Science.gov

Sample records for proteomic safety biomarkers

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

    SciTech Connect

    Amacher, David E.

    2010-05-15

    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

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

    PubMed

    Amacher, David E

    2010-05-15

    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

  3. Proteomic Approaches for Biomarker Panels in Cancer.

    PubMed

    Tanase, Cristiana; Albulescu, Radu; Neagu, Monica

    2016-01-01

    Proteomic technologies remain the main backbone of biomarkers discovery in cancer. The continuous development of proteomic technologies also enlarges the bioinformatics domain, thus founding the main pillars of cancer therapy. The main source for diagnostic/prognostic/therapy monitoring biomarker panels are molecules that have a dual role, being both indicators of disease development and therapy targets. Proteomic technologies, such as mass-spectrometry approaches and protein array technologies, represent the main technologies that can depict these biomarkers. Herein, we will illustrate some of the most recent strategies for biomarker discovery in cancer, including the development of immune-markers and the use of cancer stem cells as target therapy. The challenges of proteomic biomarker discovery need new forms of cross-disciplinary conglomerates that will result in increased and tailored access to treatments for patients; diagnostic companies would benefit from the enhanced co-development of companion diagnostics and pharmaceutical companies. In the technology optimization in biomarkers, immune assays are the leaders of discovery machinery. PMID:26565430

  4. Innovative proteomic approaches for cancer biomarker discovery.

    PubMed

    Faca, Vitor; Krasnoselsky, Alexei; Hanash, Samir

    2007-09-01

    Substantial technological advances in proteomics and related computational science have been made in the past few years. These advances overcome in part the complexity and heterogeneity of the human proteome, permitting quantitative analysis and identification of protein changes associated with tumor development. Here, we discuss some of these advances that are uncovering new cancer biomarkers that have potential to detect cancer at early and curable stages and address remaining challenges. PMID:17907570

  5. Implementation of proteomic biomarkers: making it work

    PubMed Central

    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

  6. Statistical Aspects in Proteomic Biomarker Discovery.

    PubMed

    Jung, Klaus

    2016-01-01

    In the pursuit of a personalized medicine, i.e., the individual treatment of a patient, many medical decision problems are desired to be supported by biomarkers that can help to make a diagnosis, prediction, or prognosis. Proteomic biomarkers are of special interest since they can not only be detected in tissue samples but can also often be easily detected in diverse body fluids. Statistical methods play an important role in the discovery and validation of proteomic biomarkers. They are necessary in the planning of experiments, in the processing of raw signals, and in the final data analysis. This review provides an overview on the most frequent experimental settings including sample size considerations, and focuses on exploratory data analysis and classifier development. PMID:26519185

  7. Proteomic biomarkers in lung cancer.

    PubMed

    Pastor, M D; Nogal, A; Molina-Pinelo, S; Carnero, A; Paz-Ares, L

    2013-09-01

    The correct understanding of tumour development relies on the comprehensive study of proteins. They are the main orchestrators of vital processes, such as signalling pathways, which drive the carcinogenic process. Proteomic technologies can be applied to cancer research to detect differential protein expression and to assess different responses to treatment. Lung cancer is the number one cause of cancer-related death in the world. Mostly diagnosed at late stages of the disease, lung cancer has one of the lowest 5-year survival rates at 15 %. The use of different proteomic techniques such as two-dimensional gel electrophoresis (2D-PAGE), isotope labelling (ICAT, SILAC, iTRAQ) and mass spectrometry may yield new knowledge on the underlying biology of lung cancer and also allow the development of new early detection tests and the identification of changes in the cancer protein network that are associated with prognosis and drug resistance. PMID:23606351

  8. Mining the plasma proteome for cancer biomarkers.

    PubMed

    Hanash, Samir M; Pitteri, Sharon J; Faca, Vitor M

    2008-04-01

    Systematic searches for plasma proteins that are biological indicators, or biomarkers, for cancer are underway. The difficulties caused by the complexity of biological-fluid proteomes and tissue proteomes (which contribute proteins to plasma) and by the extensive heterogeneity among diseases, subjects and levels of sample procurement are gradually being overcome. This is being achieved through rigorous experimental design and in-depth quantitative studies. The expected outcome is the development of panels of biomarkers that will allow early detection of cancer and prediction of the probable response to therapy. Achieving these objectives requires high-quality specimens with well-matched controls, reagent resources, and an efficient process to confirm discoveries through independent validation studies. PMID:18385731

  9. Proteomic identification of biomarkers of vascular injury

    PubMed Central

    Huang, Ngan F; Kurpinski, Kyle; Fang, Qizhi; Lee, Randall J; Li, Song

    2011-01-01

    Predictive biomarkers may be beneficial for detecting, diagnosing, and assessing the risk of restenosis and vascular injury. We utilized proteomic profiling to identify protein markers in the blood following vascular injury, and corroborated the differential protein expression with immunological approaches. Rats underwent carotid artery injury, and plasma was collected after 2 or 5 weeks. Proteomic profiling was carried out by two-dimensional differential in-gel electrophoresis. The differentially expressed plasma proteins were identified by mass spectroscopy and confirmed by immunoblotting. Proteomic profiling by two-dimensional differential in-gel electrophoresis and mass spectroscopy revealed plasma proteins that were differentially expressed at 2 weeks after injury. Among the proteins identified included vitamin D binding protein (VDBP), aldolase A (aldo A), and apolipoproteinE (apoE). Immunoblotting results validated a significant reduction in these proteins in the plasma at 2 or 5 weeks after vascular injury, in comparison to control animals without vascular injury. These findings suggest that VDBP, aldo A, and apoE may be biomarkers for vascular injury, which will have important prognostic and diagnostic implications. PMID:21416056

  10. Infectious Disease Proteome Biomarkers: Final Technical Report

    SciTech Connect

    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.

