, a justification of the sample size should be part of the study design.

  11. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  12. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Energy Technology Data Exchange (ETDEWEB)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar; Baker, Erin M.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2018-05-01

    Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements

  13. Urine Proteomics in the Era of Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Ashley Beasley-Green

    2016-11-01

    Full Text Available With the technological advances of mass spectrometry (MS-based platforms, clinical proteomics is one of the most rapidly growing areas in biomedical research. Urine proteomics has become a popular subdiscipline of clinical proteomics because it is an ideal source for the discovery of noninvasive disease biomarkers. The urine proteome offers a comprehensive view of the local and systemic physiology since the proteome is primarily composed of proteins/peptides from the kidneys and plasma. The emergence of MS-based proteomic platforms as prominent bioanalytical tools in clinical applications has enhanced the identification of protein-based urinary biomarkers. This review highlights the characteristics of urine that make it an attractive biofluid for biomarker discovery and the impact of MS-based technologies on the clinical assessment of urinary protein biomarkers.

  14. Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation.

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

    Full Text Available Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS for CSF biomarker discovery by (1 identifying reparable sources of technical variability, (2 assessing subject variance and residual technical variability for numerous CSF proteins, and (3 testing its ability to segregate samples on the basis of desired biomarker characteristics.Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i incomplete MAF and keratins; ii globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5% whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and

  15. Application of Fluorescence Two-Dimensional Difference In-Gel Electrophoresis as a Proteomic Biomarker Discovery Tool in Muscular Dystrophy Research

    Science.gov (United States)

    Carberry, Steven; Zweyer, Margit; Swandulla, Dieter; Ohlendieck, Kay

    2013-01-01

    In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue. PMID:24833232

  16. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer.

    Directory of Open Access Journals (Sweden)

    Rachel M Ostroff

    Full Text Available BACKGROUND: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. CONCLUSIONS/SIGNIFICANCE: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels

  17. Approach to cerebrospinal fluid (CSF) biomarker discovery and evaluation in HIV infection.

    Science.gov (United States)

    Price, Richard W; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena; Smith, Richard D; Jacobs, Jon M; Brown, Joseph N; Gisslen, Magnus

    2013-12-01

    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previously-defined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  18. Approach to Cerebrospinal Fluid (CSF) Biomarker Discovery and Evaluation in HIV Infection

    Energy Technology Data Exchange (ETDEWEB)

    Price, Richard W.; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E.; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena S.; Smith, Richard D.; Jacobs, Jon M.; Brown, Joseph N.; Gisslen, Magnus

    2013-12-13

    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previouslydefined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  19. Candidate proteomic biomarkers for non-alcoholic fatty liver disease (steatosis and non-alcoholic steatohepatitis) discovered with mass-spectrometry: a systematic review.

    Science.gov (United States)

    Lădaru, Anca; Bălănescu, Paul; Stan, Mihaela; Codreanu, Ioana; Anca, Ioana Alina

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is characterized by lipid accumulation in the liver which is accompanied by a series of metabolic deregulations. There are sustained research efforts focusing upon biomarker discovery for NAFLD diagnosis and its prognosis in order investigate and follow-up patients as minimally invasive as possible. The objective of this study is to critically review proteomic studies that used mass spectrometry techniques and summarize relevant proteomic NAFLD candidate biomarkers. Medline and Embase databases were searched from inception to December 2014. A final number of 22 records were included that identified 251 candidate proteomic biomarkers. Thirty-three biomarkers were confirmed - 14 were found in liver samples, 21 in serum samples, and two from both serum and liver samples. Some of the biomarkers identified have already been extensively studied regarding their diagnostic and prognostic capacity. However, there are also more potential biomarkers that still need to be addressed in future studies.

  20. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Science.gov (United States)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2017-09-01

    In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

  1. Mass spectrometry for biomarker development

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Chaochao; Liu, Tao; Baker, Erin Shammel; Rodland, Karin D.; Smith, Richard D.

    2015-06-19

    Biomarkers potentially play a crucial role in early disease diagnosis, prognosis and targeted therapy. In the past decade, mass spectrometry based proteomics has become increasingly important in biomarker development due to large advances in technology and associated methods. This chapter mainly focuses on the application of broad (e.g. shotgun) proteomics in biomarker discovery and the utility of targeted proteomics in biomarker verification and validation. A range of mass spectrometry methodologies are discussed emphasizing their efficacy in the different stages in biomarker development, with a particular emphasis on blood biomarker development.

  2. Systemic sclerosis biomarkers discovered using mass-spectrometry-based proteomics: a systematic review.

    Science.gov (United States)

    Bălănescu, Paul; Lădaru, Anca; Bălănescu, Eugenia; Băicuş, Cristian; Dan, Gheorghe Andrei

    2014-08-01

    Systemic sclerosis (SSc) is an autoimmune disease with incompletely known physiopathology. There is a great challenge to predict its course and therapeutic response using biomarkers. To critically review proteomic biomarkers discovered from biological specimens from systemic sclerosis patients using mass spectrometry technologies. Medline and Embase databases were searched in February 2014. Out of the 199 records retrieved, a total of 20 records were included, identifying 116 candidate proteomic biomarkers. Research in SSc proteomic biomarkers should focus on biomarker validation, as there are valuable mass-spectrometry proteomics studies in the literature.

  3. Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

    Science.gov (United States)

    Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

    2014-07-01

    Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

  4. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  5. Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.

    Science.gov (United States)

    Galazis, Nicolas; Olaleye, Olalekan; Haoula, Zeina; Layfield, Robert; Atiomo, William

    2012-12-01

    To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS). Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS. Academic department of obstetrics and gynecology in the United Kingdom. A total of 180 women identified in the six studies. Tissue samples from women with OC vs. tissue samples from women without OC. Proteomic biomarkers, proteomic technique used, and methodologic quality score. A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2. These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  6. Overlap of proteomics biomarkers between women with pre-eclampsia and PCOS: a systematic review and biomarker database integration.

    Science.gov (United States)

    Khan, Gulafshana Hafeez; Galazis, Nicolas; Docheva, Nikolina; Layfield, Robert; Atiomo, William

    2015-01-01

    Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. A systematic review and update of our PCOS proteomic biomarker database was performed, along with a parallel review of PE biomarkers. The study included papers from 1980 to December 2013. In all the studies analysed, there were a total of 1423 patients and controls. The number of proteomic biomarkers that were catalogued for PE was 192. Five proteomic biomarkers were shown to be differentially expressed in women with PE and PCOS when compared with controls: transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. In PE, the biomarkers were identified in serum, plasma and placenta and in PCOS, the biomarkers were identified in serum, follicular fluid, and ovarian and omental biopsies. The techniques employed to detect proteomics have limited ability in identifying proteins that are of low abundance, some of which may have a diagnostic potential. The sample sizes and number of biomarkers identified from these studies do not exclude the risk of false positives, a limitation of all biomarker studies. The biomarkers common to PE and PCOS were identified from proteomic analyses of different tissues. This data amalgamation of the proteomic studies in PE and in PCOS, for the first time, discovered a panel of five biomarkers for PE which are common to women with PCOS, including transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. If validated, these biomarkers could provide a useful framework for the knowledge infrastructure in this area. To accomplish this goal, a

  7. Implementation of proteomic biomarkers : Making it work

    NARCIS (Netherlands)

    Mischak, Harald; Ioannidis, John P. A.; Argiles, Angel; Attwood, Teresa K.; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P.; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W.; Julien, Bruce A.; Lankisch, Tim; Leung, Hing Y.; Maahs, David; Magni, Fulvio; Manns, Michael P.; Manolis, Efthymios; Mayer, Gert; Navis, Gerarda; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H.; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P.; Vlahou, Antonia

    Eur J Clin Invest 2012; 42 (9): 10271036 Abstract While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe

  8. Major depressive disorder: insight into candidate cerebrospinal fluid protein biomarkers from proteomics studies.

    Science.gov (United States)

    Al Shweiki, Mhd Rami; Oeckl, Patrick; Steinacker, Petra; Hengerer, Bastian; Schönfeldt-Lecuona, Carlos; Otto, Markus

    2017-06-01

    Major Depressive Disorder (MDD) is the leading cause of global disability, and an increasing body of literature suggests different cerebrospinal fluid (CSF) proteins as biomarkers of MDD. The aim of this review is to summarize the suggested CSF biomarkers and to analyze the MDD proteomics studies of CSF and brain tissues for promising biomarker candidates. Areas covered: The review includes the human studies found by a PubMed search using the following terms: 'depression cerebrospinal fluid biomarker', 'major depression biomarker CSF', 'depression CSF biomarker', 'proteomics depression', 'proteomics biomarkers in depression', 'proteomics CSF biomarker in depression', and 'major depressive disorder CSF'. The literature analysis highlights promising biomarker candidates and demonstrates conflicting results on others. It reveals 42 differentially regulated proteins in MDD that were identified in more than one proteomics study. It discusses the diagnostic potential of the biomarker candidates and their association with the suggested pathologies. Expert commentary: One ultimate goal of finding biomarkers for MDD is to improve the diagnostic accuracy to achieve better treatment outcomes; due to the heterogeneous nature of MDD, using bio-signatures could be a good strategy to differentiate MDD from other neuropsychiatric disorders. Notably, further validation studies of the suggested biomarkers are still needed.

  9. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity

    International Nuclear Information System (INIS)

    Amacher, David E.

    2010-01-01

    Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in

  10. The use of time-resolved fluorescence in gel-based proteomics for improved biomarker discovery

    Science.gov (United States)

    Sandberg, AnnSofi; Buschmann, Volker; Kapusta, Peter; Erdmann, Rainer; Wheelock, Åsa M.

    2010-02-01

    This paper describes a new platform for quantitative intact proteomics, entitled Cumulative Time-resolved Emission 2-Dimensional Gel Electrophoresis (CuTEDGE). The CuTEDGE technology utilizes differences in fluorescent lifetimes to subtract the confounding background fluorescence during in-gel detection and quantification of proteins, resulting in a drastic improvement in both sensitivity and dynamic range compared to existing technology. The platform is primarily designed for image acquisition in 2-dimensional gel electrophoresis (2-DE), but is also applicable to 1-dimensional gel electrophoresis (1-DE), and proteins electroblotted to membranes. In a set of proof-of-principle measurements, we have evaluated the performance of the novel technology using the MicroTime 100 instrument (PicoQuant GmbH) in conjunction with the CyDye minimal labeling fluorochromes (GE Healthcare, Uppsala, Sweden) to perform differential gel electrophoresis (DIGE) analyses. The results indicate that the CuTEDGE technology provides an improvement in the dynamic range and sensitivity of detection of 3 orders of magnitude as compared to current state-of-the-art image acquisition instrumentation available for 2-DE (Typhoon 9410, GE Healthcare). Given the potential dynamic range of 7-8 orders of magnitude and sensitivities in the attomol range, the described invention represents a technological leap in detection of low abundance cellular proteins, which is desperately needed in the field of biomarker discovery.

  11. Differential Proteomics Identification of HSP90 as Potential Serum Biomarker in Hepatocellular Carcinoma by Two-dimensional Electrophoresis and Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Yiyi Sun

    2010-03-01

    Full Text Available The aim of the current study is to identify the potential biomarkers involved in Hepatocellular carcinoma (HCC carcinogenesis. A comparative proteomics approach was utilized to identify the differentially expressed proteins in the serum of 10 HCC patients and 10 controls. A total of 12 significantly altered proteins were identified by mass spectrometry. Of the 12 proteins identified, HSP90 was one of the most significantly altered proteins and its over-expression in the serum of 20 HCC patients was confirmed using ELISA analysis. The observations suggest that HSP90 might be a potential biomarker for early diagnosis, prognosis, and monitoring in the therapy of HCC. This work demonstrates that a comprehensive strategy of proteomic identification combined with further validation should be adopted in the field of cancer biomarker discovery.

  12. Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Duijvesz, Diederick; Burnum-Johnson, Kristin E.; Gritsenko, Marina A.; Hoogland, Marije; Vredenbregt-van den Berg, Mirella S.; Willemsen, Rob; Luider, Theo N.; Pasa-Tolic, Ljiljana; Jenster, Guido

    2013-12-31

    Introduction: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, biomarker discovery from body fluids is often hampered by the high abundance of many proteins unrelated to disease. An attractive alternative biomarker discovery approach is the isolation of small vesicles (exosomes, ~100 nm). They contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific marker discovery. Profiling prostate cancer-derived exosomes could reveal new markers for this malignancy. Materials and Methods: Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. Proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode, followed by the Accurate Mass and Time (AMT) tag approach. Exosomal proteins were validated by Western blotting. A Tissue Micro Array, containing 481 different PCa samples (radical prostatectomy), was used to correlate candidate markers with several clinical-pathological parameters such as PSA, Gleason score, biochemical recurrence, and (PCa-related) death. Results: Proteomic characterization resulted in the identification of 263 proteins by at least 2 peptides. Specifically analysis of exosomes from PNT2C2, RWPE-1, PC346C, and VCaP identified 248, 233, 169, and 216 proteins, respectively. Statistical analyses revealed 52 proteins differently expressed between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes. The Tissue Micro 4 Array showed strong correlation of higher Gleason scores and local recurrence with increased cytoplasmic XPO1 (P<0.001). Conclusions: Differentially abundant proteins of cell line-derived exosomes make a clear subdivision between

  13. Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

    Science.gov (United States)

    Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

    2016-08-18

    A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed

  14. Bayesian methods for proteomic biomarker development

    Directory of Open Access Journals (Sweden)

    Belinda Hernández

    2015-12-01

    In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.

  15. Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery.

    Science.gov (United States)

    Quanico, Jusal; Franck, Julien; Wisztorski, Maxence; Salzet, Michel; Fournier, Isabelle

    2017-01-01

    Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

  16. Emerging Concepts and Methodologies in Cancer Biomarker Discovery.

    Science.gov (United States)

    Lu, Meixia; Zhang, Jinxiang; Zhang, Lanjing

    2017-01-01

    Cancer biomarker discovery is a critical part of cancer prevention and treatment. Despite the decades of effort, only a small number of cancer biomarkers have been identified for and validated in clinical settings. Conceptual and methodological breakthroughs may help accelerate the discovery of additional cancer biomarkers, particularly their use for diagnostics. In this review, we have attempted to review the emerging concepts in cancer biomarker discovery, including real-world evidence, open access data, and data paucity in rare or uncommon cancers. We have also summarized the recent methodological progress in cancer biomarker discovery, such as high-throughput sequencing, liquid biopsy, big data, artificial intelligence (AI), and deep learning and neural networks. Much attention has been given to the methodological details and comparison of the methodologies. Notably, these concepts and methodologies interact with each other and will likely lead to synergistic effects when carefully combined. Newer, more innovative concepts and methodologies are emerging as the current emerging ones became mainstream and widely applied to the field. Some future challenges are also discussed. This review contributes to the development of future theoretical frameworks and technologies in cancer biomarker discovery and will contribute to the discovery of more useful cancer biomarkers.

  17. Mass Spectrometry for Translational Proteomics: Progress and Clinical Implications

    Energy Technology Data Exchange (ETDEWEB)

    Baker, Erin Shammel; Liu, Tao; Petyuk, Vladislav A.; Burnum-Johnson, Kristin E.; Ibrahim, Yehia M.; Anderson, Gordon A.; Smith, Richard D.

    2012-08-31

    Mass spectrometry (MS)-based proteomics measurements have become increasingly utilized in a wide range of biological and biomedical applications, and have significantly enhanced the understanding of the complex and dynamic nature of the proteome and its connections to biology and diseases. While some MS techniques such as those for targeted analysis are increasingly applied with great success, others such as global quantitative analysis (for e.g. biomarker discovery) are more challenging and continue to be developed and refined to provide the desired throughput, sensitivity and/ or specificity. New MS capabilities and proteomics-based pipelines/strategies also keep enhancing for the advancement of clinical proteomics applications such as protein biomarker discovery and validation. Herein, we provide a brief review to summarize the current state of MS-based proteomics with respect to its advantages and present limitations, while highlighting its potential in future clinical applications.

  18. Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review.

    Science.gov (United States)

    Nicolaou, Orthodoxia; Kousios, Andreas; Hadjisavvas, Andreas; Lauwerys, Bernard; Sokratous, Kleitos; Kyriacou, Kyriacos

    2017-05-01

    Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry-based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Twenty-five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  19. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Astrid Wachter

    2015-11-01

    Full Text Available Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

  20. The potential biomarkers of drug addiction: proteomic and metabolomics challenges.

    Science.gov (United States)

    Wang, Lv; Wu, Ning; Zhao, Tai-Yun; Li, Jin

    2016-07-28

    Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

  1. Biomarker discovery in low-grade breast cancer using isobaric stable isotope tags and two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS) based quantitative proteomic analysis.

    Science.gov (United States)

    Bouchal, Pavel; Roumeliotis, Theodoros; Hrstka, Roman; Nenutil, Rudolf; Vojtesek, Borivoj; Garbis, Spiros D

    2009-01-01

    The present pilot study constitutes a proof-of-principle in the use of a quantitative LC-MS/MS based proteomic method for the comparative analysis of representative low-grade breast primary tumor tissues with and without metastases and metastasis in lymph node relative to the nonmetastatic tumor type. The study method incorporated iTRAQ stable isotope labeling, two-dimensional liquid chromatography, nanoelectrospray ionization and high resolution tandem mass spectrometry using the hybrid QqTOF platform (iTRAQ-2DLC-MS/MS). The principal aims of this study were (1) to define the protein spectrum obtainable using this approach, and (2) to highlight potential candidates for verification and validation studies focused on biomarkers involved in metastatic processes in breast cancer. The study resulted in the reproducible identification of 605 nonredundant proteins (p biomarker discovery program.

  2. Integrative analysis to select cancer candidate biomarkers to targeted validation

    Science.gov (United States)

    Heberle, Henry; Domingues, Romênia R.; Granato, Daniela C.; Yokoo, Sami; Canevarolo, Rafael R.; Winck, Flavia V.; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Filgueiras, Paulo R.; Cruz, Karen S. P.; Barbuto, José Alexandre; Poppi, Ronei J.; Minghim, Rosane; Telles, Guilherme P.; Fonseca, Felipe Paiva; Fox, Jay W.; Santos-Silva, Alan R.; Coletta, Ricardo D.; Sherman, Nicholas E.; Paes Leme, Adriana F.

    2015-01-01

    Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS. PMID:26540631

  3. Mass spectrometry in biomarker applications: from untargeted discovery to targeted verification, and implications for platform convergence and clinical application

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Richard D.

    2012-03-01

    It is really only in the last ten years that mass spectrometry (MS) has had a truly significant (but still small) impact on biomedical research. Much of this impact can be attributed to proteomics and its more basic applications. Early biomedical applications have included a number of efforts aimed at developing new biomarkers; however, the success of these endeavors to date have been quite modest - essentially confined to preclinical applications - and have often suffered from combinations of immature technology and hubris. Now that MS-based proteomics is reaching adolescence, it is appropriate to ask if and when biomarker-related applications will extend to the clinical realm, and what developments will be essential for this transition. Biomarker development can be described as a multistage process consisting of discovery, qualification, verification, research assay optimization, validation, and commercialization (1). From a MS perspective, it is possible to 'bin' measurements into 1 of 2 categories - those aimed at discovering potential protein biomarkers and those seeking to verify and validate biomarkers. Approaches in both categories generally involve digesting proteins (e.g., with trypsin) as a first step to yield peptides that can be effectively detected and identified with MS. Discovery-based approaches use broad 'unbiased' or 'undirected' measurements that attempt to cover as many proteins as possible in the hope of revealing promising biomarker candidates. A key challenge with this approach stems from the extremely large dynamic range (i.e., relative stoichiometry) of proteins of potential interest in biofluids such as plasma and the expectation that biomarker proteins of the greatest clinical value for many diseases may very well be present at low relative abundances (2). Protein concentrations in plasma extend from approximately 10{sup 10} pg/mL for albumin to approximately 10 pg/mL and below for interleukins and other

  4. Proteomic analyses of host and pathogen responses during bovine mastitis.

    Science.gov (United States)

    Boehmer, Jamie L

    2011-12-01

    The pursuit of biomarkers for use as clinical screening tools, measures for early detection, disease monitoring, and as a means for assessing therapeutic responses has steadily evolved in human and veterinary medicine over the past two decades. Concurrently, advances in mass spectrometry have markedly expanded proteomic capabilities for biomarker discovery. While initial mass spectrometric biomarker discovery endeavors focused primarily on the detection of modulated proteins in human tissues and fluids, recent efforts have shifted to include proteomic analyses of biological samples from food animal species. Mastitis continues to garner attention in veterinary research due mainly to affiliated financial losses and food safety concerns over antimicrobial use, but also because there are only a limited number of efficacious mastitis treatment options. Accordingly, comparative proteomic analyses of bovine milk have emerged in recent years. Efforts to prevent agricultural-related food-borne illness have likewise fueled an interest in the proteomic evaluation of several prominent strains of bacteria, including common mastitis pathogens. The interest in establishing biomarkers of the host and pathogen responses during bovine mastitis stems largely from the need to better characterize mechanisms of the disease, to identify reliable biomarkers for use as measures of early detection and drug efficacy, and to uncover potentially novel targets for the development of alternative therapeutics. The following review focuses primarily on comparative proteomic analyses conducted on healthy versus mastitic bovine milk. However, a comparison of the host defense proteome of human and bovine milk and the proteomic analysis of common veterinary pathogens are likewise introduced.

  5. Current and Future Applications of Biomedical Engineering for Proteomic Profiling: Predictive Biomarkers in Neuro-Traumatology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers in patients with traumatic brain injury (TBI, a critical worldwide health problem with an estimated 10 billion people affected annually worldwide. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials. Only experimental articles revolving around the management of TBI, in which the role of new devices based on innovative discoveries coming from the field of nanotechnology and biomedical engineering were highlighted, have been included and analyzed in this study. Based on theresults gathered from this research on innovative methods for genomics, epigenomics, and proteomics, their future application in this field seems promising. Despite the outstanding technical challenges of identifying reliable biosignatures for TBI and the mixed nature of studies herein described (single cells proteomics, biofilms, sensors, etc., the clinical implementation of those discoveries will allow us to gain confidence in the use of advanced neuromonitoring modalities with a potential dramatic improvement in the management of those patients.

  6. Cancer Biomarker Discovery: Lectin-Based Strategies Targeting Glycoproteins

    Directory of Open Access Journals (Sweden)

    David Clark

    2012-01-01

    Full Text Available Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state.

  7. Glycoscience aids in biomarker discovery

    Directory of Open Access Journals (Sweden)

    Serenus Hua1,2 & Hyun Joo An1,2,*

    2012-06-01

    Full Text Available The glycome consists of all glycans (or carbohydrates within abiological system, and modulates a wide range of important biologicalactivities, from protein folding to cellular communications.The mining of the glycome for disease markers representsa new paradigm for biomarker discovery; however, this effortis severely complicated by the vast complexity and structuraldiversity of glycans. This review summarizes recent developmentsin analytical technology and methodology as applied tothe fields of glycomics and glycoproteomics. Mass spectrometricstrategies for glycan compositional profiling are described, as arepotential refinements which allow structure-specific profiling.Analytical methods that can discern protein glycosylation at aspecific site of modification are also discussed in detail.Biomarker discovery applications are shown at each level ofanalysis, highlighting the key role that glycoscience can play inhelping scientists understand disease biology.

  8. Top-down proteomics with mass spectrometry imaging: a pilot study towards discovery of biomarkers for neurodevelopmental disorders.

    Directory of Open Access Journals (Sweden)

    Hui Ye

    Full Text Available In the developing mammalian brain, inhibition of NMDA receptor can induce widespread neuroapoptosis, inhibit neurogenesis and cause impairment of learning and memory. Although some mechanistic insights into adverse neurological actions of these NMDA receptor antagonists exist, our understanding of the full spectrum of developmental events affected by early exposure to these chemical agents in the brain is still limited. Here we attempt to gain insights into the impact of pharmacologically induced excitatory/inhibitory imbalance in infancy on the brain proteome using mass spectrometric imaging (MSI. Our goal was to study changes in protein expression in postnatal day 10 (P10 rat brains following neonatal exposure to the NMDA receptor antagonist dizocilpine (MK801. Analysis of rat brains exposed to vehicle or MK801 and comparison of their MALDI MS images revealed differential relative abundances of several proteins. We then identified these markers such as ubiquitin, purkinje cell protein 4 (PEP-19, cytochrome c oxidase subunits and calmodulin, by a combination of reversed-phase (RP HPLC fractionation and top-down tandem MS platform. More in-depth large scale study along with validation experiments will be carried out in the future. Overall, our findings indicate that a brief neonatal exposure to a compound that alters excitatory/inhibitory balance in the brain has a long term effect on protein expression patterns during subsequent development, highlighting the utility of MALDI-MSI as a discovery tool for potential biomarkers.

  9. Application of Proteomics and Peptidomics to COPD

    Directory of Open Access Journals (Sweden)

    Girolamo Pelaia

    2014-01-01

    Full Text Available Chronic obstructive pulmonary disease (COPD is a complex disorder involving both airways and lung parenchyma, usually associated with progressive and poorly reversible airflow limitation. In order to better characterize the phenotypic heterogeneity and the prognosis of patients with COPD, there is currently an urgent need for discovery and validation of reliable disease biomarkers. Within this context, proteomic and peptidomic techniques are emerging as very valuable tools that can be applied to both systemic and pulmonary samples, including peripheral blood, induced sputum, exhaled breath condensate, bronchoalveolar lavage fluid, and lung tissues. Identification of COPD biomarkers by means of proteomic and peptidomic approaches can thus also lead to discovery of new molecular targets potentially useful to improve and personalize the therapeutic management of this widespread respiratory disease.

  10. Quantitative proteomic analysis for novel biomarkers of buccal squamous cell carcinoma arising in background of oral submucous fibrosis

    International Nuclear Information System (INIS)

    Liu, Wen; Zeng, Lijuan; Li, Ning; Wang, Fei; Jiang, Canhua; Guo, Feng; Chen, Xinqun; Su, Tong; Xu, Chunjiao; Zhang, Shanshan; Fang, Changyun

    2016-01-01

    In South and Southeast Asian, the majority of buccal squamous cell carcinoma (BSCC) can arise from oral submucous fibrosis (OSF). BSCCs develop in OSF that are often not completely resected, causing local relapse. The aim of our study was to find candidate protein biomarkers to detect OSF and predict prognosis in BSCCs by quantitative proteomics approaches. We compared normal oral mucosa (NBM) and paired biopsies of BSCC and OSF by quantitative proteomics using isobaric tags for relative and absolute quantification (iTRAQ) to discover proteins with differential expression. Gene Ontology and KEGG networks were analyzed. The prognostic value of biomarkers was evaluated in 94 BSCCs accompanied with OSF. Significant associations were assessed by Kaplan-Meier survival and Cox-proportional hazards analysis. In total 30 proteins were identified with significantly different expression (false discovery rate < 0.05) among three tissues. Two consistently upregulated proteins, ANXA4 and FLNA, were validated. The disease-free survival was negatively associated with the expression of ANXA4 (hazard ratio, 3.4; P = 0.000), FLNA (hazard ratio, 2.1; P = 0.000) and their combination (hazard ratio, 8.8; P = 0.002) in BSCCs. The present study indicates that iTRAQ quantitative proteomics analysis for tissues of BSCC and OSF is a reliable strategy. A significantly up-regulated ANXA4 and FLNA could be not only candidate biomarkers for BSCC prognosis but also potential targets for its therapy. The online version of this article (doi:10.1186/s12885-016-2650-1) contains supplementary material, which is available to authorized users

  11. The Urine Proteome as a Biomarker of Radiation Injury

    Science.gov (United States)

    Sharma, Mukut; Halligan, Brian D.; Wakim, Bassam T.; Savin, Virginia J.; Cohen, Eric P.; Moulder, John E.

    2009-01-01

    Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury. PMID:19746194

  12. Targeted proteomics guided by label-free global proteome analysis in saliva reveal transition signatures from health to periodontal disease.

    Science.gov (United States)

    Bostanci, Nagihan; Selevsek, Nathalie; Wolski, Witold; Grossmann, Jonas; Bao, Kai; Wahlander, Asa; Trachsel, Christian; Schlapbach, Ralph; Özturk, Veli Özgen; Afacan, Beral; Emingil, Gulnur; Belibasakis, Georgios N

    2018-04-02

    Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. We carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n=67, health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n=82). The LFQ platform led to the discovery of 119 proteins with at least two-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1), with maximum area under the receiver operating curve >0.97. This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum

  13. Identification of Biomarkers for Endometriosis Using Clinical Proteomics

    Directory of Open Access Journals (Sweden)

    Yang Zhao

    2015-01-01

    Full Text Available Background: We investigated possible biomarkers for endometriosis (EM using the ClinProt technique and proteomics methods. Methods: We enrolled 50 patients with EM, 34 with benign ovarian neoplasms and 40 healthy volunteers in this study. Serum proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS combined with weak cationic exchange (WCX magnetic beads. Possible biomarkers were analyzed by a random and repeat pattern model-validation method that we designed, and ClinProtools software, results were refined using online liquid chromatography-tandem MS. Results: We found a cluster of 5 peptides (4210, 5264, 2660, 5635, and 5904 Da, using 3 peptides (4210, 5904, 2660 Da to discriminate EM patients from healthy volunteers, with 96.67% sensitivity and 100% specificity. We selected 4210 and 5904 m/z, which differed most between patients with EM and controls, and identified them as fragments of ATP1B4, and the fibrinogen alpha (FGA isoform 1/2 of the FGA chain precursor, respectively. Conclusions: ClinProt can identify EM biomarkers, which - most notably - distinguish even early-stage or minimal disease. We found 5 stable peaks at 4210, 5264, 2660, 5635, and 5904 Da as potential EM biomarkers, the strongest of which were associated with ATP1B4 (4210 Da and FGA (5904 Da; this indicates that ATP1B4 and FGA are associated with EM pathogenesis.

  14. Proteomic identification of host and parasite biomarkers in saliva from patients with uncomplicated Plasmodium falciparum malaria

    Directory of Open Access Journals (Sweden)

    Huang Honglei

    2012-05-01

    Full Text Available Abstract Background Malaria cases attributed to Plasmodium falciparum account for approximately 600,000 deaths yearly, mainly in African children. The gold standard method to diagnose malaria requires the visualization of the parasite in blood. The role of non-invasive diagnostic methods to diagnose malaria remains unclear. Methods A protocol was optimized to deplete highly abundant proteins from saliva to improve the dynamic range of the proteins identified and assess their suitability as candidate biomarkers of malaria infection. A starch-based amylase depletion strategy was used in combination with four different lectins to deplete glycoproteins (Concanavalin A and Aleuria aurantia for N-linked glycoproteins; jacalin and peanut agglutinin for O-linked glycoproteins. A proteomic analysis of depleted saliva samples was performed in 17 children with fever and a positive–malaria slide and compared with that of 17 malaria-negative children with fever. Results The proteomic signature of malaria-positive patients revealed a strong up-regulation of erythrocyte-derived and inflammatory proteins. Three P. falciparum proteins, PFL0480w, PF08_0054 and PFI0875w, were identified in malaria patients and not in controls. Aleuria aurantia and jacalin showed the best results for parasite protein identification. Conclusions This study shows that saliva is a suitable clinical specimen for biomarker discovery. Parasite proteins and several potential biomarkers were identified in patients with malaria but not in patients with other causes of fever. The diagnostic performance of these markers should be addressed prospectively.

  15. Plasma biomarker discovery in preeclampsia using a novel differential isolation technology for circulating extracellular vesicles.

    Science.gov (United States)

    Tan, Kok Hian; Tan, Soon Sim; Sze, Siu Kwan; Lee, Wai Kheong Ryan; Ng, Mor Jack; Lim, Sai Kiang

    2014-10-01

    To circumvent the complex protein milieu of plasma and discover robust predictive biomarkers for preeclampsia (PE), we investigate if phospholipid-binding ligands can reduce the milieu complexity by extracting plasma extracellular vesicles for biomarker discovery. Cholera toxin B chain (CTB) and annexin V (AV) which respectively binds GM1 ganglioside and phosphatidylserine were used to isolate extracellular vesicles from plasma of PE patients and healthy pregnant women. The proteins in the vesicles were identified using enzyme-linked immunosorbent assay, antibody array, and mass spectrometry. CTB and AV were found to bind 2 distinct groups of extracellular vesicles. Antibody array and enzyme-linked immunosorbent assay revealed that PE patients had elevated levels of CD105, interleukin-6, placental growth factor, tissue inhibitor of metallopeptidase 1, and atrial natriuretic peptide in cholera toxin B- but not AV-vesicles, and elevated levels of plasminogen activator inhibitor-1, pro-calcitonin, S100b, tumor growth factor β, vascular endothelial growth factor receptor 1, brain natriuretic peptide, and placental growth factor in both cholera toxin B- and AV-vesicles. CD9 level was elevated in cholera toxin B-vesicles but reduced in AV vesicles of PE patients. Proteome analysis revealed that in cholera toxin B-vesicles, 87 and 222 proteins were present only in PE patients and healthy pregnant women respectively while in AV-vesicles, 104 and 157 proteins were present only in PE and healthy pregnant women, respectively. This study demonstrated for the first time that CTB and AV bind unique extracellular vesicles, and their protein cargo reflects the disease state of the patient. The successful use of these 2 ligands to isolate circulating plasma extracellular vesicles for biomarker discovery in PE represents a novel technology for biomarker discovery that can be applied to other specialties. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.

    Science.gov (United States)

    Mundt, Filip; Johansson, Henrik J; Forshed, Jenny; Arslan, Sertaç; Metintas, Muzaffer; Dobra, Katalin; Lehtiö, Janne; Hjerpe, Anders

    2014-03-01

    Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome

  17. Comparative Tissue Proteomics of Microdissected Specimens Reveals Novel Candidate Biomarkers of Bladder Cancer*

    Science.gov (United States)

    Chen, Chien-Lun; Chung, Ting; Wu, Chih-Ching; Ng, Kwai-Fong; Yu, Jau-Song; Tsai, Cheng-Han; Chang, Yu-Sun; Liang, Ying; Tsui, Ke-Hung; Chen, Yi-Ting

    2015-01-01

    More than 380,000 new cases of bladder cancer are diagnosed worldwide, accounting for ∼150,200 deaths each year. To discover potential biomarkers of bladder cancer, we employed a strategy combining laser microdissection, isobaric tags for relative and absolute quantitation labeling, and liquid chromatography-tandem MS (LC-MS/MS) analysis to profile proteomic changes in fresh-frozen bladder tumor specimens. Cellular proteins from four pairs of surgically resected primary bladder cancer tumor and adjacent nontumorous tissue were extracted for use in two batches of isobaric tags for relative and absolute quantitation experiments, which identified a total of 3220 proteins. A DAVID (database for annotation, visualization and integrated discovery) analysis of dysregulated proteins revealed that the three top-ranking biological processes were extracellular matrix organization, extracellular structure organization, and oxidation-reduction. Biological processes including response to organic substances, response to metal ions, and response to inorganic substances were highlighted by up-expressed proteins in bladder cancer. Seven differentially expressed proteins were selected as potential bladder cancer biomarkers for further verification. Immunohistochemical analyses showed significantly elevated levels of three proteins—SLC3A2, STMN1, and TAGLN2—in tumor cells compared with noncancerous bladder epithelial cells, and suggested that TAGLN2 could be a useful tumor tissue marker for diagnosis (AUC = 0.999) and evaluating lymph node metastasis in bladder cancer patients. ELISA results revealed significantly increased urinary levels of both STMN1 and TAGLN2 in bladder cancer subgroups compared with control groups. In comparisons with age-matched hernia urine specimens, urinary TAGLN2 in bladder cancer samples showed the largest fold change (7.13-fold), with an area-under-the-curve value of 0.70 (p < 0.001, n = 205). Overall, TAGLN2 showed the most significant

  18. Lung Cancer Serum Biomarker Discovery Using Label Free LC-MS/MS

    Science.gov (United States)

    Zeng, Xuemei; Hood, Brian L.; Zhao, Ting; Conrads, Thomas P.; Sun, Mai; Gopalakrishnan, Vanathi; Grover, Himanshu; Day, Roger S.; Weissfeld, Joel L.; Wilson, David O.; Siegfried, Jill M.; Bigbee, William L.

    2011-01-01

    Introduction Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer, and the relatively favorable survival associated with early stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. Methods We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a set of pooled non-small cell lung cancer (NSCLC) case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by LC-MS/MS. The tandem mass spectrum data were searched against the human proteome database and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring MS assays. Results A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (pbiomarkers with statistically significant differential abundance across the lung cancer case/control pools which, when validated, could improve lung cancer early detection. PMID:21304412

  19. Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective.

    Science.gov (United States)

    Findeisen, Peter; Neumaier, Michael

    2009-01-01

    Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

  20. The Urine Proteome as a Biomarker of Radiation Injury: Submitted to Proteomics- Clinical Applications Special Issue: "Renal and Urinary Proteomics (Thongboonkerd)"

    Science.gov (United States)

    Sharma, Mukut; Halligan, Brian D; Wakim, Bassam T; Savin, Virginia J; Cohen, Eric P; Moulder, John E

    2008-06-18

    Terrorist attacks or nuclear accidents could expose large numbers of people to ionizing radiation, and early biomarkers of radiation injury would be critical for triage, treatment and follow-up of such individuals. However, no such biomarkers have yet been proven to exist. We tested the potential of high throughput proteomics to identify protein biomarkers of radiation injury after total body X-ray irradiation in a rat model. Subtle functional changes in the kidney are suggested by an increased glomerular permeability for macromolecules measured within 24 hours after TBI. Ultrastructural changes in glomerular podocytes include partial loss of the interdigitating organization of foot processes. Analysis of urine by LC-MS/MS and 2D-GE showed significant changes in the urine proteome within 24 hours after TBI. Tissue kallikrein 1-related peptidase, cysteine proteinase inhibitor cystatin C and oxidized histidine were found to be increased while a number of proteinase inhibitors including kallikrein-binding protein and albumin were found to be decreased post-irradiation. Thus, TBI causes immediately detectable changes in renal structure and function and in the urinary protein profile. This suggests that both systemic and renal changes are induced by radiation and it may be possible to identify a set of biomarkers unique to radiation injury.

  1. Identification of proteomic biomarkers of preeclampsia using protein microarray and tandem mass spectrometry

    Directory of Open Access Journals (Sweden)

    Karol Charkiewicz

    2015-05-01

    Full Text Available Preeclampsia (PE is the leading cause of death of the fetus and the mother. The exact pathomechanism has not so far been clarified. PE coexists with many other diseases, but it is often difficult to explain the association between them and find a clear reason for their occurrence. There are many predictive factors, but none are highly specific in preeclampsia. The diagnosis of preeclampsia seems to be very complex, which is another argument for the exploration of knowledge on this subject. Although many of the discoveries have hitherto been made in the field of proteomics, still no single specific biomarker of preeclampsia has been discovered. Research at the genome level is important because it can help us understand the genetic predisposition of patients affected by this disease. Nevertheless, researchers have recently become more interested in the pathophysiology of PE, and they are trying to answer the question: what is the real, direct cause of preeclampsia? Thus, the discovery of a protein that is a good predictor of preeclampsia development would significantly accelerate the medical care of pregnant women, and consequently reduce the risk of occurrence of HELLP syndrome and fetal death. Apart from the predictive and diagnostic function, such a discovery would help us to better understand the pathogenesis of preeclampsia and to find in the future a medical drug to suppress this disease. In order to make a breakthrough in this field, scientists need to use the most modern methods of proteomics, which allow for the analysis of small amounts of biological material in the shortest possible time, thereby giving a lot of information about existing proteins in the sample. Such optimization allows two methods, most commonly used by researchers: tandem mass spectrometry and protein microarray technique.

  2. Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Campos, Benito; Winther, Ole

    2014-01-01

    directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found......Background: The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic....... Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature...

  3. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

    Science.gov (United States)

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

    2014-09-09

    Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

  4. A Standardized and Reproducible Urine Preparation Protocol for Cancer Biomarkers Discovery

    Directory of Open Access Journals (Sweden)

    Julia Beretov

    2014-01-01

    Full Text Available A suitable and standardized protein purification technique is essential to maintain consistency and to allow data comparison between proteomic studies for urine biomarker discovery. Ultimately, efforts should be made to standardize urine preparation protocols. The aim of this study was to develop an optimal analytical protocol to achieve maximal protein yield and to ensure that this method was applicable to examine urine protein patterns that distinguish disease and disease-free states. In this pilot study, we compared seven different urine sample preparation methods to remove salts, and to precipitate and isolate urinary proteins. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE profiles showed that the sequential preparation of urinary proteins by combining acetone and trichloroacetic acid (TCA alongside high speed centrifugation (HSC provided the best separation, and retained the most urinary proteins. Therefore, this approach is the preferred method for all further urine protein analysis.

  5. Effects of Three Commonly-used Diuretics on the Urinary Proteome

    Directory of Open Access Journals (Sweden)

    Xundou Li

    2014-06-01

    Full Text Available Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography–tandem mass spectrometry (LC–MS/MS. Based on the criteria of P ⩽ 0.05, a fold change ⩾2, a spectral count ⩾5, and false positive rate (FDR ⩽1%, 14 proteins (seven for F, five for H, and two for S were identified by Progenesis LC–MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics.

  6. Effects of three commonly-used diuretics on the urinary proteome.

    Science.gov (United States)

    Li, Xundou; Zhao, Mindi; Li, Menglin; Jia, Lulu; Gao, Youhe

    2014-06-01

    Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the criteria of P≤0.05, a fold change ≥2, a spectral count ≥5, and false positive rate (FDR) ≤1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC-MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. Copyright © 2014. Production and hosting by Elsevier Ltd.

  7. The Proteome of Primary Prostate Cancer

    DEFF Research Database (Denmark)

    Iglesias-Gato, Diego; Wikström, Pernilla; Tyanova, Stefka

    2016-01-01

    for disease aggressiveness. DESIGN, SETTING, AND PARTICIPANTS: Mass spectrometry was used for genome-scale quantitative proteomic profiling of 28 prostate tumors (Gleason score 6-9) and neighboring nonmalignant tissue in eight cases, obtained from formalin-fixed paraffin-embedded prostatectomy samples. Two...... changes occurring during prostate cancer (PCa) initiation and progression can result in clinically relevant discoveries. OBJECTIVES: To study cellular processes altered in PCa using system-wide quantitative analysis of changes in protein expression in clinical samples and to identify prognostic biomarkers......BACKGROUND: Clinical management of the prostate needs improved prognostic tests and treatment strategies. Because proteins are the ultimate effectors of most cellular reactions, are targets for drug actions and constitute potential biomarkers; a quantitative systemic overview of the proteome...

  8. Characterization of potential ionizing radiation biomarkers by a proteomic approach

    Energy Technology Data Exchange (ETDEWEB)

    Guipaud, O; Vereycken-Holler, V; Benderitter, M [Institut de Radioprotection et de Surete Nucleaire, Lab. de Radiopathologie, 92 - Fontenay aux Roses (France); Royer, N; Vinh, J [Ecole Superieure de Physique et de Chimie Industrielles, 75 - Paris (France)

    2006-07-01

    Radio-induced lesions are tissue specific, hardly predictable, and can arise months or years later. The finding of prognostic bio-markers is of fundamental relevance for the settlement of therapeutic or preventive strategies. Using two-dimensional gel electrophoresis and mass spectrometry, a proteomic study was applied to look for differentially expressed proteins, i.e. potential bio-markers candidates, in mouse serums after a local irradiation of the dorsal skin. Our results clearly indicated that serum protein content was dynamically modified after a local skin irradiation. A set of specific proteins were early down- or up-regulated and could turn out to be good candidates as diagnostic or prognostic bio-markers. (author)

  9. Characterization of potential ionizing radiation biomarkers by a proteomic approach

    International Nuclear Information System (INIS)

    Guipaud, O.; Vereycken-Holler, V.; Benderitter, M.; Royer, N.; Vinh, J.

    2006-01-01

    Radio-induced lesions are tissue specific, hardly predictable, and can arise months or years later. The finding of prognostic bio-markers is of fundamental relevance for the settlement of therapeutic or preventive strategies. Using two-dimensional gel electrophoresis and mass spectrometry, a proteomic study was applied to look for differentially expressed proteins, i.e. potential bio-markers candidates, in mouse serums after a local irradiation of the dorsal skin. Our results clearly indicated that serum protein content was dynamically modified after a local skin irradiation. A set of specific proteins were early down- or up-regulated and could turn out to be good candidates as diagnostic or prognostic bio-markers. (author)

  10. Allergic asthma biomarkers using systems approaches

    Directory of Open Access Journals (Sweden)

    Gaurab eSircar

    2014-01-01

    Full Text Available Asthma is characterized by lung inflammation caused by complex interaction between the immune system and environmental factors such as allergens and inorganic pollutants. Recent research in this field is focused on discovering new biomarkers associated with asthma pathogenesis. This review illustrates updated research associating biomarkers of allergic asthma and their potential use in systems biology of the disease. We focus on biomolecules with altered expression, which may serve as inflammatory, diagnostic and therapeutic biomarkers of asthma discovered in human or experimental asthma model using genomic, proteomic and epigenomic approaches for gene and protein expression profiling. These include high-throughput technologies such as state of the art microarray and proteomics Mass Spectrometry (MS platforms. Emerging concepts of molecular interactions and pathways may provide new insights in searching potential clinical biomarkers. We summarized certain pathways with significant linkage to asthma pathophysiology by analyzing the compiled biomarkers. Systems approaches with this data can identify the regulating networks, which will eventually identify the key biomarkers to be used for diagnostics and drug discovery.

  11. Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

    DEFF Research Database (Denmark)

    Alkhalaf, Alaa; Zürbig, Petra; Bakker, Stephan J L

    2010-01-01

    /d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82). METHODOLOGY/PRINCIPAL FINDINGS: Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously......BACKGROUND: Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers...... with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg...

  12. Unrestrictive identification of post-translational modifications in the urine proteome without enrichment

    Science.gov (United States)

    2013-01-01

    Background Research on the human urine proteome may lay the foundation for the discovery of relevant disease biomarkers. Post-translational modifications (PTMs) have important effects on the functions of protein biomarkers. Identifying PTMs without enrichment adds no extra steps to conventional identification procedures for urine proteomics. The only difference is that this method requires software that can conduct unrestrictive identifications of PTMs. In this study, routine urine proteomics techniques were used to identify urine proteins. Unspecified PTMs were searched by MODa and PEAKS 6 automated software, followed by a manual search to screen out in vivo PTMs by removing all in vitro PTMs and amino acid substitutions. Results There were 75 peptides with 6 in vivo PTMs that were found by both MODa and PEAKS 6. Of these, 34 peptides in 18 proteins have novel in vivo PTMs compared with the annotation information of these proteins on the Universal Protein Resource website. These new in vivo PTMs had undergone methylation, dehydration, oxidation, hydroxylation, phosphorylation, or dihydroxylation. Conclusions In this study, we identified PTMs of urine proteins without the need for enrichment. Our investigation may provide a useful reference for biomarker discovery in the future. PMID:23317149

  13. BioinformatiqTM - integrating data types for proteomic discovery

    International Nuclear Information System (INIS)

    Arthur, J.W.; Harrison, M.; Manoharan, A.; Traini, M.; Shaw, E.; Wilkins, M.

    2001-01-01

    Proteomics (Wilkins et al. 1997) involves the large-scale analysis of expressed proteins. At each stage of the discovery process the researcher accumulates large volumes of data. These include: clinical or biological data about the sample being studied; details of sample purification and separation; images of 2D gels and associated information; MALDI mass spectra; MS/MS and PSD spectra; as well as meta-data relating to the projects undertaken and experiments performed. All this must be combined with existing databases of protein and EST sequences, post-translational modifications, and protein glycosylation, then processed with sophisticated bioinformatics tools in order to extract meaningful answers to questions of biological, clinical, and agricultural significance. BioinformatlQ TM is a web-based application for the storage, management, and automated bioinformatic analysis of proteomic information. This poster will demonstrate the integration of these disparate data sources in proteomics

  14. Noninvasive diagnosis of intraamniotic infection: proteomic biomarkers in vaginal fluid.

    Science.gov (United States)

    Hitti, Jane; Lapidus, Jodi A; Lu, Xinfang; Reddy, Ashok P; Jacob, Thomas; Dasari, Surendra; Eschenbach, David A; Gravett, Michael G; Nagalla, Srinivasa R

    2010-07-01

    We analyzed the vaginal fluid proteome to identify biomarkers of intraamniotic infection among women in preterm labor. Proteome analysis was performed on vaginal fluid specimens from women with preterm labor, using multidimensional liquid chromatography, tandem mass spectrometry, and label-free quantification. Enzyme immunoassays were used to quantify candidate proteins. Classification accuracy for intraamniotic infection (positive amniotic fluid bacterial culture and/or interleukin-6 >2 ng/mL) was evaluated using receiver-operator characteristic curves obtained by logistic regression. Of 170 subjects, 30 (18%) had intraamniotic infection. Vaginal fluid proteome analysis revealed 338 unique proteins. Label-free quantification identified 15 proteins differentially expressed in intraamniotic infection, including acute-phase reactants, immune modulators, high-abundance amniotic fluid proteins and extracellular matrix-signaling factors; these findings were confirmed by enzyme immunoassay. A multi-analyte algorithm showed accurate classification of intraamniotic infection. Vaginal fluid proteome analyses identified proteins capable of discriminating between patients with and without intraamniotic infection. Copyright (c) 2010 Mosby, Inc. All rights reserved.