  11. Proteomics biomarkers for non-small cell lung cancer.

    PubMed

    Kisluk, Joanna; Ciborowski, Michal; Niemira, Magdalena; Kretowski, Adam; Niklinski, Jacek

    2014-12-01

    In the last decade, proteomic analysis has become an integral tool for investigation of tumor biology, complementing the genetic analysis. The idea of proteomics is to characterize proteins by evaluation of their expressions, functions, and interactions. Proteomics may also provide information about post-translational modifications of proteins and evaluate their value as specific disease biomarkers. The major purpose of clinical proteomics studies is to improve diagnostic procedures including the precise evaluation of biological features of tumor cells and to understand the molecular pathogenesis of cancers to invent novel therapeutic strategies and targets. This review briefly describes the latest reports in proteomic studies of NSCLC. It contains a summary of the methods used to detect proteomic markers in different types of biological material and their clinical application as diagnostic, prognostic, and predictive biomarkers compiled on the basis of the most recent literature and our own experience. PMID:25175018

  12. A novel profile biomarker diagnosis for mass spectral proteomics.

    PubMed

    Han, Henry

    2014-01-01

    Mass spectrometry based proteomics technologies have allowed for a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, they face acute challenges from a data reproducibility standpoint, in that no two independent studies have been found to produce the same proteomic patterns. Such reproducibility issues cause the identified biomarker patterns to lose repeatability and prevent real clinical usage. In this work, we propose a profile biomarker approach to overcome this problem from a machine-learning viewpoint by developing a novel derivative component analysis (DCA). As an implicit feature selection algorithm, derivative component analysis enables the separation of true signals from red herrings by capturing subtle data behaviors and removing system noises from a proteomic profile. We further demonstrate its advantages in disease diagnosis by viewing input data as a profile biomarker. The results from our profile biomarker diagnosis suggest an effective solution to overcoming proteomics data's reproducibility problem, present an alternative method for biomarker discovery in proteomics, and provide a good candidate for clinical proteomic diagnosis. PMID:24297560

  13. Recommendations for biomarker identification and qualification in clinical proteomics.

    PubMed

    Mischak, Harald; Allmaier, Günter; Apweiler, Rolf; Attwood, Teresa; Baumann, Marc; Benigni, Ariela; Bennett, Samuel E; Bischoff, Rainer; Bongcam-Rudloff, Erik; Capasso, Giovambattista; Coon, Joshua J; D'Haese, Patrick; Dominiczak, Anna F; Dakna, Mohammed; Dihazi, Hassan; Ehrich, Jochen H; Fernandez-Llama, Patricia; Fliser, Danilo; Frokiaer, Jorgen; Garin, Jerome; Girolami, Mark; Hancock, William S; Haubitz, Marion; Hochstrasser, Denis; Holman, Rury R; Ioannidis, John P A; Jankowski, Joachim; Julian, Bruce A; Klein, Jon B; Kolch, Walter; Luider, Theo; Massy, Ziad; Mattes, William B; Molina, Franck; Monsarrat, Bernard; Novak, Jan; Peter, Karlheinz; Rossing, Peter; Sánchez-Carbayo, Marta; Schanstra, Joost P; Semmes, O John; Spasovski, Goce; Theodorescu, Dan; Thongboonkerd, Visith; Vanholder, Raymond; Veenstra, Timothy D; Weissinger, Eva; Yamamoto, Tadashi; Vlahou, Antonia

    2010-08-25

    Clinical proteomics has yielded some early positive results-the identification of potential disease biomarkers-indicating the promise for this analytical approach to improve the current state of the art in clinical practice. However, the inability to verify some candidate molecules in subsequent studies has led to skepticism among many clinicians and regulatory bodies, and it has become evident that commonly encountered shortcomings in fundamental aspects of experimental design mainly during biomarker discovery must be addressed in order to provide robust data. In this Perspective, we assert that successful studies generally use suitable statistical approaches for biomarker definition and confirm results in independent test sets; in addition, we describe a brief set of practical and feasible recommendations that we have developed for investigators to properly identify and qualify proteomic biomarkers, which could also be used as reporting requirements. Such recommendations should help put proteomic biomarker discovery on the solid ground needed for turning the old promise into a new reality. PMID:20739680

  14. Proteomics, biomarkers, and HIV‐1: A current perspective

    PubMed Central

    Donnelly, Maire Rose

    2015-01-01

    Despite more than three decades of extensive research, HIV‐1 infection although well controlled with cART, remains incurable. Multifactorial complexity of the viral life‐cycle poses great challenges in understanding molecular mechanisms underlying this infection and the development of biomarkers, which we hope will lead us to its eradication. For a more in‐depth understanding of how the virus interacts with host target cells, T cells and macrophages, proteomic profiling techniques that offer strategies to investigate the proteome in its entirety were employed. Here, we review proteomic studies related to HIV‐1 infection and discuss perspectives and limitations of proteomic and systems biology approaches in future studies. PMID:26033875

  15. Secretome proteomics for discovery of cancer biomarkers.

    PubMed

    Makridakis, Manousos; Vlahou, Antonia

    2010-11-10

    "Secretome" is referred to as the rich, complex set of molecules secreted from living cells. In a less strict definition frequently followed in "secretome" studies, the term also includes molecules shed from the surface of living cells. Proteins of secretome (will be referred to as secreted) play a key role in cell signaling, communication and migration. The need for developing more effective cancer biomarkers and therapeutic modalities has led to the study of cancer cell secretome as a means to identify and characterize diagnostic and prognostic markers and potential drug and therapeutic targets. Significant technological advances in the field of proteomics during the last two decades have greatly facilitated research towards this direction. Nevertheless, secretome analysis still faces some difficulties mainly related to sample collection and preparation. The goal of this article is to provide an overview of the main findings from the analysis of cancer cell secretome. Specifically, we focus on the presentation of main methodological approaches that have been developed for the study of secreted proteins and the results thereof from the analysis of secretome in different types of malignancies; special emphasis is given on correlation of findings with protein expression in body fluids. PMID:20637910

  16. Definition of Valid Proteomic Biomarkers: A Bayesian Solution

    NASA Astrophysics Data System (ADS)

    Harris, Keith; Girolami, Mark; Mischak, Harald

    Clinical proteomics is suffering from high hopes generated by reports on apparent biomarkers, most of which could not be later substantiated via validation. This has brought into focus the need for improved methods of finding a panel of clearly defined biomarkers. To examine this problem, urinary proteome data was collected from healthy adult males and females, and analysed to find biomarkers that differentiated between genders. We believe that models that incorporate sparsity in terms of variables are desirable for biomarker selection, as proteomics data typically contains a huge number of variables (peptides) and few samples making the selection process potentially unstable. This suggests the application of a two-level hierarchical Bayesian probit regression model for variable selection which assumes a prior that favours sparseness. The classification performance of this method is shown to improve that of the Probabilistic K-Nearest Neighbour model.

  17. Inconvenient truth: cancer biomarker development by using proteomics.

    PubMed

    Kondo, Tadashi

    2014-05-01

    A biomarker is a crucial tool for measuring the progress of disease and the effects of treatment for better clinical outcomes in cancer patients. Diagnostic, predictive, and prognostic biomarkers are required in various clinical settings. The proteome, a functional translation of the genome, is considered a rich source of biomarkers; therefore, sizable time and funding have been spent in proteomics to develop biomarkers. Although significant progress has been made in technologies toward comprehensive protein expression profiling, and many biomarker candidates published, none of the reported biomarkers have proven to be beneficial for cancer patients. The present deceleration in biomarker research can be attributed to technical limitations. Additional efforts are required to further technical progress; however, there are many examples demonstrating that problems in biomarker research are not so much with the technology but in the study design. In the study of biomarkers for early diagnosis, candidates are screened and validated by comparing cases and controls of similar sample size, and the low prevalence of disease is often ignored. Although it is reasonable to take advantage of multiple rather than single biomarkers when studying diverse disease mechanisms, the annotation of individual components of reported multiple biomarkers does not often explain the variety of molecular events underlying the clinical observations. In tissue biomarker studies, the heterogeneity of disease tissues and pathological observations are often not considered, and tissues are homogenized as a whole for protein extraction. In addition to the challenge of technical limitations, the fundamental aspects of biomarker development in a disease study need to be addressed. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:23896458

  18. Perspective: Proteomic approach to detect biomarkers of human growth hormone

    PubMed Central

    Ding, Juan; List, Edward O.; Okada, Shigeru; Kopchick, John J.

    2009-01-01

    Several serum biomarkers for recombinant human growth hormone (rhGH) have been established, however, none alone or in combination have generate a specific, sensitive, and reproducible ‘kit’ for the detection of rhGH abuse. Thus, the search for additional GH specific biomarkers continues. In this review, we focus on the use of proteomics in general and 2-dimensional electrophoresis (2-DE) in particular for the discovery of new GH induced serum biomarkers. Also, we review some of the protocols involved in 2DE. Finally, the possibility of tissues other than blood for biomarker discovery is discussed. PMID:19501004

  19. Proteomic global profiling for cancer biomarker discovery.

    PubMed

    Faca, Vitor; Wang, Hong; Hanash, Samir

    2009-01-01

    The ultimate goal of cancer molecular diagnostics is the development of simple tests to predict cancer risk, detect cancer early, classify tumors, and monitor response to therapy. Proteomics is well suited for these tasks. However, there are substantial challenges that need to be met to identify the most informative markers using proteomics. Approaches for in-depth quantitative proteomic analysis based on isotopic labeling and protein fractionation are presented in this chapter. PMID:19241042

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

    PubMed

    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. PMID:25556002

  1. A proteomics perspective: from animal welfare to food safety.

    PubMed

    Bassols, Anna; Turk, Romana; Roncada, Paola

    2014-03-01

    A fundamental issue of farm animal welfare is to keep animals clinically healthy, without disease or stress, particularly in intensive breeding, in order to produce safe and quality food. This issue is highly relevant for the food industry worldwide as they are directly linked to public health and welfare. The aim of this review is to explore how proteomics can assess and improve the knowledge useful for the strategic management of products of animal origin. Useful indications are provided about the latest proteomics tools for the development of novel biotechnologies serving the public health. The multivariate proteomics approach provides the bases for the discovery of biomarkers useful to investigate adaptation syndromes and oxidative stress. These two responses represent the milestones for the study of animal welfare. Moreover their implementation in the characterization and standardization of raw materials, process development, and quality and safety control of the final product of animal origin represents the current frontier in official surveillance and tests development. PMID:24555902

  2. Genomic and Proteomic Biomarkers for Cancer: A Multitude of Opportunities

    PubMed Central

    Tainsky, Michael A.

    2009-01-01

    Biomarkers are molecular indicators of a biological status, and as biochemical species can be assayed to evaluate the presence of cancer and therapeutic interventions. Through a variety of mechanisms cancer cells provide the biomarker material for their own detection. Biomarkers may be detectable in the blood, other body fluids, or tissues. The expectation is that the level of an informative biomarker is related to the specific type of disease present in the body. Biomarkers have potential both as diagnostic indicators and monitors of the effectiveness of clinical interventions. Biomarkers are also able to stratify cancer patients to the most appropriate treatment. Effective biomarkers for the early detection of cancer should provide a patient with a better outcome which in turn will translate into more efficient delivery of healthcare. Technologies for the early detection of cancer have resulted in reductions in disease-associated mortalities from cancers that are otherwise deadly if allowed to progress. Such screening technologies have proven that early detection will decrease the morbidity and mortality from cancer. An emerging theme in biomarker research is the expectation that panels of biomarker analytes rather than single markers will be needed to have sufficient sensitivity and specificity for the presymptomatic detection of cancer. Biomarkers may provide prognostic information of disease enabling interventions using targeted therapeutic agents as well as course-corrections in cancer treatment. Novel genomic, proteomic and metabolomic technologies are being used to discover and validate tumor biomarkers individually and in panels. PMID:19406210

  3. Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

    PubMed Central

    Lakhan, Shaheen Emmanuel

    2006-01-01

    Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science. PMID:16846510

  4. Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

    PubMed Central

    2014-01-01

    Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic–based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research. PMID:24679154

  5. Proteomics of gliomas: Initial biomarker discovery and evolution of technology

    PubMed Central

    Kalinina, Juliya; Peng, Junmin; Ritchie, James C.; Van Meir, Erwin G.