  15. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2015-01-01

    To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases. PMID:26090402

  16. Preparation of the low molecular weight serum proteome for mass spectrometry analysis.

    Science.gov (United States)

    Waybright, Timothy J; Chan, King C; Veenstra, Timothy D; Xiao, Zhen

    2013-01-01

    The discovery of viable biomarkers or indicators of disease states is complicated by the inherent complexity of the chosen biological specimen. Every sample, whether it is serum, plasma, urine, tissue, cells, or a host of others, contains thousands of large and small components, each interacting in multiple ways. The need to concentrate on a group of these components to narrow the focus on a potential biomarker candidate becomes, out of necessity, a priority, especially in the search for immune-related low molecular weight serum biomarkers. One such method in the field of proteomics is to divide the sample proteome into groups based on the size of the protein, analyze each group, and mine the data for statistically significant items. This chapter details a portion of this method, concentrating on a method for fractionating and analyzing the low molecular weight proteome of human serum.

  17. Plasma Proteome Biomarkers of Inflammation in School Aged Children in Nepal.

    Directory of Open Access Journals (Sweden)

    Sun Eun Lee

    Full Text Available Inflammation is a condition stemming from complex host defense and tissue repair mechanisms, often simply characterized by plasma levels of a single acute reactant. We attempted to identify candidate biomarkers of systemic inflammation within the plasma proteome. We applied quantitative proteomics using isobaric mass tags (iTRAQ tandem mass spectrometry to quantify proteins in plasma of 500 Nepalese children 6-8 years of age. We evaluated those that co-vary with inflammation, indexed by α-1-acid glycoprotein (AGP, a conventional biomarker of inflammation in population studies. Among 982 proteins quantified in >10% of samples, 99 were strongly associated with AGP at a family-wise error rate of 0.1%. Magnitude and significance of association varied more among proteins positively (n = 41 than negatively associated (n = 58 with AGP. The former included known positive acute phase proteins including C-reactive protein, serum amyloid A, complement components, protease inhibitors, transport proteins with anti-oxidative activity, and numerous unexpected intracellular signaling molecules. Negatively associated proteins exhibited distinct differences in abundance between secretory hepatic proteins involved in transporting or binding lipids, micronutrients (vitamin A and calcium, growth factors and sex hormones, and proteins of largely extra-hepatic origin involved in the formation and metabolic regulation of extracellular matrix. With the same analytical approach and the significance threshold, seventy-two out of the 99 proteins were commonly associated with CRP, an established biomarker of inflammation, suggesting the validity of the identified proteins. Our findings have revealed a vast plasma proteome within a free-living population of children that comprise functional biomarkers of homeostatic and induced host defense, nutrient metabolism and tissue repair, representing a set of plasma proteins that may be used to assess dynamics and extent of

  18. Urinary proteomic biomarkers for diagnosis and risk stratification of autosomal dominant polycystic kidney disease: a multicentric study.

    Directory of Open Access Journals (Sweden)

    Andreas D Kistler

    Full Text Available Treatment options for autosomal dominant polycystic kidney disease (ADPKD will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS, we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI. The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001 with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD.

  19. Improving the quality of biomarker discovery research: the right samples and enough of them.

    Science.gov (United States)

    Pepe, Margaret S; Li, Christopher I; Feng, Ziding

    2015-06-01

    Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

  20. Using Aptamers for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Yun Min Chang

    2013-01-01

    Full Text Available Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment SELEX and cell-based SELEX (cell-SELEX. Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics.

  1. Potential Peripheral Biomarkers for the Diagnosis of Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Seema Patel

    2011-01-01

    Full Text Available Advances in the discovery of a peripheral biomarker for the diagnosis of Alzheimer's would provide a way to better detect the onset of this debilitating disease in a manner that is both noninvasive and universally available. This paper examines the current approaches that are being used to discover potential biomarker candidates available in the periphery. The search for a peripheral biomarker that could be utilized diagnostically has resulted in an extensive amount of studies that employ several biological approaches, including the assessment of tissues, genomics, proteomics, epigenetics, and metabolomics. Although a definitive biomarker has yet to be confirmed, advances in the understanding of the mechanisms of the disease and major susceptibility factors have been uncovered and reveal promising possibilities for the future discovery of a useful biomarker.

  2. Autoantibody profiling on human proteome microarray for biomarker discovery in cerebrospinal fluid and sera of neuropsychiatric lupus.

    Directory of Open Access Journals (Sweden)

    Chaojun Hu

    Full Text Available Autoantibodies in cerebrospinal fluid (CSF from patients with neuropsychiatric systemic lupus erythematosus (NPSLE may be potential biomarkers for prediction, diagnosis, or prognosis of NPSLE. We used a human proteome microarray with~17,000 unique full-length human proteins to investigate autoantibodies associated with NPSLE. Twenty-nine CSF specimens from 12 NPSLE, 7 non-NPSLE, and 10 control (non-systemic lupus erythematosuspatients were screened for NPSLE-associated autoantibodies with proteome microarrays. A focused autoantigen microarray of candidate NPSLE autoantigens was applied to profile a larger cohort of CSF with patient-matched sera. We identified 137 autoantigens associated with NPSLE. Ingenuity Pathway Analysis revealed that these autoantigens were enriched for functions involved in neurological diseases (score = 43.Anti-proliferating cell nuclear antigen (PCNA was found in the CSF of NPSLE and non-NPSLE patients. The positive rates of 4 autoantibodies in CSF specimens were significantly different between the SLE (i.e., NPSLE and non-NPSLE and control groups: anti-ribosomal protein RPLP0, anti-RPLP1, anti-RPLP2, and anti-TROVE2 (also known as anti-Ro/SS-A. The positive rate for anti-SS-A associated with NPSLE was higher than that for non-NPSLE (31.11% cf. 10.71%; P = 0.045.Further analysis showed that anti-SS-A in CSF specimens was related to neuropsychiatric syndromes of the central nervous system in SLE (P = 0.009. Analysis with Spearman's rank correlation coefficient indicated that the titers of anti-RPLP2 and anti-SS-A in paired CSF and serum specimens significantly correlated. Human proteome microarrays offer a powerful platform to discover novel autoantibodies in CSF samples. Anti-SS-A autoantibodies may be potential CSF markers for NPSLE.

  3. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

    Boot, Rolf G; van Breemen, Mariëlle J; Wegdam, Wouter

    2009-01-01

    Gaucher disease is an inherited lysosomal storage disorder, characterized by massive accumulation of glucosylceramide-laden macrophages in the spleen, liver and bone marrow as a consequence of deficient activity of glucocerebrosidase. Gaucher disease has been the playground to develop new therape...... in clinical management of Gaucher patients are discussed. Moreover, the use of several modern proteomic technologies for the identification of Gaucher biomarkers is reviewed....

  4. Adapting mass spectrometry-based platforms for clinical proteomics applications: The capillary electrophoresis coupled mass spectrometry paradigm

    Science.gov (United States)

    Metzger, Jochen; Luppa, Peter B.; Good, David M.; Mischak, Harald

    2018-01-01

    Single biomarker detection is common in clinical laboratories due to the currently available method spectrum. For various diseases, however, no specific single biomarker could be identified. A strategy to overcome this diagnostic void is to shift from single analyte detection to multiplexed biomarker profiling. Mass spectrometric methods were employed for biomarker discovery in body fluids. The enormous complexity of biofluidic proteome compartments implies upstream fractionation. For this reason, mass spectrometry (MS) was coupled to two-dimensional gel electrophoresis, liquid chromatography, surface-enhanced laser desorption/ionization, or capillary electrophoresis (CE). Differences in performance and operating characteristics make them differentially suited for routine laboratory applications. Progress in the field of clinical proteomics relies not only on the use of an adequate technological platform, but also on a fast and efficient proteomic workflow including standardized sample preparation, proteomic data processing, statistical validation of biomarker selection, and sample classification. Based on CE-MS analysis, we describe how proteomic technology can be implemented in a clinical laboratory environment. In the last part of this review, we give an overview of CE-MS-based clinical studies and present information on identity and biological significance of the identified peptide biomarkers providing evidence of disease-induced changes in proteolytic processing and posttranslational modification. PMID:19404829

  5. Non-invasively collected amniotic fluid as a source of possible biomarkers for premature rupture of membranes investigated by proteomic approach.

    Science.gov (United States)

    Consonni, Sara; Mainini, Veronica; Pizzardi, Agnese; Gianazza, Erica; Chinello, Clizia; Locatelli, Anna; Magni, Fulvio

    2014-02-01

    Preterm delivery is one of the main causes of perinatal morbidity and mortality and it accounts for 75 % of perinatal mortality and more than half of the long-term morbidity. We applied a proteomic approach based on mass spectrometry (MS) for biomarkers discovery of preterm premature rupture of membranes (pPROM) by investigating amniotic fluid (AF) invasively and non-invasively collected. Amniotic fluid was obtained from vagina of women with pPROM (group 1), PROM at term (group 2) and by genetic amniocentesis (group 3). Pre-fractionated AF proteome was analyzed through matrix assisted laser desorption ionization-time of flight (MALDI-TOF) MS. The characterization of proteins/peptides of interest was obtained by high performance liquid chromatography-electrospray tandem MS. Three peptides overexpressed in pPROM and able to discriminate the groups 1 and 2 were detected. One peptide was identified as the fragment Gly452LAVPDGPLGLPPKPro466 of the protein KIAA1522, expressed by fetal brain and liver. This peptide was overexpressed in a patient of the group 3, completely asymptomatic at the time of the amniocentesis, who later developed pPROM. Amniotic fluid invasively and non-invasively collected can be analyzed by MALDI-TOF MS to obtain proteomic profiles. Proteomic analysis identified a peptide with promising diagnostic capability for pPROM.

  6. Plasma membrane proteomics and its application in clinical cancer biomarker discovery

    DEFF Research Database (Denmark)

    Leth-Larsen, Rikke; Lund, Rikke; Ditzel, Henrik J

    2010-01-01

    Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions...... targeted by protein drugs, such as human antibodies, that have enhanced survival of several groups of cancer patients. The combination of novel analytical approaches and subcellular fractionation procedures has made it possible to study the plasma membrane proteome in more detail, which will elucidate...... cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal...

  7. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

    2017-08-01

    Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of 4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

  8. Bioinformatics and biomarker discovery "Omic" data analysis for personalized medicine

    CERN Document Server

    Azuaje, Francisco

    2010-01-01

    This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided w

  9. The path from biomarker discovery to regulatory qualification

    CERN Document Server

    Goodsaid, Federico

    2013-01-01

    The Path from Biomarker Discovery to Regulatory Qualification is a unique guide that focuses on biomarker qualification, its history and current regulatory settings in both the US and abroad. This multi-contributed book provides a detailed look at the next step to developing biomarkers for clinical use and covers overall concepts, challenges, strategies and solutions based on the experiences of regulatory authorities and scientists. Members of the regulatory, pharmaceutical and biomarker development communities will benefit the most from using this book-it is a complete and practical guide to biomarker qualification, providing valuable insight to an ever-evolving and important area of regulatory science. For complimentary access to chapter 13, 'Classic' Biomarkers of Liver Injury, by John R. Senior, Associate Director for Science, Food and Drug Administration, Silver Spring, Maryland, USA, please visit the following site:  http://tinyurl.com/ClassicBiomarkers Contains a collection of experiences of different...

  10. Mining the human urine proteome for monitoring renal transplant injury

    Energy Technology Data Exchange (ETDEWEB)

    Sigdel, Tara K.; Gao, Yuqian; He, Jintang; Wang, Anyou; Nicora, Carrie D.; Fillmore, Thomas L.; Shi, Tujin; Webb-Robertson, Bobbie-Jo; Smith, Richard D.; Qian, Wei-Jun; Salvatierra, Oscar; Camp, David G.; Sarwal, Minnie M.

    2016-06-01

    The human urinary proteome reflects systemic and inherent renal injury perturbations and can be analyzed to harness specific biomarkers for different kidney transplant injury states. 396 unique urine samples were collected contemporaneously with an allograft biopsy from 396 unique kidney transplant recipients. Centralized, blinded histology on the graft was used to classify matched urine samples into categories of acute rejection (AR), chronic allograft nephropathy (CAN), BK virus nephritis (BKVN), and stable graft (STA). Liquid chromatography–mass spectrometry (LC-MS) based proteomics using iTRAQ based discovery (n=108) and global label-free LC-MS analyses of individual samples (n=137) for quantitative proteome assessment were used in the discovery step. Selected reaction monitoring (SRM) was applied to identify and validate minimal urine protein/peptide biomarkers to accurately segregate organ injury causation and pathology on unique urine samples (n=151). A total of 958 proteins were initially quantified by iTRAQ, 87% of which were also identified among 1574 urine proteins detected in LC-MS validation. 103 urine proteins were significantly (p<0.05) perturbed in injury and enriched for humoral immunity, complement activation, and lymphocyte trafficking. A set of 131 peptides corresponding to 78 proteins were assessed by SRM for their significance in an independent sample cohort. A minimal set of 35 peptides mapping to 33 proteins, were modeled to segregate different injury groups (AUC =93% for AR, 99% for CAN, 83% for BKVN). Urinary proteome discovery and targeted validation identified urine protein fingerprints for non-invasive differentiation of kidney transplant injuries, thus opening the door for personalized immune risk assessment and therapy.

  11. What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema.

    Science.gov (United States)

    Ptolemy, Adam S; Rifai, Nader

    2010-01-01

    A continual trend of annual growth can be seen within research devoted to the discovery and validation of disease biomarkers within both the natural and clinical sciences. This expansion of intellectual endeavours was quantified through database searches of (a) research grant awards provided by the various branches of the National Institutes of Health (NIH) and (b) academic publications. A search of awards presented between 1986 and 2009 revealed a total of 28,856 grants awarded by the NIH containing the term "biomarker". The total funds for these awards in 2008 and 2009 alone were over $2.5 billion. During the same respective time frames, searches of "biomarker" and either "discovery", "genomics", "proteomics" or "metabolomics" yielded a total of 4,928 NIH grants whose combined funding exceeded $1.2 billion. The derived trend in NIH awards paralleled the annual expansion in "biomarker" literature. A PubMed search for the term, between 1990 and 2009, revealed a total of 441,510 published articles, with 38,457 published in 2008. These enormous investments and academic outputs however have not translated into the expected integration of new biomarkers for patient care. For example no proteomics derived biomarkers are currently being utilized in routine clinical management. This translational chasm necessitates a review of the previously proposed biomarker definitions and evaluation schema. A subsequent discussion of both the analytical and pre-analytical considerations for such research is also presented within. This required knowledge should aid scientists in their pursuit and validation of new biological markers of disease.

  12. Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

    Science.gov (United States)

    Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

    2016-11-01

    Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

  13. Quantitative Tissue Proteomics Analysis Reveals Versican as Potential Biomarker for Early-Stage Hepatocellular Carcinoma.

    Science.gov (United States)

    Naboulsi, Wael; Megger, Dominik A; Bracht, Thilo; Kohl, Michael; Turewicz, Michael; Eisenacher, Martin; Voss, Don Marvin; Schlaak, Jörg F; Hoffmann, Andreas-Claudius; Weber, Frank; Baba, Hideo A; Meyer, Helmut E; Sitek, Barbara

    2016-01-04

    Hepatocellular carcinoma (HCC) is one of the most aggressive tumors, and the treatment outcome of this disease is improved when the cancer is diagnosed at an early stage. This requires biomarkers allowing an accurate and early tumor diagnosis. To identify potential markers for such applications, we analyzed a patient cohort consisting of 50 patients (50 HCC and 50 adjacent nontumorous tissue samples as controls) using two independent proteomics approaches. We performed label-free discovery analysis on 19 HCC and corresponding tissue samples. The data were analyzed considering events known to take place in early events of HCC development, such as abnormal regulation of Wnt/b-catenin and activation of receptor tyrosine kinases (RTKs). 31 proteins were selected for verification experiments. For this analysis, the second set of the patient cohort (31 HCC and corresponding tissue samples) was analyzed using selected (multiple) reaction monitoring (SRM/MRM). We present the overexpression of ATP-dependent RNA helicase (DDX39), Fibulin-5 (FBLN5), myristoylated alanine-rich C-kinase substrate (MARCKS), and Serpin H1 (SERPINH1) in HCC for the first time. We demonstrate Versican core protein (VCAN) to be significantly associated with well differentiated and low-stage HCC. We revealed for the first time the evidence of VCAN as a potential biomarker for early-HCC diagnosis.

  14. One Sample, One Shot - Evaluation of sample preparation protocols for the mass spectrometric proteome analysis of human bile fluid without extensive fractionation

    NARCIS (Netherlands)

    Megger, D.A.; Padden, J.; Rosowski, K.; Uszkoreit, J.; Bracht, T.; Eisenacher, M.; Gerges, C.; Neuhaus, H.; Schumacher, B.; Schlaak, J.F.; Sitek, B.

    2017-01-01

    The proteome analysis of bile fluid represents a promising strategy to identify biomarker candidates for various diseases of the hepatobiliary system. However, to obtain substantive results in biomarker discovery studies large patient cohorts necessarily need to be analyzed. Consequently, this would

  15. Intraluminal proteome and peptidome of human urinary extracellular vesicles.

    Science.gov (United States)

    Liu, Xinyu; Chinello, Clizia; Musante, Luca; Cazzaniga, Marta; Tataruch, Dorota; Calzaferri, Giulio; James Smith, Andrew; De Sio, Gabriele; Magni, Fulvio; Zou, Hequn; Holthofer, Harry

    2015-06-01

    Urinary extracellular vesicles (UEVs) are a novel source for disease biomarker discovery. However, Tamm-Horsfall protein (THP) is still a challenge for proteomic analysis since it can inhibit detection of low-abundance proteins. Here, we introduce a new approach that does not involve an ultracentrifugation step to enrich vesicles and that reduces the amount of THP to manageable levels. UEVs were dialyzed and ultrafiltered after reduction and alkylation. The retained fraction was digested with trypsin to reduce the remaining THP and incubated with deoxycholate (DOC). The internal peptidome and internal proteome were analyzed by LC-ESI-MS. A total of 942 different proteins and 3115 unique endogenous peptide fragments deriving from 973 different protein isoforms were identified. Around 82% of the key endosomal sorting complex required for transport components of UEVs generation could be detected from the intraluminal content. Our UEVs preparation protocol provides a simplified way to investigate the intraluminal proteome and peptidome, in particular the subpopulation of UEVs of the trypsin-resistant class of exosomes (positive for tumor susceptibility gene101) and eliminates the majority of interfering proteins such as THP. This method allows the possibility to study endoproteome and endopeptidome of UEVs, thus greatly facilitating biomarker discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics

    Directory of Open Access Journals (Sweden)

    Sorette M

    2004-12-01

    Full Text Available Abstract Background Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. Results Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. Conclusion The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings.

  17. Using a novel "Integrated Biomarker Proteomic" index to assess the effects of freshwater pollutants in European eel peripheral blood mononuclear cells.

    Science.gov (United States)

    Roland, Kathleen; Kestemont, Patrick; Dieu, Marc; Raes, Martine; Silvestre, Frédéric

    2016-03-30

    Using proteomic data as biomarkers of environmental pollution has the potential to be of a great interest in ecological risk assessment as they constitute early warning indicators of ecologically relevant effects on biological systems. To develop such specific and sensitive biomarkers, the use of a set of proteins is required and the identification of protein expression signatures (PES) may reflect the exposure to specific classes of pollutants. Using 2D-DIGE (Differential in Gel Electrophoresis) methodology, this study aimed at identifying specific PES on European eel (Anguilla anguilla) peripheral blood mononuclear cells (PBMC) after 48 h in vitro exposure to two sublethal concentrations of dichlorodiphenyltrichloroethane (p,p'-DDT) (10 μg/L and 1mg/L) or cadmium (Cd) (1 μg/L and 100 μg/L). The present results have been supplemented with data of a first in vitro study on cells exposed to perfluorooctane sulfonate (PFOS) (10 μg/L and 1mg/L). A total of thirty-four protein spots, belonging to 18 different identified proteins found in all conditions, have been selected as possible biomarkers to develop a synthetic Integrated Biomarker Proteomic (IBP) index. IBP follows a dose-response relationship with higher values at the highest tested concentration for each pollutant (Cd: 9.96; DDT: 7.44; PFOS: 7.94) compared to the lowest tested concentration (Cd: 3.81; DDT: 2.91; PFOS: 2.06). In a second step, star plot graphs have been applied to proteomic data in order to allow visual integration of a set of early warning responses measured with protein biomarkers. Such star plots permit to discriminate the type of pollutant inducing a proteomic response. We conclude that using IBP is relevant in environmental risk assessment, giving to this index the potential to be applied as a global index of proteome alteration in endangered species such as the European eel. In this study, 34 protein spots have been selected as possible biomarkers to develop a synthetic Integrated

  18. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...... and the state or level of a large number of molecular entities is investigated. Such associative analysis could be confounded by several factors, leading to false discoveries. For example, it is assumed that with the exception of the true biomarkers most molecular entities such as gene expression levels show...... random distribution in a given cohort. However, gene expression levels may also be affected by technical bias when the actual measurement technology or sample handling may introduce a systematic error. If the distribution of systematic errors correlates with the biological phenotype then the risk...

  19. Novel Pneumocystis Antigen Discovery Using Fungal Surface Proteomics

    OpenAIRE

    Zheng, Mingquan; Cai, Yang; Eddens, Taylor; Ricks, David M.; Kolls, Jay K.

    2014-01-01

    Pneumonia due to the fungus Pneumocystis jirovecii is a life-threatening infection that occurs in immunocompromised patients. The inability to culture the organism as well as the lack of an annotated genome has hindered antigen discovery that could be useful in developing novel vaccine- or antibody-based therapies as well as diagnostics for this infection. Here we report a novel method of surface proteomics analysis of Pneumocystis murina that reliably detected putative surface proteins that ...

  20. Data from a targeted proteomics approach to discover biomarkers in saliva for the clinical diagnosis of periodontitis

    Directory of Open Access Journals (Sweden)

    V. Orti

    2018-06-01

    Full Text Available This study focused on the search for new biomarkers based on liquid chromatography-multiple reaction monitoring (LC-MRM proteomics profiling of whole saliva from patients with periodontitis compared to healthy subjects. The LC-MRM profiling approach is a new and innovative method that has already been validated for the absolute and multiplexed quantification of biomarkers in several diseases. The dataset for this study was produced using LC-MRM to monitor protein levels in a multiplex assay, it provides clinical information on salivary biomarkers of periodontitis. The data presented here is an extension of our recently published research article (Mertens et al., 2017 [1]. Keywords: Clinical chemistry, Mass spectrometry, Proteomics, Saliva biochemistry, Oral disease, Periodontitis

  1. Comprehensive data analysis of human ureter proteome

    Directory of Open Access Journals (Sweden)

    Sameh Magdeldin

    2016-03-01

    Full Text Available Comprehensive human ureter proteome dataset was generated from OFFGel fractionated ureter samples. Our result showed that among 2217 non-redundant ureter proteins, 751 protein candidates (33.8% were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48 that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, Cytoscape GO annotation was examined on the final ureter dataset to better understand proteins molecular function, biological processes, and cellular component. The ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery.

  2. A qualitative and quantitative evaluation of the peptide characteristics of microwave- and ultrasound-assisted digestion in discovery and targeted proteomic analyses.

    Science.gov (United States)

    Guo, Zhengguang; Cheng, Jie; Sun, Haidan; Sun, Wei

    2017-08-30

    Fast digestion methods can dramatically accelerate enzyme digestion and increase the throughput of proteomic analysis. However, the peptide characteristics of fast digestion methods and their performance in discovery and targeted proteomic analysis must be systematically evaluated. Three digestion methods, including overnight digestion, microwave-assisted protein enzymatic digestion (MAPED), and high-intensity focused ultrasonic-assisted enzymatic digestion (HIFUSAED), in trypsin or in trypsin/Lys-C were comprehensively compared in both discovery and targeted proteomics analysis using the HeLa cell proteome. In discovery proteomic analysis, the highest numbers of peptides and proteins were identified when the sample was digested via the MAPED method with trypsin/Lys-C. The fast digestion methods showed a higher mis-cleavage rate and a lower semi-tryptic rate than the overnight digestion method. In both label-free quantitative analysis and targeted proteomic analysis, both fully cleaved peptides (FCPs) and mis-cleaved peptides (MCPs) from the fast digestion methods and the overnight digestion method showed good reproducibility if they showed good abundance. When both the FCPs and MCPs were included in the analysis, the MAPED with trypsin/Lys-C method showed the best results for both discovery proteomic analysis and relative quantitative targeted proteomic analysis. These results will be beneficial for the application of fast digestion methods to proteomics. Copyright © 2017 John Wiley & Sons, Ltd.

  3. Comparative proteomic analysis of human malignant ascitic fluids for the development of gastric cancer biomarkers.

    Science.gov (United States)

    Jin, Jonghwa; Son, Minsoo; Kim, Hyeyoon; Kim, Hyeyeon; Kong, Seong-Ho; Kim, Hark Kyun; Kim, Youngsoo; Han, Dohyun

    2018-04-11

    Malignant ascites is a sign of peritoneal seeding, which is one of the most frequent forms of incurable distant metastasis. Because the development of malignant ascites is associated with an extremely poor prognosis, determining whether it resulted from peritoneal seeding has critical clinical implications in diagnosis, choice of treatment, and active surveillance. At present, the molecular characterizations of malignant ascites are especially limited in case of gastric cancer. We aimed to identify malignant ascites-specific proteins that may contribute to the development of alternative methods for diagnosis and therapeutic monitoring and also increase our understanding of the pathophysiology of peritoneal seeding. First, comprehensive proteomic strategies were employed to construct an in-depth proteome of ascitic fluids. Label-free quantitative proteomic analysis was subsequently performed to identify candidates that can differentiate between malignant ascitic fluilds of gastric cancer patients from benign ascitic fluids. Finally, two candidate proteins were verified by ELISA in 84 samples with gastric cancer or liver cirrhosis. Comprehensive proteome profiling resulted in the identification of 5347 ascites proteins. Using label-free quantification, we identified 299 proteins that were differentially expressed in ascitic fluids between liver cirrhosis and stage IV gastric cancer patients. In addition, we identified 645 proteins that were significantly expressed in ascitic fluids between liver cirrhosis and gastric cancer patients with peritoneal seeding. Finally, Gastriscin and Periostin that can distinguish malignant ascites from benign ascites were verified by ELISA. This study identified and verified protein markers that can distinguish malignant ascites with or without peritoneal seeding from benign ascites. Consequently, our results could be a significant resource for gastric cancer research and biomarker discovery in the diagnosis of malignant ascites

  4. Defining Diagnostic Biomarkers Using Shotgun Proteomics and MALDI-TOF Mass Spectrometry.

    Science.gov (United States)

    Armengaud, Jean

    2017-01-01

    Whole-cell MALDI-TOF has become a robust and widely used tool to quickly identify any pathogen. In addition to being routinely used in hospitals, it is also useful for low cost dereplication in large scale screening procedures of new environmental isolates for environmental biotechnology or taxonomical applications. Here, I describe how specific biomarkers can be defined using shotgun proteomics and whole-cell MALDI-TOF mass spectrometry. Based on MALDI-TOF spectra recorded on a given set of pathogens with internal calibrants, m/z values of interest are extracted. The proteins which contribute to these peaks are deduced from label-free shotgun proteomics measurements carried out on the same sample. Quantitative information based on the spectral count approach allows ranking the most probable candidates. Proteogenomic approaches help to define whether these proteins give the same m/z values along the whole taxon under consideration or result in heterogeneous lists. These specific biomarkers nicely complement conventional profiling approaches and may help to better define groups of organisms, for example at the subspecies level.

  5. A novel proteomic biomarker panel as a diagnostic tool for patients with ovarian cancer

    DEFF Research Database (Denmark)

    Høgdall, Claus; Fung, Eric T; Christensen, Ib J

    2011-01-01

    Previous reports have shown that the proteomic markers apolipoprotein A1, hepcidin, transferrin, inter-alpha trypsin IV internal fragment, transthyretin, connective-tissue activating protein 3 and beta-2 microglobulin may discriminate between a benign pelvic mass and ovarian cancer (OC). The aim...... was to determine if these serum proteomic biomarkers alone as well as in combination with age and serum CA125, could be helpful in triage of women with a pelvic mass....

  6. Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

    Directory of Open Access Journals (Sweden)

    Kai P. Law

    2015-05-01

    Full Text Available Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered.

  7. Mass Spectrometry-Based Proteomics for Pre-Eclampsia and Preterm Birth

    Science.gov (United States)

    Law, Kai P.; Han, Ting-Li; Tong, Chao; Baker, Philip N.

    2015-01-01

    Pregnancy-related complications such as pre-eclampsia and preterm birth now represent a notable burden of adverse health. Pre-eclampsia is a hypertensive disorder unique to pregnancy. It is an important cause of maternal death worldwide and a leading cause of fetal growth restriction and iatrogenic prematurity. Fifteen million infants are born preterm each year globally, but more than one million of those do not survive their first month of life. Currently there are no predictive tests available for diagnosis of these pregnancy-related complications and the biological mechanisms of the diseases have not been fully elucidated. Mass spectrometry-based proteomics have all the necessary attributes to provide the needed breakthrough in understanding the pathophysiology of complex human diseases thorough the discovery of biomarkers. The mass spectrometry methodologies employed in the studies for pregnancy-related complications are evaluated in this article. Top-down proteomic and peptidomic profiling by laser mass spectrometry, liquid chromatography or capillary electrophoresis coupled to mass spectrometry, and bottom-up quantitative proteomics and targeted proteomics by liquid chromatography mass spectrometry have been applied to elucidate protein biomarkers and biological mechanism of pregnancy-related complications. The proteomes of serum, urine, amniotic fluid, cervical-vaginal fluid, placental tissue, and cytotrophoblastic cells have all been investigated. Numerous biomarkers or biomarker candidates that could distinguish complicated pregnancies from healthy controls have been proposed. Nevertheless, questions as to the clinically utility and the capacity to elucidate the pathogenesis of the pre-eclampsia and preterm birth remain to be answered. PMID:26006232

  8. Proteomic analysis of tissue samples in translational breast cancer research

    DEFF Research Database (Denmark)

    Gromov, Pavel; Moreira, José; Gromova, Irina

    2014-01-01

    In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis...... the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens....

  9. Network-based analysis of proteomic profiles

    KAUST Repository

    Wong, Limsoon

    2016-01-26

    Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

  10. Systems biology and biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.

    2010-12-01

    Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of large complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.

  11. Mass spectrometry imaging enriches biomarker discovery approaches with candidate mapping.

    Science.gov (United States)

    Scott, Alison J; Jones, Jace W; Orschell, Christie M; MacVittie, Thomas J; Kane, Maureen A; Ernst, Robert K

    2014-01-01

    Integral to the characterization of radiation-induced tissue damage is the identification of unique biomarkers. Biomarker discovery is a challenging and complex endeavor requiring both sophisticated experimental design and accessible technology. The resources within the National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Consortium, Medical Countermeasures Against Radiological Threats (MCART), allow for leveraging robust animal models with novel molecular imaging techniques. One such imaging technique, MALDI (matrix-assisted laser desorption ionization) mass spectrometry imaging (MSI), allows for the direct spatial visualization of lipids, proteins, small molecules, and drugs/drug metabolites-or biomarkers-in an unbiased manner. MALDI-MSI acquires mass spectra directly from an intact tissue slice in discrete locations across an x, y grid that are then rendered into a spatial distribution map composed of ion mass and intensity. The unique mass signals can be plotted to generate a spatial map of biomarkers that reflects pathology and molecular events. The crucial unanswered questions that can be addressed with MALDI-MSI include identification of biomarkers for radiation damage that reflect the response to radiation dose over time and the efficacy of therapeutic interventions. Techniques in MALDI-MSI also enable integration of biomarker identification among diverse animal models. Analysis of early, sublethally irradiated tissue injury samples from diverse mouse tissues (lung and ileum) shows membrane phospholipid signatures correlated with histological features of these unique tissues. This paper will discuss the application of MALDI-MSI for use in a larger biomarker discovery pipeline.

  12. A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles

    Directory of Open Access Journals (Sweden)

    Dey Dipak K

    2008-01-01

    Full Text Available Abstract Background The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI and matrix assisted laser desorption (MALDI time-of-flight (TOF mass spectrometry have been used to identify biomarkers both in proteomics and metabonomics studies. Data sets generated from such studies are generally very large in size and thus require the use of sophisticated statistical techniques to glean useful information. Most recent attempts to process these types of data model each compound's intensity either discretely by positional (mass to charge ratio clustering or through each compounds' own intensity distribution. Traditionally data processing steps such as noise removal, background elimination and m/z alignment, are generally carried out separately resulting in unsatisfactory propagation of signals in the final model. Results In the present study a novel semi-parametric approach has been developed to distinguish urinary metabolic profiles in a group of traumatic patients from those of a control group consisting of normal individuals. Data sets obtained from the replicates of a single subject were used to develop a functional profile through Dirichlet mixture of beta distribution. This functional profile is flexible enough to accommodate variability of the instrument and the inherent variability of each individual, thus simultaneously addressing different sources of systematic error. To address instrument variability, all data sets were analyzed in replicate, an important issue ignored by most studies in the past. Different model comparisons were performed to select the best model for each subject. The m/z values in the window of the irregular pattern are then further recommended for possible biomarker discovery. Conclusion To the best of our knowledge this is the very first attempt to model the physical process behind the time-of flight mass

  13. Advances in the proteomic discovery of novel therapeutic targets in cancer

    Directory of Open Access Journals (Sweden)

    Guo S

    2013-10-01

    Full Text Available Shanchun Guo,1 Jin Zou,2 Guangdi Wang3 1Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, 2Center for Cancer Research and Therapeutic Development, Clark Atlanta University, Atlanta, GA, USA; 3Research Centers in Minority Institutions Cancer Research Program, Xavier University of Louisiana, New Orleans, LA, USA Abstract: Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed. Keywords: proteomics, cancer, therapeutic target, signaling network, tumorigenesis

  14. Infectious Disease Proteome Biomarkers: Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, Charles L.

    2011-12-31

    Research for the DOE Infectious Disease Proteome Biomarkers focused on Rift Valley fever virus (RVFV) and Venezuelan Equine Encephalitis Virus (VEEV). RVFV and VEEV are Category A and B pathogens respectively. Among the priority threats, RVFV and VEEV rank high in their potential for being weaponized and introduced to the United States, spreading quickly, and having a large health and economic impact. In addition, they both have live attenuated vaccine, which allows work to be performed at BSL-2. While the molecular biology of RVFV and VEEV are increasingly well-characterized, little is known about its host-pathogen interactions. Our research is aimed at determining critical alterations in host signaling pathways to identify therapeutics targeted against the host.

  15. Neopeptide Analyser: A software tool for neopeptide discovery in proteomics data [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Mandy Peffers

    2017-04-01

    Full Text Available Experiments involving mass spectrometry (MS-based proteomics are widely used for analyses of connective tissues. Common examples include the use of relative quantification to identify differentially expressed peptides and proteins in cartilage and tendon. We are working on characterising so-called ‘neopeptides’, i.e. peptides formed due to native cleavage of proteins, for example under pathological conditions. Unlike peptides typically quantified in MS workflows due to the in vitro use of an enzyme such as trypsin, a neopeptide has at least one terminus that was not due to the use of trypsin in the workflow. The identification of neopeptides within these datasets is important in understanding disease pathology, and the development of antibodies that could be utilised as diagnostic biomarkers for diseases, such as osteoarthritis, and targets for novel treatments. Our previously described neopeptide data analysis workflow was laborious and was not amenable to robust statistical analysis, which reduced confidence in the neopeptides identified. To overcome this, we developed ‘Neopeptide Analyser’, a user friendly neopeptide analysis tool used in conjunction with label-free MS quantification tool Progenesis QIP for proteomics. Neopeptide Analyser filters data sourced from Progenesis QIP output to identify neopeptide sequences, as well as give the residues that are adjacent to the peptide in its corresponding protein sequence. It also produces normalised values for the neopeptide quantification values and uses these to perform statistical tests, which are also included in the output. Neopeptide Analyser is available as a Java application for Mac, Windows and Linux. The analysis features and ease of use encourages data exploration, which could aid the discovery of novel pathways in extracellular matrix degradation, the identification of potential biomarkers and as a tool to investigate matrix turnover. Neopeptide Analyser is available from

  16. MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes

    DEFF Research Database (Denmark)

    Zhang, Yanling; Zhang, Yong; Adachi, Jun

    2007-01-01

    and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http......://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic...... annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools....

  17. Proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Xing [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China); Xu, Yanli [Fuyang People’s Hospital (China); Meng, Qian [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China); Zheng, Qingqing [Digestive Endoscopic Center, Shanghai Jiaotong University Affiliated Sixth People’s Hospital (China); Wu, Jianhong [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China); Wang, Chen; Jia, Weiping [Shanghai Key Laboratory of Diabetes Mellitus, Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital (China); Figeys, Daniel [Department of Biochemistry, Microbiology and Immunology, and Department of Chemistry and Biomolecular Sciences, University of Ottawa (Canada); Chang, Ying, E-mail: emulan@163.com [Digestive Endoscopic Center, Shanghai Jiaotong University Affiliated Sixth People’s Hospital (China); Zhou, Hu, E-mail: zhouhu@simm.ac.cn [Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences (China)

    2016-08-05

    Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP and NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.

  18. Proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling

    International Nuclear Information System (INIS)

    Liu, Xing; Xu, Yanli; Meng, Qian; Zheng, Qingqing; Wu, Jianhong; Wang, Chen; Jia, Weiping; Figeys, Daniel; Chang, Ying; Zhou, Hu

    2016-01-01

    Colorectal cancer (CRC) is one of the most common types of malignant tumor worldwide. Currently, although many researchers have been devoting themselves in CRC studies, the process of locating biomarkers for CRC early diagnosis and prognostic is still very slow. Using a centrifugal proteomic reactor-based proteomic analysis of minute amount of colonic biopsies by enteroscopy sampling, 2620 protein groups were quantified between cancer mucosa and adjacent normal colorectal mucosa. Of which, 403 protein groups were differentially expressed with statistic significance between cancer and normal tissues, including 195 up-regulated and 208 down-regulated proteins in cancer tissues. Three proteins (SOD3, PRELP and NGAL) were selected for further Western blot validation. And the resulting Western blot experimental results were consistent with the quantitative proteomic data. SOD3 and PRELP are down-regulated in CRC mucosa comparing to adjacent normal tissue, while NGAL is up-regulated in CRC mucosa. In conclusion, the centrifugal proteomic reactor-based label-free quantitative proteomic approach provides a highly sensitive and powerful tool for analyzing minute protein sample from tiny colorectal biopsies, which may facilitate CRC biomarkers discovery for diagnoses and prognoses. -- Highlights: •Minute amount of colonic biopsies by endoscopy is suitable for proteomic analysis. •Centrifugal proteomic reactor can be used for processing tiny clinic biopsy sample. •SOD3 and PRELP are down-regulated in CRC, while NGAL is up-regulated in CRC.

  19. Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel

    Science.gov (United States)

    2016-12-01

    Award Number: W81XWH-12-1-0382 TITLE: Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel PRINCIPAL...SUBTITLE Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel 5a. CONTRACT NUMBER W81XWH-12-1-0382 5b. GRANT...of the 1990-1991 Gulf War are affected by Gulf War illness (GWI), the chronic condition currently defined only by veterans’ self-reported symptoms

  20. A Timely shift from shotgun to targeted proteomics and how it can be groundbreaking for cancer research

    DEFF Research Database (Denmark)

    Faria, Sara S.; Morris, Carlos F.M.; Silva, Adriano R.

    2017-01-01

    shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated...... to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples...... applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm...

  1. Glyco-centric lectin magnetic bead array (LeMBA − proteomics dataset of human serum samples from healthy, Barrett׳s esophagus and esophageal adenocarcinoma individuals

    Directory of Open Access Journals (Sweden)

    Alok K. Shah

    2016-06-01

    Full Text Available This data article describes serum glycoprotein biomarker discovery and qualification datasets generated using lectin magnetic bead array (LeMBA – mass spectrometry techniques, “Serum glycoprotein biomarker discovery and qualification pipeline reveals novel diagnostic biomarker candidates for esophageal adenocarcinoma” [1]. Serum samples collected from healthy, metaplastic Barrett׳s esophagus (BE and esophageal adenocarcinoma (EAC individuals were profiled for glycoprotein subsets via differential lectin binding. The biomarker discovery proteomics dataset consisting of 20 individual lectin pull-downs for 29 serum samples with a spiked-in internal standard chicken ovalbumin protein has been deposited in the PRIDE partner repository of the ProteomeXchange Consortium with the data set identifier PRIDE: http://www.ebi.ac.uk/pride/archive/projects/PXD002442. Annotated MS/MS spectra for the peptide identifications can be viewed using MS-Viewer (〈http://prospector2.ucsf.edu/prospector/cgi-bin/msform.cgi?form=msviewer〉 using search key “jn7qafftux”. The qualification dataset contained 6-lectin pulldown-coupled multiple reaction monitoring-mass spectrometry (MRM-MS data for 41 protein candidates, from 60 serum samples. This dataset is available as a supplemental files with the original publication [1].

  2. Data-Independent Acquisition-Based Quantitative Proteomic Analysis Reveals Potential Biomarkers of Kidney Cancer.

    Science.gov (United States)

    Song, Yimeng; Zhong, Lijun; Zhou, Juntuo; Lu, Min; Xing, Tianying; Ma, Lulin; Shen, Jing

    2017-12-01

    Renal cell carcinoma (RCC) is a malignant and metastatic cancer with 95% mortality, and clear cell RCC (ccRCC) is the most observed among the five major subtypes of RCC. Specific biomarkers that can distinguish cancer tissues from adjacent normal tissues should be developed to diagnose this disease in early stages and conduct a reliable prognostic evaluation. Data-independent acquisition (DIA) strategy has been widely employed in proteomic analysis because of various advantages, including enhanced protein coverage and reliable data acquisition. In this study, a DIA workflow is constructed on a quadrupole-Orbitrap LC-MS platform to reveal dysregulated proteins between ccRCC and adjacent normal tissues. More than 4000 proteins are identified, 436 of these proteins are dysregulated in ccRCC tissues. Bioinformatic analysis reveals that multiple pathways and Gene Ontology items are strongly associated with ccRCC. The expression levels of L-lactate dehydrogenase A chain, annexin A4, nicotinamide N-methyltransferase, and perilipin-2 examined through RT-qPCR, Western blot, and immunohistochemistry confirm the validity of the proteomic analysis results. The proposed DIA workflow yields optimum time efficiency and data reliability and provides a good choice for proteomic analysis in biological and clinical studies, and these dysregulated proteins might be potential biomarkers for ccRCC diagnosis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Biomarker discovery for colon cancer using a 761 gene RT-PCR assay

    Directory of Open Access Journals (Sweden)

    Hackett James R

    2007-08-01

    Full Text Available Abstract Background Reverse transcription PCR (RT-PCR is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan® RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis and the likelihood of tumor response to standard chemotherapy regimens (prediction. We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. Results RNA was extracted from formalin fixed paraffin embedded (FPE tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan® reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. Conclusion We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of

  4. Prediction of acute coronary syndromes by urinary proteome analysis.

    Directory of Open Access Journals (Sweden)

    Nay M Htun

    Full Text Available Identification of individuals who are at risk of suffering from acute coronary syndromes (ACS may allow to introduce preventative measures. We aimed to identify ACS-related urinary peptides, that combined as a pattern can be used as prognostic biomarker. Proteomic data of 252 individuals enrolled in four prospective studies from Australia, Europe and North America were analyzed. 126 of these had suffered from ACS within a period of up to 5 years post urine sampling (cases. Proteomic analysis of 84 cases and 84 matched controls resulted in the discovery of 75 ACS-related urinary peptides. Combining these to a peptide pattern, we established a prognostic biomarker named Acute Coronary Syndrome Predictor 75 (ACSP75. ACSP75 demonstrated reasonable prognostic discrimination (c-statistic = 0.664, which was similar to Framingham risk scoring (c-statistics = 0.644 in a validation cohort of 42 cases and 42 controls. However, generating by a composite algorithm named Acute Coronary Syndrome Composite Predictor (ACSCP, combining the biomarker pattern ACSP75 with the previously established urinary proteomic biomarker CAD238 characterizing coronary artery disease as the underlying aetiology, and age as a risk factor, further improved discrimination (c-statistic = 0.751 resulting in an added prognostic value over Framingham risk scoring expressed by an integrated discrimination improvement of 0.273 ± 0.048 (P < 0.0001 and net reclassification improvement of 0.405 ± 0.113 (P = 0.0007. In conclusion, we demonstrate that urinary peptide biomarkers have the potential to predict future ACS events in asymptomatic patients. Further large scale studies are warranted to determine the role of urinary biomarkers in clinical practice.

  5. Proteomics analysis after traumatic brain injury in rats: the search for potential biomarkers

    Directory of Open Access Journals (Sweden)

    Jun Ding

    2015-04-01

    Full Text Available Many studies of protein expression after traumatic brain injury (TBI have identified biomarkers for diagnosing or determining the prognosis of TBI. In this study, we searched for additional protein markers of TBI using a fluid perfusion impact device to model TBI in S-D rats. Two-dimensional gel electrophoresis and mass spectrometry were used to identify differentially expressed proteins. After proteomic analysis, we detected 405 and 371 protein spots within a pH range of 3-10 from sham-treated and contused brain cortex, respectively. Eighty protein spots were differentially expressed in the two groups and 20 of these proteins were identified. This study validated the established biomarkers of TBI and identified potential biomarkers that could be examined in future work.

  6. Time- and radiation-dose dependent changes in the plasma proteome after total body irradiation of non-human primates: Implications for biomarker selection.

    Directory of Open Access Journals (Sweden)

    Stephanie D Byrum

    Full Text Available Acute radiation syndrome (ARS is a complex multi-organ disease resulting from total body exposure to high doses of radiation. Individuals can be exposed to total body irradiation (TBI in a number of ways, including terrorist radiological weapons or nuclear accidents. In order to determine whether an individual has been exposed to high doses of radiation and needs countermeasure treatment, robust biomarkers are needed to estimate radiation exposure from biospecimens such as blood or urine. In order to identity such candidate biomarkers of radiation exposure, high-resolution proteomics was used to analyze plasma from non-human primates following whole body irradiation (Co-60 at 6.7 Gy and 7.4 Gy with a twelve day observation period. A total of 663 proteins were evaluated from the plasma proteome analysis. A panel of plasma proteins with characteristic time- and dose-dependent changes was identified. In addition to the plasma proteomics study reported here, we recently identified candidate biomarkers using urine from these same non-human primates. From the proteomic analysis of both plasma and urine, we identified ten overlapping proteins that significantly differentiate both time and dose variables. These shared plasma and urine proteins represent optimal candidate biomarkers of radiation exposure.

  7. Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

    Science.gov (United States)

    Barkla, Bronwyn J

    2016-09-08

    Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

  8. Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

    Directory of Open Access Journals (Sweden)

    Bronwyn J. Barkla

    2016-09-01

    Full Text Available Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

  9. The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

    Directory of Open Access Journals (Sweden)

    Pierre-Olivier Gaudreau

    2016-01-01

    Full Text Available Prostate cancer (PC is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development.

  10. Serum quantitative proteomic analysis reveals potential zinc-associated biomarkers for nonbacterial prostatitis.

    Science.gov (United States)

    Yang, Xiaoli; Li, Hongtao; Zhang, Chengdong; Lin, Zhidi; Zhang, Xinhua; Zhang, Youjie; Yu, Yanbao; Liu, Kun; Li, Muyan; Zhang, Yuening; Lv, Wenxin; Xie, Yuanliang; Lu, Zheng; Wu, Chunlei; Teng, Ruobing; Lu, Shaoming; He, Min; Mo, Zengnan

    2015-10-01

    Prostatitis is one of the most common urological problems afflicting adult men. The etiology and pathogenesis of nonbacterial prostatitis, which accounts for 90-95% of cases, is largely unknown. As serum proteins often indicate the overall pathologic status of patients, we hypothesized that protein biomarkers of prostatitis might be identified by comparing the serum proteomes of patients with and without nonbacterial prostatitis. All untreated samples were collected from subjects attending the Fangchenggang Area Male Health and Examination Survey (FAMHES). We profiled pooled serum samples from four carefully selected groups of patients (n = 10/group) representing the various categories of nonbacterial prostatitis (IIIa, IIIb, and IV) and matched healthy controls using a mass spectrometry-based 4-plex iTRAQ proteomic approach. More than 160 samples were validated by ELISA. Overall, 69 proteins were identified. Among them, 42, 52, and 37 proteins were identified with differential expression in Category IIIa, IIIb, and IV prostatitis, respectively. The 19 common proteins were related to immunity and defense, ion binding, transport, and proteolysis. Two zinc-binding proteins, superoxide dismutase 3 (SOD3), and carbonic anhydrase I (CA1), were significantly higher in all types of prostatitis than in the control. A receiver operating characteristic curve estimated sensitivities of 50.4 and 68.1% and specificities of 92.1 and 83.8% for CA1 and SOD3, respectively, in detecting nonbacterial prostatitis. The serum CA1 concentration was inversely correlated to the zinc concentration in expressed-prostatic secretions. Our findings suggest that SOD3 and CA1 are potential diagnostic markers of nonbacterial prostatitis, although further large-scale studies are required. The molecular profiles of nonbacterial prostatitis pathogenesis may lay a foundation for discovery of new therapies. © 2015 Wiley Periodicals, Inc.

  11. Proteomic profiling of exosomes leads to the identification of novel biomarkers for prostate cancer

    NARCIS (Netherlands)

    D. Duijvesz (Diederick); K.E. Burnum-Johnson (Kristin); M.A. Gritsenko (Marina); A.M. Hoogland (Marije); M.S. Vredenbregt-van den Berg (Mirella); R. Willemsen (Rob); T.M. Luider (Theo); L. Paša-Tolić (Ljiljana); G.W. Jenster (Guido)

    2013-01-01

    textabstractBackground: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes,

  12. Comparison of serum fractionation methods by data independent label-free proteomics

    Directory of Open Access Journals (Sweden)

    D. Baiwir

    2015-12-01

    Full Text Available Off-line sample prefractionations applied prior to biomarker discovery proteomics are options to enable more protein identifications and detect low-abundance proteins. This work compared five commercial methods efficiency to raw serum analysis using label-free proteomics. The variability of the protein quantities determined for each process was similar to the unprefractionated serum. A 49% increase in protein identifications and 12.2% of reliable quantification were obtained. A 61 times lower limit of protein quantitation was reached compared to protein concentrations observed in raw serum. The concentrations of detected proteins were confronted to estimated reference values.