    2011-01-01

    Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers. PMID:21852429

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

    PubMed Central

    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

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

    PubMed

    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

  8. Proteomics for discovery of candidate colorectal cancer biomarkers

    PubMed Central

    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

  9. Proteomics and biomarkers in clinical trials for drug development.

    PubMed

    Lee, Jung-min; Han, Jasmine J; Altwerger, Gary; Kohn, Elise C

    2011-11-18

    Proteomics allows characterization of protein structure and function, protein-protein interactions, and peptide modifications. It has given us insight into the perturbations of signaling pathways within tumor cells and has improved the discovery of new therapeutic targets and possible indicators of response to and duration of therapy. The discovery, verification, and validation of novel biomarkers are critical in streamlining clinical development of targeted compounds, and directing rational treatments for patients whose tumors are dependent upon select signaling pathways. Studies are now underway in many diseases to examine the immune or inflammatory proteome, vascular proteome, cancer or disease proteome, and other subsets of the specific pathology microenvironment. Successful assay verification and biological validation of such biomarkers will speed development of potential agents to targetable dominant pathways and lead to selection of individuals most likely to benefit. Reconsideration of analytical and clinical trials methods for acquisition, examination, and translation of proteomics data must occur before we march further into future of drug development. PMID:21570499

  10. Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

    PubMed Central

    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

    2010-01-01

    Background The interrogation of proteomes (“proteomics”) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. Methodology/Principal Findings 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. Conclusions/Significance 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

  11. Identification of Biomarkers for Endometriosis Using Clinical Proteomics

    PubMed Central

    Zhao, Yang; Liu, Ya-Nan; Li, Yi; Tian, Li; Ye, Xue; Cui, Heng; Chang, Xiao-Hong

    2015-01-01

    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. PMID:25673457

  12. In-depth quantitative proteomics for pancreatic cancer biomarker discovery.

    PubMed

    Faca, Vitor; Hanash, Samir

    2007-09-01

    Pancreatic adenocarcinoma is one of the leading causes of cancer-related death due to common presentation at an advanced stage. Although early detection and screening are likely to improve outcome, effective strategies are lacking. Proteomics holds substantial promise for the identification of blood-based biomarkers. Discovery strategies that have been investigated include analysis of tumor tissue and tumor cells, biologic fluids and serum and plasma for the identification of circulating biomarkers. A promising, complementary strategy consists of harnessing the immune response to tumor antigens for detecting pancreatic cancer at an early stage through a seropositive response to pancreatic cancer antigens. In addition, mouse models of pancreatic cancer may represent a rich source of candidate biomarkers applicable to humans. Although much work remains to be done, the findings so far are encouraging with respect to prospects for early detection and effective diagnosis. PMID:23489270

  13. Utilizing human blood plasma for proteomic biomarker discovery

    SciTech Connect

    Jacobs, Jon M.; Adkins, Joshua N.; Qian, Weijun; Liu, Tao; Shen, Yufeng; Camp, David G.; Smith, Richard D.

    2005-08-01

    Application of proteomic biomarker discovery efforts towards human plasma entails both incredible clinical potential as well as significant challenges to overcome the intrinsic characteristics of plasma. The dynamic range of proteins within plasma, coupled with the likely presence of potential biomarkers in the more difficult to detect lower abundance range has driven the development of various methodologies and strategies to maximize the possible detective dynamic range within this biofluid. Discussed is the array of the available approaches currently used by our laboratory and others to utilized human plasma as a viable medium for biomarker discovery efforts. Various separation, depletion, enrichment, and quantitative efforts have resulted in a measurable improvement in the detectability of the low abundance fraction of proteins but more advances are needed to bridge the gap between the current range of detection and what remains unobservable to fully maximize the potential of this sample.

  14. Assessing the statistical validity of proteomics based biomarkers.

    PubMed

    Smit, Suzanne; van Breemen, Mariëlle J; Hoefsloot, Huub C J; Smilde, Age K; Aerts, Johannes M F G; de Koster, Chris G

    2007-06-01

    A strategy is presented for the statistical validation of discrimination models in proteomics studies. Several existing tools are combined to form a solid statistical basis for biomarker discovery that should precede a biochemical validation of any biomarker. These tools consist of permutation tests, single and double cross-validation. The cross-validation steps can simply be combined with a new variable selection method, called rank products. The strategy is especially suited for the low-samples-to-variables-ratio (undersampling) case, as is often encountered in proteomics and metabolomics studies. As a classification method, principal component discriminant analysis is used; however, the methodology can be used with any classifier. A dataset containing serum samples from Gaucher patients and healthy controls serves as a test case. Double cross-validation shows that the sensitivity of the model is 89% and the specificity 90%. Potential putative biomarkers are identified using the novel variable selection method. Results from permutation tests support the choice of double cross-validation as the tool for determining error rates when the modelling procedure involves a tuneable parameter. This shows that even cross-validation does not guarantee unbiased results. The validation of discrimination models with a combination of permutation tests and double cross-validation helps to avoid erroneous results which may result from the undersampling. PMID:17512828

  15. Postgenomics biomarkers for rabies—the next decade of proteomics.

    PubMed

    Mehta, Shraddha M; Banerjee, Shefali M; Chowdhary, Abhay S

    2015-02-01

    Rabies is one of the oldest diseases known to mankind. The pathogenic mechanisms by which rabies virus infection leads to development of neurological disease and death are still poorly understood. Analysis of rabies-infected proteomes may help identify novel biomarkers for antemortem diagnosis of the disease and target molecules for therapeutic intervention. This article offers a literature synthesis and critique of the differentially expressed proteins that have been previously reported from various in vitro/in vivo model systems and naturally infected clinical specimens. The emerging data collectively indicate that, in addition to the obvious alterations in proteins involved in synapse and neurotransmission, a majority of cytoskeletal proteins are relevant as well, providing evidence of neuronal degeneration. An interesting observation is that certain molecules, such as KPNA4, could be potential diagnostic markers for rabies. Importantly, proteomic studies with body fluids such as cerebrospinal fluid provide newer insights into antemortem diagnosis. In order to develop a complete integrative biology picture, it is essential to analyze the entire CNS (region-wise) and in particular, the brain. We suggest the use of laboratory animal models over cell culture systems using a combinatorial proteomics approach, as the former is a closer match to the actual host response. While most studies have focused on the terminal stages of the disease in mice, a time-series analysis could provide deeper insights for therapy. Postgenomics technologies such as proteomics warrant more extensive applications in rabies and similar diseases impacting public health around the world. PMID:25611201

  16. The proteome of Hypobaric Induced Hypoxic Lung: Insights from Temporal Proteomic Profiling for Biomarker Discovery

    PubMed Central

    Ahmad, Yasmin; Sharma, Narendra K.; Ahmad, Mohammad Faiz; Sharma, Manish; Garg, Iti; Srivastava, Mousami; Bhargava, Kalpana

    2015-01-01

    Exposure to high altitude induces physiological responses due to hypoxia. Lungs being at the first level to face the alterations in oxygen levels are critical to counter and balance these changes. Studies have been done analysing pulmonary proteome alterations in response to exposure to hypobaric hypoxia. However, such studies have reported the alterations at specific time points and do not reflect the gradual proteomic changes. These studies also identify the various biochemical pathways and responses induced after immediate exposure and the resolution of these effects in challenge to hypobaric hypoxia. In the present study, using 2-DE/MS approach, we attempt to resolve these shortcomings by analysing the proteome alterations in lungs in response to different durations of exposure to hypobaric hypoxia. Our study thus highlights the gradual and dynamic changes in pulmonary proteome following hypobaric hypoxia. For the first time, we also report the possible consideration of SULT1A1, as a biomarker for the diagnosis of high altitude pulmonary edema (HAPE). Higher SULT1A1 levels were observed in rats as well as in humans exposed to high altitude, when compared to sea-level controls. This study can thus form the basis for identifying biomarkers for diagnostic and prognostic purposes in responses to hypobaric hypoxia. PMID:26022216

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

    PubMed Central

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

    2015-01-01

    STUDY QUESTION Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). SUMMARY ANSWER Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. WHAT IS KNOWN ALREADY Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. STUDY DESIGN, SIZE, DURATION 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. PARTICIPANTS/MATERIALS, SETTING, METHODS 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. MAIN RESULTS AND THE ROLE OF CHANCE 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. LIMITATIONS, REASONS FOR CAUTION 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. WIDER IMPLICATIONS OF THE FINDINGS 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

  18. Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review

    PubMed Central

    Kimhofer, T; Fye, H; Taylor-Robinson, S; Thursz, M; Holmes, E

    2015-01-01

    Hepatocellular carcinoma (HCC) ranks third in overall global cancer-related mortality. Symptomatic presentation often means advanced disease where potentially curative treatment options become very limited. Numerous international guidelines propose the routine monitoring of those with the highest risk factors for the condition in order to diagnose potential tumourigenesis early. To aid this, the fields of metabonomic- and proteomic-based biomarker discovery have applied advanced tools to identify early changes in protein and metabolite expression in HCC patients vs controls. With robust validation, it is anticipated that from these candidates will rise a high-performance non-invasive test able to diagnose early HCC and related conditions. This review gathers the numerous markers proposed by studies using mass spectrometry and proton nuclear magnetic resonance spectroscopy and evaluates areas of consistency as well as discordance. PMID:25826224

  19. Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review.

    PubMed

    Kimhofer, T; Fye, H; Taylor-Robinson, S; Thursz, M; Holmes, E

    2015-03-31

    Hepatocellular carcinoma (HCC) ranks third in overall global cancer-related mortality. Symptomatic presentation often means advanced disease where potentially curative treatment options become very limited. Numerous international guidelines propose the routine monitoring of those with the highest risk factors for the condition in order to diagnose potential tumourigenesis early. To aid this, the fields of metabonomic- and proteomic-based biomarker discovery have applied advanced tools to identify early changes in protein and metabolite expression in HCC patients vs controls. With robust validation, it is anticipated that from these candidates will rise a high-performance non-invasive test able to diagnose early HCC and related conditions. This review gathers the numerous markers proposed by studies using mass spectrometry and proton nuclear magnetic resonance spectroscopy and evaluates areas of consistency as well as discordance. PMID:25826224

  20. Current application of proteomics in biomarker discovery for inflammatory bowel disease.

    PubMed

    Chan, Patrick Py; Wasinger, Valerie C; Leong, Rupert W

    2016-02-15

    Recently, the field of proteomics has rapidly expanded in its application towards clinical research with objectives ranging from elucidating disease pathogenesis to discovering clinical biomarkers. As proteins govern and/or reflect underlying cellular processes, the study of proteomics provides an attractive avenue for research as it allows for the rapid identification of protein profiles in a biological sample. Inflammatory bowel disease (IBD) encompasses several heterogeneous and chronic conditions of the gastrointestinal tract. Proteomic technology provides a powerful means of addressing major challenges in IBD today, especially for identifying biomarkers to improve its diagnosis and management. This review will examine the current state of IBD proteomics research and its use in biomarker research. Furthermore, we also discuss the challenges of translating proteomic research into clinically relevant tools. The potential application of this growing field is enormous and is likely to provide significant insights towards improving our future understanding and management of IBD. PMID:26909226

  1. Current application of proteomics in biomarker discovery for inflammatory bowel disease

    PubMed Central

    Chan, Patrick PY; Wasinger, Valerie C; Leong, Rupert W

    2016-01-01

    Recently, the field of proteomics has rapidly expanded in its application towards clinical research with objectives ranging from elucidating disease pathogenesis to discovering clinical biomarkers. As proteins govern and/or reflect underlying cellular processes, the study of proteomics provides an attractive avenue for research as it allows for the rapid identification of protein profiles in a biological sample. Inflammatory bowel disease (IBD) encompasses several heterogeneous and chronic conditions of the gastrointestinal tract. Proteomic technology provides a powerful means of addressing major challenges in IBD today, especially for identifying biomarkers to improve its diagnosis and management. This review will examine the current state of IBD proteomics research and its use in biomarker research. Furthermore, we also discuss the challenges of translating proteomic research into clinically relevant tools. The potential application of this growing field is enormous and is likely to provide significant insights towards improving our future understanding and management of IBD. PMID:26909226