  13. An individual urinary proteome analysis in normal human beings to define the minimal sample number to represent the normal urinary proteome

    Directory of Open Access Journals (Sweden)

    Liu Xuejiao

    2012-11-01

    Full Text Available Abstract Background The urinary proteome has been widely used for biomarker discovery. A urinary proteome database from normal humans can provide a background for discovery proteomics and candidate proteins/peptides for targeted proteomics. Therefore, it is necessary to define the minimum number of individuals required for sampling to represent the normal urinary proteome. Methods In this study, inter-individual and inter-gender variations of urinary proteome were taken into consideration to achieve a representative database. An individual analysis was performed on overnight urine samples from 20 normal volunteers (10 males and 10 females by 1DLC/MS/MS. To obtain a representative result of each sample, a replicate 1DLCMS/MS analysis was performed. The minimal sample number was estimated by statistical analysis. Results For qualitative analysis, less than 5% of new proteins/peptides were identified in a male/female normal group by adding a new sample when the sample number exceeded nine. In addition, in a normal group, the percentage of newly identified proteins/peptides was less than 5% upon adding a new sample when the sample number reached 10. Furthermore, a statistical analysis indicated that urinary proteomes from normal males and females showed different patterns. For quantitative analysis, the variation of protein abundance was defined by spectrum count and western blotting methods. And then the minimal sample number for quantitative proteomic analysis was identified. Conclusions For qualitative analysis, when considering the inter-individual and inter-gender variations, the minimum sample number is 10 and requires a balanced number of males and females in order to obtain a representative normal human urinary proteome. For quantitative analysis, the minimal sample number is much greater than that for qualitative analysis and depends on the experimental methods used for quantification.

  14. Integrating proteomic and functional genomic technologies in discovery-driven translational breast cancer research

    DEFF Research Database (Denmark)

    Celis, Julio E; Gromov, Pavel; Gromova, Irina

    2003-01-01

    The application of state-of-the-art proteomics and functional genomics technologies to the study of cancer is rapidly shifting toward the analysis of clinically relevant samples derived from patients, as the ultimate aim of translational research is to bring basic discoveries closer to the bedside...

  15. Biomarker discovery in high grade sarcomas by mass spectrometry imaging

    OpenAIRE

    Lou, S.

    2017-01-01

    This thesis demonstrates a detailed biomarker discovery Mass Spectrometry Imaging workflow for histologically heterogeneous high grade sarcomas. Panels of protein and metabolite signatures were discovered either distinguishing different histological subtypes or stratifying high risk patients with poor survival.

  16. Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance : Simultaneous Component Analysis

    NARCIS (Netherlands)

    Mitra, V.; Govorukhina, N.; Zwanenburg, G.; Hoefsloot, H.; Westra, I.; Smilde, A.; Reijmers, T.; van der Zee, A.G.J.; Suits, F.; Bischoff, R.; Horvatovich, P.

    2016-01-01

    Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome

  17. Advances of Salivary Proteomics in Oral Squamous Cell Carcinoma (OSCC Detection: An Update

    Directory of Open Access Journals (Sweden)

    Rabia Sannam Khan

    2016-12-01

    Full Text Available Oral cancer refers to malignancies that have higher morbidity and mortality rates due to the late stage diagnosis and no early detection of a reliable diagnostic marker, while oral squamous cell carcinoma (OSCC is amongst the world’s top ten most common cancers. Diagnosis of cancer requires highly sensitive and specific diagnostic tools which can support untraceable hidden sites of OSCC, yet to be unleashed, for which plenty of biomarkers are identified; the most recommended biomarker detection medium for OSCC includes biological fluids, such as blood and saliva. Saliva holds a promising future in the search for new clinical biomarkers that are easily accessible, less complex, accurate, and cost effective as well as being a non-invasive technique to follow, by analysing the malignant cells’ molecular pathology obtained from saliva through proteomic, genomic and transcriptomic approaches. However, protein biomarkers provide an immense potential for developing novel marker-based assays for oral cancer, hence this current review offers an overall focus on the discovery of a panel of candidates as salivary protein biomarkers, as well as the proteomic tools used for their identification and their significance in early oral cancer detection.

  18. Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases.

    Science.gov (United States)

    Pieragostino, Damiana; D'Alessandro, Michele; di Ioia, Maria; Di Ilio, Carmine; Sacchetta, Paolo; Del Boccio, Piero

    2015-02-01

    Proteomics and metabolomics investigations of body fluids present several challenges for biomarker discovery of several diseases. The search for biomarkers is actually conducted in different body fluids, even if the ideal biomarker can be found in an easily accessible biological fluid, because, if validated, the biomarker could be sought in the healthy population. In this regard, tears could be considered an optimum material obtained by noninvasive procedures. In the past years, the scientific community has become more interested in the study of tears for the research of new biomarkers not only for ocular diseases. In this review, we provide a discussion on the current state of biomarkers research in tears and their relevance for clinical practice, and report the main results of clinical proteomics studies on systemic and eye diseases. We summarize the main methods for tear samples analyses and report recent advances in "omics" platforms for tears investigations. Moreover, we want to take stock of the emerging field of metabolomics and lipidomics as a new and integrated approach to study protein-metabolites interplay for biomarkers research, where tears represent a still unexplored and attractive field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Federica Villanova

    Full Text Available Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid flow cytometry platform (CFP and a unique lyoplate-based flow cytometry platform (LFP in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10 and activation markers (Foxp3 and CD25. Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  20. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

    Science.gov (United States)

    Villanova, Federica; Di Meglio, Paola; Inokuma, Margaret; Aghaeepour, Nima; Perucha, Esperanza; Mollon, Jennifer; Nomura, Laurel; Hernandez-Fuentes, Maria; Cope, Andrew; Prevost, A Toby; Heck, Susanne; Maino, Vernon; Lord, Graham; Brinkman, Ryan R; Nestle, Frank O

    2013-01-01

    Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid) flow cytometry platform (CFP) and a unique lyoplate-based flow cytometry platform (LFP) in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10) and activation markers (Foxp3 and CD25). Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  1. Mass Spectrometry–based Proteomic Profiling of Lung Cancer

    Science.gov (United States)

    Ocak, Sebahat; Chaurand, Pierre; Massion, Pierre P.

    2009-01-01

    In an effort to further our understanding of lung cancer biology and to identify new candidate biomarkers to be used in the management of lung cancer, we need to probe these tissues and biological fluids with tools that address the biology of lung cancer directly at the protein level. Proteins are responsible of the function and phenotype of cells. Cancer cells express proteins that distinguish them from normal cells. Proteomics is defined as the study of the proteome, the complete set of proteins produced by a species, using the technologies of large-scale protein separation and identification. As a result, new technologies are being developed to allow the rapid and systematic analysis of thousands of proteins. The analytical advantages of mass spectrometry (MS), including sensitivity and high-throughput, promise to make it a mainstay of novel biomarker discovery to differentiate cancer from normal cells and to predict individuals likely to develop or recur with lung cancer. In this review, we summarize the progress made in clinical proteomics as it applies to the management of lung cancer. We will focus our discussion on how MS approaches may advance the areas of early detection, response to therapy, and prognostic evaluation. PMID:19349484

  2. Identification and characterization of N-glycosylated proteins using proteomics

    DEFF Research Database (Denmark)

    Selby, David S; Larsen, Martin R; Calvano, Cosima Damiana

    2008-01-01

    and analysis of glycoproteins and glycopeptides. Combinations of affinity-enrichment techniques, chemical and biochemical protocols, and advanced mass spectrometry facilitate detailed glycoprotein analysis in proteomics, from fundamental biological studies to biomarker discovery in biomedicine....... is a complex task and is currently achieved by mass spectrometry-based methods that enable identification of glycoproteins and localization, classification, and analysis of individual glycan structures on proteins. In this chapter we briefly introduce a range of analytical technologies for recovery...

  3. A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

    Science.gov (United States)

    Reis, Henning; Pütter, Carolin; Megger, Dominik A; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-C; Bertram, Stefanie; Wohlschläger, Jeremias; Hagemann, Sascha; Eisenacher, Martin; Scherag, André; Schlaak, Jörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

    2015-06-01

    Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Systems Biology Modeling of the Radiation Sensitivity Network: A Biomarker Discovery Platform

    International Nuclear Information System (INIS)

    Eschrich, Steven; Zhang Hongling; Zhao Haiyan; Boulware, David; Lee, Ji-Hyun; Bloom, Gregory; Torres-Roca, Javier F.

    2009-01-01

    Purpose: The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials: Radiosensitivity, as represented by the survival fraction at 2 Gy was modeled in 48 human cancer cell lines. We applied a linear regression algorithm that integrates gene expression with biological variables, including ras status (mut/wt), tissue of origin and p53 status (mut/wt). Results: The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression analysis. This network was reduced to a 10-hub network that includes c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1, and IRF1. Nine targets associated with radiosensitization drugs are linked to the network, demonstrating clinical relevance. Furthermore, the model identified four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis, as was the tissue of origin, and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included DNA repair, cell cycle, apoptosis, and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon, and breast cancers. Conclusion: We have developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We believe this platform will play a central role in the integration of biology into clinical radiation oncology practice.

  5. State of the Art in Tumor Antigen and Biomarker Discovery

    International Nuclear Information System (INIS)

    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

    2011-01-01

    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology

  6. Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches

    Science.gov (United States)

    2010-07-01

    EMMPRIN is implicated in metastasis via its ability to confer resistance of breast cancer cells to anoikis by inhibiting BIM [21], and its association with...of Bim . J Biol Chem 2006;281:9719–9727. 22. Gupta N, Wollscheid B, Watts JD, Scheer B, Aebersold R, DeFranco AL. Quantitative proteomic analysis of B...disseminated in electronic form, nor  deployed in part or in whole in any  marketing , promotional or educational  contexts without authorization from

  7. MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

    International Nuclear Information System (INIS)

    Yang, Xu; Lazar, Iulia M

    2009-01-01

    The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented. MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000. Preliminary experiments have

  8. Identification of Hip BMD Loss and Fracture Risk Markers Through Population-Based Serum Proteomics: HIP BMD LOSS & FRACTURE RISK MARKERS BY POPULATION-BASED SERUM PROTEOMICS

    Energy Technology Data Exchange (ETDEWEB)

    Nielson, Carrie; Wiedrick, Jack; Shen, Jian; Jacobs, Jon M.; Baker, Erin M.; Baraff, Aaron; Piehowski, Paul D.; Lee, Christine; Baratt, Arie; Petyuk, Vladislav A.; Mcweeney, Shannon K.; Lim, Jeong Youn; Bauer, Douglas C.; Lane, Nancy E.; Cawthon, Peggy M.; Smith, Richard D.; Lapidus, Jodi; Orwoll, Eric S.

    2017-04-06

    Accelerated bone loss significantly increases the risk of osteoporosis and fracture. The mechanisms underlying bone loss remain incompletely understood, and there are few available biomarkers. We utilized a novel proteomics approach to identify serum peptides and proteins associated with bone loss in 1967 older men who were randomly chosen from the Osteoporotic Fracture in Men Study (MrOS study) (age ≥ 65 yrs). Men had 2-3 measures of femoral neck BMD over an average follow-up of 4.6 years. Change in BMD was estimated and then categorized into three groups: maintained BMD (n=453), expected loss (n=1185) and accelerated loss (n=237). A liquid chromatography–ion mobility separation-mass spectrometry (LC-IMS-MS) proteomics platform was used to identify and quantify peptides from serum proteins. The whole cohort was randomly divided into discovery (N= 960) and validation (N= 915) sub-cohorts. Linear regression models and a random forest approach were used to discover differentially abundant individual peptides and a proteomic signature that distinguished individuals with accelerated bone loss from those who maintained BMD. Network analyses were performed using the MetaCore knowledgebase. We identified 12 peptides that were associated with BMD loss in both discovery (P< 0.1 FDR) and replication sub-cohorts (P<0.05). Those 12 peptides mapped to the following proteins: ALS, LYVE1, RNAS1, C2, ICOSL, C163A, C7, HEMO, CD14, CERU, CRAC1 and CD59. Meta-analysis of peptidesassociated with bone loss identified 6 additional proteins including GRP78, IGF-2, SHBG, ENPP2, IBP2 and IBP6. We also identified a proteomic signature that was predictive of BMD loss with a discriminative value similar to serum bone marker carboxy-terminal collagen crosslink peptide (CTX). Interestingly, combining the proteomic signature with CTX significantly improved the ability to discriminate men with accelerated loss. In summary, we have identified potential new biomarkers for bone loss that provide

  9. Identification of azurocidin as a potential periodontitis biomarker by a proteomic analysis of gingival crevicular fluid

    Directory of Open Access Journals (Sweden)

    Lee Jae-Mok

    2011-07-01

    Full Text Available Abstract Background The inflammatory disease periodontitis results in tooth loss and can even lead to diseases of the whole body if not treated. Gingival crevicular fluid (GCF reflects the condition of the gingiva and contains proteins transuded from serum or cells at inflamed sites. In this study, we aimed to discover potential protein biomarkers for periodontitis in GCF proteome using LC-MS/MS. Results We identified 305 proteins from GCF of healthy individuals and periodontitis patients collected using a sterile gel loading tip by ESI-MS/MS coupled to nano-LC. Among these proteins, about 45 proteins were differentially expressed in the GCF proteome of moderate periodontitis patients when compared to the healthy individuals. We first identified azurocidin in the GCF, but not the saliva, as an upregulated protein in the periodontitis patients and verified its increased expression during periodontitis by ELISA using the GCF of the classified periodontitis patients compared to the healthy individuals. In addition, we found that azurocidin inhibited the differentiation of bone marrow-derived macrophages to osteoclasts. Conclusions Our results show that GCF collection using a gel loading tip and subsequent LC-MS/MS analysis following 1D-PAGE proteomic separation are effective for the analysis of the GCF proteome. Our current results also suggest that azurocidin could be a potential biomarker candidate for the early detection of inflammatory periodontal destruction by gingivitis and some chronic periodontitis. Our data also suggest that azurocidin may have an inhibitory role in osteoclast differentiation and, thus, a protective role in alveolar bone loss during the early stages of periodontitis.

  10. Identification of Novel Translational Urinary Biomarkers for Acetaminophen-Induced Acute Liver Injury Using Proteomic Profiling in Mice

    NARCIS (Netherlands)

    van Swelm, Rachel P. L.; Laarakkers, Coby M. M.; van der Kuur, Ellen C.; Morava-Kozicz, Eva; Wevers, Ron A.; Augustijn, Kevin D.; Touw, Daan J.; Sandel, Maro H.; Masereeuw, Rosalinde; Russel, Frans G. M.

    2012-01-01

    Drug-induced liver injury (DILI) is the leading cause of acute liver failure. Currently, no adequate predictive biomarkers for DILI are available. This study describes a translational approach using proteomic profiling for the identification of urinary proteins related to acute liver injury induced

  11. A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

    Science.gov (United States)

    Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

    2017-07-01

    Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

  12. A review of studies of the proteomes of circulating microparticles

    DEFF Research Database (Denmark)

    Nielsen, Christoffer T.; Østergaard, Ole; Rasmussen, Niclas S.

    2017-01-01

    understood, MVs are involved in trafficking of information from cell-to-cell, and are implicated in the regulation of immunity, thrombosis, and coagulation. Different subtypes of extracellular MVs exist. This review focuses on the cell membrane-derived shedded MVs (ranging in size from 200 to 1000 nm...... conditions such as cancer and chronic viral infections. This review highlights the methodology and results of the proteome studies behind these discoveries and places them in a pathophysiological and biomarker perspective....

  13. Low molecular weight protein enrichment on mesoporous silica thin films for biomarker discovery.

    Science.gov (United States)

    Fan, Jia; Gallagher, James W; Wu, Hung-Jen; Landry, Matthew G; Sakamoto, Jason; Ferrari, Mauro; Hu, Ye

    2012-04-17

    The identification of circulating biomarkers holds great potential for non invasive approaches in early diagnosis and prognosis, as well as for the monitoring of therapeutic efficiency.(1-3) The circulating low molecular weight proteome (LMWP) composed of small proteins shed from tissues and cells or peptide fragments derived from the proteolytic degradation of larger proteins, has been associated with the pathological condition in patients and likely reflects the state of disease.(4,5) Despite these potential clinical applications, the use of Mass Spectrometry (MS) to profile the LMWP from biological fluids has proven to be very challenging due to the large dynamic range of protein and peptide concentrations in serum.(6) Without sample pre-treatment, some of the more highly abundant proteins obscure the detection of low-abundance species in serum/plasma. Current proteomic-based approaches, such as two-dimensional polyacrylamide gel-electrophoresis (2D-PAGE) and shotgun proteomics methods are labor-intensive, low throughput and offer limited suitability for clinical applications.(7-9) Therefore, a more effective strategy is needed to isolate LMWP from blood and allow the high throughput screening of clinical samples. Here, we present a fast, efficient and reliable multi-fractionation system based on mesoporous silica chips to specifically target and enrich LMWP.(10,11) Mesoporous silica (MPS) thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different polymer templates and polymer concentrations in the precursor solution, various pore size distributions, pore structures, connectivity and surface properties were determined and applied for selective recovery of low mass proteins. The selective parsing of the enriched peptides into different subclasses according to their physicochemical properties will enhance the efficiency of recovery and detection of low abundance species. In combination with mass

  14. Proteomic candidate biomarkers of drug-induced nephrotoxicity in the rat.

    Directory of Open Access Journals (Sweden)

    Rodney Rouse

    Full Text Available Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10-20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity.

  15. Identification of Potential Plasma Biomarkers for Nonalcoholic Fatty Liver Disease by Integrating Transcriptomics and Proteomics in Laying Hens.

    Science.gov (United States)

    Tsai, Meng-Tsz; Chen, Yu-Jen; Chen, Ching-Yi; Tsai, Mong-Hsun; Han, Chia-Li; Chen, Yu-Ju; Mersmann, Harry J; Ding, Shih-Torng

    2017-03-01

    Background: Prevalent worldwide obesity is associated with increased incidence of nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome. The identification of noninvasive biomarkers for NAFLD is of recent interest. Because primary de novo lipogenesis occurs in chicken liver as in human liver, adult chickens with age-associated steatosis resembling human NAFLD is an appealing animal model. Objective: The objective of this study was to screen potential biomarkers in the chicken model for NAFLD by transcriptomic and proteomic analysis. Methods: Hy-Line W-36 laying hens were fed standard feed from 25 to 45 wk of age to induce fatty liver. They were killed every 4 wk, and liver and plasma were collected at each time point to assess fatty liver development and for transcriptomic and proteomic analysis. Next, selected biomarkers were confirmed in additional experiments by providing supplements of the hepatoprotective nutrients betaine [300, 600, or 900 parts per million (ppm) in vivo; 2 mM in vitro] or docosahexaenoic acid (DHA; 1% in vivo; 100 μM in vitro) to 30-wk-old Hy-Line W-36 laying hens for 4 mo and to Hy-Line W-36 chicken primary hepatocytes with oleic acid-induced steatosis. Liver or hepatocyte lipid contents and the expression of biomarkers were then examined. Results: Plasma acetoacetyl-CoA synthetase (AACS), dipeptidyl-peptidase 4 (DPP4), glutamine synthetase (GLUL), and glutathione S -transferase (GST) concentrations are well-established biomarkers for NAFLD. Selected biomarkers had significant positive associations with hepatic lipid deposition ( P steatosis accompanied by the reduced expression of selected biomarkers in vivo and in vitro ( P < 0.05). Conclusion: This study used adult laying hens to identify biomarkers for NAFLD and indicated that AACS, DPP4, GLUL, and GST could be considered to be potential diagnostic indicators for NAFLD in the future. © 2017 American Society for Nutrition.

  16. Proteomics mapping of cord blood identifies haptoglobin "switch-on" pattern as biomarker of early-onset neonatal sepsis in preterm newborns.

    Science.gov (United States)

    Buhimschi, Catalin S; Bhandari, Vineet; Dulay, Antonette T; Nayeri, Unzila A; Abdel-Razeq, Sonya S; Pettker, Christian M; Thung, Stephen; Zhao, Guomao; Han, Yiping W; Bizzarro, Matthew; Buhimschi, Irina A

    2011-01-01

    Intra-amniotic infection and/or inflammation (IAI) are important causes of preterm birth and early-onset neonatal sepsis (EONS). A prompt and accurate diagnosis of EONS is critical for improved neonatal outcomes. We sought to explore the cord blood proteome and identify biomarkers and functional protein networks characterizing EONS in preterm newborns. We studied a prospective cohort of 180 premature newborns delivered May 2004-September 2009. A proteomics discovery phase employing two-dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry identified 19 differentially-expressed proteins in cord blood of newborns with culture-confirmed EONS (n = 3) versus GA-matched controls (n = 3). Ontological classifications of the proteins included transfer/carrier, immunity/defense, protease/extracellular matrix. The 1(st)-level external validation conducted in the remaining 174 samples confirmed elevated haptoglobin and haptoglobin-related protein immunoreactivity (Hp&HpRP) in newborns with EONS (presumed and culture-confirmed) independent of GA at birth and birthweight (PLCA) was further used for unbiased classification of all 180 cases based on probability of "antenatal IAI exposure" as latent variable. This was then subjected to 2(nd)-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. This approach reclassified ∼30% of clinical EONS diagnoses lowering the number needed to harm and increasing the odds ratios for several adverse outcomes including intra-ventricular hemorrhage. Antenatal exposure to IAI results in precocious switch-on of Hp&HpRP expression. As EONS biomarker, cord blood Hp&HpRP has potential to improve the selection of newborns for prompt and targeted treatment at birth.

  17. Biomarkers as drug development tools: discovery, validation, qualification and use.

    Science.gov (United States)

    Kraus, Virginia B

    2018-06-01

    The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

  18. Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

    Science.gov (United States)

    Megger, Dominik Andre; Rosowski, Kristin; Ahrens, Maike; Bracht, Thilo; Eisenacher, Martin; Schlaak, Jörg F; Weber, Frank; Hoffmann, Andreas-Claudius; Meyer, Helmut E; Baba, Hideo A; Sitek, Barbara

    2017-03-01

    Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. RAB1A was verified to be a potent biomarker candidate for HCC.

  19. Data for a comprehensive map and functional annotation of the human cerebrospinal fluid proteome

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2015-06-01

    Full Text Available Knowledge about the normal human cerebrospinal fluid (CSF proteome serves as a baseline reference for CSF biomarker discovery and provides insight into CSF physiology. In this study, high-pH reverse-phase liquid chromatography (hp-RPLC was first integrated with a TripleTOF 5600 mass spectrometer to comprehensively profile the normal CSF proteome. A total of 49,836 unique peptides and 3256 non-redundant proteins were identified. To obtain high-confidence results, 2513 proteins with at least 2 unique peptides were further selected as bona fide CSF proteins. Nearly 30% of the identified CSF proteins have not been previously reported in the normal CSF proteome. More than 25% of the CSF proteins were components of CNS cell microenvironments, and network analyses indicated their roles in the pathogenesis of neurological diseases. The top canonical pathway in which the CSF proteins participated was axon guidance signaling. More than one-third of the CSF proteins (788 proteins were related to neurological diseases, and these proteins constitute potential CSF biomarker candidates. The mapping results can be freely downloaded at http://122.70.220.102:8088/csf/, which can be used to navigate the CSF proteome. For more information about the data, please refer to the related original article [1], which has been recently accepted by Journal of Proteomics.

  20. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

    Kracun, Stjepan Kresimir; Cló, Emiliano; Clausen, Henrik

    2010-01-01

    have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA...... to other tumor glycoforms by on-bead enzymatic glycosylation reactions with recombinant glycosyltransferases. Hence, we have developed a high-throughput flexible platform for rapid discovery of O-glycopeptide biomarkers and the method has applicability in other types of assays such as lectin...

  1. MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes.

    Science.gov (United States)

    Zhang, Yanling; Zhang, Yong; Adachi, Jun; Olsen, Jesper V; Shi, Rong; de Souza, Gustavo; Pasini, Erica; Foster, Leonard J; Macek, Boris; Zougman, Alexandre; Kumar, Chanchal; Wisniewski, Jacek R; Jun, Wang; Mann, Matthias

    2007-01-01

    Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at http://www.mapuproteome.com using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

  2. Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology

    Science.gov (United States)

    Swan, Anna Louise; Mobasheri, Ali; Allaway, David; Liddell, Susan

    2013-01-01

    Abstract Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes. PMID:24116388

  3. Technological advances for deciphering the complexity of psychiatric disorders: merging proteomics with cell biology.

    Science.gov (United States)

    Wesseling, Hendrik; Guest, Paul C; Lago, Santiago G; Bahn, Sabine

    2014-08-01

    Proteomic studies have increased our understanding of the molecular pathways affected in psychiatric disorders. Mass spectrometry and two-dimensional gel electrophoresis analyses of post-mortem brain samples from psychiatric patients have revealed effects on synaptic, cytoskeletal, antioxidant and mitochondrial protein networks. Multiplex immunoassay profiling studies have found alterations in hormones, growth factors, transport and inflammation-related proteins in serum and plasma from living first-onset patients. Despite these advances, there are still difficulties in translating these findings into platforms for improved treatment of patients and for discovery of new drugs with better efficacy and side effect profiles. This review describes how the next phase of proteomic investigations in psychiatry should include stringent replication studies for validation of biomarker candidates and functional follow-up studies which can be used to test the impact on physiological function. All biomarker candidates should now be tested in series with traditional and emerging cell biological approaches. This should include investigations of the effects of post-translational modifications, protein dynamics and network analyses using targeted proteomic approaches. Most importantly, there is still an urgent need for development of disease-relevant cellular models for improved translation of proteomic findings into a means of developing novel drug treatments for patients with these life-altering disorders.

  4. Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

    Science.gov (United States)

    Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana; Hu, Shen

    2017-01-01

    Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients' saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects ( p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

  5. Mining novel biomarkers for prognosis of gastric cancer with serum proteomics

    Directory of Open Access Journals (Sweden)

    Sui Mei-Hua

    2009-09-01

    Full Text Available Abstract Background Although gastric caner (GC remains the second cause of cancer-related death, useful biomarkers for prognosis are still unavailable. We present here the attempt of mining novel biomarkers for GC prognosis by using serum proteomics. Methods Sera from 43 GC patients and 41 controls with gastritis as Group 1 and 11 GC patients as Group 2 was successively detected by Surface Enhanced Laser Desorption/ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS with Q10 chip. Peaks were acquired by Ciphergen ProteinChip Software 3.2.0 and analyzed by Zhejiang University-ProteinChip Data Analysis System (ZJU-PDAS. CEA level were evaluated by chemiluminescence immunoassay. Results After median follow-up periods of 33 months, Group 1 with 4 GC patients lost was divided into 20 good-prognosis GC patients (overall survival more than 24 months and 19 poor-prognosis GC patients (no more than 24 months. The established prognosis pattern consisted of 5 novel prognosis biomarkers with 84.2% sensitivity and 85.0% specificity, which were significantly higher than those of carcinoembryonic antigen (CEA and TNM stage. We also tested prognosis pattern blindly in Group 2 with 66.7% sensitivity and 80.0% specificity. Moreover, we found that 4474-Da peak elevated significantly in GC and was associated with advanced stage (III+IV and short survival (p Conclusion We have identified a number of novel biomarkers for prognosis prediction of GC by using SELDI-TOF-MS combined with sophisticated bioinformatics. Particularly, elevated expression of 4474-Da peak showed very promising to be developed into a novel biomarker associated with biologically aggressive features of GC.

  6. Single-Nucleotide Variations in Cardiac Arrhythmias: Prospects for Genomics and Proteomics Based Biomarker Discovery and Diagnostics

    Directory of Open Access Journals (Sweden)

    Ayman Abunimer

    2014-03-01

    Full Text Available Cardiovascular diseases are a large contributor to causes of early death in developed countries. Some of these conditions, such as sudden cardiac death and atrial fibrillation, stem from arrhythmias—a spectrum of conditions with abnormal electrical activity in the heart. Genome-wide association studies can identify single nucleotide variations (SNVs that may predispose individuals to developing acquired forms of arrhythmias. Through manual curation of published genome-wide association studies, we have collected a comprehensive list of 75 SNVs associated with cardiac arrhythmias. Ten of the SNVs result in amino acid changes and can be used in proteomic-based detection methods. In an effort to identify additional non-synonymous mutations that affect the proteome, we analyzed the post-translational modification S-nitrosylation, which is known to affect cardiac arrhythmias. We identified loss of seven known S-nitrosylation sites due to non-synonymous single nucleotide variations (nsSNVs. For predicted nitrosylation sites we found 1429 proteins where the sites are modified due to nsSNV. Analysis of the predicted S-nitrosylation dataset for over- or under-representation (compared to the complete human proteome of pathways and functional elements shows significant statistical over-representation of the blood coagulation pathway. Gene Ontology (GO analysis displays statistically over-represented terms related to muscle contraction, receptor activity, motor activity, cystoskeleton components, and microtubule activity. Through the genomic and proteomic context of SNVs and S-nitrosylation sites presented in this study, researchers can look for variation that can predispose individuals to cardiac arrhythmias. Such attempts to elucidate mechanisms of arrhythmia thereby add yet another useful parameter in predicting susceptibility for cardiac diseases.

  7. Proteomics Mapping of Cord Blood Identifies Haptoglobin “Switch-On” Pattern as Biomarker of Early-Onset Neonatal Sepsis in Preterm Newborns

    Science.gov (United States)

    Buhimschi, Catalin S.; Bhandari, Vineet; Dulay, Antonette T.; Nayeri, Unzila A.; Abdel-Razeq, Sonya S.; Pettker, Christian M.; Thung, Stephen; Zhao, Guomao; Han, Yiping W.; Bizzarro, Matthew; Buhimschi, Irina A.

    2011-01-01

    Background Intra-amniotic infection and/or inflammation (IAI) are important causes of preterm birth and early-onset neonatal sepsis (EONS). A prompt and accurate diagnosis of EONS is critical for improved neonatal outcomes. We sought to explore the cord blood proteome and identify biomarkers and functional protein networks characterizing EONS in preterm newborns. Methodology/Principal Findings We studied a prospective cohort of 180 premature newborns delivered May 2004-September 2009. A proteomics discovery phase employing two-dimensional differential gel electrophoresis (2D-DIGE) and mass spectrometry identified 19 differentially-expressed proteins in cord blood of newborns with culture-confirmed EONS (n = 3) versus GA-matched controls (n = 3). Ontological classifications of the proteins included transfer/carrier, immunity/defense, protease/extracellular matrix. The 1st-level external validation conducted in the remaining 174 samples confirmed elevated haptoglobin and haptoglobin-related protein immunoreactivity (Hp&HpRP) in newborns with EONS (presumed and culture-confirmed) independent of GA at birth and birthweight (PLCA) was further used for unbiased classification of all 180 cases based on probability of “antenatal IAI exposure” as latent variable. This was then subjected to 2nd-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. This approach reclassified ∼30% of clinical EONS diagnoses lowering the number needed to harm and increasing the odds ratios for several adverse outcomes including intra-ventricular hemorrhage. Conclusions/Significance Antenatal exposure to IAI results in precocious switch-on of Hp&HpRP expression. As EONS biomarker, cord blood Hp&HpRP has potential to improve the

  8. Identification of novel biomarkers for sepsis prognosis via urinary proteomic analysis using iTRAQ labeling and 2D-LC-MS/MS.

    Directory of Open Access Journals (Sweden)

    Longxiang Su

    Full Text Available Sepsis is the major cause of death for critically ill patients. Recent progress in proteomics permits a thorough characterization of the mechanisms associated with critical illness. The purpose of this study was to screen potential biomarkers for early prognostic assessment of patients with sepsis.For the discovery stage, 30 sepsis patients with different prognoses were selected. Urinary proteins were identified using isobaric tags for relative and absolute quantitation (iTRAQ coupled with LC-MS/MS. Mass spec instrument analysis were performed with Mascot software and the International Protein Index (IPI; bioinformatic analyses were used by the algorithm of set and the Gene Ontology (GO Database. For the verification stage, the study involved another 54 sepsis-hospitalized patients, with equal numbers of patients in survivor and non-survivor groups based on 28-day survival. Differentially expressed proteins were verified by Western Blot.A total of 232 unique proteins were identified. Proteins that were differentially expressed were further analyzed based on the pathophysiology of sepsis and biomathematics. For sepsis prognosis, five proteins were significantly up-regulated: selenium binding protein-1, heparan sulfate proteoglycan-2, alpha-1-B glycoprotein, haptoglobin, and lipocalin; two proteins were significantly down-regulated: lysosome-associated membrane proteins-1 and dipeptidyl peptidase-4. Based on gene ontology clustering, these proteins were associated with the biological processes of lipid homeostasis, cartilage development, iron ion transport, and certain metabolic processes. Urinary LAMP-1 was down-regulated, consistent with the Western Blot validation.This study provides the proteomic analysis of urine to identify prognostic biomarkers of sepsis. The seven identified proteins provide insight into the mechanism of sepsis. Low urinary LAMP-1 levels may be useful for early prognostic assessment of sepsis.ClinicalTrial.gov NCT01493492.

  9. Quantitative iTRAQ-Based Proteomic Identification of Candidate Biomarkers for Diabetic Nephropathy in Plasma of Type 1 Diabetic Patients

    DEFF Research Database (Denmark)

    Overgaard, Anne Julie; Thingholm, Tine Engberg; Larsen, Martin R

    2010-01-01

    INTRODUCTION: As part of a clinical proteomics programme focused on diabetes and its complications, it was our goal to investigate the proteome of plasma in order to find improved candidate biomarkers to predict diabetic nephropathy. METHODS: Proteins derived from plasma from a cross-sectional co...... nephropathy; however, they need to be confirmed in a longitudinal cohort. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12014-010-9053-0) contains supplementary material, which is available to authorized users....

  10. Comprehensive proteomic analysis of human pancreatic juice

    DEFF Research Database (Denmark)

    Grønborg, Mads; Bunkenborg, Jakob; Kristiansen, Troels Zakarias

    2004-01-01

    Proteomic technologies provide an excellent means for analysis of body fluids for cataloging protein constituents and identifying biomarkers for early detection of cancers. The biomarkers currently available for pancreatic cancer, such as CA19-9, lack adequate sensitivity and specificity...... contributing to late diagnosis of this deadly disease. In this study, we carried out a comprehensive characterization of the "pancreatic juice proteome" in patients with pancreatic adenocarcinoma. Pancreatic juice was first fractionated by 1-dimensional gel electrophoresis and subsequently analyzed by liquid...... in this study could be directly assessed for their potential as biomarkers for pancreatic cancer by quantitative proteomics methods or immunoassays....

  11. Analytical methods for proteome data obtained from SDS-PAGE multi-dimensional separation and mass spectrometry

    Directory of Open Access Journals (Sweden)

    Gun Wook Park

    2010-03-01

    Full Text Available For proteome analysis, various experimental protocols using mass spectrometry have been developed over thelast decade. The different protocols have differing performances and degrees of accuracy. Furthermore, the “best”protocol for a proteomic analysis of a sample depends on the purpose of the analysis, especially in connection withdisease proteomics, including biomarker discovery and therapeutics analyses of human serum or plasma. Theprotein complexity and the wide dynamic range of blood samples require high-dimensional separation technology.In this article, we review proteome analysis protocols in which both Sodium Dodecyl Sulfate-Polyacryl Amide GelElectrophoresis(SDS-PAGE and liquid chromatography are used for peptide and protein separations. Multidimensionalseparation technology supplies a high-quality dataset of tandem mass spectra and reveals signals fromlow-abundance proteins, although it can be time-consuming and laborious work. We survey shotgun proteomicsprotocols using SDS-PAGE and liquid chromatography and introduce bioinformatics tools for the analysis ofproteomics data. We also review efforts toward the biological interpretation of the proteome.

  12. Proteomic profiling of renal allograft rejection in serum using magnetic bead-based sample fractionation and MALDI-TOF MS.

    Science.gov (United States)

    Sui, Weiguo; Huang, Liling; Dai, Yong; Chen, Jiejing; Yan, Qiang; Huang, He

    2010-12-01

    Proteomics is one of the emerging techniques for biomarker discovery. Biomarkers can be used for early noninvasive diagnosis and prognosis of diseases and treatment efficacy evaluation. In the present study, the well-established research systems of ClinProt Micro solution incorporated unique magnetic bead sample preparation technology, which, based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), have become very successful in bioinformatics due to its outstanding performance and reproducibility for discovery disease-related biomarker. We collected fasting blood samples from patients with biopsy-confirmed acute renal allograft rejection (n = 12), chronic rejection (n = 12), stable graft function (n = 12) and also from healthy volunteers (n = 13) to study serum peptidome patterns. Specimens were purified with magnetic bead-based weak cation exchange chromatography and analyzed with a MALDI-TOF mass spectrometer. The results indicated that 18 differential peptide peaks were selected as potential biomarkers of acute renal allograft rejection, and 6 differential peptide peaks were selected as potential biomarkers of chronic rejection. A Quick Classifier Algorithm was used to set up the classification models for acute and chronic renal allograft rejection. The algorithm models recognize 82.64% of acute rejection and 98.96% of chronic rejection episodes, respectively. We were able to identify serum protein fingerprints in small sample sizes of recipients with renal allograft rejection and establish the models for diagnosis of renal allograft rejection. This preliminary study demonstrated that proteomics is an emerging tool for early diagnosis of renal allograft rejection and helps us to better understand the pathogenesis of disease process.

  13. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Science.gov (United States)

    Tahara, Hideaki; Sato, Marimo; Thurin, Magdalena; Wang, Ena; Butterfield, Lisa H; Disis, Mary L; Fox, Bernard A; Lee, Peter P; Khleif, Samir N; Wigginton, Jon M; Ambs, Stefan; Akutsu, Yasunori; Chaussabel, Damien; Doki, Yuichiro; Eremin, Oleg; Fridman, Wolf Hervé; Hirohashi, Yoshihiko; Imai, Kohzoh; Jacobson, James; Jinushi, Masahisa; Kanamoto, Akira; Kashani-Sabet, Mohammed; Kato, Kazunori; Kawakami, Yutaka; Kirkwood, John M; Kleen, Thomas O; Lehmann, Paul V; Liotta, Lance; Lotze, Michael T; Maio, Michele; Malyguine, Anatoli; Masucci, Giuseppe; Matsubara, Hisahiro; Mayrand-Chung, Shawmarie; Nakamura, Kiminori; Nishikawa, Hiroyoshi; Palucka, A Karolina; Petricoin, Emanuel F; Pos, Zoltan; Ribas, Antoni; Rivoltini, Licia; Sato, Noriyuki; Shiku, Hiroshi; Slingluff, Craig L; Streicher, Howard; Stroncek, David F; Takeuchi, Hiroya; Toyota, Minoru; Wada, Hisashi; Wu, Xifeng; Wulfkuhle, Julia; Yaguchi, Tomonori; Zeskind, Benjamin; Zhao, Yingdong; Zocca, Mai-Britt; Marincola, Francesco M

    2009-01-01

    Supported by the Office of International Affairs, National Cancer Institute (NCI), the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc) and the United States Food and Drug Administration (FDA) to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a) to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b) to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD) of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs) likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers were recognized that

  14. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Directory of Open Access Journals (Sweden)

    Rivoltini Licia

    2009-06-01

    Full Text Available Abstract Supported by the Office of International Affairs, National Cancer Institute (NCI, the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc and the United States Food and Drug Administration (FDA to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers

  15. Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease.

    Directory of Open Access Journals (Sweden)

    Esther Nkuipou-Kenfack

    Full Text Available Chronic kidney disease (CKD is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR at mild (59.9±16.5 mL/min/1.73 m2; n = 10 or advanced (8.9±4.5 mL/min/1.73 m2; n = 10 CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = -0.8031; p<0.0001 and ρ = -0.6009; p = 0.0019, respectively. Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = -0.6557; p = 0.0001 and ρ = -0.6574; p = 0.0005. A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = -0.7752; p<0.0001 and ρ = -0.8400; p<0.0001. The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In

  16. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  17. Mining the granule proteome

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Goetze, Jens P; Johnsen, Anders H

    2015-01-01

    Proteomics of secretory granules is an emerging strategy for identifying secreted proteins, including potentially novel candidate biomarkers and peptide hormones. In addition, proteomics can provide information about the abundance, localization and structure (post-translational modification) of g...

  18. Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics.

    Science.gov (United States)

    Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

    2016-09-01

    Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

  19. Liver proteomics in progressive alcoholic steatosis

    Energy Technology Data Exchange (ETDEWEB)

    Fernando, Harshica [Department of Pathology, The University of Texas Medical Branch, Galveston, TX 77555 (United States); Wiktorowicz, John E.; Soman, Kizhake V. [Department of Biochemistry and Molecular Biology, The University of Texas Medical Branch, Galveston, TX 77555 (United States); Kaphalia, Bhupendra S.; Khan, M. Firoze [Department of Pathology, The University of Texas Medical Branch, Galveston, TX 77555 (United States); Shakeel Ansari, G.A., E-mail: sansari@utmb.edu [Department of Pathology, The University of Texas Medical Branch, Galveston, TX 77555 (United States)

    2013-02-01

    Fatty liver is an early stage of alcoholic and nonalcoholic liver disease (ALD and NALD) that progresses to steatohepatitis and other irreversible conditions. In this study, we identified proteins that were differentially expressed in the livers of rats fed 5% ethanol in a Lieber–DeCarli diet daily for 1 and 3 months by discovery proteomics (two-dimensional gel electrophoresis and mass spectrometry) and non-parametric modeling (Multivariate Adaptive Regression Splines). Hepatic fatty infiltration was significantly higher in ethanol-fed animals as compared to controls, and more pronounced at 3 months of ethanol feeding. Discovery proteomics identified changes in the expression of proteins involved in alcohol, lipid, and amino acid metabolism after ethanol feeding. At 1 and 3 months, 12 and 15 different proteins were differentially expressed. Of the identified proteins, down regulation of alcohol dehydrogenase (− 1.6) at 1 month and up regulation of aldehyde dehydrogenase (2.1) at 3 months could be a protective/adaptive mechanism against ethanol toxicity. In addition, betaine-homocysteine S-methyltransferase 2 a protein responsible for methionine metabolism and previously implicated in fatty liver development was significantly up regulated (1.4) at ethanol-induced fatty liver stage (1 month) while peroxiredoxin-1 was down regulated (− 1.5) at late fatty liver stage (3 months). Nonparametric analysis of the protein spots yielded fewer proteins and narrowed the list of possible markers and identified D-dopachrome tautomerase (− 1.7, at 3 months) as a possible marker for ethanol-induced early steatohepatitis. The observed differential regulation of proteins have potential to serve as biomarker signature for the detection of steatosis and its progression to steatohepatitis once validated in plasma/serum. -- Graphical abstract: The figure shows the Hierarchial cluster analysis of differentially expressed protein spots obtained after ethanol feeding for 1 (1–3

  20. Identification of 10 Candidate Biomarkers Distinguishing Tuberculous and Malignant Pleural Fluid by Proteomic Methods

    OpenAIRE

    Lee, Chang Youl; Hong, Ji Young; Lee, Myung-Goo; Suh, In-Bum

    2017-01-01

    Purpose Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. Materials and Methods We used samples from five patients with t...

  1. Biomarker Analysis of Stored Blood Products: Emphasis on Pre-Analytical Issues

    Science.gov (United States)

    Delobel, Julien; Rubin, Olivier; Prudent, Michel; Crettaz, David; Tissot, Jean-Daniel; Lion, Niels

    2010-01-01

    Millions of blood products are transfused every year; many lives are thus directly concerned by transfusion. The three main labile blood products used in transfusion are erythrocyte concentrates, platelet concentrates and fresh frozen plasma. Each of these products has to be stored according to its particular components. However, during storage, modifications or degradation of those components may occur, and are known as storage lesions. Thus, biomarker discovery of in vivo blood aging as well as in vitro labile blood products storage lesions is of high interest for the transfusion medicine community. Pre-analytical issues are of major importance in analyzing the various blood products during storage conditions as well as according to various protocols that are currently used in blood banks for their preparations. This paper will review key elements that have to be taken into account in the context of proteomic-based biomarker discovery applied to blood banking. PMID:21151459

  2. Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

    2015-11-06

    Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

  3. Semen proteomics and male infertility.

    Science.gov (United States)

    Jodar, Meritxell; Soler-Ventura, Ada; Oliva, Rafael

    2017-06-06

    Semen is a complex body fluid containing an admixture of spermatozoa suspended in secretions from the testes and epididymis which are mixed at the time of ejaculation with secretions from other accessory sex glands such as the prostate and seminal vesicles. High-throughput technologies have revealed that, contrary to the idea that sperm cells are simply a silent delivery vehicle of the male genome to the oocyte, the sperm cells in fact provide both a specific epigenetically marked DNA together with a complex population of proteins and RNAs crucial for embryogenesis. Similarly, -omic technologies have also enlightened that seminal fluid seems to play a much greater role than simply being a medium to carry the spermatozoa through the female reproductive tract. In the present review, we briefly overview the sperm cell biology, consider the key issues in sperm and seminal fluid sample preparation for high-throughput proteomic studies, describe the current state of the sperm and seminal fluid proteomes generated by high-throughput proteomic technologies and provide new insights into the potential communication between sperm and seminal fluid. In addition, comparative proteomic studies open a window to explore the potential pathogenic mechanisms of infertility and the discovery of potential biomarkers with clinical significance. The review updates the numerous proteomics studies performed on semen, including spermatozoa and seminal fluid. In addition, an integrative analysis of the testes, sperm and seminal fluid proteomes is also included providing insights into the molecular mechanisms that regulate the generation, maturation and transit of spermatozoa. Furthermore, the compilation of several differential proteomic studies focused on male infertility reveals potential pathways disturbed in specific subtypes of male infertility and points out towards future research directions in the field. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. A Proteomic Approach for Plasma Biomarker Discovery with iTRAQ Labelling and OFFGEL Fractionation

    Directory of Open Access Journals (Sweden)

    Emilie Ernoult

    2010-01-01

    Full Text Available Human blood plasma contains a plethora of proteins, encompassing not only proteins that have plasma-based functionalities, but also possibly every other form of low concentrated human proteins. As it circulates through the tissues, the plasma picks up proteins that are released from their origin due to physiological events such as tissue remodeling and cell death. Specific disease processes or tumors are often characterized by plasma “signatures,” which may become obvious via changes in the plasma proteome profile, for example, through over expression of proteins. However, the wide dynamic range of proteins present in plasma makes their analysis very challenging, because high-abundance proteins tend to mask those of lower abundance. In the present study, we used a strategy combining iTRAQ as a reagent which improved the peptide ionization and peptide OFFGEL fractionation that has already been shown, in our previous research, to improve the proteome coverage of cellular extracts. Two prefractioning methods were compared: immunodepletion and a bead-based library of combinatorial hexapeptide technology. Our data suggested that both methods were complementary, with regard to the number of identified proteins. iTRAQ labelling, in association with OFFGEL fractionation, allowed more than 300 different proteins to be characterized from 400 μg of plasma proteins.

  6. A proteomic approach for plasma biomarker discovery with iTRAQ labelling and OFFGEL fractionation.

    Science.gov (United States)

    Ernoult, Emilie; Bourreau, Anthony; Gamelin, Erick; Guette, Catherine

    2010-01-01

    Human blood plasma contains a plethora of proteins, encompassing not only proteins that have plasma-based functionalities, but also possibly every other form of low concentrated human proteins. As it circulates through the tissues, the plasma picks up proteins that are released from their origin due to physiological events such as tissue remodeling and cell death. Specific disease processes or tumors are often characterized by plasma "signatures," which may become obvious via changes in the plasma proteome profile, for example, through over expression of proteins. However, the wide dynamic range of proteins present in plasma makes their analysis very challenging, because high-abundance proteins tend to mask those of lower abundance. In the present study, we used a strategy combining iTRAQ as a reagent which improved the peptide ionization and peptide OFFGEL fractionation that has already been shown, in our previous research, to improve the proteome coverage of cellular extracts. Two prefractioning methods were compared: immunodepletion and a bead-based library of combinatorial hexapeptide technology. Our data suggested that both methods were complementary, with regard to the number of identified proteins. iTRAQ labelling, in association with OFFGEL fractionation, allowed more than 300 different proteins to be characterized from 400 microg of plasma proteins.

  7. Identification of candidate diagnostic serum biomarkers for Kawasaki disease using proteomic analysis

    Science.gov (United States)

    Kimura, Yayoi; Yanagimachi, Masakatsu; Ino, Yoko; Aketagawa, Mao; Matsuo, Michie; Okayama, Akiko; Shimizu, Hiroyuki; Oba, Kunihiro; Morioka, Ichiro; Imagawa, Tomoyuki; Kaneko, Tetsuji; Yokota, Shumpei; Hirano, Hisashi; Mori, Masaaki

    2017-01-01

    Kawasaki disease (KD) is a systemic vasculitis and childhood febrile disease that can lead to cardiovascular complications. The diagnosis of KD depends on its clinical features, and thus it is sometimes difficult to make a definitive diagnosis. In order to identify diagnostic serum biomarkers for KD, we explored serum KD-related proteins, which differentially expressed during the acute and recovery phases of two patients by mass spectrometry (MS). We identified a total of 1,879 proteins by MS-based proteomic analysis. The levels of three of these proteins, namely lipopolysaccharide-binding protein (LBP), leucine-rich alpha-2-glycoprotein (LRG1), and angiotensinogen (AGT), were higher in acute phase patients. In contrast, the level of retinol-binding protein 4 (RBP4) was decreased. To confirm the usefulness of these proteins as biomarkers, we analyzed a total of 270 samples, including those collected from 55 patients with acute phase KD, by using western blot analysis and microarray enzyme-linked immunosorbent assays (ELISAs). Over the course of this experiment, we determined that the expression level of these proteins changes specifically in the acute phase of KD, rather than the recovery phase of KD or other febrile illness. Thus, LRG1 could be used as biomarkers to facilitate KD diagnosis based on clinical features. PMID:28262744

  8. A single lysis solution for the analysis of tissue samples by different proteomic technologies

    DEFF Research Database (Denmark)

    Gromov, P.; Celis, J.E.; Gromova, I.