  2. Quantitative proteomics for identifying biomarkers for tuberculous meningitis

    PubMed Central

    2012-01-01

    Introduction Tuberculous meningitis is a frequent extrapulmonary disease caused by Mycobacterium tuberculosis and is associated with high mortality rates and severe neurological sequelae. In an earlier study employing DNA microarrays, we had identified genes that were differentially expressed at the transcript level in human brain tissue from cases of tuberculous meningitis. In the current study, we used a quantitative proteomics approach to discover protein biomarkers for tuberculous meningitis. Methods To compare brain tissues from confirmed cased of tuberculous meningitis with uninfected brain tissue, we carried out quantitative protein expression profiling using iTRAQ labeling and LC-MS/MS analysis of SCX fractionated peptides on Agilent’s accurate mass QTOF mass spectrometer. Results and conclusions Through this approach, we identified both known and novel differentially regulated molecules. Those described previously included signal-regulatory protein alpha (SIRPA) and protein disulfide isomerase family A, member 6 (PDIA6), which have been shown to be overexpressed at the mRNA level in tuberculous meningitis. The novel overexpressed proteins identified in our study included amphiphysin (AMPH) and neurofascin (NFASC) while ferritin light chain (FTL) was found to be downregulated in TBM. We validated amphiphysin, neurofascin and ferritin light chain using immunohistochemistry which confirmed their differential expression in tuberculous meningitis. Overall, our data provides insights into the host response in tuberculous meningitis at the molecular level in addition to providing candidate diagnostic biomarkers for tuberculous meningitis. PMID:23198679

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

    PubMed Central

    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

  4. A Tool for Biomarker Discovery in the Urinary Proteome: A Manually Curated Human and Animal Urine Protein Biomarker Database*

    PubMed Central

    Shao, Chen; Li, Menglin; Li, Xundou; Wei, Lilong; Zhu, Lisi; Yang, Fan; Jia, Lulu; Mu, Yi; Wang, Jiangning; Guo, Zhengguang; Zhang, Dan; Yin, Jianrui; Wang, Zhigang; Sun, Wei; Zhang, Zhengguo; Gao, Youhe

    2011-01-01

    Urine is an important source of biomarkers. A single proteomics assay can identify hundreds of differentially expressed proteins between disease and control samples; however, the ability to select biomarker candidates with the most promise for further validation study remains difficult. A bioinformatics tool that allows accurate and convenient comparison of all of the existing related studies can markedly aid the development of this area. In this study, we constructed the Urinary Protein Biomarker (UPB) database to collect existing studies of urinary protein biomarkers from published literature. To ensure the quality of data collection, all literature was manually curated. The website (http://122.70.220.102/biomarker) allows users to browse the database by disease categories and search by protein IDs in bulk. Researchers can easily determine whether a biomarker candidate has already been identified by another group for the same disease or for other diseases, which allows for the confidence and disease specificity of their biomarker candidate to be evaluated. Additionally, the pathophysiological processes of the diseases can be studied using our database with the hypothesis that diseases that share biomarkers may have the same pathophysiological processes. Because of the natural relationship between urinary proteins and the urinary system, this database may be especially suitable for studying the pathogenesis of urological diseases. Currently, the database contains 553 and 275 records compiled from 174 and 31 publications of human and animal studies, respectively. We found that biomarkers identified by different proteomic methods had a poor overlap with each other. The differences between sample preparation and separation methods, mass spectrometers, and data analysis algorithms may be influencing factors. Biomarkers identified from animal models also overlapped poorly with those from human samples, but the overlap rate was not lower than that of human proteomics

  5. Searching for the Non-Invasive Biomarker Holy Grail: Are Urine Proteomics the Answer?

    PubMed Central

    Voss, Joachim; Goo, Young Ah; Cain, Kevin; Woods, Nancy; Jarrett, Monica; Smith, Lynne; Shulman, Robert; Heitkemper, Margaret

    2013-01-01

    Recently, biobehavioral nursing scientists have focused attention on the search for biomarkers or biological signatures to identify patients at risk for various health problems and poor disease outcomes. In response to the national impetus for biomarker discovery, the measurement of biological fluids and tissues has become increasingly sophisticated. Urine proteomics in particular, may hold great promise for biobehavioral-focused nursing scientists for examination of symptom- and syndrome- related research questions. Urine proteins are easily accessible secreted proteins that provide a direct and indirect window into bodily functions. Advances in proteomics and biomarker discovery provide new opportunities to conduct research studies with banked and fresh urine to benefit diagnosis, prognosis, and evaluate outcomes in various disease populations. This paper provides a review of proteomics and a rationale for specifically utilizing urine proteomics in biobehavioral research. It addresses as well some of the specific challenges involved in data collection and sample preparation. PMID:21586496

  6. A Systems Approach to the Proteomic Identification of Novel Cancer Biomarkers

    PubMed Central

    Pitteri, Sharon; Hanash, Sam

    2010-01-01

    The proteomics field has experienced rapid growth with technologies achieving ever increasing accuracy, sensitivity, and throughput, and with availability of computational tools to address particular applications. Given that the proteome represents the most functional component encoded for in the genome, a systems approach to disease investigations and biomarker identification benefits substantially from integration of proteome level studies. Here we present proteomic approaches that have allowed systematic searches for potential cancer markers by integrating cancer cell profiling with additional sources of data, as illustrated with recent studies of ovarian cancer. PMID:20534908

  7. Mass Spectrometry-based Proteomics and Peptidomics for Systems Biology and Biomarker Discovery

    PubMed Central

    Cunningham, Robert; Ma, Di; Li, Lingjun

    2013-01-01

    The scientific community has shown great interest in the field of mass spectrometry-based proteomics and peptidomics for its applications in biology. Proteomics technologies have evolved to produce large datasets of proteins or peptides involved in various biological and disease progression processes producing testable hypothesis for complex biological questions. This review provides an introduction and insight to relevant topics in proteomics and peptidomics including biological material selection, sample preparation, separation techniques, peptide fragmentation, post-translation modifications, quantification, bioinformatics, and biomarker discovery and validation. In addition, current literature and remaining challenges and emerging technologies for proteomics and peptidomics are presented. PMID:24504115