    2008-01-01

    -based proteomics (reverse-phase lysate arrays or direct antibody arrays), allowing the direct comparison of qualitative and quantitative data yielded by these technologies when applied to the same samples. The usefulness of the CLB1 solution for gel-based proteomics was further established by 2D PAGE analysis...... dissease, is driving scientists to increasingly use clinically relevant samples for biomarker and target discovery. Tissues are heterogeneous and as a result optimization of sample preparation is critical for generating accurate, representative, and highly reproducible quantitative data. Although a large...... number of protocols for preparation of tissue lysates has been published, so far no single recipe is able to provide a "one-size fits all" solubilization procedure that can be used to analyse the same lysate using different proteomics technologies. Here we present evidence showing that cell lysis buffer...

  9. Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications.

    Science.gov (United States)

    Sajic, Tatjana; Liu, Yansheng; Aebersold, Ruedi

    2015-04-01

    In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics.

    Science.gov (United States)

    Gao, Yan; Lim, Teck Kwang; Lin, Qingsong; Li, Sam Fong Yau

    2016-04-29

    Cypermethrin (CYP) is one of the most widely used pesticides in large scale for agricultural and domestic purpose and the residue often seriously affects aquatic system. Environmental pollutant-induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of action. While proteomics investigations of CYP stress in some animal models have been well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001μg/L, 0.01μg/L and 1μg/L) of CYP on green algae Chlorella vulgaris for 24h and 96h was investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrate metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticide-exposed plant and algae. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

    Directory of Open Access Journals (Sweden)

    Ana Rita Lima

    2016-08-01

    Full Text Available Prostate cancer (PCa is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

  12. Candidate biomarker discovery and selection for ‘Granny Smith' superficial scald risk management and diagnosis, poster board

    Science.gov (United States)

    Discovery of candidate biomarkers for superficial scald, a peel disorder that develops during storage of susceptible apple cultivars, is part of a larger project aimed at developing biomarker-based risk-management and diagnostic tools for multiple apple postharvest disorders (http://www.tfrec.wsu.ed...

  13. Quantitative Clinical Chemistry Proteomics (qCCP) using mass spectrometry: general characteristics and application.

    Science.gov (United States)

    Lehmann, Sylvain; Hoofnagle, Andrew; Hochstrasser, Denis; Brede, Cato; Glueckmann, Matthias; Cocho, José A; Ceglarek, Uta; Lenz, Christof; Vialaret, Jérôme; Scherl, Alexander; Hirtz, Christophe

    2013-05-01

    Proteomics studies typically aim to exhaustively detect peptides/proteins in a given biological sample. Over the past decade, the number of publications using proteomics methodologies has exploded. This was made possible due to the availability of high-quality genomic data and many technological advances in the fields of microfluidics and mass spectrometry. Proteomics in biomedical research was initially used in 'functional' studies for the identification of proteins involved in pathophysiological processes, complexes and networks. Improved sensitivity of instrumentation facilitated the analysis of even more complex sample types, including human biological fluids. It is at that point the field of clinical proteomics was born, and its fundamental aim was the discovery and (ideally) validation of biomarkers for the diagnosis, prognosis, or therapeutic monitoring of disease. Eventually, it was recognized that the technologies used in clinical proteomics studies [particularly liquid chromatography-tandem mass spectrometry (LC-MS/MS)] could represent an alternative to classical immunochemical assays. Prior to deploying MS in the measurement of peptides/proteins in the clinical laboratory, it seems likely that traditional proteomics workflows and data management systems will need to adapt to the clinical environment and meet in vitro diagnostic (IVD) regulatory constraints. This defines a new field, as reviewed in this article, that we have termed quantitative Clinical Chemistry Proteomics (qCCP).

  14. Informatics-guided procurement of patient samples for biomarker discovery projects in cancer research.

    Science.gov (United States)

    Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H

    2009-02-01

    Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.

  15. Biomarker Gene Signature Discovery Integrating Network Knowledge

    Directory of Open Access Journals (Sweden)

    Holger Fröhlich

    2012-02-01

    Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

  16. One Sample, One Shot - Evaluation of sample preparation protocols for the mass spectrometric proteome analysis of human bile fluid without extensive fractionation.

    Science.gov (United States)

    Megger, Dominik A; Padden, Juliet; Rosowski, Kristin; Uszkoreit, Julian; Bracht, Thilo; Eisenacher, Martin; Gerges, Christian; Neuhaus, Horst; Schumacher, Brigitte; Schlaak, Jörg F; Sitek, Barbara

    2017-02-10

    The proteome analysis of bile fluid represents a promising strategy to identify biomarker candidates for various diseases of the hepatobiliary system. However, to obtain substantive results in biomarker discovery studies large patient cohorts necessarily need to be analyzed. Consequently, this would lead to an unmanageable number of samples to be analyzed if sample preparation protocols with extensive fractionation methods are applied. Hence, the performance of simple workflows allowing for "one sample, one shot" experiments have been evaluated in this study. In detail, sixteen different protocols implying modifications at the stages of desalting, delipidation, deglycosylation and tryptic digestion have been examined. Each method has been individually evaluated regarding various performance criteria and comparative analyses have been conducted to uncover possible complementarities. Here, the best performance in terms of proteome coverage has been assessed for a combination of acetone precipitation with in-gel digestion. Finally, a mapping of all obtained protein identifications with putative biomarkers for hepatocellular carcinoma (HCC) and cholangiocellular carcinoma (CCC) revealed several proteins easily detectable in bile fluid. These results can build the basis for future studies with large and well-defined patient cohorts in a more disease-related context. Human bile fluid is a proximal body fluid and supposed to be a potential source of disease markers. However, due to its biochemical composition, the proteome analysis of bile fluid still represents a challenging task and is therefore mostly conducted using extensive fractionation procedures. This in turn leads to a high number of mass spectrometric measurements for one biological sample. Considering the fact that in order to overcome the biological variability a high number of biological samples needs to be analyzed in biomarker discovery studies, this leads to the dilemma of an unmanageable number of

  17. Proteomics and metabolomics in ageing research: from biomarkers to systems biology.

    Science.gov (United States)

    Hoffman, Jessica M; Lyu, Yang; Pletcher, Scott D; Promislow, Daniel E L

    2017-07-15

    Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible 'biomarkers', which are predictors of one's biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying 'endophenotypes' in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  18. Urine sample preparation for proteomic analysis.

    Science.gov (United States)

    Olszowy, Pawel; Buszewski, Boguslaw

    2014-10-01

    Sample preparation for both environmental and more importantly biological matrices is a bottleneck of all kinds of analytical processes. In the case of proteomic analysis this element is even more important due to the amount of cross-reactions that should be taken into consideration. The incorporation of new post-translational modifications, protein hydrolysis, or even its degradation is possible as side effects of proteins sample processing. If protocols are evaluated appropriately, then identification of such proteins does not bring difficulties. However, if structural changes are provided without sufficient attention then protein sequence coverage will be reduced or even identification of such proteins could be impossible. This review summarizes obstacles and achievements in protein sample preparation of urine for proteome analysis using different tools for mass spectrometry analysis. The main aim is to present comprehensively the idea of urine application as a valuable matrix. This article is dedicated to sample preparation and application of urine mainly in novel cancer biomarkers discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins.

    Science.gov (United States)

    Banfi, Cristina; Baetta, Roberta; Gianazza, Erica; Tremoli, Elena

    2017-06-01

    Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker

    International Nuclear Information System (INIS)

    Kang, Un-Beom; Ahn, Younghee; Lee, Jong Won; Kim, Yong-Hak; Kim, Joon; Yu, Myeong-Hee; Noh, Dong-Young; Lee, Cheolju

    2010-01-01

    Breast cancer is one of the leading causes of women's death worldwide. It is important to discover a reliable biomarker for the detection of breast cancer. Plasma is the most ideal source for cancer biomarker discovery since many cells cross-communicate through the secretion of soluble proteins into blood. Plasma proteomes obtained from 6 breast cancer patients and 6 normal healthy women were analyzed by using the isotope-coded affinity tag (ICAT) labeling approach and tandem mass spectrometry. All the plasma samples used were depleted of highly abundant 6 plasma proteins by immune-affinity column chromatography before ICAT labeling. Several proteins showing differential abundance level were selected based on literature searches and their specificity to the commercially available antibodies, and then verified by immunoblot assays. A total of 155 proteins were identified and quantified by ICAT method. Among them, 33 proteins showed abundance changes by more than 1.5-fold between the plasmas of breast cancer patients and healthy women. We chose 5 proteins for the follow-up confirmation in the individual plasma samples using immunoblot assay. Four proteins, α1-acid glycoprotein 2, monocyte differentiation antigen CD14, biotinidase (BTD), and glutathione peroxidase 3, showed similar abundance ratio to ICAT result. Using a blind set of plasmas obtained from 21 breast cancer patients and 21 normal healthy controls, we confirmed that BTD was significantly down-regulated in breast cancer plasma (Wilcoxon rank-sum test, p = 0.002). BTD levels were lowered in all cancer grades (I-IV) except cancer grade zero. The area under the receiver operating characteristic curve of BTD was 0.78. Estrogen receptor status (p = 0.940) and progesterone receptor status (p = 0.440) were not associated with the plasma BTD levels. Our study suggests that BTD is a potential serological biomarker for the detection of breast cancer

  1. Serum proteome profiling in canine idiopathic dilated cardiomyopathy using TMT-based quantitative proteomics approach.

    Science.gov (United States)

    Bilić, Petra; Guillemin, Nicolas; Kovačević, Alan; Beer Ljubić, Blanka; Jović, Ines; Galan, Asier; Eckersall, Peter David; Burchmore, Richard; Mrljak, Vladimir

    2018-05-15

    Idiopathic dilated cardiomyopathy (iDCM) is a primary myocardial disorder with an unknown aetiology, characterized by reduced contractility and ventricular dilation of the left or both ventricles. Naturally occurring canine iDCM was used herein to identify serum proteomic signature of the disease compared to the healthy state, providing an insight into underlying mechanisms and revealing proteins with biomarker potential. To achieve this, we used high-throughput label-based quantitative LC-MS/MS proteomics approach and bioinformatics analysis of the in silico inferred interactome protein network created from the initial list of differential proteins. To complement the proteomic analysis, serum biochemical parameters and levels of know biomarkers of cardiac function were measured. Several proteins with biomarker potential were identified, such as inter-alpha-trypsin inhibitor heavy chain H4, microfibril-associated glycoprotein 4 and apolipoprotein A-IV, which were validated using an independent method (Western blotting) and showed high specificity and sensitivity according to the receiver operating characteristic curve analysis. Bioinformatics analysis revealed involvement of different pathways in iDCM, such as complement cascade activation, lipoprotein particles dynamics, elastic fibre formation, GPCR signalling and respiratory electron transport chain. Idiopathic dilated cardiomyopathy is a severe primary myocardial disease of unknown cause, affecting both humans and dogs. This study is a contribution to the canine heart disease research by means of proteomic and bioinformatic state of the art analyses, following similar approach in human iDCM research. Importantly, we used serum as non-invasive and easily accessible biological source of information and contributed to the scarce data on biofluid proteome research on this topic. Bioinformatics analysis revealed biological pathways modulated in canine iDCM with potential of further targeted research. Also, several

  2. Human cervicovaginal fluid biomarkers to predict term and preterm labor

    Science.gov (United States)

    Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

    2015-01-01

    Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

  3. High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

    Science.gov (United States)

    Lin, Lin; Zheng, Jiaxin; Yu, Quan; Chen, Wendong; Xing, Jinchun; Chen, Chenxi; Tian, Ruijun

    2018-03-01

    Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application

  4. PODCAST: From Lost in Translation to Paradise Found: Enabling Protein Biomarker Method Transfer by Mass Spectrometry | Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    Translation of novel biomarkers into clinical care for the evaluation of therapeutic safety and efficacy has been slow, partly attributable to the cost and complexity of immunoassay development.  The potential for liquid chromatography-tandem mass spectrometry (LC-MS/MS) to streamline the translation of novel protein biomarkers is profound.  Drs. Henry Rodriguez and Andrew Hoofnagle discuss what the future may be for clinical proteomics. This is an American Association for Clinical Chemistry (AACC) podcast.

  5. Proteomic and metabolomic biomarkers for III-V semiconductors: And prospects for application to nano-materials

    International Nuclear Information System (INIS)

    Fowler, Bruce A.; Conner, Elizabeth A.; Yamauchi, Hiroshi

    2008-01-01

    There has been an increased appreciation over the last 20 years that chemical agents at very low dose levels can produce biological responses in protein expression patterns (proteomic responses) or alterations in sensitive metabolic pathways (metabolomic responses). Marked improvements in analytical methodologies, such as 2-D gel electrophoresis, matrix-assisted laser desorption-time of flight (MALDI-TOF) and surface enhanced laser desorption-time of flight (SELDI-TOF) technologies are capable of identifying specific protein patterns related to exposure to chemicals either alone or as mixtures. The detection and interpretation of early cellular responses to chemical agents have also made great advances through correlative ultrastructural morphometric and biochemical studies. Similarly, advances in analytical technologies such as HPLC, proton NMR, MALDI-TOF, and SELDI-TOF have permitted early detection of changes in a number of essential metabolic pathways following chemical exposures by measurement of alterations in metabolic products from those pathways. Data from these approaches are increasingly regarded as potentially useful biomarkers of chemical exposure and early cellular responses. Validation and establishment of linkages to biological outcomes are needed in order for biomarkers of effect to be established. This short review will cover a number of the above techniques and report data from chemical exposures to two binary III-V semiconductor compounds to illustrate gender differences in proteomic responses. In addition, the use of these methodologies in relation to rapid safety evaluations of nanotechnology products will be discussed. (Supported in part by NIH R01-ES4879)

  6. Qualitative and quantitative characterization of plasma proteins when incorporating traveling wave ion mobility into a liquid chromatography-mass spectrometry workflow for biomarker discovery: use of product ion quantitation as an alternative data analysis tool for label free quantitation.

    Science.gov (United States)

    Daly, Charlotte E; Ng, Leong L; Hakimi, Amirmansoor; Willingale, Richard; Jones, Donald J L

    2014-02-18

    Discovery of protein biomarkers in clinical samples necessitates significant prefractionation prior to liquid chromatography-mass spectrometry (LC-MS) analysis. Integrating traveling wave ion mobility spectrometry (TWIMS) enables in-line gas phase separation which when coupled with nanoflow liquid chromatography and data independent acquisition tandem mass spectrometry, confers significant advantages to the discovery of protein biomarkers by improving separation and inherent sensitivity. Incorporation of TWIMS leads to a packet of concentrated ions which ultimately provides a significant improvement in sensitivity. As a consequence of ion packeting, when present at high concentrations, accurate quantitation of proteins can be affected due to detector saturation effects. Human plasma was analyzed in triplicate using liquid-chromatography data independent acquisition mass spectrometry (LC-DIA-MS) and using liquid-chromatography ion-mobility data independent acquisition mass spectrometry (LC-IM-DIA-MS). The inclusion of TWIMS was assessed for the effect on sample throughput, data integrity, confidence of protein and peptide identification, and dynamic range. The number of identified proteins is significantly increased by an average of 84% while both the precursor and product mass accuracies are maintained between the modalities. Sample dynamic range is also maintained while quantitation is achieved for all but the most abundant proteins by incorporating a novel data interpretation method that allows accurate quantitation to occur. This additional separation is all achieved within a workflow with no discernible deleterious effect on throughput. Consequently, TWIMS greatly enhances proteome coverage and can be reliably used for quantification when using an alternative product ion quantification strategy. Using TWIMS in biomarker discovery in human plasma is thus recommended.

  7. Catch and measure-mass spectrometry-based immunoassays in biomarker research.

    Science.gov (United States)

    Weiß, Frederik; van den Berg, Bart H J; Planatscher, Hannes; Pynn, Christopher J; Joos, Thomas O; Poetz, Oliver

    2014-05-01

    Mass spectrometry-based (MS) methods are effective tools for discovering protein biomarker candidates that can differentiate between physiological and pathophysiological states. Promising candidates are validated in studies comprising large patient cohorts. Here, targeted protein analytics are used to increase sample throughput. Methods involving antibodies, such as sandwich immunoassays or Western blots, are commonly applied at this stage. Highly-specific and sensitive mass spectrometry-based immunoassays that have been established in recent years offer a suitable alternative to sandwich immunoassays for quantifying proteins. Mass Spectrometric ImmunoAssays (MSIA) and Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA/iMALDI) are two prominent types of MS-based immunoassays in which the capture is done either at the protein or the peptide level. We present an overview of these emerging types of immunoassays and discuss their suitability for the discovery and validation of protein biomarkers. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

  8. Ocular Proteomics with Emphasis on Two-Dimensional Gel Electrophoresis and Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Honoré Bent

    2010-01-01

    Full Text Available Abstract The intention of this review is to provide an overview of current methodologies employed in the rapidly developing field of ocular proteomics with emphasis on sample preparation, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE and mass spectrometry (MS. Appropriate sample preparation for the diverse range of cells and tissues of the eye is essential to ensure reliable results. Current methods of protein staining for 2D-PAGE, protein labelling for two-dimensional difference gel electrophoresis, gel-based expression analysis and protein identification by MS are summarised. The uses of gel-free MS-based strategies (MuDPIT, iTRAQ, ICAT and SILAC are also discussed. Proteomic technologies promise to shed new light onto ocular disease processes that could lead to the discovery of strong novel biomarkers and therapeutic targets useful in many ophthalmic conditions.

  9. Secreted autoantibody repertoires in Sjögren's syndrome and systemic lupus erythematosus: A proteomic approach.

    Science.gov (United States)

    Al Kindi, Mahmood A; Colella, Alex D; Chataway, Tim K; Jackson, Michael W; Wang, Jing J; Gordon, Tom P

    2016-04-01

    The structures of epitopes bound by autoantibodies against RNA-protein complexes have been well-defined over several decades, but little is known of the clonality, immunoglobulin (Ig) variable (V) gene usage and mutational status of the autoantibodies themselves at the level of the secreted (serum) proteome. A novel proteomic workflow is presented based on affinity purification of specific Igs from serum, high-resolution two-dimensional gel electrophoresis, and de novo and database-driven sequencing of V-region proteins by mass spectrometry. Analysis of anti-Ro52/Ro60/La proteomes in primary Sjögren's syndrome (SS) and anti-Sm and anti-ribosomal P proteomes in systemic lupus erythematosus (SLE) has revealed that these antibody responses are dominated by restricted sets of public (shared) clonotypes, consistent with common pathways of production across unrelated individuals. The discovery of shared sets of specific V-region peptides can be exploited for diagnostic biomarkers in targeted mass spectrometry platforms and for tracking and removal of pathogenic clones. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Analysis of the plasma proteome in COPD: Novel low abundance proteins reflect the severity of lung remodeling.

    Science.gov (United States)

    Merali, Salim; Barrero, Carlos A; Bowler, Russell P; Chen, Diane Er; Criner, Gerard; Braverman, Alan; Litwin, Samuel; Yeung, Anthony; Kelsen, Steven G

    2014-04-01

    The search for COPD biomarkers has largely employed a targeted approach that focuses on plasma proteins involved in the systemic inflammatory response and in lung injury and repair. This proof of concept study was designed to test the idea that an open, unbiased, in-depth proteomics approach could identify novel, low abundance plasma proteins i.e., ng/mL concentration, which could serve as potential biomarkers. Differentially expressed proteins were identified in a discovery group with severe COPD (FEV1 <45% predicted; n = 10). Subjects with normal lung function matched for age, sex, ethnicity and smoking history served as controls (n = 10). Pooled plasma from each group was exhaustively immunodepleted of abundant proteins, d separated by 1-D gel electrophoresis and extensively fractionated prior to LC-tandem mass spectroscopy (GeLC-MS). Thirty one differentially expressed proteins were identified in the discovery group including markers of lung defense against oxidant stress, alveolar macrophage activation, and lung tissue injury and repair. Four of the 31 proteins (i.e., GRP78, soluble CD163, IL1AP and MSPT9) were measured in a separate verification group of 80 subjects with varying COPD severity by immunoassay. All 4 were significantly altered in COPD and 2 (GRP78 and soluble CD163) correlated with both FEV1 and the extent of emphysema. In-depth, plasma proteomic analysis identified a group of novel, differentially expressed, low abundance proteins that reflect known pathogenic mechanisms and the severity of lung remodeling in COPD. These proteins may also prove useful as COPD biomarkers.

  11. Protein corona as a proteome fingerprint: The example of hidden biomarkers for cow mastitis.

    Science.gov (United States)

    Miotto, Giovanni; Magro, Massimiliano; Terzo, Milo; Zaccarin, Mattia; Da Dalt, Laura; Bonaiuto, Emanuela; Baratella, Davide; Gabai, Gianfranco; Vianello, Fabio

    2016-04-01

    Proteome modifications in a biological fluid can potentially indicate the occurrence of pathologies, even if the identification of a proteome fingerprint correlated to a specific disease represents a very difficult task. When a nanomaterial is introduced into a biological fluid, macromolecules compete to form a protein corona on the nanoparticle surface, and depending on the specific proteome, different patterns of proteins will form the final protein corona shell depending on their affinity for the nanoparticle surface. Novel surface active maghemite nanoparticles (SAMNs) display a remarkable selectivity toward protein corona formation, and they are able to concentrate proteins and peptides presenting high affinities for their surface even if they are present in very low amounts. Thus, SAMNs may confer visibility to hidden biomarkers correlated to the occurrence of a pathology. In the present report, SAMNs were introduced into milk samples from healthy cows and from animals affected by mastitis, and the selectively bound protein corona shell was easily analyzed and quantified by gel electrophoresis and characterized by mass spectrometry. Upon incubation in mastitic milk, SAMNs were able to selectively bind αs2-casein fragments containing the FALPQYLK sequence, as part of the larger casocidin-1 peptide with strong antibacterial activity, which were not present in healthy samples. Thus, SAMNs can be used as a future candidate for the rapid diagnosis of mastitis in bovine milk. The present report proposes protein competition for SAMN protein corona formation as a means of mirroring proteome modifications. Thus, the selected protein shell on the nanoparticles results in a fingerprint of the specific pathology. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. The importance of accounting for sex in the search of proteomic signatures of mycotoxin exposure.

    Science.gov (United States)

    Soler, L; Oswald, I P

    2018-04-30

    between sexes makes that results obtained in males are often not directly transferrable to females. In this review, we want to highlight (1) that proteomics has a great potential on mycotoxin research, and (2) the need in taking into account sex differences in proteomic studies, mostly when the discovery of robust biomarkers of mycotoxins response is desired. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Characterization of the canine urinary proteome.

    Science.gov (United States)

    Brandt, Laura E; Ehrhart, E J; Scherman, Hataichanok; Olver, Christine S; Bohn, Andrea A; Prenni, Jessica E

    2014-06-01

    Urine is an attractive biofluid for biomarker discovery as it is easy and minimally invasive to obtain. While numerous studies have focused on the characterization of human urine, much less research has focused on canine urine. The objectives of this study were to characterize the universal canine urinary proteome (both soluble and exosomal), to determine the overlap between the canine proteome and a representative human urinary proteome study, to generate a resource for future canine studies, and to determine the suitability of the dog as a large animal model for human diseases. The soluble and exosomal fractions of normal canine urine were characterized using liquid chromatography tandem mass spectrometry (LC-MS/MS). Biological Networks Gene Ontology (BiNGO) software was utilized to assign the canine urinary proteome to respective Gene Ontology categories, such as Cellular Component, Molecular Function, and Biological Process. Over 500 proteins were confidently identified in normal canine urine. Gene Ontology analysis revealed that exosomal proteins were largely derived from an intracellular location, while soluble proteins included both extracellular and membrane proteins. Exosome proteins were assigned to metabolic processes and localization, while soluble proteins were primarily annotated to specific localization processes. Several proteins identified in normal canine urine have previously been identified in human urine where these proteins are related to various extrarenal and renal diseases. The results of this study illustrate the potential of the dog as an animal model for human disease states and provide the framework for future studies of canine renal diseases. © 2014 American Society for Veterinary Clinical Pathology and European Society for Veterinary Clinical Pathology.

  14. Identifying Predictors of Taxane-Induced Peripheral Neuropathy Using Mass Spectrometry-Based Proteomics Technology.

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    Emily I Chen

    Full Text Available Major advances in early detection and therapy have significantly increased the survival of breast cancer patients. Unfortunately, most cancer therapies are known to carry a substantial risk of adverse long-term treatment-related effects. Little is known about patient susceptibility to severe side effects after chemotherapy. Chemotherapy-induced peripheral neuropathy (CIPN is a common side effect of taxanes. Recent advances in genome-wide genotyping and sequencing technologies have supported the discoveries of a number of pharmacogenetic markers that predict response to chemotherapy. However, effectively implementing these pharmacogenetic markers in the clinic remains a major challenge. On the other hand, recent advances in proteomic technologies incorporating mass spectrometry (MS for biomarker discovery show great promise to provide clinically relevant protein biomarkers. In this study, we evaluated the association between protein content in serum exosomes and severity of CIPN. Women with early stage breast cancer receiving adjuvant taxane chemotherapy were assessed with the FACT-Ntx score and serum was collected before and after the taxane treatment. Based on the change in FACT-Ntx score from baseline to 12 month follow-up, we separated patients into two groups: those who had no change (Group 1, N = 9 and those who had a ≥20% worsening (Group 1, N = 8. MS-based proteomics technology was used to identify proteins present in serum exosomes to determine potential biomarkers. Mann-Whitney-Wilcoxon analysis was applied and maximum FDR was controlled at 20%. From the serum exosomes derived from this cohort, we identified over 700 proteins known to be in different subcellular locations and have different functions. Statistical analysis revealed a 12-protein signature that resulted in a distinct separation between baseline serum samples of both groups (q<0.2 suggesting that the baseline samples can predict subsequent neurotoxicity. These toxicity

  15. Biology and Biomarkers for Wound Healing

    Science.gov (United States)

    Lindley, Linsey E.; Stojadinovic, Olivera; Pastar, Irena; Tomic-Canic, Marjana

    2016-01-01

    Background As the population grows older, the incidence and prevalence of conditions which lead to a predisposition for poor wound healing also increases. Ultimately, this increase in non-healing wounds has led to significant morbidity and mortality with subsequent huge economic ramifications. Therefore, understanding specific molecular mechanisms underlying aberrant wound healing is of great importance. It has, and will continue to be the leading pathway to the discovery of therapeutic targets as well as diagnostic molecular biomarkers. Biomarkers may help identify and stratify subsets of non-healing patients for whom biomarker-guided approaches may aid in healing. Methods A series of literature searches were performed using Medline, PubMed, Cochrane Library, and Internet searches. Results Currently, biomarkers are being identified using biomaterials sourced locally, from human wounds and/or systemically using systematic high-throughput “omics” modalities (genomic, proteomic, lipidomic, metabolomic analysis). In this review we highlight the current status of clinically applicable biomarkers and propose multiple steps in validation and implementation spectrum including those measured in tissue specimens e.g. β-catenin and c-myc, wound fluid e.g. MMP’s and interleukins, swabs e.g. wound microbiota and serum e.g. procalcitonin and MMP’s. Conclusions Identification of numerous potential biomarkers utilizing different avenues of sample collection and molecular approaches is currently underway. A focus on simplicity, and consistent implementation of these biomarkers as well as an emphasis on efficacious follow-up therapeutics is necessary for transition of this technology to clinically feasible point-of-care applications. PMID:27556760

  16. Stage-Specific Transcriptome and Proteome Analyses of the Filarial Parasite Onchocerca volvulus and Its Wolbachia Endosymbiont

    Science.gov (United States)

    Bennuru, Sasisekhar; Cotton, James A.; Ribeiro, Jose M. C.; Grote, Alexandra; Harsha, Bhavana; Holroyd, Nancy; Mhashilkar, Amruta; Molina, Douglas M.; Randall, Arlo Z.; Shandling, Adam D.; Unnasch, Thomas R.; Ghedin, Elodie; Berriman, Matthew

    2016-01-01

    ABSTRACT Onchocerciasis (river blindness) is a neglected tropical disease that has been successfully targeted by mass drug treatment programs in the Americas and small parts of Africa. Achieving the long-term goal of elimination of onchocerciasis, however, requires additional tools, including drugs, vaccines, and biomarkers of infection. Here, we describe the transcriptome and proteome profiles of the major vector and the human host stages (L1, L2, L3, molting L3, L4, adult male, and adult female) of Onchocerca volvulus along with the proteome of each parasitic stage and of its Wolbachia endosymbiont (wOv). In so doing, we have identified stage-specific pathways important to the parasite’s adaptation to its human host during its early development. Further, we generated a protein array that, when screened with well-characterized human samples, identified novel diagnostic biomarkers of O. volvulus infection and new potential vaccine candidates. This immunomic approach not only demonstrates the power of this postgenomic discovery platform but also provides additional tools for onchocerciasis control programs. PMID:27881553

  17. Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

    Science.gov (United States)

    Chauhan, Ranjit; Lahiri, Nivedita

    2016-01-01

    Hepatocellular carcinoma (HCC), one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future. PMID:27398029

  18. Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

    Directory of Open Access Journals (Sweden)

    Ranjit Chauhan

    2016-01-01

    Full Text Available Hepatocellular carcinoma (HCC, one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future.

  19. Integrative proteomics and tissue microarray profiling indicate the association between overexpressed serum proteins and non-small cell lung cancer.

    Directory of Open Access Journals (Sweden)

    Yansheng Liu

    Full Text Available Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA and Multiple reaction monitoring (MRM assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG and Leucine-rich alpha-2-glycoprotein (LRG1, two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

  20. Biomarkers in cancer screening: a public health perspective.

    Science.gov (United States)

    Srivastava, Sudhir; Gopal-Srivastava, Rashmi

    2002-08-01

    The last three decades have witnessed a rapid advancement and diffusion of technology in health services. Technological innovations have given health service providers the means to diagnose and treat an increasing number of illnesses, including cancer. In this effort, research on biomarkers for cancer detection and risk assessment has taken a center stage in our effort to reduce cancer deaths. For the first time, scientists have the technologies to decipher and understand these biomarkers and to apply them to earlier cancer detection. By identifying people at high risk of developing cancer, it would be possible to develop intervention efforts on prevention rather than treatment. Once fully developed and validated, then the regular clinical use of biomarkers in early detection and risk assessment will meet nationally recognized health care needs: detection of cancer at its earliest stage. The dramatic rise in health care costs in the past three decades is partly related to the proliferation of new technologies. More recent analysis indicates that technological change, such as new procedures, products and capabilities, is the primary explanation of the historical increase in expenditure. Biomarkers are the new entrants in this competing environment. Biomarkers are considered as a competing, halfway or add-on technology. Technology such as laboratory tests of biomarkers will cost less compared with computed tomography (CT) scans and other radiographs. However, biomarkers for earlier detection and risk assessment have not achieved the level of confidence required for clinical applications. This paper discusses some issues related to biomarker development, validation and quality assurance. Some data on the trends of diagnostic technologies, proteomics and genomics are presented and discussed in terms of the market share. Eventually, the use of biomarkers in health care could reduce cost by providing noninvasive, sensitive and reliable assays at a fraction of the cost of

  1. Gel-free proteomics reveal potential biomarkers of priming-induced salt tolerance in durum wheat.

    Science.gov (United States)

    Fercha, Azzedine; Capriotti, Anna Laura; Caruso, Giuseppe; Cavaliere, Chiara; Gherroucha, Hocine; Samperi, Roberto; Stampachiacchiere, Serena; Lagana, Aldo

    2013-10-08

    Seed priming has been successfully demonstrated to be an efficient method to improve crop productivity under stressful conditions. As a first step toward better understanding of the mechanisms underlying the priming-induced salt stress tolerance in durum wheat, and to overcome the limitations of the gel-based approach, a comparative gel-free proteomic analysis was conducted with durum wheat seed samples of varying vigor as generated by hydro- and ascorbate-priming treatments. Results indicate that hydro-priming was accompanied by significant changes of 72 proteins, most of which are involved in proteolysis, protein synthesis, metabolism and disease/defense response. Ascorbate-priming was, however, accompanied by significant changes of 83 proteins, which are mainly involved in protein metabolism, antioxidant protection, repair processes and, interestingly, in methionine-related metabolism. The present study provides new information for understanding how 'priming-memory' invokes seed stress tolerance. The current work describes the first study in which gel-free shotgun proteomics were used to investigate the metabolic seed protein fraction in durum wheat. A combined approach of protein fractionation, hydrogel nanoparticle enrichment technique, and gel-free shotgun proteomic analysis allowed us to identify over 380 proteins exhibiting greater molecular weight diversity (ranging from 7 to 258kDa). Accordingly, we propose that this approach could be useful to acquire a wider perspective and a better understanding of the seed proteome. In the present work, we employed this method to investigate the potential biomarkers of priming-induced salt tolerance in durum wheat. In this way, we identified several previously unrecognized proteins which were never been reported before, particularly for the ascorbate-priming treatment. These findings could provide new avenues for improving crop productivity, particularly under unfavorable environmental conditions. © 2013.

  2. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

    Science.gov (United States)

    Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

    2018-03-20

    The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

  3. Big Biomedical data as the key resource for discovery science

    Energy Technology Data Exchange (ETDEWEB)

    Toga, Arthur W.; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W.; Price, Nathan D.; Glusman, Gustavo; Heavner, Benjamin D.; Dinov, Ivo D.; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

    2015-07-21

    Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an “-ome to home” approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center’s computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson’s and Alzheimer’s.

  4. [Search for potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry].

    Science.gov (United States)

    Shevchenko, V E; Arnotskaia, N E; Ogorodnikova, E V; Davydov, M M; Ibraev, M A; Turkin, I N; Davydov, M I

    2014-01-01

    Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1-17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.

  5. Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

    Directory of Open Access Journals (Sweden)

    Peter Feist

    2015-02-01

    Full Text Available Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

  6. Proteomic Challenges: Sample Preparation Techniques for Microgram-Quantity Protein Analysis from Biological Samples

    Science.gov (United States)

    Feist, Peter; Hummon, Amanda B.

    2015-01-01

    Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed. PMID:25664860

  7. Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples.

    Science.gov (United States)

    Feist, Peter; Hummon, Amanda B

    2015-02-05

    Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

  8. Proteomic Analysis of the Human Olfactory Bulb.

    Science.gov (United States)

    Dammalli, Manjunath; Dey, Gourav; Madugundu, Anil K; Kumar, Manish; Rodrigues, Benvil; Gowda, Harsha; Siddaiah, Bychapur Gowrishankar; Mahadevan, Anita; Shankar, Susarla Krishna; Prasad, Thottethodi Subrahmanya Keshava

    2017-08-01

    The importance of olfaction to human health and disease is often underappreciated. Olfactory dysfunction has been reported in association with a host of common complex diseases, including neurological diseases such as Alzheimer's disease and Parkinson's disease. For health, olfaction or the sense of smell is also important for most mammals, for optimal engagement with their environment. Indeed, animals have developed sophisticated olfactory systems to detect and interpret the rich information presented to them to assist in day-to-day activities such as locating food sources, differentiating food from poisons, identifying mates, promoting reproduction, avoiding predators, and averting death. In this context, the olfactory bulb is a vital component of the olfactory system receiving sensory information from the axons of the olfactory receptor neurons located in the nasal cavity and the first place that processes the olfactory information. We report in this study original observations on the human olfactory bulb proteome in healthy subjects, using a high-resolution mass spectrometry-based proteomic approach. We identified 7750 nonredundant proteins from human olfactory bulbs. Bioinformatics analysis of these proteins showed their involvement in biological processes associated with signal transduction, metabolism, transport, and olfaction. These new observations provide a crucial baseline molecular profile of the human olfactory bulb proteome, and should assist the future discovery of biomarker proteins and novel diagnostics associated with diseases characterized by olfactory dysfunction.

  9. Liver Proteome in Diabetes Type 1 Rat Model: Insulin-Dependent and -Independent Changes.

    Science.gov (United States)

    Braga, Camila Pereira; Boone, Cory H T; Grove, Ryan A; Adamcova, Dana; Fernandes, Ana Angélica Henrique; Adamec, Jiri; de Magalhães Padilha, Pedro

    2016-12-01

    Diabetes mellitus type 1 (DM1) is a major public health problem that continues to burden the healthcare systems worldwide, costing exponentially more as the epidemic grows. Innovative strategies and omics system diagnostics for earlier diagnosis or prognostication of DM1 are essential to prevent secondary complications and alleviate the associated economic burden. In a preclinical study design that involved streptozotocin (STZ)-induced DM1, insulin-treated STZ-induced DM1, and control rats, we characterized the insulin-dependent and -independent changes in protein profiles in liver samples. Digested proteins were subjected to LC-MS E for proteomic data. Progenesis QI data processing and analysis of variance were utilized for statistical analyses. We found 305 proteins with significantly altered abundance among the control, DM1, and insulin-treated DM1 groups (p < 0.05). These differentially regulated proteins were related to enzymes that function in key metabolic pathways and stress responses. For example, gluconeogenesis appeared to return to control levels in the DM1 group after insulin treatment, with the restoration of gluconeogenesis regulatory enzyme, FBP1. Insulin administration to DM1 rats also restored the blood glucose levels and enzymes of general stress and antioxidant response systems. These observations are crucial for insights on DM1 pathophysiology and new molecular targets for future clinical biomarkers, drug discovery, and development. Additionally, we underscore that proteomics offers much potential in preclinical biomarker discovery for diabetes as well as common complex diseases such as cancer, dementia, and infectious disorders.

  10. Identification of EBP50 as a Specific Biomarker for Carcinogens Via the Analysis of Mouse Lymphoma Cellular Proteome

    Science.gov (United States)

    Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

    2012-01-01

    To identify specific biomarkers generated upon exposure of L5178Y mouse lymphoma cells to carcinogens, 2-DE and MALDI-TOF MS analysis were conducted using the cellular proteome of L5178Y cells that had been treated with the known carcinogens, 1,2-dibromoethane and O-nitrotoluene and the noncarcinogens, emodin and D-mannitol. Eight protein spots that showed a greater than 1.5-fold increase or decrease in intensity following carcinogen treatment compared with treatment with noncarcinogens were selected. Of the identified proteins, we focused on the candidate biomarker ERM-binding phosphoprotein 50 (EBP50), the expression of which was specifically increased in response to treatment with the carcinogens. The expression level of EBP50 was determined by western analysis using polyclonal rabbit anti-EBP50 antibody. Further, the expression level of EBP50 was increased in cells treated with seven additional carcinogens, verifying that EBP50 could serve as a specific biomarker for carcinogens. PMID:22434383

  11. Bioinformatical Analysis of Organ-Related (Heart, Brain, Liver, and Kidney and Serum Proteomic Data to Identify Protein Regulation Patterns and Potential Sepsis Biomarkers

    Directory of Open Access Journals (Sweden)

    Andreas Hohn

    2018-01-01

    Full Text Available During the last years, proteomic studies have revealed several interesting findings in experimental sepsis models and septic patients. However, most studies investigated protein alterations only in single organs or in whole blood. To identify possible sepsis biomarkers and to evaluate the relationship between protein alteration in sepsis affected organs and blood, proteomics data from the heart, brain, liver, kidney, and serum were analysed. Using functional network analyses in combination with hierarchical cluster analysis, we found that protein regulation patterns in organ tissues as well as in serum are highly dynamic. In the tissue proteome, the main functions and pathways affected were the oxidoreductive activity, cell energy generation, or metabolism, whereas in the serum proteome, functions were associated with lipoproteins metabolism and, to a minor extent, with coagulation, inflammatory response, and organ regeneration. Proteins from network analyses of organ tissue did not correlate with statistically significantly regulated serum proteins or with predicted proteins of serum functions. In this study, the combination of proteomic network analyses with cluster analyses is introduced as an approach to deal with high-throughput proteomics data to evaluate the dynamics of protein regulation during sepsis.

  12. Multi-dimensional discovery of biomarker and phenotype complexes

    Directory of Open Access Journals (Sweden)

    Huang Kun

    2010-10-01

    Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

  13. 2-DE Mapping of the Blue Mussel Gill Proteome: The Usual Suspects Revisited

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    Béatrice Rocher

    2015-01-01

    Full Text Available The Blue Mussel (Mytilus edulis, L. 1758 is an ecologically important and commercially relevant bivalve. Because of its ability to bioconcentrate xenobiotics, it is also a widespread sentinel species for environmental pollution, which has been used in ecotoxicological studies for biomarker assessment. Consequently, numerous proteomics studies have been carried out in various research contexts using mussels of the genus Mytilus, which intended to improve our understanding of complex physiological processes related to reproduction, adaptation to physical stressors or shell formation and for biomarker discovery. Differential-display 2-DE proteomics relies on an extensive knowledge of the proteome with as many proteoforms identified as possible. To this end, extensive characterization of proteins was performed in order to increase our knowledge of the Mytilus gill proteome. On average, 700 spots were detected on 2-DE gels by colloidal blue staining, of which 122 different, non-redundant proteins comprising 203 proteoforms could be identified by tandem mass spectrometry. These proteins could be attributed to four major categories: (i “metabolism”, including antioxidant defence and degradation of xenobiotics; (ii “genetic information processing”, comprising transcription and translation as well as folding, sorting, repair and degradation; (iii “cellular processes”, such as cell motility, transport and catabolism; (iv “environmental information processing”, including signal transduction and signalling molecules and interaction. The role of cytoskeleton proteins, energetic metabolism, chaperones/stress proteins, protein trafficking and the proteasome are discussed in the light of the exigencies of the intertidal environment, leading to an enhanced stress response, as well as the structural and physiological particularities of the bivalve gill tissue.

  14. Adipokines: a treasure trove for the discovery of biomarkers for metabolic disorders.

    Science.gov (United States)

    Lehr, Stefan; Hartwig, Sonja; Sell, Henrike

    2012-01-01

    Adipose tissue is a major endocrine organ, releasing signaling and mediator proteins, termed adipokines, via which adipose tissue communicates with other organs. Expansion of adipose tissue in obesity alters adipokine secretion which may contribute to the development of metabolic diseases. Consequently, this correlation has emphasized the importance to further characterize the adipocyte secretion profile, and several attempts have been made to characterize the complex nature of the adipose tissue secretome by utilizing diverse proteomic profiling approaches. Although the entirety of human adipokines is still incompletely characterized, to date more than 600 potentially secretory proteins were identified providing a rich source to identify putative novel biomarkers associated with metabolic diseases. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer.

    Directory of Open Access Journals (Sweden)

    Meredith C Henderson

    Full Text Available Despite significant advances in breast imaging, the ability to accurately detect Breast Cancer (BC remains a challenge. With the discovery of key biomarkers and protein signatures for BC, proteomic technologies are currently poised to serve as an ideal diagnostic adjunct to imaging. Research studies have shown that breast tumors are associated with systemic changes in levels of both serum protein biomarkers (SPB and tumor associated autoantibodies (TAAb. However, the independent contribution of SPB and TAAb expression data for identifying BC relative to a combinatorial SPB and TAAb approach has not been fully investigated. This study evaluates these contributions using a retrospective cohort of pre-biopsy serum samples with known clinical outcomes collected from a single site, thus minimizing potential site-to-site variation and enabling direct assessment of SPB and TAAb contributions to identify BC. All serum samples (n = 210 were collected prior to biopsy. These specimens were obtained from 18 participants with no evidence of breast disease (ND, 92 participants diagnosed with Benign Breast Disease (BBD and 100 participants diagnosed with BC, including DCIS. All BBD and BC diagnoses were based on pathology results from biopsy. Statistical models were developed to differentiate BC from non-BC (i.e., BBD and ND using expression data from SPB alone, TAAb alone, and a combination of SPB and TAAb. When SPB data was independently used for modeling, clinical sensitivity and specificity for detection of BC were 74.7% and 77.0%, respectively. When TAAb data was independently used, clinical sensitivity and specificity for detection of BC were 72.2% and 70.8%, respectively. When modeling integrated data from both SPB and TAAb, the clinical sensitivity and specificity for detection of BC improved to 81.0% and 78.8%, respectively. These data demonstrate the benefit of the integration of SPB and TAAb data and strongly support the further development of

  16. The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

    Science.gov (United States)

    Serkova, Natalie J.; Standiford, Theodore J.

    2011-01-01

    Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

  17. Data for iTRAQ profiling of micro-vesicular plasma specimens: In search of potential prognostic circulatory biomarkers for Lacunar infarction

    Directory of Open Access Journals (Sweden)

    Arnab Datta

    2015-09-01

    Full Text Available To discover potential prognostic biomarkers of Lacunar infarction (LACI, here we present quantitative proteomics data of plasma microvesicle-enriched fraction derived by comparative isobaric profiling of three groups of prospectively followed-up LACI patients (LACI – no adverse outcome, LACI –recurrent vascular event and LACI – cognitive decline and a demographically matched control group. We confidently (unused prot score >3, FDR=1.1% identified 183 proteins, 43 out of which were significantly regulated (p-value<0.05 in at least one of the three LACI groups in comparison to control group. Bioinformatics analysis and data mining revealed upregulation of brain-specific proteins including myelin basic protein, proteins of coagulation cascade (e.g., fibrinogen alpha chain, fibrinogen beta chain and focal adhesion (e.g., integrin alpha-IIb, talin-1, and filamin-A while albumin was downregulated in both groups of patients with adverse outcome. The data of this study are also in line with our previously published article entitled “Discovery of prognostic biomarker candidates of Lacunar infarction by quantitative proteomics of microvesicles enriched plasma” by Datta et al. (2014. The raw data had been deposited to the ProteomeXchange consortium with identifier PXD000748.

  18. Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

    Directory of Open Access Journals (Sweden)

    Cui Ziyou

    2009-03-01

    Full Text Available Abstract Background Acute lymphoblastic leukemia (ALL is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML patients. Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS. A classification model was established by Biomarker Pattern Software (BPS. Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4 and pro-platelet basic protein precursor (PBP. Two other candidate protein peaks (8137 and 8937 m/z were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a. Conclusion Platelet factor (PF4, connective tissue activating peptide III (CTAP-III and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with

  19. Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

    Science.gov (United States)

    Shi, Linan; Zhang, Jun; Wu, Peng; Feng, Kai; Li, Jing; Xie, Zhensheng; Xue, Peng; Cai, Tanxi; Cui, Ziyou; Chen, Xiulan; Hou, Junjie; Zhang, Jianzhong; Yang, Fuquan

    2009-01-01

    Background Acute lymphoblastic leukemia (ALL) is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls) and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML) patients). Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS). A classification model was established by Biomarker Pattern Software (BPS). Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z) were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z) were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4) and pro-platelet basic protein precursor (PBP). Two other candidate protein peaks (8137 and 8937 m/z) were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a). Conclusion Platelet factor (PF4), connective tissue activating peptide III (CTAP-III) and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with additional

  20. Current status of fluid biomarkers in mild traumatic brain injury

    Science.gov (United States)

    Kulbe, Jacqueline R.; Geddes, James W.

    2015-01-01

    Mild traumatic brain injury (mTBI) affects millions of people annually and is difficult to diagnose. Mild injury is insensitive to conventional imaging techniques and diagnoses are often made using subjective criteria such as self-reported symptoms. Many people who sustain a mTBI develop persistent post-concussive symptoms. Athletes and military personnel are at great risk for repeat injury which can result in second impact syndrome or chronic traumatic encephalopathy. An objective and quantifiable measure, such as a serum biomarker, is needed to aid in mTBI diagnosis, prognosis, return to play/duty assessments, and would further elucidate mTBI pathophysiology. The majority of TBI biomarker research focuses on severe TBI with few studies specific to mild injury. Most studies use a hypothesis-driven approach, screening biofluids for markers known to be associated with TBI pathophysiology. This approach has yielded limited success in identifying markers that can be used clinically, additional candidate biomarkers are needed. Innovative and unbiased methods such as proteomics, microRNA arrays, urinary screens, autoantibody identification and phage display would complement more traditional approaches to aid in the discovery of novel mTBI biomarkers. PMID:25981889

  1. Profilin-1 overexpression in MDA-MB-231 breast cancer cells is associated with alterations in proteomics biomarkers of cell proliferation, survival, and motility as revealed by global proteomics analyses.

    Science.gov (United States)

    Coumans, Joëlle V F; Gau, David; Poljak, Anne; Wasinger, Valerie; Roy, Partha; Moens, Pierre D J

    2014-12-01

    Despite early screening programs and new therapeutic strategies, metastatic breast cancer is still the leading cause of cancer death in women in industrialized countries and regions. There is a need for novel biomarkers of susceptibility, progression, and therapeutic response. Global analyses or systems science approaches with omics technologies offer concrete ways forward in biomarker discovery for breast cancer. Previous studies have shown that expression of profilin-1 (PFN1), a ubiquitously expressed actin-binding protein, is downregulated in invasive and metastatic breast cancer. It has also been reported that PFN1 overexpression can suppress tumorigenic ability and motility/invasiveness of breast cancer cells. To obtain insights into the underlying molecular mechanisms of how elevating PFN1 level induces these phenotypic changes in breast cancer cells, we investigated the alteration in global protein expression profiles of breast cancer cells upon stable overexpression of PFN1 by a combination of three different proteome analysis methods (2-DE, iTRAQ, label-free). Using MDA-MB-231 as a model breast cancer cell line, we provide evidence that PFN1 overexpression is associated with alterations in the expression of proteins that have been functionally linked to cell proliferation (FKPB1A, HDGF, MIF, PRDX1, TXNRD1, LGALS1, STMN1, LASP1, S100A11, S100A6), survival (HSPE1, HSPB1, HSPD1, HSPA5 and PPIA, YWHAZ, CFL1, NME1) and motility (CFL1, CORO1B, PFN2, PLS3, FLNA, FLNB, NME2, ARHGDIB). In view of the pleotropic effects of PFN1 overexpression in breast cancer cells as suggested by these new findings, we propose that PFN1-induced phenotypic changes in cancer cells involve multiple mechanisms. Our data reported here might also offer innovative strategies for identification and validation of novel therapeutic targets and companion diagnostics for persons with, or susceptibility to, breast cancer.

  2. Advances of Proteomic Sciences in Dentistry.

    Science.gov (United States)

    Khurshid, Zohaib; Zohaib, Sana; Najeeb, Shariq; Zafar, Muhammad Sohail; Rehman, Rabia; Rehman, Ihtesham Ur

    2016-05-13

    Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed.

  3. Systemic effects of ionizing radiation at the proteome and metabolome levels in the blood of cancer patients treated with radiotherapy: the influence of inflammation and radiation toxicity.

    Science.gov (United States)

    Jelonek, Karol; Pietrowska, Monika; Widlak, Piotr

    2017-07-01

    Blood is the most common replacement tissue used to study systemic responses of organisms to different types of pathological conditions and environmental insults. Local irradiation during cancer radiotherapy induces whole body responses that can be observed at the blood proteome and metabolome levels. Hence, comparative blood proteomics and metabolomics are emerging approaches used in the discovery of radiation biomarkers. These techniques enable the simultaneous measurement of hundreds of molecules and the identification of sets of components that can discriminate different physiological states of the human body. Radiation-induced changes are affected by the dose and volume of irradiated tissues; hence, the molecular composition of blood is a hypothetical source of biomarkers for dose assessment and the prediction and monitoring of systemic responses to radiation. This review aims to provide a comprehensive overview on the available evidence regarding molecular responses to ionizing radiation detected at the level of the human blood proteome and metabolome. It focuses on patients exposed to radiation during cancer radiotherapy and emphasizes effects related to radiation-induced toxicity and inflammation. Systemic responses to radiation detected at the blood proteome and metabolome levels are primarily related to the intensity of radiation-induced toxicity, including inflammatory responses. Thus, several inflammation-associated molecules can be used to monitor or even predict radiation-induced toxicity. However, these abundant molecular features have a rather limited applicability as universal biomarkers for dose assessment, reflecting the individual predisposition of the immune system and tissue-specific mechanisms involved in radiation-induced damage.

  4. A Selected Reaction Monitoring Mass Spectrometry Protocol for Validation of Proteomic Biomarker Candidates in Studies of Psychiatric Disorders.

    Science.gov (United States)

    Reis-de-Oliveira, Guilherme; Garcia, Sheila; Guest, Paul C; Cassoli, Juliana S; Martins-de-Souza, Daniel

    2017-01-01

    Most biomarker candidates arising from proteomic studies of psychiatric disorders have not progressed for use in clinical studies due to insufficient validation steps. Here we describe a selective reaction monitoring mass spectrometry (SRM-MS) approach that could be used as a follow-up validation tool of proteins identified in blood serum or plasma. This protocol specifically covers the stages of peptide selection and optimization. The increasing application of SRM-MS should enable fast, sensitive, and robust methods with the potential for use in clinical studies involving sampling of serum or plasma. Understanding the molecular mechanisms and identifying potential biomarkers for risk assessment, diagnosis, prognosis, and prediction of drug response goes toward the implementation of translational medicine strategies for improved treatment of patients with psychiatric disorders and other debilitating diseases.

  5. Lessons from the proteomic study of osteoarthritis.

    Science.gov (United States)

    Ruiz-Romero, Cristina; Fernández-Puente, Patricia; Calamia, Valentina; Blanco, Francisco J

    2015-08-01

    Osteoarthritis is the most common rheumatic pathology and one of the leading causes of disability worldwide. It is a very complex disease whose etiopathogenesis is not fully understood. Furthermore, there are serious limitations for its management, since it lacks specific and sensitive biomarkers for early diagnosis, prognosis and therapeutic monitoring. Proteomic approaches performed in the last few decades have contributed to the knowledge on the molecular mechanisms that participate in this pathology and they have also led to interesting panels of putative biomarker candidates. In the next few years, further efforts should be made for translating these findings into the clinical routines. It is expected that targeted proteomics strategies will be highly valuable for the verification and qualification of biomarkers of osteoarthritis.

  6. Quantitative proteomic analysis by iTRAQ® for the identification of candidate biomarkers in ovarian cancer serum

    Directory of Open Access Journals (Sweden)

    Higgins LeeAnn

    2010-06-01

    Full Text Available Abstract Background Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ®. Results Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified. Conclusions This study provides the first analysis of immunodepleted serum in combination with iTRAQ® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

  7. The 3rd Central and Eastern European Proteomic Conference

    Czech Academy of Sciences Publication Activity Database

    Gadher, S. J.; Martinková, Jiřina; Drahoš, L.; Vékey, K.; Allmaier, G.; Kovářová, Hana

    2010-01-01

    Roč. 7, č. 1 (2010), s. 15-17 ISSN 1478-9450 Institutional research plan: CEZ:AV0Z50450515 Keywords : proteomics * proteome research * biomarkers Subject RIV: CE - Biochemistry Impact factor: 4.406, year: 2010

  8. Evening and morning alterations in Obstructive Sleep Apnea red blood cell proteome

    Directory of Open Access Journals (Sweden)

    Amélia Feliciano

    2017-04-01

    Full Text Available This article presents proteomics data referenced in [1] Using proteomics-based evaluation of red blood cells (RBCs, we have identified differentially abundant proteins associated with Obstructive Sleep Apnea Syndrome (OSA. RBCs were collected from peripheral blood of patients with moderate/severe OSA or snoring at pre- (evening and post-night (morning polysomnography, so that proteome variations between these time points could be assessed. RBC cytoplasmic fraction depleted of hemoglobin, using Hemovoid™ system, were analyzed by two-dimensional fluorescence difference gel electrophoresis (2D-DIGE, the 2D image software-based analyzed and relevant differentially abundant proteins identified by mass spectrometry (MS. MS identified 31 protein spots differentially abundant corresponding to 21 unique proteins possibly due to the existence of post-translational modification regulations. Functional analysis by bioinformatics tools indicated that most proteins are associated with catalytic, oxidoreductase, peroxidase, hydrolase, ATPase and anti-oxidant activity. At morning a larger numbers of differential proteins including response to chemical stimulus, oxidation reduction, regulation of catalytic activity and response to stress were observed in OSA. The data might support further research in OSA biomarker discovery and validation.

  9. In vitro biomarker discovery in the parasitic flatworm Fasciola hepatica for monitoring chemotherapeutic treatment

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    Russell M. Morphew

    2014-06-01

    Full Text Available The parasitic flatworm Fasciola hepatica is a global food security risk. With no vaccines, the sustainability of triclabendazole (TCBZ is threatened by emerging resistance. F. hepatica excretory/secretory (ES products can be detected in host faeces and used to estimate TCBZ success and failure. However, there are no faecal based molecular diagnostics dedicated to assessing drug failure or resistance to TCBZ in the field. Utilising in vitro maintenance and sub-proteomic approaches two TCBZ stress ES protein response fingerprints were identified: markers of non-killing and lethal doses. This study provides candidate protein/peptide biomarkers to validate for detection of TCBZ failure and resistance.

  10. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu{sup 2+}: An exploratory biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Tânia, E-mail: tania.gomes@niva.no; Chora, Suze; Pereira, Catarina G.; Cardoso, Cátia; Bebianno, Maria João

    2014-10-15

    the other hand, Cu{sup 2+} affected a protein associated with adhesion and mobility, precollagen-D that is associated with the detoxification mechanism of Cu{sup 2+}. Protein identification clearly showed that the toxicity of CuO NPs is not solely due to Cu{sup 2+} dissolution and can result in mitochondrial and nucleus stress-induced cell signalling cascades that can lead to apoptosis. While the absence of the mussel genome precluded the identification of other proteins relevant to clarify the effects of CuO NPs in mussels’ tissues, proteomics analysis provided additional knowledge of their potential effects at the protein level that after confirmation and validation can be used as putative new biomarkers in nanotoxicology.

  11. Biomarkers for AAA: Encouraging steps but clinical relevance still to be delivered.

    Science.gov (United States)

    Htun, Nay Min; Peter, Karlheinz

    2014-10-01

    Potential biomarkers have been investigated using proteomic studies in a variety of diseases. Some biomarkers have central roles in both diagnosis and monitoring of various disorders in clinical medicine, such as troponins, brain natriuretic peptide, and C-reactive protein. Although several biomarkers have been suggested in human abdominal aortic aneurysm (AAA), reliable markers have been lacking. In this issue, Moxon et al. [Proteomics Clin Appl. 2014, 8, 762-772] undertook a broad and systematic proteomic approach toward identification of biomarkers in a commonly used AAA mouse model (AAA created by angiotensin-II infusion). In this mouse model, apolipoprotein C1 and matrix metalloproteinase-9 were identified as novel biomarkers of stable AAA. This finding represents an important step forward, toward a clinically relevant role of biomarkers in AAA. This also encourages for further studies toward the identification of biomarkers (or their combinations) that can predict AAA progression and rupture, which would represent a major progress in AAA management and would establish an AAA biomarker as a much anticipated clinical tool. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Proteomic analysis identifies galectin-1 as a predictive biomarker for relapsed/refractory disease in classical Hodgkin lymphoma

    DEFF Research Database (Denmark)

    Kamper, Peter; Ludvigsen, Maja; Bendix, Knud

    2011-01-01

    Considerable effort has been spent identifying prognostic biomarkers in classic Hodgkin lymphoma (cHL). The aim of our study was to search for possible prognostic parameters in advanced-stage cHL using a proteomics-based strategy. A total of 14 cHL pretreatment tissue samples from younger, advanced......-stage patients were included. Patients were grouped according to treatment response. Proteins that were differentially expressed between the groups were analyzed using 2D-PAGE and identified by liquid chromatography mass spectrometry. Selected proteins were validated using Western blot analysis. One...

  13. Integrated Detection of Pathogens and Host Biomarkers for Wounds

    Energy Technology Data Exchange (ETDEWEB)

    Jaing, C

    2012-03-19

    The increasing incidence and complications arising from combat wounds has necessitated a reassessment of methods for effective treatment. Infection, excessive inflammation, and incidence of drug-resistant organisms all contribute toward negative outcomes for afflicted individuals. The organisms and host processes involved in wound progression, however, are incompletely understood. We therefore set out, using our unique technical resources, to construct a profile of combat wounds which did or did not successfully resolve. We employed the Lawrence Livermore Microbial Detection Array and identified a number of nosocomial pathogens present in wound samples. Some of these identities corresponded with bacterial isolates previously cultured, while others were not obtained via standard microbiology. Further, we optimized proteomics protocols for the identification of host biomarkers indicative of various stages in wound progression. In combination with our pathogen data, our biomarker discovery efforts will provide a profile corresponding to wound complications, and will assist significantly in treatment of these complex cases.

  14. Blood-Based Biomarker Candidates of Cerebral Amyloid Using PiB PET in Non-Demented Elderly

    Science.gov (United States)

    Westwood, Sarah; Leoni, Emanuela; Hye, Abdul; Lynham, Steven; Khondoker, Mizanur R.; Ashton, Nicholas J.; Kiddle, Steven J.; Baird, Alison L.; Sainz-Fuertes, Ricardo; Leung, Rufina; Graf, John; Hehir, Cristina Tan; Baker, David; Cereda, Cristina; Bazenet, Chantal; Ward, Malcolm; Thambisetty, Madhav; Lovestone, Simon

    2018-01-01

    Increasingly, clinical trials for Alzheimer’s disease (AD) are being conducted earlier in the disease phase and with biomarker confirmation using in vivo amyloid PET imaging or CSF tau and Aβ measures to quantify pathology. However, making such a pre-clinical AD diagnosis is relatively costly and the screening failure rate is likely to be high. Having a blood-based marker that would reduce such costs and accelerate clinical trials through identifying potential participants with likely pre-clinical AD would be a substantial advance. In order to seek such a candidate biomarker, discovery phase proteomic analyses using 2DGE and gel-free LC-MS/MS for high and low molecular weight analytes were conducted on longitudinal plasma samples collected over a 12-year period from non-demented older individuals who exhibited a range of 11C-PiB PET measures of amyloid load. We then sought to extend our discovery findings by investigating whether our candidate biomarkers were also associated with brain amyloid burden in disease, in an independent cohort. Seven plasma proteins, including A2M, Apo-A1, and multiple complement proteins, were identified as pre-clinical biomarkers of amyloid burden and were consistent across three time points (p biomarker signature indicative of AD pathology at a stage long before the onset of clinical disease manifestation. As in previous studies, acute phase reactants and inflammatory markers dominate this signature. PMID:27031486

  15. Molecular correlates of trait anxiety: expanding biomarker discovery from protein expression to turnover

    OpenAIRE

    Zhang, Yaoyang

    2010-01-01

    Depression and anxiety disorders affect a great number of people in the world. Although remarkable efforts have been devoted to understanding the clinical and biological basis of these disorders, progress has been relatively slow. Furthermore, no laboratory test currently is available for diagnosis of anxiety and depression. These disorders are mainly diagnosed empirically on the basis of a doctor’s personal observations and experiences. Hence, discovery of biomarkers for these psychiatric di...

  16. Repeatability and Reproducibility in Proteomic Identifications by Liquid Chromatography—Tandem Mass Spectrometry

    Science.gov (United States)

    Tabb, David L.; Vega-Montoto, Lorenzo; Rudnick, Paul A.; Variyath, Asokan Mulayath; Ham, Amy-Joan L.; Bunk, David M.; Kilpatrick, Lisa E.; Billheimer, Dean D.; Blackman, Ronald K.; Cardasis, Helene L.; Carr, Steven A.; Clauser, Karl R.; Jaffe, Jacob D.; Kowalski, Kevin A.; Neubert, Thomas A.; Regnier, Fred E.; Schilling, Birgit; Tegeler, Tony J.; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Fisher, Susan J.; Gibson, Bradford W.; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Stein, Steven E.; Tempst, Paul; Paulovich, Amanda G.; Liebler, Daniel C.; Spiegelman, Cliff

    2009-01-01

    The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35–60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind

  17. Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease.

    Directory of Open Access Journals (Sweden)

    Jochen Neuhaus

    Full Text Available BACKGROUND: Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease. METHODOLOGY/PRINCIPAL FINDINGS: In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls were enrolled in 3 centres. Biomarker panels a for PCa diagnosis (comparison of PCa patients versus benign controls and b for advanced disease (comparison of patients with post surgery Gleason score 7 were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase, prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study. CONCLUSIONS/SIGNIFICANCE: Seminal plasma represents a robust source of potential peptide makers

  18. Proteomic-Based Approaches for the Study of Cytokines in Lung Cancer

    Directory of Open Access Journals (Sweden)

    Ángela Marrugal

    2016-01-01

    Full Text Available Proteomic techniques are currently used to understand the biology of different human diseases, including studies of the cell signaling pathways implicated in cancer progression, which is important in knowing the roles of different proteins in tumor development. Due to its poor prognosis, proteomic approaches are focused on the identification of new biomarkers for the early diagnosis, prognosis, and targeted treatment of lung cancer. Cytokines are proteins involved in inflammatory processes and have been proposed as lung cancer biomarkers and therapeutic targets because it has been reported that some cytokines play important roles in tumor development, invasion, and metastasis. In this review, we aim to summarize the different proteomic techniques used to discover new lung cancer biomarkers and therapeutic targets. Several cytokines have been identified as important players in lung cancer using these techniques. We underline the most important cytokines that are useful as biomarkers and therapeutic targets. We also summarize some of the therapeutic strategies targeted for these cytokines in lung cancer.

  19. Sample handling for mass spectrometric proteomic investigations of human sera.

    NARCIS (Netherlands)

    West-Nielsen, M.; Hogdall, E.V.; Marchiori, E.; Hogdall, C.K.; Schou, C.; Heegaard, N.H.H.

    2005-01-01

    Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers

  20. Signaling pathway networks mined from human pituitary adenoma proteomics data

    Directory of Open Access Journals (Sweden)

    Zhan Xianquan

    2010-04-01

    Full Text Available Abstract Background We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins, comparative proteomic data (56 differentially expressed proteins, and nitroproteomic data (17 nitroproteins. There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. Methods The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. Results For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a

  1. Using MALDI-IMS and MRM to stablish a pipeline for discovery and validation of tumor neovasculature biomarker candidates. — EDRN Public Portal

    Science.gov (United States)

    In an effort to circumvent the limitations associated with biomarker discovery workflows involving cell lines and cell cultures, histology-directed MALDI protein profiling and imaging mass spectrometry will be used for identification of vascular endothelial biomarkers suitable for early prostate cancer detection by CEUS targeted molecular imaging

  2. Proteomic analysis identifies insulin-like growth factor-binding protein-related protein-1 as a podocyte product.

    Science.gov (United States)

    Matsumoto, Takayuki; Hess, Sonja; Kajiyama, Hiroshi; Sakairi, Toru; Saleem, Moin A; Mathieson, Peter W; Nojima, Yoshihisa; Kopp, Jeffrey B

    2010-10-01

    The podocyte secretory proteome may influence the phenotype of adjacent podocytes, endothelial cells, parietal epithelial cells, and tubular epithelial cells but has not been systematically characterized. We have initiated studies to characterize this proteome, with the goal of further understanding the podocyte cell biology. We cultured differentiated conditionally immortalized human podocytes and subjected the proteins in conditioned medium to mass spectrometry. At a false discovery rate of factor-binding protein-related protein-1 (IGFBP-rP1), was expressed in mRNA and protein of cultured podocytes. In addition, transforming growth factor-β1 stimulation increased IGFBP-rP1 in conditioned medium. We analyzed IGFBP-rP1 glomerular expression in a mouse model of human immunodeficiency virus-associated nephropathy. IGFBP-rP1 was absent from podocytes of normal mice and was expressed in podocytes and pseudocrescents of transgenic mice, where it was coexpressed with desmin, a podocyte injury marker. We conclude that IGFBP-rP1 may be a product of injured podocytes. Further analysis of the podocyte secretory proteome may identify biomarkers of podocyte injury.

  3. Identification of peroxiredoxin-1 as a novel biomarker of abdominal aortic aneurysm

    DEFF Research Database (Denmark)

    Martinez-Pinna, Roxana; Ramos-Mozo, Priscila; Madrigal-Matute, Julio

    2011-01-01

    In the search of novel biomarkers of abdominal aortic aneurysm (AAA) progression, proteins released by intraluminal thrombus (ILT) were analyzed by a differential proteomic approach.......In the search of novel biomarkers of abdominal aortic aneurysm (AAA) progression, proteins released by intraluminal thrombus (ILT) were analyzed by a differential proteomic approach....

  4. Proteomics Mapping of Cord Blood Identifies Haptoglobin ?Switch-On? Pattern as Biomarker of Early-Onset Neonatal Sepsis in Preterm Newborns

    OpenAIRE

    Buhimschi, Catalin S.; Bhandari, Vineet; Dulay, Antonette T.; Nayeri, Unzila A.; Abdel-Razeq, Sonya S.; Pettker, Christian M.; Thung, Stephen; Zhao, Guomao; Han, Yiping W.; Bizzarro, Matthew; Buhimschi, Irina A.

    2011-01-01

    Background Intra-amniotic infection and/or inflammation (IAI) are important causes of preterm birth and early-onset neonatal sepsis (EONS). A prompt and accurate diagnosis of EONS is critical for improved neonatal outcomes. We sought to explore the cord blood proteome and identify biomarkers and functional protein networks characterizing EONS in preterm newborns. Methodology/Principal Findings We studied a prospective cohort of 180 premature newborns delivered May 2004-September 2009. A prote...

  5. Metabolomics in cancer biomarker discovery: current trends and future perspectives.

    Science.gov (United States)

    Armitage, Emily G; Barbas, Coral

    2014-01-01

    Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels. Following this, cancer central carbon metabolism has been researched extensively and beyond respiration, cancer has been found to involve a wide range of metabolic processes, and many more are still to be unveiled. Studying cancer through metabolomics could reveal new biomarkers for cancer that could be useful for its future prognosis, diagnosis and therapy. Metabolomics is becoming an increasingly popular tool in the life sciences since it is a relatively fast and accurate technique that can be applied with either a particular focus or in a global manner to reveal new knowledge about biological systems. There have been many examples of its application to reveal potential biomarkers in different cancers that have employed a range of different analytical platforms. In this review, approaches in metabolomics that have been employed in cancer biomarker discovery are discussed and some of the most noteworthy research in the field is highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Proteomic workflow for analysis of archival formalin-fixed and paraffin-embedded clinical samples to a depth of 10 000 proteins.

    Science.gov (United States)

    Wiśniewski, Jacek R; Duś, Kamila; Mann, Matthias

    2013-04-01

    Archival formalin-fixed and paraffin-embedded clinical samples represent a very diverse source of material for proteomic investigation of diseases, often with follow-up patient information. Here, we describe an analytical workflow for analysis of laser-capture microdissected formalin-fixed and paraffin-embedded samples that allows studying proteomes to a depth of 10 000 proteins per sample. The workflow involves lysis of tissue in SDS-containing buffer, detergent removal, and consecutive digestion of the proteins with two enzymes by the multienzyme digestion filter-aided sample preparation method. Resulting peptides are fractionated by pipette-tip based strong anion exchange into six fractions and analyzed by LC-MS/MS on a bench top quadrupole Orbitrap mass spectrometer. Analysis of the data using the MaxQuant software resulted in the identification of 9502 ± 28 protein groups per a 110 nL sample of microdissected cells from human colonic adenoma. This depth of proteome analysis enables systemic insights into the organization of the adenoma cells and an estimation of the abundances of known biomarkers. It also allows the identification of proteins expressed from tumor suppressors, oncogenes, and other key players in the development and progression of the colorectal cancer. Our proteomic platform can be used for quantitative comparisons between samples representing different stages of diseases and thus can be applied to the discovery of biomarkers or drug targets. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Biomarker discovery for cervical cancer

    NARCIS (Netherlands)

    Govorukhina, Natalia I.

    2007-01-01

    Proteomics of human boy fluids is still in its early stage of development with major methodological challenges ahead. This implies that much attention is given to improving the methods and strategies. One major challenge is that many samples that have been acquired in the past may not fulfill the

  8. Tools for monitoring system suitability in LC MS/MS centric proteomic experiments.

    Science.gov (United States)

    Bereman, Michael S

    2015-03-01

    With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    International Nuclear Information System (INIS)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M.C.; Wijmenga, Sybren S.

    2012-01-01

    Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  10. Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

    Science.gov (United States)

    Park, Gun Wook; Hwang, Heeyoun; Kim, Kwang Hoe; Lee, Ju Yeon; Lee, Hyun Kyoung; Park, Ji Yeong; Ji, Eun Sun; Park, Sung-Kyu Robin; Yates, John R; Kwon, Kyung-Hoon; Park, Young Mok; Lee, Hyoung-Joo; Paik, Young-Ki; Kim, Jin Young; Yoo, Jong Shin

    2016-11-04

    In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

  11. Urinary proteomics to support diagnosis of stroke.

    Directory of Open Access Journals (Sweden)

    Jesse Dawson

    Full Text Available Accurate diagnosis in suspected ischaemic stroke can be difficult. We explored the urinary proteome in patients with stroke (n = 69, compared to controls (n = 33, and developed a biomarker model for the diagnosis of stroke. We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Potentially disease-specific peptides were identified and a classifier based on these was generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. We developed two biomarker-based classifiers, employing 14 biomarkers (nominal p-value <0.004 or 35 biomarkers (nominal p-value <0.01. When tested on a blinded test set of 47 independent samples, the classification factor was significantly different between groups; for the 35 biomarker model, median value of the classifier was 0.49 (-0.30 to 1.25 in cases compared to -1.04 (IQR -1.86 to -0.09 in controls, p<0.001. The 35 biomarker classifier gave sensitivity of 56%, specificity was 93% and the AUC on ROC analysis was 0.86. This study supports the potential for urinary proteomic biomarker models to assist with the diagnosis of acute stroke in those with mild symptoms. We now plan to refine further and explore the clinical utility of such a test in large prospective clinical trials.

  12. Proteome screening of pleural effusions identifies IL1A as a diagnostic biomarker for non-small cell lung cancer.

    Science.gov (United States)

    Li, Yuanyuan; Lian, Hengning; Jia, Qingzhu; Wan, Ying

    2015-02-06

    Non-small cell lung cancer (NSCLC) is a common malignant disease, and in ~10-20% of patients, pleural effusion is the first symptom. The pleural effusion proteome contains information on pulmonary disease that directly or indirectly reflects pathophysiological status. However, the proteome of pleural effusion in NSCLC patients is not well understood, nor is the variability in protein composition between malignant and benign pleural effusions. Here, we investigated the different proteins in pleural effusions from NSCLC and tuberculosis (TB) patients by using nano-scale liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. In total, 363 proteins were identified in the NSCLC pleural effusion proteome with a low false discovery rate (pleural effusion were involved in cell adhesion, proteolysis, and cell migration. Furthermore, interleukin 1 alpha (IL1A), a protein that regulates tumor growth, angiogenesis, and metastasis, was significantly more abundant in the NSCLC group compared to the TB group, a finding that was validated with an ELISA assay. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Dietary Yeast Cell Wall Extract Alters the Proteome of the Skin Mucous Barrier in Atlantic Salmon (Salmo salar: Increased Abundance and Expression of a Calreticulin-Like Protein.

    Directory of Open Access Journals (Sweden)

    Giulia Micallef

    Full Text Available In order to improve fish health and reduce use of chemotherapeutants in aquaculture production, the immunomodulatory effect of various nutritional ingredients has been explored. In salmon, there is evidence that functional feeds can reduce the abundance of sea lice. This study aimed to determine if there were consistent changes in the skin mucus proteome that could serve as a biomarker for dietary yeast cell wall extract. The effect of dietary yeast cell wall extract on the skin mucus proteome of Atlantic salmon was examined using two-dimensional gel electrophoresis. Forty-nine spots showed a statistically significant change in their normalised volumes between the control and yeast cell wall diets. Thirteen spots were successfully identified by peptide fragment fingerprinting and LC-MS/MS and these belonged to a variety of functions and pathways. To assess the validity of the results from the proteome approach, the gene expression of a selection of these proteins was studied in skin mRNA from two different independent feeding trials using yeast cell wall extracts. A calreticulin-like protein increased in abundance at both the protein and transcript level in response to dietary yeast cell wall extract. The calreticulin-like protein was identified as a possible biomarker for yeast-derived functional feeds since it showed the most consistent change in expression in both the mucus proteome and skin transcriptome. The discovery of such a biomarker is expected to quicken the pace of research in the application of yeast cell wall extracts.

  14. Proteomic Analysis of Saliva Identifies Potential Biomarkers for Orthodontic Tooth Movement

    Science.gov (United States)

    Ellias, Mohd Faiz; Zainal Ariffin, Shahrul Hisham; Karsani, Saiful Anuar; Abdul Rahman, Mariati; Senafi, Shahidan; Megat Abdul Wahab, Rohaya

    2012-01-01

    Orthodontic treatment has been shown to induce inflammation, followed by bone remodelling in the periodontium. These processes trigger the secretion of various proteins and enzymes into the saliva. This study aims to identify salivary proteins that change in expression during orthodontic tooth movement. These differentially expressed proteins can potentially serve as protein biomarkers for the monitoring of orthodontic treatment and tooth movement. Whole saliva from three healthy female subjects were collected before force application using fixed appliance and at 14 days after 0.014′′ Niti wire was applied. Salivary proteins were resolved using two-dimensional gel electrophoresis (2DE) over a pH range of 3–10, and the resulting proteome profiles were compared. Differentially expressed protein spots were then identified by MALDI-TOF/TOF tandem mass spectrometry. Nine proteins were found to be differentially expressed; however, only eight were identified by MALDI-TOF/TOF. Four of these proteins—Protein S100-A9, immunoglobulin J chain, Ig alpha-1 chain C region, and CRISP-3—have known roles in inflammation and bone resorption. PMID:22919344

  15. Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification

    Science.gov (United States)

    Book Chapter 18, titled Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification, will be published in the book titled High Performance Liquid Chromatography in Pesticide Residue Analysis (Part of the C...

  16. Proteomic analysis of bronchoalveolar lavage fluid (BALF) from lung cancer patients using label-free mass spectrometry.

    Science.gov (United States)

    Hmmier, Abduladim; O'Brien, Michael Emmet; Lynch, Vincent; Clynes, Martin; Morgan, Ross; Dowling, Paul

    2017-06-01

    Lung cancer is the leading cause of cancer-related mortality in both men and women throughout the world. The need to detect lung cancer at an early, potentially curable stage, is essential and may reduce mortality by 20%. The aim of this study was to identify distinct proteomic profiles in bronchoalveolar fluid (BALF) and plasma that are able to discriminate individuals with benign disease from those with non-small cell lung cancer (NSCLC). Using label-free mass spectrometry analysis of BALF during discovery-phase analysis, a significant number of proteins were found to have different abundance levels when comparing control to adenocarcinoma (AD) or squamous cell lung carcinoma (SqCC). Validation of candidate biomarkers identified in BALF was performed in a larger cohort of plasma samples by detection with enzyme-linked immunoassay. Four proteins (Cystatin-C, TIMP-1, Lipocalin-2 and HSP70/HSPA1A) were selected as a representative group from discovery phase mass spectrometry BALF analysis. Plasma levels of TIMP-1, Lipocalin-2 and Cystatin-C were found to be significantly elevated in AD and SqCC compared to control. The results presented in this study indicate that BALF is an important proximal biofluid for the discovery and identification of candidate lung cancer biomarkers. There is good correlation between the trend of protein abundance levels in BALF and that of plasma which validates this approach to develop a blood biomarker to aid lung cancer diagnosis, particularly in the era of lung cancer screening. The protein signatures identified also provide insight into the molecular mechanisms associated with lung malignancy.

  17. Effects of High-Pressure Treatment on the Muscle Proteome of Hake by Bottom-Up Proteomics.

    Science.gov (United States)

    Carrera, Mónica; Fidalgo, Liliana G; Saraiva, Jorge A; Aubourg, Santiago P

    2018-05-02

    A bottom-up proteomics approach was applied for the study of the effects of high-pressure (HP) treatment on the muscle proteome of fish. The performance of the approach was established for a previous HP treatment (150-450 MPa for 2 min) on frozen (up to 5 months at -10 °C) European hake ( Merluccius merluccius). Concerning possible protein biomarkers of quality changes, a significant degradation after applying a pressure ≥430 MPa could be observed for phosphoglycerate mutase-1, enolase, creatine kinase, fructose bisphosphate aldolase, triosephosphate isomerase, and nucleoside diphosphate kinase; contrary, electrophoretic bands assigned to tropomyosin, glyceraldehyde-3-phosphate dehydrogenase, and beta parvalbumin increased their intensity after applying a pressure ≥430 MPa. This repository of potential protein biomarkers may be very useful for further HP investigations related to fish quality.

  18. Proteomic profiling reveals candidate markers for arsenic-induced skin keratosis.

    Science.gov (United States)

    Guo, Zhiling; Hu, Qin; Tian, Jijing; Yan, Li; Jing, Chuanyong; Xie, Heidi Qunhui; Bao, Wenjun; Rice, Robert H; Zhao, Bin; Jiang, Guibin

    2016-11-01

    Proteomics technology is an attractive biomarker candidate discovery tool that can be applied to study large sets of biological molecules. To identify novel biomarkers and molecular targets in arsenic-induced skin lesions, we have determined the protein profile of arsenic-affected human epidermal stratum corneum by shotgun proteomics. Samples of palm and foot sole from healthy subjects were analyzed, demonstrating similar protein patterns in palm and sole. Samples were collected from the palms of subjects with arsenic keratosis (lesional and adjacent non-lesional samples) and arsenic-exposed subjects without lesions (normal). Samples from non-exposed healthy individuals served as controls. We found that three proteins in arsenic-exposed lesional epidermis were consistently distinguishably expressed from the unaffected epidermis. One of these proteins, the cadherin-like transmembrane glycoprotein, desmoglein 1 (DSG1) was suppressed. Down-regulation of DSG1 may lead to reduced cell-cell adhesion, resulting in abnormal epidermal differentiation. The expression of keratin 6c (KRT6C) and fatty acid binding protein 5 (FABP5) were significantly increased. FABP5 is an intracellular lipid chaperone that plays an essential role in fatty acid metabolism in human skin. This raises a possibility that overexpression of FABP5 may affect the proliferation or differentiation of keratinocytes by altering lipid metabolism. KRT6C is a constituent of the cytoskeleton that maintains epidermal integrity and cohesion. Abnormal expression of KRT6C may affect its structural role in the epidermis. Our findings suggest an important approach for future studies of arsenic-mediated toxicity and skin cancer, where certain proteins may represent useful biomarkers of early diagnoses in high-risk populations and hopefully new treatment targets. Further studies are required to understand the biological role of these markers in skin pathogenesis from arsenic exposure. Copyright © 2016 Elsevier Ltd

  19. Opportunities and Challenges of Proteomics in Pediatric Patients: Circulating Biomarkers After Hematopoietic Stem Cell Transplantation As a Successful Example

    Science.gov (United States)

    Paczesny, Sophie; Duncan, Christine; Jacobsohn, David; Krance, Robert; Leung, Kathryn; Carpenter, Paul; Bollard, Catherine; Renbarger, Jamie; Cooke, Kenneth

    2015-01-01

    Biomarkers have the potential to improve diagnosis and prognosis, facilitate targeted treatment, and reduce health care costs. Thus, there is great hope that biomarkers will be integrated in all clinical decisions in the near future. A decade ago, the biomarker field was launched with great enthusiasm because mass spectrometry revealed that blood contains a rich library of candidate biomarkers. However, biomarker research has not yet delivered on its promise due to several limitations: (i) improper sample handling and tracking as well as limited sample availability in the pediatric population, (ii) omission of appropriate controls in original study designs, (iii) lability and low abundance of interesting biomarkers in blood, and (iv) the inability to mechanistically tie biomarker presence to disease biology. These limitations as well as successful strategies to overcome them are discussed in this review. Several advances in biomarker discovery and validation have been made in hematopoietic stem cell transplantation, the current most effective tumor immunotherapy, and these could serve as examples for other conditions. This review provides fresh optimism that biomarkers clinically relevant in pediatrics are closer to being realized based on: (i) a uniform protocol for low-volume blood collection and preservation, (ii) inclusion of well-controlled independent cohorts, (iii) novel technologies and instrumentation with low analytical sensitivity, and (iv) integrated animal models for exploring potential biomarkers and targeted therapies. PMID:25196024

  20. Diabetic retinopathy: Proteomic approaches to help the differential diagnosis and to understand the underlying molecular mechanisms.

    Science.gov (United States)

    Csősz, Éva; Deák, Eszter; Kalló, Gergő; Csutak, Adrienne; Tőzsér, József

    2017-01-06

    Diabetic retinopathy is the most common diabetic eye disease and a leading cause of blindness among patients with diabetes. The appearance and the severity of the symptoms correlate with the duration of diabetes and poor blood glucose level management. Diabetic retinopathy is also categorized as a chronic low-level inflammatory disease; the high blood glucose level promotes the accumulation of the advanced glycation end products and leads to the stimulation of monocytes and macrophages. Examination of protein level alterations in tears using state-of the art proteomics techniques have identified several proteins as possible biomarkers for the different stages of the diabetic retinopathy. Some of the differentially expressed tear proteins have a role in the barrier function of tears linking the diabetic retinopathy with another eye complication of diabetes, namely the diabetic keratopathy resulting in impaired wound healing. Understanding the molecular events leading to the eye complications caused by hyperglycemia may help the identification of novel biomarkers as well as therapeutic targets in order to improve quality of life of diabetic patients. Diabetic retinopathy (DR), the leading cause of blindness among diabetic patients can develop without any serious symptoms therefore the early detection is crucial. Because of the increasing prevalence there is a high need for improved screening methods able to diagnose DR as soon as possible. The non-invasive collection and the relatively high protein concentration make the tear fluid a good source for biomarker discovery helping the early diagnosis. In this work we have reviewed the administration of advanced proteomics techniques used in tear biomarker studies and the identified biomarkers with potential to improve the already existing screening methods for DR detection. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Proteomic Changes in Cerebrospinal Fluid of Presymptomatic and Affected Persons Carrying Familial Alzheimer Disease Mutations

    Science.gov (United States)

    Ringman, John M.; Schulman, Howard; Becker, Chris; Jones, Ted; Bai, Yuchen; Immermann, Fred; Cole, Gregory; Sokolow, Sophie; Gylys, Karen; Geschwind, Daniel H.; Cummings, Jeffrey L.; Wan, Hong I.

    2013-01-01

    Objective To identify cerebrospinal fluid (CSF) protein changes in persons who will develop familial Alzheimer disease (FAD) due to PSEN1 and APP mutations, using unbiased proteomics. Design We compared proteomic profiles of CSF from individuals with FAD who were mutation carriers (MCs) and related noncarriers (NCs). Abundant proteins were depleted and samples were analyzed using liquid chromatography– electrospray ionization–mass spectrometry on a high-resolution time-of-flight instrument. Tryptic peptides were identified by tandem mass spectrometry. Proteins differing in concentration between the MCs and NCs were identified. Setting A tertiary dementia referral center and a proteomic biomarker discovery laboratory. Participants Fourteen FAD MCs (mean age, 34.2 years; 10 are asymptomatic, 12 have presenilin-1 [PSEN1] gene mutations, and 2 have amyloid precursor protein [APP] gene mutations) and 5 related NCs (mean age, 37.6 years). Results Fifty-six proteins were identified, represented by multiple tryptic peptides showing significant differences between MCs and NCs (46 upregulated and 10 downregulated); 40 of these proteins differed when the analysis was restricted to asymptomatic individuals. Fourteen proteins have been reported in prior proteomic studies in late-onset AD, including amyloid precursor protein, transferrin, α1β-glycoprotein, complement components, afamin precursor, spondin 1, plasminogen, hemopexin, and neuronal pentraxin receptor. Many other proteins were unique to our study, including calsyntenin 3, AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) 4 glutamate receptor, CD99 antigen, di-N-acetyl-chitobiase, and secreted phosphoprotein 1. Conclusions We found much overlap in CSF protein changes between individuals with presymptomatic and symptomatic FAD and those with late-onset AD. Our results are consistent with inflammation and synaptic loss early in FAD and suggest new presymptomatic biomarkers of potential usefulness in drug

  2. Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

    Science.gov (United States)

    Page, Sandra; Birerdinc, Aybike; Estep, Michael; Stepanova, Maria; Afendy, Arian; Petricoin, Emanuel; Younossi, Zobair; Chandhoke, Vikas; Baranova, Ancha

    2013-01-01

    The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

  3. Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

    Directory of Open Access Journals (Sweden)

    Sandra Page

    Full Text Available The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1 NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2 biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

  4. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    Energy Technology Data Exchange (ETDEWEB)

    Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

    2012-10-31

    Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  5. Big biomedical data as the key resource for discovery science.

    Science.gov (United States)

    Toga, Arthur W; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W; Price, Nathan D; Glusman, Gustavo; Heavner, Benjamin D; Dinov, Ivo D; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

    2015-11-01

    Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome.

    Science.gov (United States)

    Ghodasara, P; Sadowski, P; Satake, N; Kopp, S; Mills, P C

    2017-12-01

    Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Chemical proteomics for target discovery of head-to-tail cyclized mini-proteins

    Science.gov (United States)

    Hellinger, Roland; Thell, Kathrin; Vasileva, Mina; Muhammad, Taj; Gunasekera, Sunithi; Kümmel, Daniel; Göransson, Ulf; Becker, Christian W.; Gruber, Christian W.

    2017-10-01

    Target deconvolution is one of the most challenging tasks in drug discovery, but a key step in drug development. In contrast to small molecules, there is a lack of validated and robust methodologies for target elucidation of peptides. In particular, it is difficult to apply these methods to cyclic and cysteine-stabilized peptides since they exhibit reduced amenability to chemical modification and affinity capture; however, such ribosomal synthesized and post-translationally modified peptide natural products are rich sources of promising drug candidates. For example, plant-derived circular peptides called cyclotides have recently attracted much attention due to their immunosuppressive effects and oral activity in the treatment of multiple sclerosis in mice, but their molecular target has hitherto not been reported. In this study a chemical proteomics approach using photo-affinity crosslinking was developed to determine a target of the circular peptide [T20K]kalata B1. Using this prototypic nature-derived peptide enabled the identification of a possible modulation of 14-3-3 proteins. This biochemical interaction was validated via competition pull down assays as well as a cellular reporter assay indicating an effect on 14-3-3-dependent transcriptional activity. As proof of concept, the presented approach may be applicable for target elucidation of various cyclic peptides and mini-proteins, in particular cyclotides, which represent a promising class of molecules in drug discovery and development.

  8. Liver proteome response of largemouth bass (Micropterus salmoides) exposed to several environmental contaminants: Potential insights into biomarker development

    International Nuclear Information System (INIS)

    Sanchez, Brian C.; Ralston-Hooper, Kimberly J.; Kowalski, Kevin A.; Dorota Inerowicz, H.; Adamec, Jiri; Sepulveda, Maria S.

    2009-01-01

    Liver proteome response of largemouth bass (Micropterus salmoides) exposed to environmental contaminants was analyzed to identify novel biomarkers of exposure. Adult male bass were exposed to cadmium chloride (CdCl 2 ), atrazine, PCB 126, phenanthrene, or toxaphene via intraperitoneal injection with target body burdens of 0.00067, 3.0, 2.5, 50, and 100 μg/g, respectively. After a 96 h exposure, hepatic proteins were separated with two-dimensional gel electrophoresis and differentially expressed proteins (vs. controls) recognized and identified with MALDI-TOF/TOF mass spectrometry. We identified, 30, 18, eight, 19, and five proteins as differentially expressed within the CdCl 2 , atrazine, PCB 126, phenanthrene, and toxaphene treatments, respectively. Alterations were observed in the expression of proteins associated with cellular ion homeostasis (toxaphene), oxidative stress (phenanthrene, PCB 126), and energy production including glycolysis (CdCl 2 , atrazine) and ATP synthesis (atrazine). This work supports the further evaluation of several of these proteins as biomarkers of contaminant exposure in fish.

  9. Proteomic profile of acute myeloid leukaemia: A review update ...

    African Journals Online (AJOL)

    This review draws attention to the progress and advancements in cancer proteomics technology with the aim of simplifying the understanding of the mechanisms underlying the disease and to contribute to detection of biomarkers in addition to the development of novel treatments. Given that proteome is a dynamic entity of ...

  10. Disease Classification and Biomarker Discovery Using ECG Data

    Directory of Open Access Journals (Sweden)

    Rong Huang

    2015-01-01

    Full Text Available In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA, SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

  11. The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer.

    LENUS (Irish Health Repository)

    Tonry, Claire L

    2016-07-18

    Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and\\/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

  12. The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Claire L. Tonry

    2016-07-01

    Full Text Available Prostate Cancer (PCa is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i might best receive no treatment (active surveillance of the disease; (ii would benefit from existing treatments; or (iii those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

  13. Identification of the soluble form of tyrosine kinase receptor Axl as a potential biomarker for intracranial aneurysm rupture.

    Science.gov (United States)

    Xu, Jing; Ma, Feiqiang; Yan, Wei; Qiao, Sen; Xu, Shengquan; Li, Yi; Luo, Jianhong; Zhang, Jianmin; Jin, Jinghua

    2015-03-05

    Subarachnoid hemorrhage caused by a ruptured intracranial aneurysm (RIA) is a devastating condition with significant morbidity and mortality. Despite the fact that RIAs can be prevented by microsurgical clipping or endovascular coiling, there are no reliable means of effectively predicting IA patients at risk for rupture. The purpose of our study was to discover differentially-expressed glycoproteins in IAs with or without rupture as potential biomarkers to predict rupture. Forty age/gender-matched patients with RIA, unruptured IA (UIA), healthy controls (HCs) and disease controls (DCs) (discovery cohort, n = 10 per group) were recruited and a multiplex quantitative proteomic method, iTRAQ (isobaric Tagging for Relative and Absolute protein Quantification), was used to quantify relative changes in the lectin-purified glycoproteins in CSF from RIAs and UIAs compared to HCs and DCs. Then we verified the proteomic results in an independent set of samples (validation cohort, n = 20 per group) by enzyme-linked immunosorbent assay. Finally, we evaluated the specificity and sensitivity of the candidate marker with receiver operating characteristic (ROC) curve methods. The proteomic findings identified 294 proteins, 40 of which displayed quantitative changes unique to RIA, 13 to UIA, and 20 to IA. One of these proteins, receptor tyrosine kinase Axl, was significantly increased in RIA, as confirmed in CSF from the discovery cohort as well as in CSF and plasma from the validation cohort (p IA.

  14. Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

    Science.gov (United States)

    Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

    2015-10-01

    The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

  15. Gene Expression and Proteome Analysis as Sources of Biomarkers in Basal Cell Carcinoma

    Science.gov (United States)

    Ghita, Mihaela Adriana; Voiculescu, Suzana; Rosca, Adrian E.; Moraru, Liliana; Greabu, Maria

    2016-01-01

    Basal cell carcinoma (BCC) is the world's leading skin cancer in terms of frequency at the moment and its incidence continues to rise each year, leading to profound negative psychosocial and economic consequences. UV exposure is the most important environmental factor in the development of BCC in genetically predisposed individuals, this being reflected by the anatomical distribution of lesions mainly on sun-exposed skin areas. Early diagnosis and prompt management are of crucial importance in order to prevent local tissue destruction and subsequent disfigurement. Although various noninvasive or minimal invasive techniques have demonstrated their utility in increasing diagnostic accuracy of BCC and progress has been made in its treatment options, recurrent, aggressive, and metastatic variants of BCC still pose significant challenge for the healthcare system. Analysis of gene expression and proteomic profiling of tumor cells and of tumoral microenvironment in various tissues strongly suggests that certain molecules involved in skin cancer pathogenic pathways might represent novel predictive and prognostic biomarkers in BCC. PMID:27578920

  16. Gene Expression and Proteome Analysis as Sources of Biomarkers in Basal Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    Mihai Lupu

    2016-01-01

    Full Text Available Basal cell carcinoma (BCC is the world’s leading skin cancer in terms of frequency at the moment and its incidence continues to rise each year, leading to profound negative psychosocial and economic consequences. UV exposure is the most important environmental factor in the development of BCC in genetically predisposed individuals, this being reflected by the anatomical distribution of lesions mainly on sun-exposed skin areas. Early diagnosis and prompt management are of crucial importance in order to prevent local tissue destruction and subsequent disfigurement. Although various noninvasive or minimal invasive techniques have demonstrated their utility in increasing diagnostic accuracy of BCC and progress has been made in its treatment options, recurrent, aggressive, and metastatic variants of BCC still pose significant challenge for the healthcare system. Analysis of gene expression and proteomic profiling of tumor cells and of tumoral microenvironment in various tissues strongly suggests that certain molecules involved in skin cancer pathogenic pathways might represent novel predictive and prognostic biomarkers in BCC.

  17. Analytical Pipeline for Discovery and Verification of Glycoproteins from Plasma-Derived Extracellular Vesicles as Breast Cancer Biomarkers.

    Science.gov (United States)

    Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy

    2018-05-15

    Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

  18. From the endometrium physiology to a comprehensive strategy for the discovery of ovarian cancer biomarkers

    OpenAIRE

    Janos L. Tanyi; Nathalie Scholler

    2011-01-01

    The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and p...

  19. Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes.

    Science.gov (United States)

    Wen, Li; Liu, Ye-Fang; Jiang, Cen; Zeng, Shao-Qian; Su, Yue; Wu, Wen-Jun; Liu, Xi-Yang; Wang, Jian; Liu, Ying; Su, Chen; Li, Bai-Xue; Feng, Quan-Sheng

    2018-03-08

    Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.

  20. Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

    Directory of Open Access Journals (Sweden)

    Jinfeng Zou

    Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

  1. Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

    Science.gov (United States)

    Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

    2008-04-01

    The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

  2. Candidate proteins, metabolites and transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA clinical study.

    Directory of Open Access Journals (Sweden)

    Richard S Finkel

    Full Text Available Spinal Muscular Atrophy (SMA is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1 gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets.To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches.A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2-12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS and to a number of secondary clinical measures.A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites and 44 urine metabolites. No transcripts correlated with MHFMS.In this cross-sectional study, "BforSMA" (Biomarkers for SMA, candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm these findings, demonstrate sensitivity to change with

  3. Database-augmented Mass Spectrometry Analysis of Exosomes Identifies Claudin 3 as a Putative Prostate Cancer Biomarker.