  8. Discovery of putative pancreatic cancer biomarkers using subcellular proteomics.

    PubMed

    McKinney, Kimberly Q; Lee, Yong-Yook; Choi, Hyun-Su; Groseclose, Gale; Iannitti, David A; Martinie, John B; Russo, Mark W; Lundgren, Deborah H; Han, David K; Bonkovsky, Herbert L; Hwang, Sun-Il

    2011-01-01

    Pancreatic cancer (PC) is a highly aggressive disease that frequently remains undetected until it has progressed to an advanced, systemic stage. Successful treatment of PC is hindered by the lack of early detection. The application of proteomic analysis to PC combined with subcellular fractionation has introduced new possibilities in the field of biomarker discovery. We utilized matched pairs of pancreas tumor and non-tumor pancreas from patients undergoing tumor resection. The tissues were treated to obtain cellular protein fractions corresponding to cytosol, membrane, nucleus and cytoskeleton. The fractions were then separated by molecular weight and digested with trypsin, followed by liquid chromatography and tandem mass spectrometry. The spectra obtained were searched using Sequest engine and combined into a single analysis file to obtain a semi-quantitative number, spectral count, using Scaffold software. We identified 2393 unique proteins in non-tumor and cancer pancreas. Utilizing PLGEM statistical analysis we determined 104 proteins were significantly changed in cancer. From these, we further validated four secreted proteins that are up-regulated in cancer and have potential for development as minimally-invasive diagnostic markers. We conclude that subcellular fractionation followed by gel electrophoresis and tandem mass spectrometry is a powerful strategy for identification of differentially expressed proteins in pancreatic cancer. PMID:20807598

  9. Impact of biomarker development on drug safety assessment

    SciTech Connect

    Marrer, Estelle; Dieterle, Frank

    2010-03-01

    Drug safety has always been a key aspect of drug development. Recently, the Vioxx case and several cases of serious adverse events being linked to high-profile products have increased the importance of drug safety, especially in the eyes of drug development companies and global regulatory agencies. Safety biomarkers are increasingly being seen as helping to provide the clarity, predictability, and certainty needed to gain confidence in decision making: early-stage projects can be stopped quicker, late-stage projects become less risky. Public and private organizations are investing heavily in terms of time, money and manpower on safety biomarker development. An illustrative and 'door opening' safety biomarker success story is the recent recognition of kidney safety biomarkers for pre-clinical and limited translational contexts by FDA and EMEA. This milestone achieved for kidney biomarkers and the 'know how' acquired is being transferred to other organ toxicities, namely liver, heart, vascular system. New technologies and molecular-based approaches, i.e., molecular pathology as a complement to the classical toolbox, allow promising discoveries in the safety biomarker field. This review will focus on the utility and use of safety biomarkers all along drug development, highlighting the present gaps and opportunities identified in organ toxicity monitoring. A last part will be dedicated to safety biomarker development in general, from identification to diagnostic tests, using the kidney safety biomarkers success as an illustrative example.

  10. Impact of biomarker development on drug safety assessment.

    PubMed

    Marrer, Estelle; Dieterle, Frank

    2010-03-01

    Drug safety has always been a key aspect of drug development. Recently, the Vioxx case and several cases of serious adverse events being linked to high-profile products have increased the importance of drug safety, especially in the eyes of drug development companies and global regulatory agencies. Safety biomarkers are increasingly being seen as helping to provide the clarity, predictability, and certainty needed to gain confidence in decision making: early-stage projects can be stopped quicker, late-stage projects become less risky. Public and private organizations are investing heavily in terms of time, money and manpower on safety biomarker development. An illustrative and "door opening" safety biomarker success story is the recent recognition of kidney safety biomarkers for pre-clinical and limited translational contexts by FDA and EMEA. This milestone achieved for kidney biomarkers and the "know how" acquired is being transferred to other organ toxicities, namely liver, heart, vascular system. New technologies and molecular-based approaches, i.e., molecular pathology as a complement to the classical toolbox, allow promising discoveries in the safety biomarker field. This review will focus on the utility and use of safety biomarkers all along drug development, highlighting the present gaps and opportunities identified in organ toxicity monitoring. A last part will be dedicated to safety biomarker development in general, from identification to diagnostic tests, using the kidney safety biomarkers success as an illustrative example. PMID:20036272

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

    PubMed

    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. PMID:25626423

  12. Proteomic-driven biomarker discovery in gestational diabetes mellitus: a review.

    PubMed

    Singh, Apoorva; Subramani, Elavarasan; Datta Ray, Chaitali; Rapole, Srikanth; Chaudhury, Koel

    2015-09-01

    Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy and it affects 18% of pregnant women worldwide. GDM is considered a high-risk state which may lead to type II diabetes which is associated with an increase in a number of interrelated adverse perinatal outcomes. Given the fact that the progress of a successful pregnancy is dependent on the intricate communication between several biological molecules, identification of the proteomic profile perturbations in women with GDM is expected to help in understanding the disease pathogenesis and also discovery of clinical biomarker(s). In recent years, both gel-free and gel-based proteomics have been extensively investigated for improving maternal and child health. Although there are several reports integrating various aspects of proteomics in pregnancy related diseases such as preeclampsia, extensive Pubmed search shows no review so far on the application of proteomics in gestational diabetes. In this review, we focus on various high-throughput proteomic technologies for the identification of unique biosignatures and biomarkers responsible for the early prediction of GDM. Further, different analytical strategies and biological samples involved in proteomic analysis of this pregnancy-related disease are discussed.This article is part of a Special Issue entitled: Proteomics in India. PMID:26216595

  13. Proteomics of pediatric heart failure: from traditional biomarkers to new discovery strategies.

    PubMed

    Xu, Mingguo; Ramirez-Correa, Genaro A; Murphy, Anne M

    2015-08-01

    Heart failure in children is a complex clinical syndrome with multiple aetiologies. The underlying disorders that lead to heart failure in children differ significantly from those in adults. Some clinical biomarkers for heart failure status and prognosis appear to be useful in both age groups. This review outlines the use and the present status of biomarkers for heart failure in paediatric cardiology. Furthermore, clinical scenarios in which development of new biomarkers might address management or prognosis are discussed. Finally, strategies for proteomic discovery of novel biomarkers and application to practice are described. PMID:26377710

  14. Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches*

    PubMed Central

    Morris, Jeffrey S.