    Science.gov (United States)

    Worst, Thomas Stefan; von Hardenberg, Jost; Gross, Julia Christina; Erben, Philipp; Schnölzer, Martina; Hausser, Ingrid; Bugert, Peter; Michel, Maurice Stephan; Boutros, Michael

    2017-06-01

    In prostate cancer and other malignancies sensitive and robust biomarkers are lacking or have relevant limitations. Prostate specific antigen (PSA), the only biomarker widely used in prostate cancer, is suffering from low specificity. Exosomes offer new perspectives in the discovery of blood-based biomarkers. Here we present a proof-of principle study for a proteomics-based identification pipeline, implementing existing data sources, to exemplarily identify exosome-based biomarker candidates in prostate cancer.Exosomes from malignant PC3 and benign PNT1A cells and from FBS-containing medium were isolated using sequential ultracentrifugation. Exosome and control samples were analyzed on an LTQ-Orbitrap XL mass spectrometer. Proteomic data is available via ProteomeXchange with identifier PXD003651. We developed a scoring scheme to rank 64 proteins exclusively found in PC3 exosomes, integrating data from four public databases and published mass spectrometry data sets. Among the top candidates, we focused on the tight junction protein claudin 3. Retests under serum-free conditions using immunoblotting and immunogold labeling confirmed the presence of claudin 3 on PC3 exosomes. Claudin 3 levels were determined in the blood plasma of patients with localized ( n = 58; 42 with Gleason score 6-7, 16 with Gleason score ≥8) and metastatic prostate cancer ( n = 11) compared with patients with benign prostatic hyperplasia ( n = 15) and healthy individuals ( n = 15) using ELISA, without prior laborious exosome isolation. ANOVA showed different CLDN3 plasma levels in these groups ( p = 0.004). CLDN3 levels were higher in patients with Gleason ≥8 tumors compared with patients with benign prostatic hyperplasia ( p = 0.012) and Gleason 6-7 tumors ( p = 0.029). In patients with localized tumors CLDN3 levels predicted a Gleason score ≥ 8 (AUC = 0.705; p = 0.016) and did not correlate with serum PSA.By using the described workflow claudin 3 was identified and validated as a

  4. Regional differences of the urinary proteomes in healthy Chinese individuals

    OpenAIRE

    Qin, Weiwei; Wu, Jianqiang; Pan, Li; Zhang, Fanshuang; Wang, Xiaorong; Zhang, Biao; Shan, Guangliang; Gao, Youhe

    2017-01-01

    Urine is a promising biomarker source for clinical proteomics studies. Although regional physiological differences are common in multi-center clinical studies, the presence of significant differences in the urinary proteomes of individuals from different regions remains unknown. In this study, morning urine samples were collected from healthy urban residents in three regions of China and urinary proteins were preserved using a membrane-based method (Urimem). The urine proteomes of 27 normal s...

  5. Longitudinal Bank for Serum, Plasma, and DNA for Detection of Biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Vogelzang, Nicolas [Nevada Cancer Inst., Las Vegas, NV (United States); Fink, Louis [Nevada Cancer Inst., Las Vegas, NV (United States)

    2007-11-12

    The discovery of genetic or biochemical markers to discriminate malignant cancers from normal or benign disease states, markers to stage cancer or monitor disease progression and markers that provide an early indication of an individual’s response to chemotherapy have become a major research objectives of the oncology community over the past few years. The goal of the project is to create a patient specimen bank of serum, plasma, urine and tissues from approximately 1500 individuals. The collection of samples from individuals on a longitudinal basis provided proteomic and biochemical data to be correlated with clinical endpoints. This greatly enhanced our ability to identify biomarkers for staging different cancers and to detect patient responsiveness to therapy at an early state in the treatment process.

  6. The proteome of human saliva

    Science.gov (United States)

    Griffin, Timothy J.

    2013-05-01

    Human saliva holds tremendous potential for transforming disease and health diagnostics given its richness of molecular information and non-invasive collection. Enumerating its molecular constituents is an important first step towards reaching this potential. Among the molecules in saliva, proteins and peptides arguably have the most value: they can directly indicate biochemical functions linked to a health condition/disease state, and they are attractive targets for biomarker assay development. However, cataloging and defining the human salivary proteome is challenging given the dynamic, chemically heterogeneous and complex nature of the system. In addition, the overall human saliva proteome is composed of several "sub-proteomes" which include: intact full length proteins, proteins carrying post-translational modifications (PTMs), low molecular weight peptides, and the metaproteome, derived from protein products from nonhuman organisms (e.g. microbes) present in the oral cavity. Presented here will be a summary of communal efforts to meet the challenge of characterizing the multifaceted saliva proteome, focusing on the use of mass spectrometry as the proteomic technology of choice. Implications of these efforts to characterize the salivary proteome in the context of disease diagnostics will also be discussed.

  7. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

    Science.gov (United States)

    Wilson, Jennifer L; Altman, Russ B

    2018-02-01

    Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

  8. Application of a global proteomic approach to archival precursor lesions: deleted in malignant brain tumors 1 and tissue transglutaminase 2 are upregulated in pancreatic cancer precursors

    DEFF Research Database (Denmark)

    Cheung, Wang; Darfler, Marlene M; Alvarez, Hector

    2008-01-01

    BACKGROUND: Pancreatic cancer is an almost uniformly fatal disease, and early detection is a critical determinant of improved survival. A variety of noninvasive precursor lesions of pancreatic adenocarcinoma have been identified, which provide a unique opportunity for intervention prior to onset ...... their overexpression in IPMNs. CONCLUSION: Global proteomics analysis using the Liquid Tissue workflow is a feasible approach for unbiased biomarker discovery in limited archival material, particularly applicable to precursor lesions of cancer......., and mass spectrometry to conduct a global proteomic analysis of an intraductal papillary mucinous neoplasm (IPMN). Tissue microarrays comprised of 38 IPMNs were used for validation of candidate proteins. RESULTS: The proteomic analysis of the IPMN Liquid Tissue lysate resulted in identification of 1......,534 peptides corresponding to 523 unique proteins. A subset of 25 proteins was identified that had previously been reported as upregulated in pancreatic cancer. Immunohistochemical analysis for two of these, deleted in malignant brain tumors 1 (DMBT1) and tissue transglutaminase 2 (TGM2), confirmed...

  9. Unravelling the nuclear matrix proteome

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Knol, Jaco C; Jimenez, Connie R

    2009-01-01

    The nuclear matrix (NM) model posits the presence of a protein/RNA scaffold that spans the mammalian nucleus. The NM proteins are involved in basic nuclear function and are a promising source of protein biomarkers for cancer. Importantly, the NM proteome is operationally defined as the proteins...

  10. Biomarker candidate discovery in Atlantic cod (Gadus morhua) continuously exposed to North Sea produced water from egg to fry

    DEFF Research Database (Denmark)

    Bohne-Kjersem, Anneli; Bache, Nicolai; Meier, Sonnich

    2010-01-01

    were able to compare the induced changes by PW to the mode of action of oestrogens. Changes in the proteome in response to exposure in whole cod fry (approximately 80 days post-hatching, dph) were detected by two-dimensional gel electrophoresis and image analysis and identified by MALDI-ToF-ToF mass...... spectrometry, using a newly developed cod EST database and the NCBI database. Many of the protein changes occurred at low levels (0.01% and 0.1% PW) of exposure, indicating putative biological responses at lower levels than previously detected. Using discriminant analysis, we identified a set of protein...... changes that may be useful as biomarker candidates of produced water (PW) and oestradiol exposure in Atlantic cod fry. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring exposure and effects of discharges from the petroleum...

  11. Effects of diuretics on urinary proteins.

    Science.gov (United States)

    Li, Xundou

    2015-01-01

    Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. The human orthologs of most of these 14 proteins affected are stable in the healthy human urinary proteome, and 10 of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics.

  12. Emerging Biomarkers and Metabolomics for Assessing Toxic Nephropathy and Acute Kidney Injury (AKI in Neonatology

    Directory of Open Access Journals (Sweden)

    M. Mussap

    2014-01-01

    Full Text Available Identification of novel drug-induced toxic nephropathy and acute kidney injury (AKI biomarkers has been designated as a top priority by the American Society of Nephrology. Increasing knowledge in the science of biology and medicine is leading to the discovery of still more new biomarkers and of their roles in molecular pathways triggered by physiological and pathological conditions. Concomitantly, the development of the so-called “omics” allows the progressive clinical utilization of a multitude of information, from those related to the human genome (genomics and proteome (proteomics, including the emerging epigenomics, to those related to metabolites (metabolomics. In preterm newborns, one of the most important factors causing the pathogenesis and the progression of AKI is the interaction between the individual genetic code, the environment, the gestational age, and the disease. By analyzing a small urine sample, metabolomics allows to identify instantly any change in phenotype, including changes due to genetic modifications. The role of liquid chromatography-mass spectrometry (LC-MS, proton nuclear magnetic resonance (1H NMR, and other emerging technologies is strategic, contributing basically to the sudden development of new biochemical and molecular tests. Urine neutrophil gelatinase-associated lipocalin (uNGAL and kidney injury molecule-1 (KIM-1 are closely correlated with the severity of kidney injury, representing noninvasive sensitive surrogate biomarkers for diagnosing, monitoring, and quantifying kidney damage. To become routine tests, uNGAL and KIM-1 should be carefully tested in multicenter clinical trials and should be measured in biological fluids by robust, standardized analytical methods.

  13. Identification of cancer protein biomarkers using proteomic techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

    2016-10-18

    The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

  14. Detecting differential protein expression in large-scale population proteomics

    Energy Technology Data Exchange (ETDEWEB)

    Ryu, Soyoung; Qian, Weijun; Camp, David G.; Smith, Richard D.; Tompkins, Ronald G.; Davis, Ronald W.; Xiao, Wenzhong

    2014-06-17

    Mass spectrometry-based high-throughput quantitative proteomics shows great potential in clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, methods are needed to appropriately handle issues/challenges unique to mass spectrometry data in order to detect as many biomarker proteins as possible. One issue is that different mass spectrometry experiments generate quite different total numbers of quantified peptides, which can result in more missing peptide abundances in an experiment with a smaller total number of quantified peptides. Another issue is that the quantification of peptides is sometimes absent, especially for less abundant peptides and such missing values contain the information about the peptide abundance. Here, we propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients’ sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data.

  15. Characterization of Foodborne Strains of Staphylococcus aureus by Shotgun Proteomics: Functional Networks, Virulence Factors and Species-Specific Peptide Biomarkers

    Science.gov (United States)

    Carrera, Mónica; Böhme, Karola; Gallardo, José M.; Barros-Velázquez, Jorge; Cañas, Benito; Calo-Mata, Pilar

    2017-01-01

    In the present work, we applied a shotgun proteomics approach for the fast and easy characterization of 20 different foodborne strains of Staphylococcus aureus (S. aureus), one of the most recognized foodborne pathogenic bacteria. A total of 644 non-redundant proteins were identified and analyzed via an easy and rapid protein sample preparation procedure. The results allowed the differentiation of several proteome datasets from the different strains (common, accessory, and unique datasets), which were used to determine relevant functional pathways and differentiate the strains into different Euclidean hierarchical clusters. Moreover, a predicted protein-protein interaction network of the foodborne S. aureus strains was created. The whole confidence network contains 77 nodes and 769 interactions. Most of the identified proteins were surface-associated proteins that were related to pathways and networks of energy, lipid metabolism and virulence. Twenty-seven virulence factors were identified, and most of them corresponded to autolysins, N-acetylmuramoyl-L-alanine amidases, phenol-soluble modulins, extracellular fibrinogen-binding proteins and virulence factor EsxA. Potential species-specific peptide biomarkers were screened. Twenty-one species-specific peptide biomarkers, belonging to eight different proteins (nickel-ABC transporter, N-acetylmuramoyl-L-alanine amidase, autolysin, clumping factor A, gram-positive signal peptide YSIRK, cysteine protease/staphopain, transcriptional regulator MarR, and transcriptional regulator Sar-A), were proposed to identify S. aureus. These results constitute the first major dataset of peptides and proteins of foodborne S. aureus strains. This repository may be useful for further studies, for the development of new therapeutic treatments for S. aureus food intoxications and for microbial source-tracking in foodstuffs. PMID:29312172

  16. Crowdsourcing Disease Biomarker Discovery Research: The IP4IC Study.

    Science.gov (United States)

    Chancellor, Michael B; Bartolone, Sarah N; Veerecke, Andrew; Lamb, Laura E

    2018-05-01

    Biomarker discovery is limited by readily assessable, cost efficient human samples available in large numbers that represent the entire heterogeneity of the disease. We developed a novel, active participation crowdsourcing method to determine BP-RS (Bladder Permeability Defect Risk Score). It is based on noninvasive urinary cytokines to discriminate patients with interstitial cystitis/bladder pain syndrome who had Hunner lesions from controls and patients with interstitial cystitis/bladder pain syndrome but without Hunner lesions. We performed a national crowdsourcing study in cooperation with the Interstitial Cystitis Association. Patients answered demographic, symptom severity and urinary frequency questionnaires on a HIPAA (Health Insurance Portability and Accountability Act) compliant website. Urine samples were collected at home, stabilized with a preservative and sent to Beaumont Hospital for analysis. The expression of 3 urinary cytokines was used in a machine learning algorithm to develop BP-RS. The IP4IC study collected a total of 448 urine samples, representing 153 patients (147 females and 6 males) with interstitial cystitis/bladder pain syndrome, of whom 54 (50 females and 4 males) had Hunner lesions. A total of 159 female and 136 male controls also participated, who were age matched. A defined BP-RS was calculated to predict interstitial cystitis/bladder pain syndrome with Hunner lesions or a bladder permeability defect etiology with 89% validity. In this novel participation crowdsourcing study we obtained a large number of urine samples from 46 states, which were collected at home, shipped and stored at room temperature. Using a machine learning algorithm we developed BP-RS to quantify the risk of interstitial cystitis/bladder pain syndrome with Hunner lesions, which is indicative of a bladder permeability defect etiology. To our knowledge BP-RS is the first validated urine biomarker assay for interstitial cystitis/bladder pain syndrome and one of the

  17. A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma

    Science.gov (United States)

    Ueda, Koji; Saichi, Naomi; Takami, Sachiko; Kang, Daechun; Toyama, Atsuhiko; Daigo, Yataro; Ishikawa, Nobuhisa; Kohno, Nobuoki; Tamura, Kenji; Shuin, Taro; Nakayama, Masato; Sato, Taka-Aki; Nakamura, Yusuke; Nakagawa, Hidewaki

    2011-01-01

    The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens. PMID:21533267

  18. Strategies, models and biomarkers in experimental non-alcoholic fatty liver disease research

    Science.gov (United States)

    Willebrords, Joost; Pereira, Isabel Veloso Alves; Maes, Michaël; Yanguas, Sara Crespo; Colle, Isabelle; Van Den Bossche, Bert; Da silva, Tereza Cristina; Oliveira, Cláudia P; Andraus, Wellington; Alves, Venâncio Avancini Ferreira; Cogliati, Bruno; Vinken, Mathieu

    2015-01-01

    Non-alcoholic fatty liver disease encompasses a spectrum of liver diseases, including simple steatosis, steatohepatitis, liver fibrosis and cirrhosis and hepatocellular carcinoma. Non-alcoholic fatty liver disease is currently the most dominant chronic liver disease in Western countries due to the fact that hepatic steatosis is associated with insulin resistance, type 2 diabetes mellitus, obesity, metabolic syndrome and drug-induced injury. A variety of chemicals, mainly drugs, and diets is known to cause hepatic steatosis in humans and rodents. Experimental non-alcoholic fatty liver disease models rely on the application of a diet or the administration of drugs to laboratory animals or the exposure of hepatic cell lines to these drugs. More recently, genetically modified rodents or zebrafish have been introduced as non-alcoholic fatty liver disease models. Considerable interest now lies in the discovery and development of novel non-invasive biomarkers of non-alcoholic fatty liver disease, with specific focus on hepatic steatosis. Experimental diagnostic biomarkers of non-alcoholic fatty liver disease, such as (epi)genetic parameters and ‘-omics’-based read-outs are still in their infancy, but show great promise. . In this paper, the array of tools and models for the study of liver steatosis is discussed. Furthermore, the current state-of-art regarding experimental biomarkers such as epigenetic, genetic, transcriptomic, proteomic and metabonomic biomarkers will be reviewed. PMID:26073454

  19. Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.

    Directory of Open Access Journals (Sweden)

    Paul R West

    Full Text Available The diagnosis of autism spectrum disorder (ASD at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age.To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment.Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD.A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set.This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1 determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2 gaining new insight into the biochemical mechanisms of various subtypes of ASD 3 identifying biomolecular targets for new modes of therapy, and 4 providing the basis for individualized treatment recommendations.

  20. Metabolomics as a Tool for Discovery of Biomarkers of Autism Spectrum Disorder in the Blood Plasma of Children

    Science.gov (United States)

    West, Paul R.; Amaral, David G.; Bais, Preeti; Smith, Alan M.; Egnash, Laura A.; Ross, Mark E.; Palmer, Jessica A.; Fontaine, Burr R.; Conard, Kevin R.; Corbett, Blythe A.; Cezar, Gabriela G.; Donley, Elizabeth L. R.; Burrier, Robert E.

    2014-01-01

    Background The diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age. Objectives To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment. Methods Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD. Results A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set. Conclusions This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1) determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2) gaining new insight into the biochemical mechanisms of various subtypes of ASD 3) identifying biomolecular targets for new modes of therapy, and 4) providing the basis for individualized treatment

  1. Tear film proteome in age-related macular degeneration.

    Science.gov (United States)

    Winiarczyk, Mateusz; Kaarniranta, Kai; Winiarczyk, Stanisław; Adaszek, Łukasz; Winiarczyk, Dagmara; Mackiewicz, Jerzy

    2018-06-01

    Age-related macular degeneration (AMD) is the main reason for blindness in elderly people in the developed countries. Current screening protocols have limitations in detecting the early signs of retinal degeneration. Therefore, it would be desirable to find novel biomarkers for early detection of AMD. Development of novel biomarkers would help in the prevention, diagnostics, and treatment of AMD. Proteomic analysis of tear film has shown promise in this research area. If an optimal set of biomarkers could be obtained from accessible body fluids, it would represent a reliable way to monitor disease progression and response to novel therapies. Tear films were collected on Schirmer strips from a total of 22 patients (8 with wet AMD, 6 with dry AMD, and 8 control individuals). 2D electrophoresis was used to separate tear film proteins prior to their identification with matrix-assisted laser desorption/ionization time of flight spectrometer (MALDI-TOF/TOF) and matching with functional databases. A total of 342 proteins were identified. Most of them were previously described in various proteomic studies concerning AMD. Shootin-1, histatin-3, fidgetin-like protein 1, SRC kinase signaling inhibitor, Graves disease carrier protein, actin cytoplasmic 1, prolactin-inducible protein 1, and protein S100-A7A were upregulated in the tear film samples isolated from AMD patients and were not previously linked with this disease in any proteomic analysis. The upregulated proteins supplement our current knowledge of AMD pathogenesis, providing evidence that certain specific proteins are expressed into the tear film in AMD. As far we are aware, this is the first study to have undertaken a comprehensive in-depth analysis of the human tear film proteome in AMD patients.

  2. Positional proteomics in the era of the human proteome project on the doorstep of precision medicine.

    Science.gov (United States)

    Eckhard, Ulrich; Marino, Giada; Butler, Georgina S; Overall, Christopher M

    2016-03-01

    Proteolytic processing is a pervasive and irreversible post-translational modification that expands the protein universe by generating new proteoforms (protein isoforms). Unlike signal peptide or prodomain removal, protease-generated proteoforms can rarely be predicted from gene sequences. Positional proteomic techniques that enrich for N- or C-terminal peptides from proteomes are indispensable for a comprehensive understanding of a protein's function in biological environments since protease cleavage frequently results in altered protein activity and localization. Proteases often process other proteases and protease inhibitors which perturbs proteolytic networks and potentiates the initial cleavage event to affect other molecular networks and cellular processes in physiological and pathological conditions. This review is aimed at researchers with a keen interest in state of the art systems level positional proteomic approaches that: (i) enable the study of complex protease-protease, protease-inhibitor and protease-substrate crosstalk and networks; (ii) allow the identification of proteolytic signatures as candidate disease biomarkers; and (iii) are expected to fill the Human Proteome Project missing proteins gap. We predict that these methodologies will be an integral part of emerging precision medicine initiatives that aim to customize healthcare, converting reactive medicine into a personalized and proactive approach, improving clinical care and maximizing patient health and wellbeing, while decreasing health costs by eliminating ineffective therapies, trial-and-error prescribing, and adverse drug effects. Such initiatives require quantitative and functional proteome profiling and dynamic disease biomarkers in addition to current pharmacogenomics approaches. With proteases at the pathogenic center of many diseases, high-throughput protein termini identification techniques such as TAILS (Terminal Amine Isotopic Labeling of Substrates) and COFRADIC (COmbined

  3. The Emerging Role of Proteomics in Precision Medicine: Applications in Neurodegenerative Diseases and Neurotrauma.

    Science.gov (United States)

    Alaaeddine, Rana; Fayad, Mira; Nehme, Eliana; Bahmad, Hisham F; Kobeissy, Firas

    2017-01-01

    Inter-individual variability in response to pharmacotherapy has provoked a higher demand to personalize medical decisions. As the field of pharmacogenomics has served to translate personalized medicine from concept to practice, the contribution of the "omics" disciplines to the era of precision medicine seems to be vital in improving therapeutic outcomes. Although we have observed significant advances in the field of genomics towards personalized medicine , the field of proteomics-with all its capabilities- is still in its infancy towards the area of personalized precision medicine. Neurodegenerative diseases and neurotrauma are among the areas where the implementation of neuroproteomics approaches has enabled neuroscientists to broaden their understanding of neural disease mechanisms and characteristics. It has been shown that the influence of epigenetics, genetics and environmental factors were among the recognized factors contributing to the diverse presentation of a single disease as well as its treatment establishing the factor-disease interaction. Thus, management of these variable single disease presentation/outcome necessitated the need for factoring the influence of epigenetics, genetics, epigenetics, and other factors on disease progression to create a custom treatment plan unique to each individual. In fact, neuroproteomics with its high ability to decipher protein alterations along with their post translational modifications (PTMs) can be an ideal tool for personalized medicine goals including: discovery of molecular mechanisms underlying disease pathobiology, development of novel diagnostics, enhancement of pharmacological neurotherapeutic approaches and finally, providing a "proteome identity" for patients with certain disorders and diseases. So far, neuroproteomics approaches have excelled in the areas of biomarker discovery arena where several diagnostic, prognostic and injury markers have been identified with a direct impact on the

  4. Biomarkers in rheumatic diseases: how can they facilitate diagnosis and assessment of disease activity?

    Science.gov (United States)

    Mohan, Chandra; Assassi, Shervin

    2015-11-26

    Serological and proteomic biomarkers can help clinicians diagnose rheumatic diseases earlier and assess disease activity more accurately. These markers have been incorporated into the recently revised classification criteria of several diseases to enable early diagnosis and timely initiation of treatment. Furthermore, they also facilitate more accurate subclassification and more focused monitoring for the detection of certain disease manifestations, such as lung and renal involvement. These biomarkers can also make the assessment of disease activity and treatment response more reliable. Simultaneously, several new serological and proteomic biomarkers have become available in the routine clinical setting--for example, a protein biomarker panel for rheumatoid arthritis and a myositis antibody panel for dermatomyositis and polymyositis. This review will focus on commercially available antibody and proteomic biomarkers in rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis (scleroderma), dermatomyositis and polymyositis, and axial spondyloarthritis (including ankylosing spondylitis). It will discuss how these markers can facilitate early diagnosis as well as more accurate subclassification and assessment of disease activity in the clinical setting. The ultimate goal of current and future biomarkers in rheumatic diseases is to enable early detection of these diseases and their clinical manifestations, and to provide effective monitoring and treatment regimens that are tailored to each patient's needs and prognosis. © BMJ Publishing Group Ltd 2015.

  5. Differential proteomics of human seminal plasma: A potential target for searching male infertility marker proteins.

    Science.gov (United States)

    Tomar, Anil Kumar; Sooch, Balwinder Singh; Singh, Sarman; Yadav, Savita

    2012-04-01

    The clinical fertility tests, available in the market, fail to define the exact cause of male infertility in almost half of the cases and point toward a crucial need of developing better ways of infertility investigations. The protein biomarkers may help us toward better understanding of unknown cases of male infertility that, in turn, can guide us to find better therapeutic solutions. Many clinical attempts have been made to identify biomarkers of male infertility in sperm proteome but only few studies have targeted seminal plasma. Human seminal plasma is a rich source of proteins that are essentially required for development of sperm and successful fertilization. This viewpoint article highlights the importance of human seminal plasma proteome in reproductive physiology and suggests that differential proteomics integrated with functional analysis may help us in searching potential biomarkers of male infertility. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Mathematical biodescriptors of proteomics maps: background and applications.

    Science.gov (United States)

    Basak, Subhash C; Gute, Brian D

    2008-05-01

    This article reviews recent developments in the formulation and application of biodescriptors to characterize proteomics maps. Such biodescriptors can be derived by applying techniques from discrete mathematics (graph theory, linear algebra and information theory). This review focuses on the development of biodescriptors for proteomics maps derived from 2D gel electrophoresis. Preliminary results demonstrated that such descriptors have a reasonable ability to differentiate between proteomics patterns that result from exposure to closely related individual chemicals and complex mixtures, such as the jet fuel JP-8. Further research is required to evaluate the utility of these proteomics-based biodescriptors for drug discovery and predictive toxicology.

  7. The application of cell cultures, body fluids and tissues in oncoproteomics

    Directory of Open Access Journals (Sweden)

    Kamila Duś-Szachniewicz

    2014-11-01

    Full Text Available Mass spectrometry (MS-based proteomics is a rapidly developing technology for the large scale analysis of proteins, their interactions and subcellular localization. In recent years proteomics has attracted much attention in medicine. Since a single biomarker might not have sufficient sensitivity and specificity in clinical practice, the identification of biomarker panels that comprise several proteins would improve the detection and clinical management of cancer patients. Additionally, the characteristics of protein profiles of most severe human malignancies certainly contribute to the understanding of the biology of cancer and fill the gap in our knowledge of carcinogenesis. This knowledge also is likely to result in the discovery of novel potential cancer markers and targets for molecular therapeutics. It is believed that the novel biomarkers will help in the development of personalized therapy tailored to the individual patient and will thereby reduce the mortality rate from cancer. In this review, the use of different types of human clinical samples (cell cultures, tissues and body fluids in oncoproteomics is explained and the latest advances in mass spectrometry-based proteomics biomarker discovery are discussed.

  8. Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

    Directory of Open Access Journals (Sweden)

    Hugo López-Fernández

    2016-05-01

    Full Text Available Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI, machine learning (ML, and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.

  9. Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

    International Nuclear Information System (INIS)

    Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M.; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan

    2016-01-01

    Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted

  10. Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

    Energy Technology Data Exchange (ETDEWEB)

    Kulkarni, Shilpa [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Koller, Antonius [Proteomics Center, Stony Brook University School of Medicine, Stony Brook, New York (United States); Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York (United States); Mani, Kartik M. [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Wen, Ruofeng [Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York (United States); Alfieri, Alan; Saha, Subhrajit [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); Wang, Jian [Center for Computational Mass Spectrometry, University of California, San Diego, California (United States); Department of Computer Science and Engineering, University of California, San Diego, California (United States); Patel, Purvi [Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York (United States); Department of Pharmacological Sciences, Stony Brook University, Stony Brook, New York (United States); Bandeira, Nuno [Center for Computational Mass Spectrometry, University of California, San Diego, California (United States); Department of Computer Science and Engineering, University of California, San Diego, California (United States); Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, California (United States); Guha, Chandan, E-mail: cguha@montefiore.org [Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, New York (United States); and others

    2016-11-01

    Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted

  11. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates

    Directory of Open Access Journals (Sweden)

    Łukasz Pietrzyk

    2016-01-01

    Full Text Available Colorectal cancer (CRC is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.

  12. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates.

    Science.gov (United States)

    Pietrzyk, Łukasz

    2016-01-01

    Colorectal cancer (CRC) is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs) are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.

  13. Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage.

    Science.gov (United States)

    Van, Phu T; Schmid, Amy K; King, Nichole L; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T; Goo, Young Ah; Deutsch, Eric W; Reiss, David J; Mallick, Parag; Baliga, Nitin S

    2008-09-01

    The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.

  14. How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology.

    Science.gov (United States)

    Ganau, Mario; Paris, Marco; Syrmos, Nikolaos; Ganau, Laura; Ligarotti, Gianfranco K I; Moghaddamjou, Ali; Prisco, Lara; Ambu, Rossano; Chibbaro, Salvatore

    2018-02-26

    The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1) the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2) a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3) the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

  15. How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1 the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2 a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3 the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

  16. A Hybrid Feature Subset Selection Algorithm for Analysis of High Correlation Proteomic Data

    Science.gov (United States)

    Kordy, Hussain Montazery; Baygi, Mohammad Hossein Miran; Moradi, Mohammad Hassan

    2012-01-01

    Pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. The surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) has been used to generate proteomic profiles from biological fluids. Mass spectrometry yields redundant noisy data that the most data points are irrelevant features for differentiating between cancer and normal cases. In this paper, we have proposed a hybrid feature subset selection algorithm based on maximum-discrimination and minimum-correlation coupled with peak scoring criteria. Our algorithm has been applied to two independent SELDI-TOF MS datasets of ovarian cancer obtained from the NCI-FDA clinical proteomics databank. The proposed algorithm has used to extract a set of proteins as potential biomarkers in each dataset. We applied the linear discriminate analysis to identify the important biomarkers. The selected biomarkers have been able to successfully diagnose the ovarian cancer patients from the noncancer control group with an accuracy of 100%, a sensitivity of 100%, and a specificity of 100% in the two datasets. The hybrid algorithm has the advantage that increases reproducibility of selected biomarkers and able to find a small set of proteins with high discrimination power. PMID:23717808

  17. Meeting Report--NASA Radiation Biomarker Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Straume, Tore; Amundson, Sally A,; Blakely, William F.; Burns, Frederic J.; Chen, Allen; Dainiak, Nicholas; Franklin, Stephen; Leary, Julie A.; Loftus, David J.; Morgan, William F.; Pellmar, Terry C.; Stolc, Viktor; Turteltaub, Kenneth W.; Vaughan, Andrew T.; Vijayakumar, Srinivasan; Wyrobek, Andrew J.

    2008-05-01

    A summary is provided of presentations and discussions from the NASA Radiation Biomarker Workshop held September 27-28, 2007, at NASA Ames Research Center in Mountain View, California. Invited speakers were distinguished scientists representing key sectors of the radiation research community. Speakers addressed recent developments in the biomarker and biotechnology fields that may provide new opportunities for health-related assessment of radiation-exposed individuals, including for long-duration space travel. Topics discussed include the space radiation environment, biomarkers of radiation sensitivity and individual susceptibility, molecular signatures of low-dose responses, multivariate analysis of gene expression, biomarkers in biodefense, biomarkers in radiation oncology, biomarkers and triage following large-scale radiological incidents, integrated and multiple biomarker approaches, advances in whole-genome tiling arrays, advances in mass-spectrometry proteomics, radiation biodosimetry for estimation of cancer risk in a rat skin model, and confounding factors. Summary conclusions are provided at the end of the report.

  18. Identification and characterization of angiogenesis targets through proteomic profiling of endothelial cells in human cancer tissues.

    Directory of Open Access Journals (Sweden)

    Mehdi Mesri

    Full Text Available Genomic and proteomic analysis of normal and cancer tissues has yielded abundant molecular information for potential biomarker and therapeutic targets. Considering potential advantages in accessibility to pharmacological intervention, identification of targets resident on the vascular endothelium within tumors is particularly attractive. By employing mass spectrometry (MS as a tool to identify proteins that are over-expressed in tumor-associated endothelium relative to normal cells, we aimed to discover targets that could be utilized in tumor angiogenesis cancer therapy. We developed proteomic methods that allowed us to focus our studies on the discovery of cell surface/secreted proteins, as they represent key antibody therapeutic and biomarker opportunities. First, we isolated endothelial cells (ECs from human normal and kidney cancer tissues by FACS using CD146 as a marker. Additionally, dispersed human colon and lung cancer tissues and their corresponding normal tissues were cultured ex-vivo and their endothelial content were preferentially expanded, isolated and passaged. Cell surface proteins were then preferentially captured, digested with trypsin and subjected to MS-based proteomic analysis. Peptides were first quantified, and then the sequences of differentially expressed peptides were resolved by MS analysis. A total of 127 unique non-overlapped (157 total tumor endothelial cell over-expressed proteins identified from directly isolated kidney-associated ECs and those identified from ex-vivo cultured lung and colon tissues including known EC markers such as CD146, CD31, and VWF. The expression analyses of a panel of the identified targets were confirmed by immunohistochemistry (IHC including CD146, B7H3, Thy-1 and ATP1B3. To determine if the proteins identified mediate any functional role, we performed siRNA studies which led to previously unidentified functional dependency for B7H3 and ATP1B3.

  19. Proteomics of anti-cancer drugs

    Czech Academy of Sciences Publication Activity Database

    Kovářová, Hana; Martinková, Jiřina; Hrabáková, Rita; Skalníková, Helena; Novák, Petr; Hajdůch, M.; Gadher, S. J.

    2009-01-01

    Roč. 276, Supplement 1 (2009), s. 84-84 E-ISSN 1742-4658. [34th FEBS Congress. 04.07.2009-09.07.2009, Praha] R&D Projects: GA MŠk LC07017 Institutional research plan: CEZ:AV0Z50450515; CEZ:AV0Z50200510 Keywords : proteomics * anti-cancer drugs * biomarkers Subject RIV: FD - Oncology ; Hematology

  20. Custom database development and biomarker discovery methods for MALDI-TOF mass spectrometry-based identification of high-consequence bacterial pathogens.

    Science.gov (United States)

    Tracz, Dobryan M; Tyler, Andrea D; Cunningham, Ian; Antonation, Kym S; Corbett, Cindi R

    2017-03-01

    A high-quality custom database of MALDI-TOF mass spectral profiles was developed with the goal of improving clinical diagnostic identification of high-consequence bacterial pathogens. A biomarker discovery method is presented for identifying and evaluating MALDI-TOF MS spectra to potentially differentiate biothreat bacteria from less-pathogenic near-neighbour species. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  1. Analysis of membrane proteome by data-dependent LC-MS/MS combined with data-independent LC-MSE technique

    Directory of Open Access Journals (Sweden)

    Joseph Kwon

    2010-03-01

    Full Text Available Proteomics work resembles the search for a needle in a haystack. The identification of protein biomarker requires the removal of the false protein data from the whole protein mixture. For high quality proteomic data, even a strict filtration step using the false discovery rate (FDR is insufficient for obtaining perfect protein information from the biological samples. In this study, the cyanobacterial whole membrane fraction was applied to the data-dependent analysis (DDA mode of LC-MS/MS, which was used along with the data-independent LC-MSE technique in order to evaluate the membrane proteomic data. Furthermore, the identified MSE-information (MSE-i data based on the peptide mass and the retention time were validated by the other database search, i.e., the probability-based MASCOT and de novo search engine PEAKS. In this present study, 208 cyanobacterial proteins with FDR of 5% were identified using the data-independent nano-UPLC/MSE acquisition with the Protein Lynx Global Server (PLGS, and 56 of these proteins were the predicted membrane proteins. When a total of 208 MSE-i proteomic data were applied to the DDA mode of LC-MS/MS, the number of identified membrane proteins was 26 and 33 from MASCOT and PEAKS with a FDR of 5%, respectively. The number of totally overlapped membrane proteins was 25. Therefore, the data-independent LC-MSE identified more proteins with a high confidence.

  2. Environmental monitoring of Domingo Rubio stream (Huelva Estuary, SW Spain) by combining conventional biomarkers and proteomic analysis in Carcinus maenas

    Energy Technology Data Exchange (ETDEWEB)

    Montes Nieto, Rafael [Department of Biochemistry and Molecular Biology, University of Cordoba, Severo Ochoa Building, Rabanales Campus, Highway A4 Km 396a, 14071 Cordoba (Spain); Garcia-Barrera, Tamara; Gomez-Ariza, Jose-Luis [Department of Chemistry and Materials Sciences, University of Huelva, Faculty of Experimental Sciences, El Carmen Campus, 21007 Huelva (Spain); Lopez-Barea, Juan, E-mail: bb1lobaj@uco.e [Department of Biochemistry and Molecular Biology, University of Cordoba, Severo Ochoa Building, Rabanales Campus, Highway A4 Km 396a, 14071 Cordoba (Spain)

    2010-02-15

    Element load, conventional biomarkers and altered protein expression profiles were studied in Carcinus maenas crabs, to assess contamination of 'Domingo Rubio' stream, an aquatic ecosystem that receives pyritic metals, industrial contaminants, and pesticides. Lower antioxidative activities - glucose-6-phosphate and 6-phosphogluconate dehydrogenases, catalase - were found in parallel to higher levels of damaged biomolecules - malondialdehyde, oxidized glutathione -, due to oxidative lesions promoted by contaminants, as the increased levels of essential - Zn, Cu, Co - and nonessential - Cr, Ni, Cd - elements. Utility of Proteomics to assess environmental quality was confirmed, especially after considering the six proteins identified by de novo sequencing through capLC-muESI-ITMS/MS and homology search on databases. They include tripartite motif-containing protein 11 and ATF7 transcription factor (upregulated), plus CBR-NHR-218 nuclear hormone receptor, two components of the ABC transporters and aldehyde dehydrogenase (downregulated). These proteins could be used as novel potential biomarkers of the deleterious effects of pollutants present in the area. - Pollution assessment at 'Domingo Rubio' stream (Spain).

  3. Urinary Biomarkers of Brain Diseases

    Directory of Open Access Journals (Sweden)

    Manxia An

    2015-12-01

    Full Text Available Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome.

  4. New biomarkers for sepsis

    Directory of Open Access Journals (Sweden)

    Li-xin XIE

    2013-01-01

    Full Text Available There is a higher sepsis rate in the intensive care unit (ICU patients, which is one of the most important causes for patient death, but the sepsis lacks specific clinical manifestations. Exploring sensitive and specific molecular markers for infection that accurately reflect infection severity and prognosis is very clinically important. In this article, based on our previous study, we introduce some new biomarkers with high sensitivity and specificity for the diagnosis and predicting the prognosis and severity of sepsis. Increase of serum soluble(s triggering receptor expressed on myeloid cells-1 (sTREM-1 suggests a poor prognosis of septic patients, and changes of locus rs2234237 of sTREM-1 may be the one of important mechanisms. Additionally, urine sTREM-1 can provide an early warning of possible secondary acute kidney injury (AKI in sepsis patients. Serum sCD163 level was found to be a more important factor than procalcitonin (PCT and C-reactive protein (CRP in prognosis of sepsis, especially severe sepsis. Moreover, urine sCD163 also shows excellent performance in the diagnosis of sepsis and sepsis-associated AKI. Circulating microRNAs, such as miR-150, miR-297, miR-574-5p, miR -146a , miR-223, miR -15a and miR-16, also play important roles in the evaluation of status of septic patients. In the foreseeable future, newly-emerging technologies, including proteomics, metabonomics and trans-omics, may exert profound effects on the discovery of valuable biomarkers for sepsis.

  5. Integrated multi-level quality control for proteomic profiling studies using mass spectrometry

    Directory of Open Access Journals (Sweden)

    Barrett Jennifer H

    2008-12-01

    Full Text Available Abstract Background Proteomic profiling using mass spectrometry (MS is one of the most promising methods for the analysis of complex biological samples such as urine, serum and tissue for biomarker discovery. Such experiments are often conducted using MALDI-TOF (matrix-assisted laser desorption/ionisation time-of-flight and SELDI-TOF (surface-enhanced laser desorption/ionisation time-of-flight MS. Using such profiling methods it is possible to identify changes in protein expression that differentiate disease states and individual proteins or patterns that may be useful as potential biomarkers. However, the incorporation of quality control (QC processes that allow the identification of low quality spectra reliably and hence allow the removal of such data before further analysis is often overlooked. In this paper we describe rigorous methods for the assessment of quality of spectral data. These procedures are presented in a user-friendly, web-based program. The data obtained post-QC is then examined using variance components analysis to quantify the amount of variance due to some of the factors in the experimental design. Results Using data from a SELDI profiling study of serum from patients with different levels of renal function, we show how the algorithms described in this paper may be used to detect systematic variability within and between sample replicates, pooled samples and SELDI chips and spots. Manual inspection of those spectral data that were identified as being of poor quality confirmed the efficacy of the algorithms. Variance components analysis demonstrated the relatively small amount of technical variance attributable to day of profile generation and experimental array. Conclusion Using the techniques described in this paper it is possible to reliably detect poor quality data within proteomic profiling experiments undertaken by MS. The removal of these spectra at the initial stages of the analysis substantially improves the

  6. Nutrition and biomarkers in psychiatry : research on micronutrient deficiencies in schizophrenia, the role of the intestine in the hyperserotonemia of autism, and a method for non-hypothesis driven discovery of biomarkers in urine

    NARCIS (Netherlands)

    Kemperman, Ramses Franciscus Jacobus

    2007-01-01

    This thesis describes the study of markers of nutrition and intestinal motility in mental disorders with a focus on schizophrenia and autism, and the development, evaluation and application of a biomarker discovery method for urine. The aim of the thesis is to investigate the role of long-chain

  7. Discovery and annotation of small proteins using genomics, proteomics and computational approaches

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Xiaohan; Tschaplinski, Timothy J.; Hurst, Gregory B.; Jawdy, Sara; Abraham, Paul E.; Lankford, Patricia K.; Adams, Rachel M.; Shah, Manesh B.; Hettich, Robert L.; Lindquist, Erika; Kalluri, Udaya C.; Gunter, Lee E.; Pennacchio, Christa; Tuskan, Gerald A.

    2011-03-02

    Small proteins (10 200 amino acids aa in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained 2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts from the EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10 200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) codingpotential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene family clustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were new to the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.

  8. From the endometrium physiology to a comprehensive strategy for the discovery of ovarian cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Janos L. Tanyi

    2011-12-01

    Full Text Available The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and peritoneum via endometrial secretions, and thus endometrium neighboring structures may have developed highly efficient protective strategies that could, in turn, be hijacked by cancer cells for survival and invasion. After literature review, we could classify the molecules involved in ovulation and menstruation pathways in three main categories: proteases, proteases inhibitors and cell-surface protectors. Strikingly, all validated biomarkers for ovarian cancers belong to at least one of these categories. We thus propose the development of comprehensive methods for identification of early diagnostic markers for gynecological cancers using systematical mapping and characterization of surface or soluble molecules belonging to physiological pathways linked to menstruation and differently expressed during luteal cycles.

  9. Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

    Science.gov (United States)

    Shukla, Hem D

    2017-10-25

    During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics

  10. Skeletal muscle proteomics: current approaches, technical challenges and emerging techniques

    LENUS (Irish Health Repository)

    Ohlendieck, Kay

    2011-02-01

    Abstract Background Skeletal muscle fibres represent one of the most abundant cell types in mammals. Their highly specialised contractile and metabolic functions depend on a large number of membrane-associated proteins with very high molecular masses, proteins with extensive posttranslational modifications and components that exist in highly complex supramolecular structures. This makes it extremely difficult to perform conventional biochemical studies of potential changes in protein clusters during physiological adaptations or pathological processes. Results Skeletal muscle proteomics attempts to establish the global identification and biochemical characterisation of all members of the muscle-associated protein complement. A considerable number of proteomic studies have employed large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography, and combined them with mass spectrometry as the method of choice for high-throughput protein identification. Muscle proteomics has been applied to the comprehensive biochemical profiling of developing, maturing and aging muscle, as well as the analysis of contractile tissues undergoing physiological adaptations seen in disuse atrophy, physical exercise and chronic muscle transformation. Biomedical investigations into proteome-wide alterations in skeletal muscle tissues were also used to establish novel biomarker signatures of neuromuscular disorders. Importantly, mass spectrometric studies have confirmed the enormous complexity of posttranslational modifications in skeletal muscle proteins. Conclusions This review critically examines the scientific impact of modern muscle proteomics and discusses its successful application for a better understanding of muscle biology, but also outlines its technical limitations and emerging techniques to establish new biomarker candidates.

  11. Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

    Science.gov (United States)

    Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva

    2017-01-01

    No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as

  12. Association of SNCA with Parkinson: replication in the Harvard NeuroDiscovery Center Biomarker Study

    Science.gov (United States)

    Ding, Hongliu; Sarokhan, Alison K.; Roderick, Sarah S.; Bakshi, Rachit; Maher, Nancy E.; Ashourian, Paymon; Kan, Caroline G.; Chang, Sunny; Santarlasci, Andrea; Swords, Kyleen E.; Ravina, Bernard M.; Hayes, Michael T.; Sohur, U. Shivraj; Wills, Anne-Marie; Flaherty, Alice W.; Unni, Vivek K.; Hung, Albert Y.; Selkoe, Dennis J.; Schwarzschild, Michael A.; Schlossmacher, Michael G.; Sudarsky, Lewis R.; Growdon, John H.; Ivinson, Adrian J.; Hyman, Bradley T.; Scherzer, Clemens R.

    2011-01-01

    Background Mutations in the α-synuclein gene (SNCA) cause autosomal dominant forms of Parkinson’s disease, but the substantial risk conferred by this locus to the common sporadic disease has only recently emerged from genome-wide association studies. Methods Here we genotyped a prioritized non-coding variant in SNCA intron-4 in 344 patients with Parkinson’s and 275 controls from the longitudinal Harvard NeuroDiscovery Center Biomarker Study. Results The common minor allele of rs2736990 was associated with elevated disease susceptibility (odds ratio = 1.40, P value = 0.0032). Conclusions This result increases confidence in the notion that in many clinically well-characterized patients genetic variation in SNCA contributes to “sporadic” disease. PMID:21953863

  13. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder.

    Science.gov (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

    2015-08-01

    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Salivary proteomic and genomic biomarkers for primary Sjogren's syndrome

    NARCIS (Netherlands)

    Hu, Shen; Wang, Jianghua; Leong, Sonya; Xie, Yongming; Yu, Tianwei; Zhou, Hui; Henry, Sharon; Vissink, Arjan; Pijpe, Justin; Kallenberg, Cees; Elashoff, David; Loo, Joseph A.; Wong, David T.

    2007-01-01

    Objective. To identify a panel of protein and messenger RNA (mRNA) biomarkers in human whole saliva (WS) that may be used in the detection of primary Sjogren's syndrome (SS). Methods. Mass spectrometry and expression microarray profiling were used to identify candidate protein and mRNA, biomarkers

  15. Salivary proteomic and genomic biomarkers for primary Sjogren's syndrome

    NARCIS (Netherlands)

    Hu, Shen; Wang, Jianghua; Leong, Sonya; Xie, Yongming; Yu, Tianwei; Zhou, Hui; Henry, Sharon; Vissink, Arjan; Pijpe, Justin; Kallenberg, Cees; Elashoff, David; Loo, Joseph A.; Wong, David T.

    Objective. To identify a panel of protein and messenger RNA (mRNA) biomarkers in human whole saliva (WS) that may be used in the detection of primary Sjogren's syndrome (SS). Methods. Mass spectrometry and expression microarray profiling were used to identify candidate protein and mRNA, biomarkers

  16. Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

    Science.gov (United States)

    Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

    2017-03-01

    Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing

  17. Serum proteomic changes after randomized prolonged erythropoietin treatment and/or endurance training: detection of novel biomarkers.

    Directory of Open Access Journals (Sweden)

    Britt Christensen

    Full Text Available Despite implementation of the biological passport to detect erythropoietin abuse, a need for additional biomarkers remains. We used a proteomic approach to identify novel serum biomarkers of prolonged erythropoiesis-stimulating agent (ESA exposure (Darbepoietin-α and/or aerobic training.Thirty-six healthy young males were randomly assigned to the following groups: Sedentary-placebo (n = 9, Sedentary-ESA (n = 9, Training-placebo (n = 10, or Training-ESA (n = 8. They were treated with placebo/Darbepoietin-α subcutaneously once/week for 10 weeks followed by a 3-week washout period. Training consisted of supervised biking 3/week for 13 weeks at the highest possible intensity. Serum was collected at baseline, week 3 (high dose Darbepoietin-α, week 10 (reduced dose Darbepoietin-α, and after a 3-week washout period.Serum proteins were separated according to charge and molecular mass (2D-gel electrophoresis. The identity of proteins from spots exhibiting altered intensity was determined by mass spectrometry.Six protein spots changed in response to Darbepoietin-α treatment. Comparing all 4 experimental groups, two protein spots (serotransferrin and haptoglobin/haptoglobin related protein showed a significant response to Darbepoietin-α treatment. The haptoglobin/haptoglobin related protein spot showed a significantly lower intensity in all subjects in the training-ESA group during the treatment period and increased during the washout period.An isoform of haptoglobin/haptoglobin related protein could be a new anti-doping marker and merits further research.ClinicalTrials.gov NCT01320449.

  18. Engineered gold nanoparticles for identification of novel ovarian biomarkers

    Science.gov (United States)

    Giri, Karuna

    Ovarian cancer is a leading cause of cancer related death among women in the US and worldwide. The disease has a high mortality rate due to limited tools available that can diagnose ovarian cancer at an early stage and the lack of effective treatments for disease free survival at late stages. Identification of proteins specifically expressed/overexpressed in ovarian cancer could lead to identification of novel diagnostic biomarkers and therapeutic targets that improve patient outcomes. In this regard, mass spectrometry is a powerful tool to probe the proteome of a cancer cell. It can aid discovery of proteins important for the pathophysiology of ovarian cancer. These proteins in turn could serve as diagnostic and treatment biomarkers of the disease. However, a limitation of mass spectrometry based proteomic analyses is that the technique lacks sensitivity and is biased against detection of low abundance proteins. With current approaches to biomarker discovery, we may therefore be overlooking candidate proteins that are important for ovarian cancer. This study presents a new approach to enrich low abundance proteins and subsequently detect them with mass spectrometry. Gold nanoparticles (AuNPs) and functionalization of their surfaces provide an excellent opportunity to capture and enrich low abundance proteins. First, the study focused on conducting an extensive investigation of the time evolution of nanoparticle-protein interaction and understanding drivers of protein attachment on nanoparticle surface. The adsorption of proteins to AuNPs was found to be highly dynamic with multiple attachment and detachment events which decreased over time. Initially, electrostatic forces played an important role in protein binding and structurally flexible proteins such as those involved in RNA processing were more likely to bind to AuNPs. More importantly, the feasibility and success of protein enrichment by AuNPs was evaluated. The AuNPs based approach was able to detect

  19. The Landscape of Protein Biomarkers Proposed for Periodontal Disease: Markers with Functional Meaning

    Directory of Open Access Journals (Sweden)

    Nuno Rosa

    2014-01-01

    Full Text Available Periodontal disease (PD is characterized by a deregulated inflammatory response which fails to resolve, activating bone resorption. The identification of the proteomes associated with PD has fuelled biomarker proposals; nevertheless, many questions remain. Biomarker selection should favour molecules representing an event which occurs throughout the disease progress. The analysis of proteome results and the information available for each protein, including its functional role, was accomplished using the OralOme database. The integrated analysis of this information ascertains if the suggested proteins reflect the cell and/or molecular mechanisms underlying the different forms of periodontal disease. The evaluation of the proteins present/absent or with very different concentrations in the proteome of each disease state was used for the identification of the mechanisms shared by different PD variants or specific to such state. The information presented is relevant for the adequate design of biomarker panels for PD. Furthermore, it will open new perspectives and help envisage future studies targeted to unveil the functional role of specific proteins and help clarify the deregulation process in the PD inflammatory response.

  20. Toxicoproteomics: serum proteomic pattern diagnostics for early detection of drug induced cardiac toxicities and cardioprotection.

    Science.gov (United States)

    Petricoin, Emanuel F; Rajapaske, Vinodh; Herman, Eugene H; Arekani, Ali M; Ross, Sally; Johann, Donald; Knapton, Alan; Zhang, J; Hitt, Ben A; Conrads, Thomas P; Veenstra, Timothy D; Liotta, Lance A; Sistare, Frank D

    2004-01-01

    Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry which communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity based processes as cascades of reinforcing information percolate through the system and become reflected in changing proteomic information content of the circulation. Serum Proteomic Pattern Diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. While this approach has shown tremendous promise in early detection of cancers, detection of drug-induced toxicity may also be possible with this same technology. Analysis of serum from rat models of anthracycline and anthracenedione induced cardiotoxicity indicate the potential clinical utility of diagnostic proteomic patterns where low molecular weight peptides and protein fragments may have higher accuracy than traditional biomarkers of cardiotoxicity such as troponins. These fragments may one day be harvested by circulating nanoparticles designed to absorb, enrich and amplify the diagnostic biomarker repertoire generated even at the critical initial stages of toxicity.

  1. Differential proteomic profiling of primary and recurrent chordomas.

    Science.gov (United States)

    Chen, Su; Xu, Wei; Jiao, Jian; Jiang, Dongjie; Liu, Jian; Chen, Tenghui; Wan, Zongmiao; Xu, Leqin; Zhou, Zhenhua; Xiao, Jianru

    2015-05-01

    Chordomas are locally destructive tumors with high rates of recurrence and a poor prognosis. The mechanisms involved in chordoma recurrence remain largely unknown. In the present study, we examined the proteomic profile of a chordoma primary tumor (CSO) and a recurrent tumor (CSR) through mass spectrum in a chordoma patient who underwent surgery. Bioinformatic analysis of the profile showed that 359 proteins had a significant expression difference and 21 pathways had a striking alteration between the CSO and the CSR. The CSR showed a significant increase in carbohydrate metabolism. Immunohistochemistry (IHC) confirmed that the cancer stem cell marker activated leukocyte cell adhesion molecule (ALCAM or CD166) expression level was higher in the recurrent than that in the primary tumor. The present study analyzed the proteomic profile change between CSO and CSR and identified a new biomarker ALCAM in recurrent chordomas. This finding sheds light on unraveling the pathophysiology of chordoma recurrence and on exploring more effective prognostic biomarkers and targeted therapies against this devastating disease.

  2. Renal Cancer Biomarkers | NCI Technology Transfer Center | TTC

    Science.gov (United States)

    The National Cancer Institute's Laboratory of Proteomics and Analytical Technologies is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize diagnostic, therapeutic and prognostic cancer biomarkers from clinical specimens.

  3. Metabolic profiling of an Echinostoma caproni infection in the mouse for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jasmina Saric

    Full Text Available BACKGROUND: Metabolic profiling holds promise with regard to deepening our understanding of infection biology and disease states. The objectives of our study were to assess the global metabolic responses to an Echinostoma caproni infection in the mouse, and to compare the biomarkers extracted from different biofluids (plasma, stool, and urine in terms of characterizing acute and chronic stages of this intestinal fluke infection. METHODOLOGY/PRINCIPAL FINDINGS: Twelve female NMRI mice were infected with 30 E. caproni metacercariae each. Plasma, stool, and urine samples were collected at 7 time points up to day 33 post-infection. Samples were also obtained from non-infected control mice at the same time points and measured using (1H nuclear magnetic resonance (NMR spectroscopy. Spectral data were subjected to multivariate statistical analyses. In plasma and urine, an altered metabolic profile was already evident 1 day post-infection, characterized by reduced levels of plasma choline, acetate, formate, and lactate, coupled with increased levels of plasma glucose, and relatively lower concentrations of urinary creatine. The main changes in the urine metabolic profile started at day 8 post-infection, characterized by increased relative concentrations of trimethylamine and phenylacetylglycine and lower levels of 2-ketoisocaproate and showed differentiation over the course of the infection. CONCLUSION/SIGNIFICANCE: The current investigation is part of a broader NMR-based metabonomics profiling strategy and confirms the utility of this approach for biomarker discovery. In the case of E. caproni, a diagnosis based on all three biofluids would deliver the most comprehensive fingerprint of an infection. For practical purposes, however, future diagnosis might aim at a single biofluid, in which case urine would be chosen for further investigation, based on quantity of biomarkers, ease of sampling, and the degree of differentiation from the non

  4. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  5. atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

    Science.gov (United States)

    Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2012-07-20

    Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

  6. Comparative proteomics in alkaptonuria provides insights into inflammation and oxidative stress.

    Science.gov (United States)

    Braconi, Daniela; Bernardini, Giulia; Paffetti, Alessandro; Millucci, Lia; Geminiani, Michela; Laschi, Marcella; Frediani, Bruno; Marzocchi, Barbara; Santucci, Annalisa

    2016-12-01

    Alkaptonuria (AKU) is an ultra-rare inborn error of metabolism associated with a defective catabolism of phenylalanine and tyrosine leading to increased systemic levels of homogentisic acid (HGA). Excess HGA is partly excreted in the urine, partly accumulated within the body and deposited onto connective tissues under the form of an ochronotic pigment, leading to a range of clinical manifestations. No clear genotype/phenotype correlation was found in AKU, and today there is the urgent need to identify biomarkers able to monitor AKU progression and evaluate response to treatment. With this aim, we provided the first proteomic study on serum and plasma samples from alkaptonuric individuals showing pathological SAA, CRP and Advanced Oxidation Protein Products (AOPP) levels. Interesting similarities with proteomic studies on other rheumatic diseases were highlighted together with proteome alterations supporting the existence of oxidative stress and inflammation in AKU. Potential candidate biomarkers to assess disease severity, monitor disease progression and evaluate response to treatment were identified as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. The Use of Proteomics in Assisted Reproduction.

    Science.gov (United States)

    Kosteria, Ioanna; Anagnostopoulos, Athanasios K; Kanaka-Gantenbein, Christina; Chrousos, George P; Tsangaris, George T

    2017-01-01

    Despite the explosive increase in the use of Assisted Reproductive Technologies (ART) over the last 30 years, their success rates remain suboptimal. Proteomics is a rapidly-evolving technology-driven science that has already been widely applied in the exploration of human reproduction and fertility, providing useful insights into its physiology and leading to the identification of numerous proteins that may be potential biomarkers and/or treatment targets of a successful ART pregnancy. Here we present a brief overview of the techniques used in proteomic analyses and attempt a comprehensive presentation of recent data from mass spectrometry-based proteomic studies in humans, regarding all components of ARTs, including the male and female gamete, the derived zygote and embryo, the endometrium and, finally, the ART offspring both pre- and postnatally. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  8. Gel-based proteomics of liver cancer progression in rat

    DEFF Research Database (Denmark)

    Albrethsen, Jakob; Miller, Leah M; Novikoff, Phyllis M

    2011-01-01

    A significant challenge in proteomics biomarker research is to identify the changes that are of highest diagnostic interest, among the many unspecific aberrations associated with disease burden and inflammation. In the present study liver tissue specimens (n=18) from six experimental stages were ...

  9. Integration of cardiac proteome biology and medicine by a specialized knowledgebase.

    Science.gov (United States)

    Zong, Nobel C; Li, Haomin; Li, Hua; Lam, Maggie P Y; Jimenez, Rafael C; Kim, Christina S; Deng, Ning; Kim, Allen K; Choi, Jeong Ho; Zelaya, Ivette; Liem, David; Meyer, David; Odeberg, Jacob; Fang, Caiyun; Lu, Hao-Jie; Xu, Tao; Weiss, James; Duan, Huilong; Uhlen, Mathias; Yates, John R; Apweiler, Rolf; Ge, Junbo; Hermjakob, Henning; Ping, Peipei

    2013-10-12

    Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans, as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes.

  10. Characterization of individual mouse cerebrospinal fluid proteomes

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Jeffrey S.; Angel, Thomas E.; Chavkin, Charles; Orton, Daniel J.; Moore, Ronald J.; Smith, Richard D.

    2014-03-20

    Analysis of cerebrospinal fluid (CSF) offers key insight into the status of the central nervous system. Characterization of murine CSF proteomes can provide a valuable resource for studying central nervous system injury and disease in animal models. However, the small volume of CSF in mice has thus far limited individual mouse proteome characterization. Through non-terminal CSF extractions in C57Bl/6 mice and high-resolution liquid chromatography-mass spectrometry analysis of individual murine samples, we report the most comprehensive proteome characterization of individual murine CSF to date. Utilizing stringent protein inclusion criteria that required the identification of at least two unique peptides (1% false discovery rate at the peptide level) we identified a total of 566 unique proteins, including 128 proteins from three individual CSF samples that have been previously identified in brain tissue. Our methods and analysis provide a mechanism for individual murine CSF proteome analysis.

  11. Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

    Science.gov (United States)

    Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna

    2017-03-01

    Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.

  12. Marine proteomics: a critical assessment of an emerging technology.

    Science.gov (United States)

    Slattery, Marc; Ankisetty, Sridevi; Corrales, Jone; Marsh-Hunkin, K Erica; Gochfeld, Deborah J; Willett, Kristine L; Rimoldi, John M

    2012-10-26

    The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for eco-physiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several "model species". Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.

  13. Lung cancer screening beyond low-dose computed tomography: the role of novel biomarkers.

    Science.gov (United States)

    Hasan, Naveed; Kumar, Rohit; Kavuru, Mani S

    2014-10-01

    Lung cancer is the most common and lethal malignancy in the world. The landmark National lung screening trial (NLST) showed a 20% relative reduction in mortality in high-risk individuals with screening low-dose computed tomography. However, the poor specificity and low prevalence of lung cancer in the NLST provide major limitations to its widespread use. Furthermore, a lung nodule on CT scan requires a nuanced and individualized approach towards management. In this regard, advances in high through-put technology (molecular diagnostics, multi-gene chips, proteomics, and bronchoscopic techniques) have led to discovery of lung cancer biomarkers that have shown potential to complement the current screening standards. Early detection of lung cancer can be achieved by analysis of biomarkers from tissue samples within the respiratory tract such as sputum, saliva, nasal/bronchial airway epithelial cells and exhaled breath condensate or through peripheral biofluids such as blood, serum and urine. Autofluorescence bronchoscopy has been employed in research setting to identify pre-invasive lesions not identified on CT scan. Although these modalities are not yet commercially available in clinic setting, they will be available in the near future and clinicians who care for patients with lung cancer should be aware. In this review, we present up-to-date state of biomarker development, discuss their clinical relevance and predict their future role in lung cancer management.

  14. Defining the Adipose Tissue Proteome of Dairy Cows to Reveal Biomarkers Related to Peripartum Insulin Resistance and Metabolic Status.

    Science.gov (United States)

    Zachut, Maya

    2015-07-02

    Adipose tissue is a central regulator of metabolism in dairy cows; however, little is known about the association between various proteins in adipose tissue and the metabolic status of peripartum cows. Therefore, the objectives were to (1) examine total protein expression in adipose tissue of dairy cows and (2) identify biomarkers in adipose that are linked to insulin resistance and to cows' metabolic status. Adipose tissue biopsies were obtained from eight multiparous cows at -17 and +4 days relative to parturition. Proteins were analyzed by intensity-based, label-free, quantitative shotgun proteomics (nanoLC-MS/MS). Cows were divided into groups with insulin-resistant (IR) and insulin-sensitive (IS) adipose according to protein kinase B phosphorylation following insulin stimulation. Cows with IR adipose lost more body weight postpartum compared with IS cows. Differential expression of 143 out of 586 proteins was detected in prepartum versus postpartum adipose. Comparing IR to IS adipose revealed differential expression of 18.9% of the proteins; those related to lipolysis (hormone-sensitive lipase, perilipin, monoglycerol lipase) were increased in IR adipose. In conclusion, we found novel biomarkers related to IR in adipose and to metabolic status that could be used to characterize high-yielding dairy cows that are better adapted to peripartum metabolic stress.

  15. CURRENT APPROACHES FOR RESEARCH OF MULTIPLE SCLEROSIS BIOMARKERS

    Directory of Open Access Journals (Sweden)

    Kolyada T.I

    2016-12-01

    Full Text Available Current data concerning features of multiple sclerosis (MS etiology, pathogenesis, clinical course and treatment of disease indicate the necessity of personalized approach to the management of MS patients. These features are the variety of possible etiological factors and mechanisms that trigger the development of MS, different courses of disease, and significant differences in treatment efficiency. Phenotypic and pathogenetic heterogeneity of MS requires, on the one hand, the stratification of patients into groups with different treatment depending on a number of criteria including genetic characteristics, disease course, stage of the pathological process, and forms of the disease. On the other hand, it requires the use of modern methods for assessment of individual risk of developing MS, its early diagnosis, evaluation and prognosis of the disease course and the treatment efficiency. This approach is based on the identification and determination of biomarkers of MS including the use of systems biology technology platforms such as genomics, proteomics, metabolomics and bioinformatics. Research and practical use of biomarkers of MS in clinical and laboratory practice requires the use of a wide range of modern medical and biological, mathematical and physicochemical methods. The group of "classical" methods used to study MS biomarkers includes physicochemical and immunological methods aimed at the selection and identification of single molecular biomarkers, as well as methods of molecular genetic analysis. This group of methods includes ELISA, western blotting, isoelectric focusing, immunohistochemical methods, flow cytometry, spectrophotometric and nephelometric methods. These techniques make it possible to carry out both qualitative and quantitative assay of molecular biomarkers. The group of "classical methods" can also include methods based on polymerase chain reaction (including multiplex and allele-specific PCR and genome sequencing

  16. Novel ageing-biomarker discovery using data-intensive technologies

    OpenAIRE

    Griffiths, H.R.; Augustyniak, E.M.; Bennett, S.J.; Debacq-Chainiaux, F.; Dunston, C.R.; Kristensen, P.; Melchjorsen, C.J.; Navarrete, Santos A.; Simm, A.; Toussaint, O.

    2015-01-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for bioma...

  17. Innovative biomarkers in psychiatric disorders: a major clinical challenge in psychiatry.

    Science.gov (United States)

    Lozupone, Madia; Seripa, Davide; Stella, Eleonora; La Montagna, Maddalena; Solfrizzi, Vincenzo; Quaranta, Nicola; Veneziani, Federica; Cester, Alberto; Sardone, Rodolfo; Bonfiglio, Caterina; Giannelli, Gianluigi; Bisceglia, Paola; Bringiotti, Roberto; Daniele, Antonio; Greco, Antonio; Bellomo, Antonello; Logroscino, Giancarlo; Panza, Francesco

    2017-09-01

    Currently, the diagnosis of psychiatric illnesses is based upon DSM-5 criteria. Although endophenotype-specificity for a particular disorder is discussed, the identification of objective biomarkers is ongoing for aiding diagnosis, prognosis, or clinical response to treatment. We need to improve the understanding of the biological abnormalities in psychiatric illnesses across conventional diagnostic boundaries. The present review investigates the innovative post-genomic knowledge used for psychiatric illness diagnostics and treatment response, with a particular focus on proteomics. Areas covered: This review underlines the contribution that psychiatric innovative biomarkers have reached in relation to diagnosis and theragnosis of psychiatric illnesses. Furthermore, it encompasses a reliable representation of their involvement in disease through proteomics, metabolomics/pharmacometabolomics and lipidomics techniques, including the possible role that gut microbiota and CYP2D6 polimorphisms may play in psychiatric illnesses. Expert opinion: Etiologic heterogeneity, variable expressivity, and epigenetics may impact clinical manifestations, making it difficult for a single measurement to be pathognomonic for multifaceted psychiatric disorders. Academic, industry, or government's partnerships may successfully identify and validate new biomarkers so that unfailing clinical tests can be developed. Proteomics, metabolomics, and lipidomics techniques are considered to be helpful tools beyond neuroimaging and neuropsychology for the phenotypic characterization of brain diseases.

  18. Proteomics in the investigation of HIV-1 interactions with host proteins.

    Science.gov (United States)

    Li, Ming

    2015-02-01

    Productive HIV-1 infection depends on host machinery, including a broad array of cellular proteins. Proteomics has played a significant role in the discovery of HIV-1 host proteins. In this review, after a brief survey of the HIV-1 host proteins that were discovered by proteomic analyses, I focus on analyzing the interactions between the virion and host proteins, as well as the technologies and strategies used in those proteomic studies. With the help of proteomics, the identification and characterization of HIV-1 host proteins can be translated into novel antiretroviral therapeutics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. The cerebrospinal fluid proteome in HIV infection: change associated with disease severity.

    Energy Technology Data Exchange (ETDEWEB)

    Angel, Thomas E.; Jacobs, Jon M.; Spudich, Serena S.; Gritsenko, Marina A.; Fuchs, Dietmar; Liegler, Teri; Zetterberg, Henrik; Camp, David G.; Price, Richard W.; Smith, Richard D.

    2012-03-20

    Central nervous system (CNS) infection is a constant feature of systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment. After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral and correlated abundances of identified proteins (a) within and between subjects, (b) with all other proteins across the entire sample set, and (c) with 'external' CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) {le}0.3 and {ge}0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with

  20. Probing the O-glycoproteome of Gastric Cancer Cell Lines for Biomarker Discovery

    DEFF Research Database (Denmark)

    Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana

    2015-01-01

    biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO "SimpleCell" (SC) strategy to characterize the O-glycoproteome of two gastric cancer SC lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses...... at least partially truncated O-glycans. Overall we identified 499 O-glycoproteins and 1,236 O-glycosites in gastric cancer SCs, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer...... with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to demonstrate that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set...

  1. Proteomics analysis of dendritic cell activation by contact allergens reveals possible biomarkers regulated by Nrf2

    Energy Technology Data Exchange (ETDEWEB)

    Mussotter, Franz, E-mail: franz.mussotter@bfr.bund.de [German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin (Germany); Tomm, Janina Melanie [Helmholtz Centre for Environmental Research (UFZ), Department of Molecular Systems Biology, Leipzig (Germany); El Ali, Zeina; Pallardy, Marc; Kerdine-Römer, Saadia [INSERM UMR 996, Univ Paris-Sud, Université Paris-Saclay, Chátenay-Malabry (France); Götz, Mario [German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin (Germany); Bergen, Martin von [Helmholtz Centre for Environmental Research (UFZ), Department of Molecular Systems Biology, Leipzig (Germany); University of Leipzig, Institute of Biochemistry, Leipzig (Germany); Aalborg University, Department of Chemistry and Bioscience, Aalborg (Denmark); Haase, Andrea; Luch, Andreas [German Federal Institute for Risk Assessment (BfR), Department of Chemical and Product Safety, Berlin (Germany)

    2016-12-15

    Allergic contact dermatitis is a widespread disease with high clinical relevance affecting approximately 20% of the general population. Typically, contact allergens are low molecular weight electrophilic compounds which can activate the Keap1/Nrf2 pathway. We performed a proteomics study to reveal possible biomarkers for dendritic cell (DC) activation by contact allergens and to further elucidate the role of Keap1/Nrf2 signaling in this process. We used bone marrow derived dendritic cells (BMDCs) of wild-type (nrf2{sup +/+}) and Nrf2 knockout (nrf2{sup −/−}) mice and studied their response against the model contact sensitizers 2,4-dinitrochlorobenzene (DNCB), cinnamaldehyde (CA) and nickel(II) sulfate by 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) in combination with electrospray ionization tandem mass spectrometry (ESI-MS/MS). Sodium dodecyl sulfate (SDS, 100 μM) served as irritant control. While treatment with nickel(II) sulfate and SDS had only little effects, CA and DNCB led to significant changes in protein expression. We found 18 and 30 protein spots up-regulated in wild-type cells treated with 50 and 100 μM CA, respectively. For 5 and 10 μM DNCB, 32 and 37 spots were up-regulated, respectively. Almost all of these proteins were not differentially expressed in nrf2{sup −/−} BMDCs, indicating an Nrf2-dependent regulation. Among them proteins were detected which are involved in oxidative stress and heat shock responses, as well as in signal transduction or basic cellular pathways. The applied approach allowed us to differentiate between Nrf2-dependent and Nrf2-independent cellular biomarkers differentially regulated upon allergen-induced DC activation. The data presented might contribute to the further development of suitable in vitro testing methods for chemical-mediated sensitization. - Highlights: • Contact allergens induce proteins involved in DC maturation Nrf2-dependently. • Induction of these proteins points to a functional

  2. Preliminary characterizations of a serum biomarker for sarcoidosis by comparative proteomic approach with tandem-mass spectrometry in ethnic Han Chinese patients.

    Science.gov (United States)

    Zhang, Yuan; Chen, Xianqiu; Hu, Yang; Du, Shanshan; Shen, Li; He, Yifan; Zhang, Yuxuan; Zhang, Xia; Li, Huiping; Yung, Rex C

    2013-02-11

    The diagnosis of sarcoidosis is still a significant challenge in China because of the need to exclude other diseases including granulomatous infections and malignancies that may be clinically and radiographically similar. The specific aim of the study is to search for serum protein biomarkers of sarcoidosis and to validate their clinical usefulness in differential diagnosis. Serum samples were collected from patients with sarcoidosis (n = 37), and compared to those from patients with tuberculosis (n = 20), other pulmonary diseases (n = 20), and healthy volunteers (n = 20) for determination of sarcoidosis-specific or -associated protein expression profiles. The first part of this study focused on proteomic analysis of serum from patients with sarcoidosis to identify a pattern of peptides capable of differentiating the studied populations using the ClinProt profiling technology based on mass spectrometry. Enzyme Linked Immunosorbent Assay (ELISA) was then used to verify corresponding elevation of the serum protein concentration of the potential biomarkers in the same patients sets. Receiver operating characteristic curve (ROC) analyses was performed to determine the optimal cutoff value for diagnosis. Immunohistochemistry was carried out to further confirm the protein expression patterns of the biomarkers in lung tissue. An unique protein peak of M/Z 3,210 Daltons (Da) was found to be differentially expressed between the sarcoidosis and control groups and was identified as the N-terminal peptide of 29 amino acids (94-122) of serum amyloid A (SAA). ELISA confirmed that the serum SAA level was significantly higher in the sarcoidosis group than that of the other 3 control groups (p biomarker for ruling-out the diagnosis of sarcoidosis in Chinese subjects.

  3. Anthelmintic metabolism in parasitic helminths: proteomic insights.

    Science.gov (United States)

    Brophy, Peter M; MacKintosh, Neil; Morphew, Russell M

    2012-08-01

    Anthelmintics are the cornerstone of parasitic helminth control. Surprisingly, understanding of the biochemical pathways used by parasitic helminths to detoxify anthelmintics is fragmented, despite the increasing global threat of anthelmintic resistance within the ruminant and equine industries. Reductionist biochemistry has likely over-estimated the enzymatic role of glutathione transferases in anthelmintic metabolism and neglected the potential role of the cytochrome P-450 superfamily (CYPs). Proteomic technologies offers the opportunity to support genomics, reverse genetics and pharmacokinetics, and provide an integrated insight into both the cellular mechanisms underpinning response to anthelmintics and also the identification of biomarker panels for monitoring the development of anthelmintic resistance. To date, there have been limited attempts to include proteomics in anthelmintic metabolism studies. Optimisations of membrane, post-translational modification and interaction proteomic technologies in helminths are needed to especially study Phase I CYPs and Phase III ABC transporter pumps for anthelmintics and their metabolites.

  4. Impact of pre-analytical factors on the proteomic analysis of formalin-fixed paraffin-embedded tissue.

    Science.gov (United States)

    Thompson, Seonaid M; Craven, Rachel A; Nirmalan, Niroshini J; Harnden, Patricia; Selby, Peter J; Banks, Rosamonde E

    2013-04-01

    Formalin-fixed paraffin-embedded (FFPE) tissue samples represent a tremendous potential resource for biomarker discovery, with large numbers of samples in hospital pathology departments and links to clinical information. However, the cross-linking of proteins and nucleic acids by formalin fixation has hampered analysis and proteomic studies have been restricted to using frozen tissue, which is more limited in availability as it needs to be collected specifically for research. This means that rare disease subtypes cannot be studied easily. Recently, improved extraction techniques have enabled analysis of FFPE tissue by a number of proteomic techniques. As with all clinical samples, pre-analytical factors are likely to impact on the results obtained, although overlooked in many studies. The aim of this review is to discuss the various pre-analytical factors, which include warm and cold ischaemic time, size of sample, fixation duration and temperature, tissue processing conditions, length of storage of archival tissue and storage conditions, and to review the studies that have considered these factors in more detail. In those areas where investigations are few or non-existent, illustrative examples of the possible importance of specific factors have been drawn from studies using frozen tissue or from immunohistochemical studies of FFPE tissue. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. A proteomic strategy to identify novel serum biomarkers for liver cirrhosis and hepatocellular cancer in individuals with fatty liver disease

    Directory of Open Access Journals (Sweden)

    Stewart Stephen

    2009-08-01

    Full Text Available Abstract Background Non-alcoholic fatty liver disease (NAFLD has a prevalence of over 20% in Western societies. Affected individuals are at risk of developing both cirrhosis and hepatocellular cancer (HCC. Presently there is no cost effective population based means of identifying cirrhotic individuals and even if there were, our ability to perform HCC surveillance in the at risk group is inadequate. We have performed a pilot proteomic study to assess this as a strategy for serum biomarker detection. Methods 2D Gel electrophoresis was performed on immune depleted sera from 3 groups of patients, namely those with (1 pre-cirrhotic NAFLD (2 cirrhotic NAFLD and (3 cirrhotic NAFLD with co-existing HCC. Five spots differentiating at least one of these three groups were characterised by mass spectroscopy. An ELISA assay was optimised and a cross sectional study assessing one of these serum spots was performed on serum from 45 patients with steatohepatitis related cirrhosis and HCC and compared to 77 patients with histologically staged steatohepatitis. Results Four of the spots identified were apolipoprotein isoforms, the pattern of which was able to differentiate the three groups. The 5th spot, seen in the serum of cirrhotic individuals and more markedly in those with HCC, was identified as CD5 antigen like (CD5L. By ELISA assay, although CD5L was markedly elevated in a number of cirrhotic individuals with HCC, its overall ability to distinguish non-cancer from cancer individuals as determined by AUC ROC analysis was poor. However, serum CD5L was dramatically increased, independently of age, sex, and the presence of necroinflammation, in the serum of individuals with NAFLD cirrhosis relative to those with pre-cirrhotic disease. Conclusion This novel proteomic strategy has identified a number of candidate biomarkers which may have benefit in the surveillance and diagnosis of individuals with chronic liver disease and/or HCC.

  6. Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

    Science.gov (United States)

    Borrebaeck, Carl A K

    2017-03-01

    Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

  7. HIP2: An online database of human plasma proteins from healthy individuals

    Directory of Open Access Journals (Sweden)

    Shen Changyu

    2008-04-01

    Full Text Available Abstract Background With the introduction of increasingly powerful mass spectrometry (MS techniques for clinical research, several recent large-scale MS proteomics studies have sought to characterize the entire human plasma proteome with a general objective for identifying thousands of proteins leaked from tissues in the circulating blood. Understanding the basic constituents, diversity, and variability of the human plasma proteome is essential to the development of sensitive molecular diagnosis and treatment monitoring solutions for future biomedical applications. Biomedical researchers today, however, do not have an integrated online resource in which they can search for plasma proteins collected from different mass spectrometry platforms, experimental protocols, and search software for healthy individuals. The lack of such a resource for comparisons has made it difficult to interpret proteomics profile changes in patients' plasma and to design protein biomarker discovery experiments. Description To aid future protein biomarker studies of disease and health from human plasma, we developed an online database, HIP2 (Healthy Human Individual's Integrated Plasma Proteome. The current version contains 12,787 protein entries linked to 86,831 peptide entries identified using different MS platforms. Conclusion This web-based database will be useful to biomedical researchers involved in biomarker discovery research. This database has been developed to be the comprehensive collection of healthy human plasma proteins, and has protein data captured in a relational database schema built to contain mappings of supporting peptide evidence from several high-quality and high-throughput mass-spectrometry (MS experimental data sets. Users can search for plasma protein/peptide annotations, peptide/protein alignments, and experimental/sample conditions with options for filter-based retrieval to achieve greater analytical power for discovery and validation.

  8. Urine protein concentration estimation for biomarker discovery

    OpenAIRE

    Mistry, Hiten D.; Bramham, Kate; Weston, Andrew; Ward, Malcolm; Thompson, Andrew; Chappell, Lucy C.

    2013-01-01

    Recent advances have been made in the study of urinary proteomics as a diagnostic tool for renal disease and pre-eclampsia which requires accurate measurement of urinary protein. We compared different protein assays (Bicinchoninic acid (BCA), Lowry and Bradford) against the ‘gold standard’ amino-acid assay in urine from 43 women (8 non-pregnant, 34 pregnant, including 8 with pre-eclampsia. BCA assay was superior to both Lowry and Bradford assays (Bland Altman bias: 0.08) compared to amino-aci...

  9. Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization.

    Science.gov (United States)

    Amur, S; LaVange, L; Zineh, I; Buckman-Garner, S; Woodcock, J

    2015-07-01

    The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration. © 2015 American Society for Clinical Pharmacology and Therapeutics.

  10. Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013.

    Science.gov (United States)

    Viglio, Simona; Stolk, Jan; Iadarola, Paolo; Giuliano, Serena; Luisetti, Maurizio; Salvini, Roberta; Fumagalli, Marco; Bardoni, Anna

    2014-01-22

    To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

  11. Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

    Directory of Open Access Journals (Sweden)

    Hem D. Shukla

    2017-10-01

    Full Text Available During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA, and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein–protein interaction

  12. iTRAQ-Based Proteomics Analysis of Serum Proteins in Wistar Rats Treated with Sodium Fluoride: Insight into the Potential Mechanism and Candidate Biomarkers of Fluorosis

    Directory of Open Access Journals (Sweden)

    Yan Wei

    2016-09-01

    Full Text Available Fluorosis induced by exposure to high level fluoride is quite widespread in the world. The manifestations of fluorosis include dental mottling, bone damage, and impaired malfunction of soft tissues. However, the molecular mechanism of fluorosis has not been clarified until now. To explore the underlying mechanisms of fluorosis and screen out serum biomarkers, we carried out a quantitative proteomics study to identify differentially expressed serum proteins in Wistar rats treated with sodium fluoride (NaF by using a proteomics approach of isobaric tagging for relative and absolute quantitation (iTRAQ. We fed Wistar rats drinking water that had 50, 150, and 250 mg/L of dissolved NaF for 24 weeks. For the experimental duration, each rat was given an examination of the lower incisors to check for the condition of dental fluorosis (DF. By the end of the treatment, fluoride ion concentration in serum and lower incisors were detected. The results showed that NaF treatment can induce rat fluorosis. By iTRAQ analysis, a total of 37 differentially expressed serum proteins were identified between NaF-treated and control rats. These proteins were further analyzed by bioinformatics, out of which two proteins were validated by enzyme-linked immunoadsorbent assays (ELISA. The major proteins were involved in complement and coagulation cascade, inflammatory response, complement activation, defense response, and wound response, suggesting that inflammation and immune reactions may play a key role in fluorosis pathogenesis. These proteins may contribute to the understanding of the mechanism of fluoride toxicity, and may serve as potential biomarkers for fluorosis.

  13. Targeted proteomics as a tool for porcine acute phase proteins measurements

    DEFF Research Database (Denmark)

    Marco-Ramell, Anna; Bassols, Anna; Bislev, Stine Lønnerup

    2013-01-01

    . Selected reaction monitoring (SRM), a targeted quantitative proteomic technique, may be used as an alternative to commercial kits for the measurement and validation of target proteins. Acute phase proteins (APPs) are widely recognized inflammation and infection biomarkers (Eckersall, 2010...

  14. False-Positive Rate Determination of Protein Target Discovery using a Covalent Modification- and Mass Spectrometry-Based Proteomics Platform

    Science.gov (United States)

    Strickland, Erin C.; Geer, M. Ariel; Hong, Jiyong; Fitzgerald, Michael C.

    2014-01-01

    Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2 % and analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

  15. A Review of the “Omics” Approach to Biomarkers of Oxidative Stress in Oryza sativa

    Directory of Open Access Journals (Sweden)

    Su Shiung Lam

    2013-04-01

    Full Text Available Physiological and ecological constraints that cause the slow growth and depleted production of crops have raised a major concern in the agriculture industry as they represent a possible threat of short food supply in the future. The key feature that regulates the stress signaling pathway is always related to the reactive oxygen species (ROS. The accumulation of ROS in plant cells would leave traces of biomarkers at the genome, proteome, and metabolome levels, which could be identified with the recent technological breakthrough coupled with improved performance of bioinformatics. This review highlights the recent breakthrough in molecular strategies (comprising transcriptomics, proteomics, and metabolomics in identifying oxidative stress biomarkers and the arising opportunities and obstacles observed in research on biomarkers in rice. The major issue in incorporating bioinformatics to validate the biomarkers from different omic platforms for the use of rice-breeding programs is also discussed. The development of powerful techniques for identification of oxidative stress-related biomarkers and the integration of data from different disciplines shed light on the oxidative response pathways in plants.

  16. Discovery of Novel Biomarkers for Alzheimer’s Disease from Blood

    Directory of Open Access Journals (Sweden)

    Jintao Long

    2016-01-01

    Full Text Available Blood-based biomarkers for Alzheimer’s disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%, specificity (>91%, and accuracy (>89%.

  17. Overview of Biomarkers and Surrogate Endpoints in Drug Development

    Directory of Open Access Journals (Sweden)

    John A. Wagner

    2002-01-01

    Full Text Available There are numerous factors that recommend the use of biomarkers in drug development including the ability to provide a rational basis for selection of lead compounds, as an aid in determining or refining mechanism of action or pathophysiology, and the ability to work towards qualification and use of a biomarker as a surrogate endpoint. Examples of biomarkers come from many different means of clinical and laboratory measurement. Total cholesterol is an example of a clinically useful biomarker that was successfully qualified for use as a surrogate endpoint. Biomarkers require validation in most circumstances. Validation of biomarker assays is a necessary component to delivery of high-quality research data necessary for effective use of biomarkers. Qualification is necessary for use of a biomarker as a surrogate endpoint. Putative biomarkers are typically identified because of a relationship to known or hypothetical steps in a pathophysiologic cascade. Biomarker discovery can also be effected by expression profiling experiment using a variety of array technologies and related methods. For example, expression profiling experiments enabled the discovery of adipocyte related complement protein of 30 kD (Acrp30 or adiponectin as a biomarker for in vivo activation of peroxisome proliferator-activated receptors (PPAR γ activity.

  18. Biomarkers of Therapeutic Response in the IL-23 Pathway in Inflammatory Bowel Disease

    OpenAIRE

    Cayatte, Corinne; Joyce-Shaikh, Barbara; Vega, Felix; Boniface, Katia; Grein, Jeffrey; Murphy, Erin; Blumenschein, Wendy M; Chen, Smiley; Malinao, Maria-Christina; Basham, Beth; Pierce, Robert H; Bowman, Edward P; McKenzie, Brent S; Elson, Charles O; Faubion, William A

    2012-01-01

    OBJECTIVES: Interleukin-23 (IL-23) has emerged as a new therapeutic target for the treatment of inflammatory bowel disease (IBD). As biomarkers of disease state and treatment efficacy are becoming increasingly important in drug development, we sought to identify efficacy biomarkers for anti-IL-23 therapy in Crohn's disease (CD). METHODS: Candidate IL-23 biomarkers, downstream of IL-23 signaling, were identified using shotgun proteomic analysis of feces and colon lavages obtained from a short-...

  19. Cellular Models for Environmental Toxicant Biomarker Discovery

    National Research Council Canada - National Science Library

    Halverson, Kelly M; Lewsis, John A; Jackson, David A; Dennis, William; Brennan, Linda; Krakaner, Teresa

    2006-01-01

    ...) is the development of biomarkers of exposure, effect, and susceptibility. As exposure monitoring using environmental sampling equipment can be impractical and doesn't account for differences in individual responses, new methodologies must be sought...

  20. SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

    Science.gov (United States)

    Petricoin, Emanuel F; Liotta, Lance A

    2004-02-01

    Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

  1. Immunoscreening of the extracellular proteome of colorectal cancer cells

    International Nuclear Information System (INIS)

    Klein-Scory, Susanne; Schwarte-Waldhoff, Irmgard; Kübler, Salwa; Diehl, Hanna; Eilert-Micus, Christina; Reinacher-Schick, Anke; Stühler, Kai; Warscheid, Bettina; Meyer, Helmut E; Schmiegel, Wolff

    2010-01-01

    The release of proteins from tumors can trigger an immune response in cancer patients involving T lymphocytes and B lymphocytes, which results in the generation of antibodies to tumor-derived proteins. Many studies aim to use humoral immune responses, namely autoantibody profiles, directly, as clinical biomarkers. Alternatively, the antibody immune response as an amplification system for tumor associated alterations may be used to indicate putative protein biomarkers with high sensitivity. Aiming at the latter approach we here have implemented an autoantibody profiling strategy which particularly focuses on proteins released by tumor cells in vitro: the so-called secretome. For immunoscreening, the extracellular proteome of five colorectal cancer cell lines was resolved on 2D gels, immobilized on PVDF membranes and used for serological screening with individual sera from 21 colorectal cancer patients and 24 healthy controls. All of the signals from each blot were assigned to a master map, and autoantigen candidates were defined based of the pattern of immunoreactivities. The corresponding proteins were isolated from preparative gels, identified by MALDI-MS and/or by nano-HPLC/ESI-MS/MS and exemplarily confirmed by duplex Western blotting combining the human serum samples with antibodies directed against the protein(s) of interest. From 281 secretome proteins stained with autoantibodies in total we first defined the 'background patterns' of frequently immunoreactive extracellular proteins in healthy and diseased people. An assignment of these proteins, among them many nominally intracellular proteins, to the subset of exosomal proteins within the secretomes revealed a large overlap. On this basis we defined and consequently confirmed novel biomarker candidates such as the extreme C-terminus of the extracellular matrix protein agrin within the set of cancer-enriched immunorectivities. Our findings suggest, first, that autoantibody responses may be due, in

  2. The distinctive gastric fluid proteome in gastric cancer reveals a multi-biomarker diagnostic profile

    Directory of Open Access Journals (Sweden)

    Eng Alvin KH

    2008-10-01

    Full Text Available Abstract Background Overall gastric cancer survival remains poor mainly because there are no reliable methods for identifying highly curable early stage disease. Multi-protein profiling of gastric fluids, obtained from the anatomic site of pathology, could reveal diagnostic proteomic fingerprints. Methods Protein profiles were generated from gastric fluid samples of 19 gastric cancer and 36 benign gastritides patients undergoing elective, clinically-indicated gastroscopy using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry on multiple ProteinChip arrays. Proteomic features were compared by significance analysis of microarray algorithm and two-way hierarchical clustering. A second blinded sample set (24 gastric cancers and 29 clinically benign gastritides was used for validation. Results By significance analysyis of microarray, 60 proteomic features were up-regulated and 46 were down-regulated in gastric cancer samples (p Conclusion This simple and reproducible multimarker proteomic assay could supplement clinical gastroscopic evaluation of symptomatic patients to enhance diagnostic accuracy for gastric cancer and pre-malignant lesions.

  3. Proteomic Technologies for the Study of Osteosarcoma

    Directory of Open Access Journals (Sweden)

    Stephanie D. Byrum

    2012-01-01

    Full Text Available Osteosarcoma is the most common primary bone cancer of children and is established during stages of rapid bone growth. The disease is a consequence of immature osteoblast differentiation, which gives way to a rapidly synthesized incompletely mineralized and disorganized bone matrix. The mechanism of osteosarcoma tumorogenesis is poorly understood, and few proteomic studies have been used to interrogate the disease thus far. Accordingly, these studies have identified proteins that have been known to be associated with other malignancies, rather than being osteosarcoma specific. In this paper, we focus on the growing list of available state-of-the-art proteomic technologies and their specific application to the discovery of novel osteosarcoma diagnostic and therapeutic targets. The current signaling markers/pathways associated with primary and metastatic osteosarcoma that have been identified by early-stage proteomic technologies thus far are also described.

  4. Modern Biotechnology of Phellinus baumii – From Fermentation to Proteomics

    Directory of Open Access Journals (Sweden)

    Hye Jin Hwang

    2007-01-01

    Full Text Available Phellinus baumii is a mushroom used as a folk medicine for a variety of human diseases in several Asian countries. Recently we have reported for the first time about the antidiabetic effect of the crude exopolysaccharides (EPS produced from submerged mycelial culture of P. baumii in streptozotocin (STZ-induced diabetic rats. The diabetic rats study revealed that orally administrated P. baumii EPS lowered the blood glucose levels and stimulated insulin excretion in diabetic rats, and consequently restored the functions of pancreas, liver, and kidney, suggesting that the EPS might be useful for the management of human diabetes mellitus. We undertook proteomic analyses for plasma, pancreas, liver, and kidney of the rats to search for novel biomarkers for monitoring diabetes before and after EPS treatments. In this article, we describe the production of EPS in submerged culture of P. baumii and studies of their hypoglycemic activity. We also explore the issue of proteomic analyses for mining biomarkers of diabetes.

  5. The proteome of neurofilament-containing protein aggregates in blood

    Directory of Open Access Journals (Sweden)

    Rocco Adiutori

    2018-07-01

    Full Text Available Protein aggregation in biofluids is a poorly understood phenomenon. Under normal physiological conditions, fluid-borne aggregates may contain plasma or cell proteins prone to aggregation. Recent observations suggest that neurofilaments (Nf, the building blocks of neurons and a biomarker of neurodegeneration, are included in high molecular weight complexes in circulation. The composition of these Nf-containing hetero-aggregates (NCH may change in systemic or organ-specific pathologies, providing the basis to develop novel disease biomarkers. We have tested ultracentrifugation (UC and a commercially available protein aggregate binder, Seprion PAD-Beads (SEP, for the enrichment of NCH from plasma of healthy individuals, and then characterised the Nf content of the aggregate fractions using gel electrophoresis and their proteome by mass spectrometry (MS. Western blot analysis of fractions obtained by UC showed that among Nf isoforms, neurofilament heavy chain (NfH was found within SDS-stable high molecular weight aggregates. Shotgun proteomics of aggregates obtained with both extraction techniques identified mostly cell structural and to a lesser extent extra-cellular matrix proteins, while functional analysis revealed pathways involved in inflammatory response, phagosome and prion-like protein behaviour. UC aggregates were specifically enriched with proteins involved in endocrine, metabolic and cell-signalling regulation. We describe the proteome of neurofilament-containing aggregates isolated from healthy individuals biofluids using different extraction methods.

  6. Proteomic profiling of mammary carcinomas identifies C7orf24, a gamma-glutamyl cyclotransferase, as a potential cancer biomarker

    DEFF Research Database (Denmark)

    Gromov, Pavel; Gromova, Irina; Friis, Esbern

    2010-01-01

    Breast cancer is the leading cause of cancer deaths in women today and is the most common cancer (excluding skin cancers) among women in the Western world. Although cancers detected by screening mammography are significantly smaller than nonscreening ones, noninvasive biomarkers for detection......, and a novel protein, C7orf24, was identified as being upregulated in cancer cells. Protein expression levels of C7orf24 were evaluated by immunohistochemical assays to qualify deregulation of this protein. Analysis of C7orf24 expression showed up-regulation in 36.4 and 23.4% of cases present in the discovery...

  7. Multiplex array proteomics detects increased MMP-8 in CSF after spinal cord injury.

    Science.gov (United States)

    Light, Matthew; Minor, Kenneth H; DeWitt, Peter; Jasper, Kyle H; Davies, Stephen J A

    2012-06-11

    A variety of methods have been used to study inflammatory changes in the acutely injured spinal cord. Recently novel multiplex assays have been used in an attempt to overcome limitations in numbers of available targets studied in a single experiment. Other technical challenges in developing pre-clinical rodent models to investigate biomarkers in cerebrospinal fluid (CSF) include relatively small volumes of sample and low concentrations of target proteins. The primary objective of this study was to characterize the inflammatory profile present in CSF at a subacute time point in a clinically relevant rodent model of traumatic spinal cord injury (SCI). Our other aim was to test a microarray proteomics platform specifically for this application. A 34 cytokine sandwich ELISA microarray was used to study inflammatory changes in CSF samples taken 12 days post-cervical SCI in adult rats. The difference between the median foreground signal and the median background signal was measured. Bonferroni and Benjamini-Hochburg multiple testing corrections were applied to limit the False Discovery Rate (FDR), and a linear mixed model was used to account for repeated measures in the array. We report a novel subacute SCI biomarker, elevated levels of matrix metalloproteinase-8 protein in CSF, and discuss application of statistical models designed for multiplex testing. Major advantages of this assay over conventional methods include high-throughput format, good sensitivity, and reduced sample consumption. This method can be useful for creating comprehensive inflammatory profiles, and biomarkers can be used in the clinic to assess injury severity and to objectively grade response to therapy.

  8. Exploring the human plasma proteome for humoral mediators of remote ischemic preconditioning--a word of caution.

    Directory of Open Access Journals (Sweden)

    Erik Helgeland

    Full Text Available Despite major advances in early revascularization techniques, cardiovascular diseases are still the leading cause of death worldwide, and myocardial infarctions contribute heavily to this. Over the past decades, it has become apparent that reperfusion of blood to a previously ischemic area of the heart causes damage in and of itself, and that this ischemia reperfusion induced injury can be reduced by up to 50% by mechanical manipulation of the blood flow to the heart. The recent discovery of remote ischemic preconditioning (RIPC provides a non-invasive approach of inducing this cardioprotection at a distance. Finding its endogenous mediators and their operative mode is an important step toward increasing the ischemic tolerance. The release of humoral factor(s upon RIPC was recently demonstrated and several candidate proteins were published as possible mediators of the cardioprotection. Before clinical applicability, these potential biomarkers and their efficiency must be validated, a task made challenging by the large heterogeneity in reported data and results. Here, in an attempt to reproduce and provide more experimental data on these mediators, we conducted an unbiased in-depth analysis of the human plasma proteome before and after RIPC. From the 68 protein markers reported in the literature, only 28 could be mapped to manually reviewed (Swiss-Prot protein sequences. 23 of them were monitored in our untargeted experiment. However, their significant regulation could not be reproducibly estimated. In fact, among the 394 plasma proteins we accurately quantified, no significant regulation could be confidently and reproducibly assessed. This indicates that it is difficult to both monitor and reproduce published data from experiments exploring for RIPC induced plasma proteomic regulations, and suggests that further work should be directed towards small humoral factors. To simplify this task, we made our proteomic dataset available via Proteome

  9. Exploring the Human Plasma Proteome for Humoral Mediators of Remote Ischemic Preconditioning - A Word of Caution

    Science.gov (United States)

    Helgeland, Erik; Breivik, Lars Ertesvåg; Vaudel, Marc; Svendsen, Øyvind Sverre; Garberg, Hilde; Nordrehaug, Jan Erik; Berven, Frode Steingrimsen; Jonassen, Anne Kristine

    2014-01-01

    Despite major advances in early revascularization techniques, cardiovascular diseases are still the leading cause of death worldwide, and myocardial infarctions contribute heavily to this. Over the past decades, it has become apparent that reperfusion of blood to a previously ischemic area of the heart causes damage in and of itself, and that this ischemia reperfusion induced injury can be reduced by up to 50% by mechanical manipulation of the blood flow to the heart. The recent discovery of remote ischemic preconditioning (RIPC) provides a non-invasive approach of inducing this cardioprotection at a distance. Finding its endogenous mediators and their operative mode is an important step toward increasing the ischemic tolerance. The release of humoral factor(s) upon RIPC was recently demonstrated and several candidate proteins were published as possible mediators of the cardioprotection. Before clinical applicability, these potential biomarkers and their efficiency must be validated, a task made challenging by the large heterogeneity in reported data and results. Here, in an attempt to reproduce and provide more experimental data on these mediators, we conducted an unbiased in-depth analysis of the human plasma proteome before and after RIPC. From the 68 protein markers reported in the literature, only 28 could be mapped to manually reviewed (Swiss-Prot) protein sequences. 23 of them were monitored in our untargeted experiment. However, their significant regulation could not be reproducibly estimated. In fact, among the 394 plasma proteins we accurately quantified, no significant regulation could be confidently and reproducibly assessed. This indicates that it is difficult to both monitor and reproduce published data from experiments exploring for RIPC induced plasma proteomic regulations, and suggests that further work should be directed towards small humoral factors. To simplify this task, we made our proteomic dataset available via ProteomeXchange, where

  10. Development stage-specific proteomic profiling uncovers small, lineage specific proteins most abundant in the Aspergillus Fumigatus conidial proteome

    Directory of Open Access Journals (Sweden)

    Suh Moo-Jin

    2012-04-01

    Full Text Available Abstract Background The pathogenic mold Aspergillus fumigatus is the most frequent infectious cause of death in severely immunocompromised individuals such as leukemia and bone marrow transplant patients. Germination of inhaled conidia (asexual spores in the host is critical for the initiation of infection, but little is known about the underlying mechanisms of this process. Results To gain insights into early germination events and facilitate the identification of potential stage-specific biomarkers and vaccine candidates, we have used quantitative shotgun proteomics to elucidate patterns of protein abundance changes during early fungal development. Four different stages were examined: dormant conidia, isotropically expanding conidia, hyphae in which germ tube emergence has just begun, and pre-septation hyphae. To enrich for glycan-linked cell wall proteins we used an alkaline cell extraction method. Shotgun proteomic resulted in the identification of 375 unique gene products with high confidence, with no evidence for enrichment of cell wall-immobilized and secreted proteins. The most interesting discovery was the identification of 52 proteins enriched in dormant conidia including 28 proteins that have never been detected in the A. fumigatus conidial proteome such as signaling protein Pil1, chaperones BipA and calnexin, and transcription factor HapB. Additionally we found many small, Aspergillus specific proteins of unknown function including 17 hypothetical proteins. Thus, the most abundant protein, Grg1 (AFUA_5G14210, was also one of the smallest proteins detected in this study (M.W. 7,367. Among previously characterized proteins were melanin pigment and pseurotin A biosynthesis enzymes, histones H3 and H4.1, and other proteins involved in conidiation and response to oxidative or hypoxic stress. In contrast, expanding conidia, hyphae with early germ tubes, and pre-septation hyphae samples were enriched for proteins responsible for

  11. Clinical proteomic analysis of scrub typhus infection.

    Science.gov (United States)

    Park, Edmond Changkyun; Lee, Sang-Yeop; Yun, Sung Ho; Choi, Chi-Won; Lee, Hayoung; Song, Hyun Seok; Jun, Sangmi; Kim, Gun-Hwa; Lee, Chang-Seop; Kim, Seung Il

    2018-01-01

    Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection. Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis. Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi , and normal expression was largely rescued by antibiotic treatment. This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

  12. Amyloid Biomarkers in Conformational Diseases at Face Value: A Systematic Review

    OpenAIRE

    Maria Fernanda Avila-Vazquez; Nelly F. Altamirano-Bustamante; Myriam M. Altamirano-Bustamante

    2017-01-01

    Conformational diseases represent a new aspect of proteomic medicine where diagnostic and therapeutic paradigms are evolving. In this context, the early biomarkers for target cell failure (neurons, β-cells, etc.) represent a challenge to translational medicine and play a multidimensional role as biomarkers and potential therapeutic targets. This systematic review, which follows the PICO and Prisma methods, analyses this new-fangled multidimensionality, its strengths and limitations, and prese...