    2012-01-01

    In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry (Cromwell) and 2D gel electrophoresis (Pinnacle) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods

  15. Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

    PubMed

    Morris, Jeffrey S

    2012-01-01

    In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry (Cromwell) and 2D gel electrophoresis (Pinnacle) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods

  16. Status and Prospects for Discovery and Verification of New Biomarkers of Cardiovascular Disease by Proteomics

    PubMed Central

    Gerszten, Robert E.; Asnani, Aarti; Carr, Steven A.

    2012-01-01

    Despite unmet needs for cardiovascular biomarkers, few new protein markers have been FDA approved for the diagnosis or screening of cardiovascular diseases. Mass spectrometry (MS)-based proteomics technologies are capable of identifying hundreds to thousands of proteins in cells, tissues and biofluids. Proteomics may therefore provide the opportunity to elucidate new biomarkers and pathways without a prior known association with cardiovascular disease. However, important obstacles remain. In this review we focus on emerging techniques that may form a coherently integrated pipeline to overcome present limitations to both the discovery and validation processes. PMID:21817166

  17. Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

    PubMed Central

    Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. Leigh; Liebler, Daniel C.; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L.; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Boja, Emily S.

    2014-01-01

    Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC), with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance, and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

  18. Towards an integrated proteomic and glycomic approach to finding cancer biomarkers.

    PubMed

    Taylor, Allen D; Hancock, William S; Hincapie, Marina; Taniguchi, Naoyuki; Hanash, Samir M

    2009-01-01

    Advances in mass spectrometry have had a great impact on the field of proteomics. A major challenge of proteomic analysis has been the elucidation of glycan modifications of proteins in complex proteomes. Glycosylation is the most structurally elaborate and diverse type of protein post-translational modification and, because of this, proteomics and glycomics have largely developed independently. However, given that such a large proportion of proteins contain glycan modifications, and that these may be important for their function or may produce biologically relevant protein variation, a convergence of the fields of glycomics and proteomics would be highly desirable. Here we review the current status of glycoproteomic efforts, focusing on the identification of glycoproteins as cancer biomarkers. PMID:19519948

  19. Towards an integrated proteomic and glycomic approach to finding cancer biomarkers

    PubMed Central

    2009-01-01

    Advances in mass spectrometry have had a great impact on the field of proteomics. A major challenge of proteomic analysis has been the elucidation of glycan modifications of proteins in complex proteomes. Glycosylation is the most structurally elaborate and diverse type of protein post-translational modification and, because of this, proteomics and glycomics have largely developed independently. However, given that such a large proportion of proteins contain glycan modifications, and that these may be important for their function or may produce biologically relevant protein variation, a convergence of the fields of glycomics and proteomics would be highly desirable. Here we review the current status of glycoproteomic efforts, focusing on the identification of glycoproteins as cancer biomarkers. PMID:19519948

  20. Urine Proteome Biomarkers in Kidney Diseases. I. Limits, Perspectives, and First Focus on Normal Urine

    PubMed Central

    Santucci, Laura; Bruschi, Maurizio; Candiano, Giovanni; Lugani, Francesca; Petretto, Andrea; Bonanni, Alice; Ghiggeri, Gian Marco

    2016-01-01

    Urine proteome is a potential source of information in renal diseases, and it is considered a natural area of investigation for biomarkers. Technology developments have markedly increased the power analysis on urinary proteins, and it is time to confront methodologies and results of major studies on the topics. This is a first part of a series of reviews that will focus on the urine proteome as a site for detecting biomarkers of renal diseases; the theme of the first review concerns methodological aspects applied to normal urine. Main issues are techniques for urine pretreatment, separation of exosomes, use of combinatorial peptide ligand libraries, mass spectrometry approaches, and analysis of data sets. Available studies show important differences, suggesting a major confounding effect of the technologies utilized for analysis. The objective is to obtain consensus about which approaches should be utilized for studying urine proteome in renal diseases. PMID:26997865

  1. Identification of Serum Biomarkers for Gastric Cancer Diagnosis Using a Human Proteome Microarray.

    PubMed

    Yang, Lina; Wang, Jingfang; Li, Jianfang; Zhang, Hainan; Guo, Shujuan; Yan, Min; Zhu, Zhenggang; Lan, Bin; Ding, Youcheng; Xu, Ming; Li, Wei; Gu, Xiaonian; Qi, Chong; Zhu, Heng; Shao, Zhifeng; Liu, Bingya; Tao, Sheng-Ce

    2016-02-01

    We aimed to globally discover serum biomarkers for diagnosis of gastric cancer (GC). GC serum autoantibodies were discovered and validated using serum samples from independent patient cohorts encompassing 1,401 participants divided into three groups, i.e. healthy, GC patients, and GC-related disease group. To discover biomarkers for GC, the human proteome microarray was first applied to screen specific autoantibodies in a total of 87 serum samples from GC patients and healthy controls. Potential biomarkers were identified via a statistical analysis protocol. Targeted protein microarrays with only the potential biomarkers were constructed and used to validate the candidate biomarkers using 914 samples. To provide further validation, the abundance of autoantibodies specific to the biomarker candidates was analyzed using enzyme-linked immunosorbent assays. Receiver operating characteristic curves were generated to evaluate the diagnostic accuracy of the serum biomarkers. Finally, the efficacy of prognosis efficacy of the final four biomarkers was evaluated by analyzing the clinical records. The final panel of biomarkers consisting of COPS2, CTSF, NT5E, and TERF1 provides high diagnostic power, with 95% sensitivity and 92% specificity to differentiate GC patients from healthy individuals. Prognosis analysis showed that the panel could also serve as independent predictors of the overall GC patient survival. The panel of four serum biomarkers (COPS2, CTSF, NT5