  13. Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase.

    Science.gov (United States)

    Sanchez-Niño, Maria Dolores; Sanz, Ana B; Ramos, Adrian M; Fernandez-Fernandez, Beatriz; Ortiz, Alberto

    2017-04-01

    Exponential technologies double in power or processing speed every year, whereas their cost halves. Deception and disruption are two key stages in the development of exponential technologies. Deception occurs when, after initial introduction, technologies are dismissed as irrelevant, while they continue to progress, perhaps not as fast or with so many immediate practical applications as initially thought. Twenty years after the first publications, clinical proteomics is still not available in most hospitals and some clinicians have felt deception at unfulfilled promises. However, there are indications that clinical proteomics may be entering the disruptive phase, where, once refined, technologies disrupt established industries or procedures. In this regard, recent manuscripts in CKJ illustrate how proteomics is entering the clinical realm, with applications ranging from the identification of amyloid proteins in the pathology lab, to a new generation of urinary biomarkers for chronic kidney disease (CKD) assessment and outcome prediction. Indeed, one such panel of urinary peptidomics biomarkers, CKD273, recently received a Food and Drug Administration letter of support, the first ever in the CKD field. In addition, a must-read resource providing information on kidney disease-related proteomics and systems biology databases and how to access and use them in clinical decision-making was also recently published in CKJ .

  14. Proteomic and metabolomic responses in hepatopancreas of Mytilus galloprovincialis challenged by Micrococcus luteus and Vibrio anguillarum.

    Science.gov (United States)

    Wu, Huifeng; Ji, Chenglong; Wei, Lei; Zhao, Jianmin; Lu, Hongjian

    2013-12-06

    The outbreak of pathogens can induce diseases and lead to massive mortalities of aquaculture animals including fish, mollusk and shrimp. In this work, the responses induced by Micrococcus luteus and Vibrio anguillarum were investigated in hepatopancreas of mussel Mytilus galloprovincialis using proteomics and metabolomics. Metabolic biomarkers demonstrated that M. luteus and V. anguillarum injections could induce osmotic stress and disturbance in energy metabolism. And the uniquely and more markedly altered metabolic biomarkers (glutamine, succinate, aspartate, glucose, ATP, homarine and tyrosine) indicated that V. anguillarum could cause more severe disturbances in osmotic regulation and energy metabolism. The differentially altered proteins meant that M. luteus and V. anguillarum induced different effects in mussels. However, the common proteomic biomarkers, arginine kinase and small heat shock protein, demonstrated that these two bacteria induced similar effects including oxidative stress and disturbance in energy metabolism in M. galloprovincialis. In addition, some metabolic biomarkers, ATP and glutamine, were confirmed by related proteins including arginine kinase, ATP synthase, nucleoside diphosphate kinase and glutamine synthetase in bacteria-challenged mussels. This study demonstrated that proteomics and metabolomics could provide an insightful view into the effects of environmental pathogens to the marine mussel M. galloprovincialis. The outbreak of pathogens can lead to diseases and massive mortalities of aquaculture animals including fish, mollusk and shrimp. The mussel M. galloprovincialis distributes widely along the Bohai coast and is popularly consumed as delicious seafood by local residents. This bivalve has become one of the important species in marine aquaculture industry in China. Therefore a study on pathogen-induced effects is necessary. In the present study, an integrated metabolomic and proteomic approach was used to elucidate the

  15. Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals

    DEFF Research Database (Denmark)

    Delles, Christian; Schiffer, Eric; von Zur Muhlen, Constantin

    2010-01-01

    We studied the urinary proteome in a total of 623 individuals with and without coronary artery disease (CAD) in order to characterize multiple biomarkers that enable prediction of the presence of CAD....

  16. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    International Nuclear Information System (INIS)

    Kumar, Bhowmik Salil; Lee, Young-Joo; Yi, Hong Jae; Chung, Bong Chul; Jung, Byung Hwa

    2010-01-01

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg -1 day -1 or 250 mg kg -1 day -1 for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  17. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Bhowmik Salil [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of); Lee, Young-Joo; Yi, Hong Jae [College of Pharmacy, Kyung Hee University, Hoegi-dong, Dongdaemun-gu, Seoul 130-791 (Korea, Republic of); Chung, Bong Chul [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); Jung, Byung Hwa, E-mail: jbhluck@kist.re.kr [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of)

    2010-02-19

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg{sup -1} day{sup -1} or 250 mg kg{sup -1} day{sup -1} for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  18. Advancement of mass spectrometry-based proteomics technologies to explore triple negative breast cancer.

    Science.gov (United States)

    Miah, Sayem; Banks, Charles A S; Adams, Mark K; Florens, Laurence; Lukong, Kiven E; Washburn, Michael P

    2016-12-20

    Understanding the complexity of cancer biology requires extensive information about the cancer proteome over the course of the disease. The recent advances in mass spectrometry-based proteomics technologies have led to the accumulation of an incredible amount of such proteomic information. This information allows us to identify protein signatures or protein biomarkers, which can be used to improve cancer diagnosis, prognosis and treatment. For example, mass spectrometry-based proteomics has been used in breast cancer research for over two decades to elucidate protein function. Breast cancer is a heterogeneous group of diseases with distinct molecular features that are reflected in tumour characteristics and clinical outcomes. Compared with all other subtypes of breast cancer, triple-negative breast cancer is perhaps the most distinct in nature and heterogeneity. In this review, we provide an introductory overview of the application of advanced proteomic technologies to triple-negative breast cancer research.

  19. Global phosphotyrosine proteomics identifies PKCδ as a marker of responsiveness to Src inhibition in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Eliot T McKinley

    Full Text Available Sensitive and specific biomarkers of protein kinase inhibition can be leveraged to accelerate drug development studies in oncology by associating early molecular responses with target inhibition. In this study, we utilized unbiased shotgun phosphotyrosine (pY proteomics to discover novel biomarkers of response to dasatinib, a small molecule Src-selective inhibitor, in preclinical models of colorectal cancer (CRC. We performed unbiased mass spectrometry shotgun pY proteomics to reveal the pY proteome of cultured HCT-116 colonic carcinoma cells, and then extended this analysis to HCT-116 xenograft tumors to identify pY biomarkers of dasatinib-responsiveness in vivo. Major dasatinib-responsive pY sites in xenograft tumors included sites on delta-type protein kinase C (PKCδ, CUB-domain-containing protein 1 (CDCP1, Type-II SH2-domain-containing inositol 5-phosphatase (SHIP2, and receptor protein-tyrosine phosphatase alpha (RPTPα. The pY313 site PKCδ was further supported as a relevant biomarker of dasatinib-mediated Src inhibition in HCT-116 xenografts by immunohistochemistry and immunoblotting with a phosphospecific antibody. Reduction of PKCδ pY313 was further correlated with dasatinib-mediated inhibition of Src and diminished growth as spheroids of a panel of human CRC cell lines. These studies reveal PKCδ pY313 as a promising readout of Src inhibition in CRC and potentially other solid tumors and may reflect responsiveness to dasatinib in a subset of colorectal cancers.

  20. Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

    Science.gov (United States)

    El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

    2017-01-01

    The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

  1. A proteomic evaluation of the effects of the pharmaceuticals diclofenac and gemfibrozil on marine mussels (Mytilus spp.): evidence for chronic sublethal effects on stress-response proteins.

    Science.gov (United States)

    Schmidt, Wiebke; Rainville, Louis-Charles; McEneff, Gillian; Sheehan, David; Quinn, Brian

    2014-03-01

    Human pharmaceuticals (e.g. the lipid regulator gemfibrozil and the non-steroidal anti-inflammatory drug diclofenac) are an emerging environmental threat in the aquatic environment. This study aimed to evaluate sublethal effects of these two commonly found pharmaceuticals on the protein profiles of marine mussels (Mytilus spp.). Mytilus spp. was exposed to environmentally relevant and elevated concentrations (1 and 1000 µg/l respectively) of both drugs for 14 days. In addition, mussels were maintained for seven days post treatment to examine the potential of blue mussels to recover from such an exposure. Differential protein expression signatures (PES) in the digestive gland of mussels were obtained using two-dimensional gel electrophoresis after 7, 14, and 21 days of exposure. Twelve spots were significantly increased or decreased by gemfibrozil and/or diclofenac, seven of which were successfully identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. These proteins were involved in energy metabolism, oxidative stress response, protein folding, and immune responses. Changes in the PES over time suggested that mussels were still experiencing oxidative stress for up to seven days post exposure. In addition, a suite of biomarkers comprising glutathione transferase, lipid peroxidation, and DNA damage were studied. An oxidative stress response was confirmed by biomarker responses. To our knowledge, this is the first investigation using proteomics to assess the potential effects of human pharmaceuticals on a non-target species in an environmentally-relevant model. The successful application of this proteomic approach supports its potential use in pollution biomonitoring and highlights its ability to aid in the discovery of new biomarkers. Copyright © 2013 John Wiley & Sons, Ltd.

  2. A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

    Directory of Open Access Journals (Sweden)

    Jianwen She

    2013-09-01

    Full Text Available Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC, reversed-phase liquid chromatography (RP–LC, and gas chromatography (GC. All three techniques are coupled to a mass spectrometer (MS in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

  3. Plasma low-molecular-weight proteome profiling identified neuropeptide-Y as a prostate cancer biomarker polypeptide.

    Science.gov (United States)

    Ueda, Koji; Tatsuguchi, Ayako; Saichi, Naomi; Toyama, Atsuhiko; Tamura, Kenji; Furihata, Mutsuo; Takata, Ryo; Akamatsu, Shusuke; Igarashi, Masahiro; Nakayama, Masato; Sato, Taka-Aki; Ogawa, Osamu; Fujioka, Tomoaki; Shuin, Taro; Nakamura, Yusuke; Nakagawa, Hidewaki

    2013-10-04

    In prostate cancer diagnosis, PSA test has greatly contributed to the early detection of prostate cancer; however, expanding overdiagnosis and unnecessary biopsies have emerged as serious issues. To explore plasma biomarkers complementing the specificity of PSA test, we developed a unique proteomic technology QUEST-MS (Quick Enrichment of Small Targets for Mass Spectrometry). The QUEST-MS method based on 96-well formatted sequential reversed-phase chromatography allowing efficient enrichment of <20 kDa proteins quickly and reproducibly. Plasma from 24 healthy controls, 19 benign prostate hypertrophy patients, and 73 prostate cancer patients were purified with QUEST-MS and analyzed by LC/MS/MS. Among 153 057 nonredundant peptides, 189 peptides showed prostate cancer specific detection pattern, which included a neurotransmitter polypeptide neuropeptide-Y (NPY). We further validated the screening results by targeted multiple reaction monitoring technology using independent sample set (n = 110). The ROC curve analysis revealed that logistic regression-based combination of NPY, and PSA showed 81.5% sensitivity and 82.2% specificity for prostate cancer diagnosis. Thus QUEST-MS technology allowed comprehensive and high-throughput profiling of plasma polypeptides and had potential to effectively uncover very low abundant tumor-derived small molecules, such as neurotransmitters, peptide hormones, or cytokines.

  4. Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

    Directory of Open Access Journals (Sweden)

    Anjali K Nath

    Full Text Available Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs. However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies.Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1 as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF samples from women carrying normal fetuses and those with CHDs.The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs.

  5. Multiple nutrient stresses at intersecting Pacific Ocean biomes detected by protein biomarkers.

    Science.gov (United States)

    Saito, Mak A; McIlvin, Matthew R; Moran, Dawn M; Goepfert, Tyler J; DiTullio, Giacomo R; Post, Anton F; Lamborg, Carl H

    2014-09-05

    Marine primary productivity is strongly influenced by the scarcity of required nutrients, yet our understanding of these nutrient limitations is informed by experimental observations with sparse geographical coverage and methodological limitations. We developed a quantitative proteomic method to directly assess nutrient stress in high-light ecotypes of the abundant cyanobacterium Prochlorococcus across a meridional transect in the central Pacific Ocean. Multiple peptide biomarkers detected widespread and overlapping regions of nutritional stress for nitrogen and phosphorus in the North Pacific Subtropical Gyre and iron in the equatorial Pacific. Quantitative protein analyses demonstrated simultaneous stress for these nutrients at biome interfaces. This application of proteomic biomarkers to diagnose ocean metabolism demonstrated Prochlorococcus actively and simultaneously deploying multiple biochemical strategies for low-nutrient conditions in the oceans. Copyright © 2014, American Association for the Advancement of Science.

  6. STATE OF THE ART IN PROTEOMICS FOR CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    Syafrizayanti Syafrizayanti

    2014-12-01

    Full Text Available The earliest stages of cancer detection determine the successful of cancer treatment andtherapy. The existing cancer test or detection methods have been routinely used, but they arelack of sensitivity and specificity that are needed to avoid false positive or negative results. Thegenomic basedtechniques have been applied, although molecular understandings of cancerfar from complete, but few genomic platforms are becoming routine. Application of proteomicsbasedtechniques provide intriguing outcome, which is cancer detection at their earliest stages.Proteomics have exposed a new perspective into the phases of tumorigenesis and depictedmore detailed molecular network scheme, which made important contributions in the discoveryof biomarker of early diagnosis, prognosis and prediction outcome of cancer therapies.The noticeable proteomic platforms to achieve these goals are protein microarray, tissuemicroarray, mass spectrometry-based proteomic, and two-dimensionalgel electrophoresis (2-DE. The application of these techniques will be overviewed, providing a general review ofcurrent proteomic methods in cancer detection and subsequently improvement in prognosisand prediction of cancer therapies.Keywords: proteomics, protein microarrays, mass spectrometry, cancer biomarkerAbstrakDeteksi dini kanker sangat menentukan keberhasilan penanganan dan terapi kanker. Hinggasaat ini, telah banyak jenis metoda deteksi dan uji kanker yang sudah rutin digunakan, akantetapi metoda-metoda tersebut memiliki tingkat sensitifitas dan spesifikasi yang rendah,sehingga sering menyebabkan terjadi kesalahan hasil uji baik secara positif ataupun negatif.Bidang genomik telah banyak digunakan untuk lebih memahami kanker pada level molekuler,meskipun hasil yang diperoleh belum mendalam, akan tetapi beberapa metoda berbasiskangenomik telah mulai rutin digunakan. Bidang pioteomik mulai banyak diaplikasikan untukkeperluan deteksi kankersedini mungkin. Proteomik memberikan perspektif

  7. Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation.

    Science.gov (United States)

    Woo, Jongmin; Han, Dohyun; Wang, Joseph Injae; Park, Joonho; Kim, Hyunsoo; Kim, Youngsoo

    2017-09-01

    discovery and label-free PRM analysis have been deposited to the ProteomeXchange Consortium with identifiers and , respectively.

  8. Metabolomics as a tool in the identification of dietary biomarkers.

    Science.gov (United States)

    Gibbons, Helena; Brennan, Lorraine

    2017-02-01

    Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.

  9. Proteomic analysis of urine in rats chronically exposed to fluoride.

    Science.gov (United States)

    Kobayashi, Claudia Ayumi Nakai; Leite, Aline de Lima; da Silva, Thelma Lopes; dos Santos, Lucilene Delazari; Nogueira, Fábio César Sousa; Santos, Keity Souza; de Oliveira, Rodrigo Cardoso; Palma, Mario Sérgio; Domont, Gilberto Barbosa; Buzalaf, Marília Afonso Rabelo

    2011-01-01

    Urine is an ideal source of materials to search for potential disease-related biomarkers as it is produced by the affected tissues and can be easily obtained by noninvasive methods. 2-DE-based proteomic approach was used to better understand the molecular mechanisms of injury induced by fluoride (F(-)) and define potential biomarkers of dental fluorosis. Three groups of weanling male Wistar rats were treated with drinking water containing 0 (control), 5, or 50 ppm F(-) for 60 days (n = 15/group). During the experimental period, the animals were kept individually in metabolic cages, to analyze the water and food consumption, as well as fecal and urinary F(-) excretion. Urinary proteome profiles were examined using 2-DE and Colloidal Coomassie Brilliant Blue staining. A dose-response regarding F(-) intake and excretion was detected. Quantitative intensity analysis revealed 8, 11, and 8 significantly altered proteins between control vs. 5 ppm F(-), control vs. 50 ppm F(-) and 5 ppm F(-) vs. 50 ppm F(-) groups, respectively. Two proteins regulated by androgens (androgen-regulated 20-KDa protein and α-2μ-globulin) and one related to detoxification (aflatoxin-B1-aldehyde-reductase) were identified by MALDI-TOF-TOF MS/MS. Thus, proteomic analysis can help to better understand the mechanisms underlying F(-) toxicity, even in low doses. Copyright © 2010 Wiley Periodicals, Inc.

  10. Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

    Science.gov (United States)

    Phan, John H.; Moffitt, Richard A.; Stokes, Todd H.; Liu, Jian; Young, Andrew N.; Nie, Shuming; Wang, May D.

    2013-01-01

    Recent advances in biomarker discovery, biocomputing, and nanotechnology have raised new opportunities for the emerging field of personalized medicine in which disease detection, diagnosis, and therapy are tailored to each individual’s molecular profile, and also for predictive medicine that uses genetic/molecular information to predict disease development, progression, and clinical outcome. Here we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, together with prospects and challenges in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases. PMID:19409634

  11. Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

    Science.gov (United States)

    Lindsey, Merry L; Mayr, Manuel; Gomes, Aldrin V; Delles, Christian; Arrell, D Kent; Murphy, Anne M; Lange, Richard A; Costello, Catherine E; Jin, Yu-Fang; Laskowitz, Daniel T; Sam, Flora; Terzic, Andre; Van Eyk, Jennifer; Srinivas, Pothur R

    2015-09-01

    The year 2014 marked the 20th anniversary of the coining of the term proteomics. The purpose of this scientific statement is to summarize advances over this period that have catalyzed our capacity to address the experimental, translational, and clinical implications of proteomics as applied to cardiovascular health and disease and to evaluate the current status of the field. Key successes that have energized the field are delineated; opportunities for proteomics to drive basic science research, facilitate clinical translation, and establish diagnostic and therapeutic healthcare algorithms are discussed; and challenges that remain to be solved before proteomic technologies can be readily translated from scientific discoveries to meaningful advances in cardiovascular care are addressed. Proteomics is the result of disruptive technologies, namely, mass spectrometry and database searching, which drove protein analysis from 1 protein at a time to protein mixture analyses that enable large-scale analysis of proteins and facilitate paradigm shifts in biological concepts that address important clinical questions. Over the past 20 years, the field of proteomics has matured, yet it is still developing rapidly. The scope of this statement will extend beyond the reaches of a typical review article and offer guidance on the use of next-generation proteomics for future scientific discovery in the basic research laboratory and clinical settings. © 2015 American Heart Association, Inc.

  12. Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

    Science.gov (United States)

    Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

    2016-01-01

    Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

  13. Averaged differential expression for the discovery of biomarkers in the blood of patients with prostate cancer.

    Directory of Open Access Journals (Sweden)

    V Uma Bai

    Full Text Available The identification of a blood-based diagnostic marker is a goal in many areas of medicine, including the early diagnosis of prostate cancer. We describe the use of averaged differential display as an efficient mechanism for biomarker discovery in whole blood RNA. The process of averaging reduces the problem of clinical heterogeneity while simultaneously minimizing sample handling.RNA was isolated from the blood of prostate cancer patients and healthy controls. Samples were pooled and subjected to the averaged differential display process. Transcripts present at different levels between patients and controls were purified and sequenced for identification. Transcript levels in the blood of prostate cancer patients and controls were verified by quantitative RT-PCR. Means were compared using a t-test and a receiver-operating curve was generated. The Ring finger protein 19A (RNF19A transcript was identified as having higher levels in prostate cancer patients compared to healthy men through the averaged differential display process. Quantitative RT-PCR analysis confirmed a more than 2-fold higher level of RNF19A mRNA levels in the blood of patients with prostate cancer than in healthy controls (p = 0.0066. The accuracy of distinguishing cancer patients from healthy men using RNF19A mRNA levels in blood as determined by the area under the receiving operator curve was 0.727.Averaged differential display offers a simplified approach for the comprehensive screening of body fluids, such as blood, to identify biomarkers in patients with prostate cancer. Furthermore, this proof-of-concept study warrants further analysis of RNF19A as a clinically relevant biomarker for prostate cancer detection.

  14. The inflammatory cytokines: molecular biomarkers for major depressive disorder?

    Science.gov (United States)

    Martin, Charlotte; Tansey, Katherine E; Schalkwyk, Leonard C; Powell, Timothy R

    2015-01-01

    Cytokines are pleotropic cell signaling proteins that, in addition to their role as inflammatory mediators, also affect neurotransmitter systems, brain functionality and mood. Here we explore the potential utility of cytokine biomarkers for major depressive disorder. Specifically, we explore how genetic, transcriptomic and proteomic information relating to the cytokines might act as biomarkers, aiding clinical diagnosis and treatment selection processes. We advise future studies to investigate whether cytokine biomarkers might differentiate major depressive disorder patients from other patient groups with overlapping clinical characteristics. Furthermore, we invite future pharmacogenetic studies to investigate whether early antidepressant-induced changes to cytokine mRNA or protein levels precede behavioral changes and act as longer-term predictors of clinical antidepressant response.

  15. Investigating the emerging role of comparative proteomics in the search for new biomarkers of metal contamination under varying abiotic conditions

    Energy Technology Data Exchange (ETDEWEB)

    Vellinger, Céline, E-mail: celine.vellinger@gmail.com [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Sohm, Bénédicte, E-mail: benedicte.sohm@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Parant, Marc, E-mail: marc.parant@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France); Immel, Françoise, E-mail: Francoise.Immel@u-bourgogne.fr [Biogéosciences, CNRS UMR 6282, Université de Bourgogne – Dijon (France); Usseglio-Polatera, Philippe, E-mail: philippe.usseglio-polatera@univ-lorraine.fr [Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC), CNRS UMR 7360, Université de Lorraine – Metz (France)

    2016-08-15

    mixture previously observed on G. pulex mortality at 10 °C. - Highlights: • We tested comparative proteomics for identifying new biomarkers of chemical exposure. • Both metal interactions and temperature confounding effects were taken into account. • 129 spots have been highlighted as potential Protein Expression Signatures at 10 °C. • Proteomics has high potential but a long way still to go to efficient multi-marker. • Recommendations and precautions for future studies have been presented.

  16. Investigating the emerging role of comparative proteomics in the search for new biomarkers of metal contamination under varying abiotic conditions

    International Nuclear Information System (INIS)

    Vellinger, Céline; Sohm, Bénédicte; Parant, Marc; Immel, Françoise; Usseglio-Polatera, Philippe

    2016-01-01

    mixture previously observed on G. pulex mortality at 10 °C. - Highlights: • We tested comparative proteomics for identifying new biomarkers of chemical exposure. • Both metal interactions and temperature confounding effects were taken into account. • 129 spots have been highlighted as potential Protein Expression Signatures at 10 °C. • Proteomics has high potential but a long way still to go to efficient multi-marker. • Recommendations and precautions for future studies have been presented.

  17. Application of a new procedure for liquid chromatography/mass spectrometry profiling of plasma amino acid-related metabolites and untargeted shotgun proteomics to identify mechanisms and biomarkers of calcific aortic stenosis.

    Science.gov (United States)

    Olkowicz, Mariola; Debski, Janusz; Jablonska, Patrycja; Dadlez, Michal; Smolenski, Ryszard T

    2017-09-29

    Calcific aortic valve stenosis (CAS) increasingly affects our ageing population, but the mechanisms of the disease and its biomarkers are not well established. Recently, plasma amino acid-related metabolite (AA) profiling has attracted attention in studies on pathology and development of biomarkers of cardiovascular diseases, but has not been studied in CAS. To evaluate the potential relationship between CAS and AA metabolome, a new ion-pairing reversed-phase liquid chromatography-tandem mass spectrometry (IP-RPLC-MS/MS) method has been developed and validated for simultaneous determination of 43 AAs in plasma of stenotic patients and age-matched control subjects. Furthermore, untargeted mass spectrometry-based proteomic analysis and confirmatory ELISA assays were performed. The method developed offered high accuracy (intra-assay imprecision averaged 4.4% for all compounds) and sensitivity (LOQ within 0.01-0.5μM). We found that 22 AAs and three AA ratios significantly changed in the CAS group as compared to control. The most pronounced differences were observed in urea cycle-related AAs and branched-chain AA (BCAA)-related AAs. The contents of asymmetric dimethylarginine (ADMA) and its monomethylated derivative (NMMA) were increased by 30-64% with CAS. The arginine/ADMA and Fischer's ratios as well as arginine, homoarginine, ADMA, symmetric dimethylarginine, hydroxyproline, betaine and 3-methylhistidine correlated with cardiac function-related parameters and concomitant systemic factors in the CAS patients. The results of proteomic analysis were consistent with involvement of inflammation, lipid abnormalities, hemostasis and extracellular matrix remodeling in CAS. In conclusion, changes in plasma AA profile and protein pattern that we identified in CAS provide information relevant to pathomechanisms and may deliver new biomarkers of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Air Force Research Laboratory Integrated Omics Research

    Science.gov (United States)

    2015-10-01

    fuel exposures and cognitive fatigue. 15. SUBJECT TERMS biomonitoring, omics, metabonomics, proteomics, genomics, epigenetics, biomarker, toxin...biomarker discovery in a number of toxicology and human performance projects, including jet fuel exposures and cognitive fatigue. INTRODUCTION One of...chemical exposure for U.S. and NATO military personnel46; inhalation and dermal have been shown to represent the primary routes of exposure47 This

  19. Halobacterium salinarum NRC-1 PeptideAtlas: strategies for targeted proteomics

    Science.gov (United States)

    Van, Phu T.; Schmid, Amy K.; King, Nichole L.; Kaur, Amardeep; Pan, Min; Whitehead, Kenia; Koide, Tie; Facciotti, Marc T.; Goo, Young-Ah; Deutsch, Eric W.; Reiss, David J.; Mallick, Parag; Baliga, Nitin S.

    2009-01-01

    The relatively small numbers of proteins and fewer possible posttranslational modifications in microbes provides a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a Peptide Atlas (PA) for 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636,000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has helped highlight plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics. PMID:18652504

  20. Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats

    Directory of Open Access Journals (Sweden)

    Firas H Kobeissy

    2016-11-01

    Full Text Available Traumatic brain injury (TBI represents a critical health problem of which diagnosis, management and treatment remain challenging. TBI is a contributing factor in approximately 1/3 of all injury-related deaths in the United States. The Centers for Disease Control and Prevention (CDC estimate that 1.7 million TBI people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics-systems biology is proving to be a prominent tool in biomarker discovery for central nervous system (CNS injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI model of experimental TBI in rat model to assess the temporal-global proteome changes after acute (1 day and for the first time, subacute (7 days, post-injury time frame using the established CAX-PAGE LC-MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entities, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day and subacute (7 days periods post TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7-days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is amongst the first to assess temporal neuroproteome

  1. Preliminary characterizations of a serum biomarker for sarcoidosis by comparative proteomic approach with tandem-mass spectrometry in ethnic Han Chinese patients

    Directory of Open Access Journals (Sweden)

    Zhang Yuan

    2013-02-01

    Full Text Available Abstract Background The diagnosis of sarcoidosis is still a significant challenge in China because of the need to exclude other diseases including granulomatous infections and malignancies that may be clinically and radiographically similar. The specific aim of the study is to search for serum protein biomarkers of sarcoidosis and to validate their clinical usefulness in differential diagnosis. Methods Serum samples were collected from patients with sarcoidosis (n = 37, and compared to those from patients with tuberculosis (n = 20, other pulmonary diseases (n = 20, and healthy volunteers (n = 20 for determination of sarcoidosis-specific or -associated protein expression profiles. The first part of this study focused on proteomic analysis of serum from patients with sarcoidosis to identify a pattern of peptides capable of differentiating the studied populations using the ClinProt profiling technology based on mass spectrometry. Enzyme Linked Immunosorbent Assay (ELISA was then used to verify corresponding elevation of the serum protein concentration of the potential biomarkers in the same patients sets. Receiver operating characteristic curve (ROC analyses was performed to determine the optimal cutoff value for diagnosis. Immunohistochemistry was carried out to further confirm the protein expression patterns of the biomarkers in lung tissue. Results An unique protein peak of M/Z 3,210 Daltons (Da was found to be differentially expressed between the sarcoidosis and control groups and was identified as the N-terminal peptide of 29 amino acids (94-122 of serum amyloid A (SAA. ELISA confirmed that the serum SAA level was significantly higher in the sarcoidosis group than that of the other 3 control groups (p p  Conclusion This is the first study to investigate serum protein markers in Chinese subjects with sarcoidosis. This study shows that the serum SAA expression profiles were different between the sarcoidosis and non

  2. Proteomics as a Tool for Understanding Schizophrenia

    OpenAIRE

    Martins-de-Souza, Daniel

    2011-01-01

    Schizophrenia is likely to be a multifactorial disorder, consequence of alterations in gene and protein expression since the neurodevelopment that together to environmental factors will trigger the establishment of the disease. In the post-genomic era, proteomics has emerged as a promising strategy for revealing disease and treatment biomarkers as well as a tool for the comprehension of the mechanisms of schizophrenia pathobiology. Here, there is a discussion of the potential pathways and str...

  3. MALDI-TOF mass spectrometry analysis of small molecular weight compounds (under 10 KDa) as biomarkers of rat hearts undergoing arecoline challenge.

    Science.gov (United States)

    Chen, Tung-Sheng; Chang, Mu-Hsin; Kuo, Wei-Wen; Lin, Yueh-Min; Yeh, Yu-Lan; Day, Cecilia Hsuan; Lin, Chien-Chung; Tsai, Fuu-Jen; Tsai, Chang-Hai; Huang, Chih-Yang

    2013-04-01

    Statistical and clinical reports indicate that betel nut chewing is strongly associated with progression of oral cancer because some ingredients in betel nuts are potential cancer promoters, especially arecoline. Early diagnosis for cancer biomarkers is the best strategy for prevention of cancer progression. Several methods are suggested for investigating cancer biomarkers. Among these methods, gel-based proteomics approach is the most powerful and recommended tool for investigating biomarkers due to its high-throughput. However, this proteomics approach is not suitable for screening biomarkers with molecular weight under 10 KDa because of the characteristics of gel electrophoresis. This study investigated biomarkers with molecular weight under 10 KDa in rats with arecoline challenge. The centrifuging vials with membrane (10 KDa molecular weight cut-off) played a crucial role in this study. After centrifuging, the filtrate (containing compounds with molecular weight under 10 KDa) was collected and spotted on a sample plate for MALDI-TOF mass spectrometry analysis. Compared to control, three extra peaks (m/z values were 1553.1611, 1668.2097 and 1740.1832, respectively) were found in sera and two extra peaks were found in heart tissue samples (408.9719 and 524.9961, respectively). These small compounds should play important roles and may be potential biomarker candidates in rats with arecoline. This study successfully reports a mass-based method for investigating biomarker candidates with small molecular weight in different types of sample (including serum and tissue). In addition, this reported method is more time-efficient (1 working day) than gel-based proteomics approach (5~7 working days).

  4. Glycoblotting method allows for rapid and efficient glycome profiling of human Alzheimer's disease brain, serum and cerebrospinal fluid towards potential biomarker discovery.

    Science.gov (United States)

    Gizaw, Solomon T; Ohashi, Tetsu; Tanaka, Masakazu; Hinou, Hiroshi; Nishimura, Shin-Ichiro

    2016-08-01

    Understanding of the significance of posttranslational glycosylation in Alzheimer's disease (AD) is of growing importance for the investigation of the pathogenesis of AD as well as discovery research of the disease-specific serum biomarkers. We designed a standard protocol for the glycoblotting combined with MALDI-TOFMS to perform rapid and quantitative profiling of the glycan parts of glycoproteins (N-glycans) and glycosphingolipids (GSLs) using human AD's post-mortem samples such as brain tissues (dissected cerebral cortices such as frontal, parietal, occipital, and temporal domains), serum and cerebrospinal fluid (CSF). The structural profiles of the major N-glycans released from glycoproteins and the total expression levels of the glycans were found to be mostly similar between the brain tissues of the AD patients and those of the normal control group. In contrast, the expression levels of the serum and CSF protein N-glycans such as bisect-type and multiply branched glycoforms were increased significantly in AD patient group. In addition, the levels of some gangliosides such as GM1, GM2 and GM3 appeared to alter in the AD patient brain and serum samples when compared with the normal control groups. Alteration of the expression levels of major N- and GSL-glycans in human brain tissues, serum and CSF of AD patients can be monitored quantitatively by means of the glycoblotting-based standard protocols. The changes in the expression levels of the glycans derived from the human post-mortem samples uncovered by the standardized glycoblotting method provides potential serum biomarkers in central nervous system disorders and can contribute to the insight into the molecular mechanisms in the pathogenesis of neurodegenerative diseases and future drug discovery. Most importantly, the present preliminary trials using human post-mortem samples of AD patients suggest that large-scale serum glycomics cohort by means of various-types of human AD patients as well as the normal

  5. ALS Biomarkers for Therapy Development: State of the Field & Future Directions

    Science.gov (United States)

    Benatar, Michael; Boylan, Kevin; Jeromin, Andreas; Rutkove, Seward B.; Berry, James; Atassi, Nazem; Bruijn, Lucie

    2015-01-01

    Biomarkers have become the focus of intense research in the field of amyotrophic lateral sclerosis (ALS), with the hope that they might aid therapy development efforts. Notwithstanding the discovery of many candidate biomarkers, none have yet emerged as validated tools for drug development. In this review we present a nuanced view of biomarkers based on the perspective of the FDA; highlight the distinction between discovery and validation; describe existing and emerging resources; review leading biological fluid-based, electrophysiological and neuroimaging candidates relevant to therapy development efforts; discuss lessons learned from biomarker initiatives in related neurodegenerative diseases; and outline specific steps that we, as a field, might take in order to hasten the development and validation of biomarkers that will prove useful in enhancing efforts to develop effective treatments for ALS patients. Most important among these perhaps is the proposal to establish a federated ALS Biomarker Consortium (ABC) in which all interested and willing stakeholders may participate with equal opportunity to contribute to the broader mission of biomarker development and validation. PMID:26574709

  6. Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

    Science.gov (United States)

    Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

    2011-01-01

    Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

  7. Multiplex array proteomics detects increased MMP-8 in CSF after spinal cord injury

    Directory of Open Access Journals (Sweden)

    Light Matthew

    2012-06-01

    Full Text Available Abstract Introduction A variety of methods have been used to study inflammatory changes in the acutely injured spinal cord. Recently novel multiplex assays have been used in an attempt to overcome limitations in numbers of available targets studied in a single experiment. Other technical challenges in developing pre-clinical rodent models to investigate biomarkers in cerebrospinal fluid (CSF include relatively small volumes of sample and low concentrations of target proteins. The primary objective of this study was to characterize the inflammatory profile present in CSF at a subacute time point in a clinically relevant rodent model of traumatic spinal cord injury (SCI. Our other aim was to test a microarray proteomics platform specifically for this application. Methods A 34 cytokine sandwich ELISA microarray was used to study inflammatory changes in CSF samples taken 12 days post-cervical SCI in adult rats. The difference between the median foreground signal and the median background signal was measured. Bonferroni and Benjamini-Hochburg multiple testing corrections were applied to limit the False Discovery Rate (FDR, and a linear mixed model was used to account for repeated measures in the array. Results We report a novel subacute SCI biomarker, elevated levels of matrix metalloproteinase-8 protein in CSF, and discuss application of statistical models designed for multiplex testing. Conclusions Major advantages of this assay over conventional methods include high-throughput format, good sensitivity, and reduced sample consumption. This method can be useful for creating comprehensive inflammatory profiles, and biomarkers can be used in the clinic to assess injury severity and to objectively grade response to therapy.

  8. Radiation Biomarker Research Using Mass Spectrometry

    National Research Council Canada - National Science Library

    Bach, Stephan B; Hubert, Walter

    2007-01-01

    .... This review is intended to give an overview of mass spectrometry and its application to biological systems and biomarker discovery and how that might relate to relevant radiation dosimetry studies...

  9. Comparison of proteomic biomarker panels in urine and serum for ovarian cancer diagnosis

    DEFF Research Database (Denmark)

    Petri, Anette Lykke; Simonsen, Anja Hviid; Høgdall, Estrid

    2010-01-01

    The purposes of this study were to confirm previously found candidate epithelial ovarian cancer biomarkers in urine and to compare a paired serum biomarker panel and a urine biomarker panel from the same study cohort with regard to the receiver operating characteristic curve (ROC) area under the ...

  10. Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

    Science.gov (United States)

    Martyanov, Viktor; Whitfield, Michael L

    2016-01-01

    The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

  11. Risk Factors and Biomarkers of Age-Related Macular Degeneration

    Science.gov (United States)

    Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

    2016-01-01

    A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

  12. Comparative proteomic analysis reveals heart toxicity induced by chronic arsenic exposure in rats

    International Nuclear Information System (INIS)

    Huang, Qingyu; Xi, Guochen; Alamdar, Ambreen; Zhang, Jie; Shen, Heqing

    2017-01-01

    Arsenic is a widespread metalloid in the environment, which poses a broad spectrum of adverse effects on human health. However, a global view of arsenic-induced heart toxicity is still lacking, and the underlying molecular mechanisms remain unclear. By performing a comparative quantitative proteomic analysis, the present study aims to investigate the alterations of proteome profile in rat heart after long-term exposure to arsenic. As a result, we found that the abundance of 81 proteins were significantly altered by arsenic treatment (35 up-regulated and 46 down-regulated). Among these, 33 proteins were specifically associated with cardiovascular system development and function, including heart development, heart morphology, cardiac contraction and dilation, and other cardiovascular functions. It is further proposed that the aberrant regulation of 14 proteins induced by arsenic would disturb cardiac contraction and relaxation, impair heart morphogenesis and development, and induce thrombosis in rats, which is mediated by the Akt/p38 MAPK signaling pathway. Overall, these findings will augment our knowledge of the involved mechanisms and develop useful biomarkers for cardiotoxicity induced by environmental arsenic exposure. - Highlights: • Arsenic exposure has been associated with a number of adverse health effects. • The molecular mechanisms involved in arsenic-induced cardiotoxicity remain unclear. • Differential proteins were identified in arsenic-exposed rat heart by proteomics. • Arsenic induces heart toxicity through the Akt/p38 MAPK signaling pathway. - Label-free quantitative proteomic analysis of rat heart reveals putative mechanisms and biomarkers for arsenic-induced cardiotoxicity.

  13. Proteomic Profiling of Mitochondrial Enzymes during Skeletal Muscle Aging

    Directory of Open Access Journals (Sweden)

    Lisa Staunton

    2011-01-01

    Full Text Available Mitochondria are of central importance for energy generation in skeletal muscles. Expression changes or functional alterations in mitochondrial enzymes play a key role during myogenesis, fibre maturation, and various neuromuscular pathologies, as well as natural fibre aging. Mass spectrometry-based proteomics suggests itself as a convenient large-scale and high-throughput approach to catalogue the mitochondrial protein complement and determine global changes during health and disease. This paper gives a brief overview of the relatively new field of mitochondrial proteomics and discusses the findings from recent proteomic surveys of mitochondrial elements in aged skeletal muscles. Changes in the abundance, biochemical activity, subcellular localization, and/or posttranslational modifications in key mitochondrial enzymes might be useful as novel biomarkers of aging. In the long term, this may advance diagnostic procedures, improve the monitoring of disease progression, help in the testing of side effects due to new drug regimes, and enhance our molecular understanding of age-related muscle degeneration.

  14. NeuCode Proteomics Reveals Bap1 Regulation of Metabolism

    Directory of Open Access Journals (Sweden)

    Joshua M. Baughman

    2016-07-01

    Full Text Available We introduce neutron-encoded (NeuCode amino acid labeling of mice as a strategy for multiplexed proteomic analysis in vivo. Using NeuCode, we characterize an inducible knockout mouse model of Bap1, a tumor suppressor and deubiquitinase whose in vivo roles outside of cancer are not well established. NeuCode proteomics revealed altered metabolic pathways following Bap1 deletion, including profound elevation of cholesterol biosynthetic machinery coincident with reduced expression of gluconeogenic and lipid homeostasis proteins in liver. Bap1 loss increased pancreatitis biomarkers and reduced expression of mitochondrial proteins. These alterations accompany a metabolic remodeling with hypoglycemia, hypercholesterolemia, hepatic lipid loss, and acinar cell degeneration. Liver-specific Bap1 null mice present with fully penetrant perinatal lethality, severe hypoglycemia, and hepatic lipid deficiency. This work reveals Bap1 as a metabolic regulator in liver and pancreas, and it establishes NeuCode as a reliable proteomic method for deciphering in vivo biology.

  15. PCAS – a precomputed proteome annotation database resource

    Directory of Open Access Journals (Sweden)

    Luo Jingchu

    2003-11-01

    Full Text Available Abstract Background Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. Results We report here the development of PCAS (ProteinCentric Annotation System as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome. PCAS is available at http://pak.cbi.pku.edu.cn/proteome/gca.php Conclusion PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms

  16. Identification of 10 Candidate Biomarkers Distinguishing Tuberculous and Malignant Pleural Fluid by Proteomic Methods.

    Science.gov (United States)

    Lee, Chang Youl; Hong, Ji Young; Lee, Myung Goo; Suh, In Bum

    2017-11-01

    Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. We used samples from five patients with transudative pleural effusions for internal standard, five patients with tuberculous pleurisy, and the same numbers of patients having malignant effusions were enrolled in the study. We analyzed the proteins in pleural fluid from patients using a technique that combined two-dimensional liquid-phase electrophoresis and matrix assisted laser desorption/ionization-time of flight-mass spectrometry. We identified a total of 10 proteins with statistical significance. Among 10 proteins, trasthyretin, haptoglobin, metastasis-associated protein 1, t-complex protein 1, and fibroblast growth factor-binding protein 1 were related with malignant pleural effusions and human ceruloplasmin, lysozyme precursor, gelsolin, clusterin C complement lysis inhibitor, and peroxirexdoxin 3 were expressed several times or more in tuberculous pleural effusions. Highly expressed proteins in malignant pleural effusion were associated with carcinogenesis and cell growth, and proteins associated with tuberculous pleural effusion played a role in the response to inflammation and fibrosis. These findings will aid in the development of novel diagnostic tools for tuberculous pleurisy and malignant pleural effusion of lung cancer. © Copyright: Yonsei University College of Medicine 2017

  17. Clinical proteomics identifies urinary CD14 as a potential biomarker for diagnosis of stable coronary artery disease.

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    Min-Yi Lee

    Full Text Available Inflammation plays a key role in coronary artery disease (CAD and other manifestations of atherosclerosis. Recently, urinary proteins were found to be useful markers for reflecting inflammation status of different organs. To identify potential biomarker for diagnosis of CAD, we performed one-dimensional SDS-gel electrophoresis followed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS. Among the proteins differentially expressed in urine samples, monocyte antigen CD14 was found to be consistently expressed in higher amounts in the CAD patients as compared to normal controls. Using enzyme-linked immunosorbent assays to analyze the concentrations of CD14 in urine and serum, we confirmed that urinary CD14 levels were significantly higher in patients (n = 73 with multi-vessel and single vessel CAD than in normal control (n = 35 (P < 0.001. Logistic regression analysis further showed that urinary CD14 concentration level is associated with severity or number of diseased vessels and SYNTAX score after adjustment for potential confounders. Concomitantly, the proportion of CD14+ monocytes was significantly increased in CAD patients (59.7 ± 3.6% as compared with healthy controls (14.9 ± 2.1% (P < 0.001, implicating that a high level of urinary CD14 may be potentially involved in mechanism(s leading to CAD pathogenesis. By performing shotgun proteomics, we further revealed that CD14-associated inflammatory response networks may play an essential role in CAD. In conclusion, the current study has demonstrated that release of CD14 in urine coupled with more CD14+ monocytes in CAD patients is significantly correlated with severity of CAD, pointing to the potential application of urinary CD14 as a novel noninvasive biomarker for large-scale diagnostic screening of susceptible CAD patients.

  18. A proteomic-based characterization of liver metabolism in dairy cows and young pigs

    DEFF Research Database (Denmark)

    Sejersen, Henrik

    This thesis deals with studies on liver metabolism in cows and pigs. Proteome analysis was used to quantify a large number of proteins involved in metabolic pathways. In cows, the objective was to characterize differences in the liver proteome between early lactation dairy cows with low or high...... liver fat content and suggest potential blood-based biomarkers for early detection of fatty liver to substantiate prevention strategies. Our results show that several proteins in liver metabolic pathways are affected by liver fat content and that blood aspartate aminotransferase, ß...

  19. Systematic biomarker discovery and coordinative validation for different primary nephrotic syndromes using gas chromatography-mass spectrometry.

    Science.gov (United States)

    Lee, Jung-Eun; Lee, Yu Ho; Kim, Se-Yun; Kim, Yang Gyun; Moon, Ju-Young; Jeong, Kyung-Hwan; Lee, Tae Won; Ihm, Chun-Gyoo; Kim, Sooah; Kim, Kyoung Heon; Kim, Dong Ki; Kim, Yon Su; Kim, Chan-Duck; Park, Cheol Whee; Lee, Do Yup; Lee, Sang-Ho

    2016-07-01

    The goal of this study is to identify systematic biomarker panel for primary nephrotic syndromes from urine samples by applying a non-target metabolite profiling, and to validate their utility in independent sampling and analysis by multiplex statistical approaches. Nephrotic syndrome (NS) is a nonspecific kidney disorder, which is mostly represented by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous glomerulonephritis (MGN). Since urine metabolites may mirror disease-specific functional perturbations in kidney injury, we examined urine samples for distinctive metabolic changes to identify biomarkers for clinical applications. We developed unbiased multi-component covarianced models from a discovery set with 48 samples (12 healthy controls, 12 MCD, 12 FSGS, and 12 MGN). To extensively validate their diagnostic potential, new batch from 54 patients with primary NS were independently examined a year after. In the independent validation set, the model including citric acid, pyruvic acid, fructose, ethanolamine, and cysteine effectively discriminated each NS using receiver operating characteristic (ROC) analysis except MCD-MGN comparison; nonetheless an additional metabolite multi-composite greatly improved the discrimination power between MCD and MGN. Finally, we proposed the re-constructed metabolic network distinctively dysregulated by the different NSs that may deepen comprehensive understanding of the disease mechanistic, and help the enhanced identification of NS and therapeutic plans for future. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

    Science.gov (United States)

    Lam, Raymond W; Milev, Roumen; Rotzinger, Susan; Andreazza, Ana C; Blier, Pierre; Brenner, Colleen; Daskalakis, Zafiris J; Dharsee, Moyez; Downar, Jonathan; Evans, Kenneth R; Farzan, Faranak; Foster, Jane A; Frey, Benicio N; Geraci, Joseph; Giacobbe, Peter; Feilotter, Harriet E; Hall, Geoffrey B; Harkness, Kate L; Hassel, Stefanie; Ismail, Zahinoor; Leri, Francesco; Liotti, Mario; MacQueen, Glenda M; McAndrews, Mary Pat; Minuzzi, Luciano; Müller, Daniel J; Parikh, Sagar V; Placenza, Franca M; Quilty, Lena C; Ravindran, Arun V; Salomons, Tim V; Soares, Claudio N; Strother, Stephen C; Turecki, Gustavo; Vaccarino, Anthony L; Vila-Rodriguez, Fidel; Kennedy, Sidney H

    2016-04-16

    Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants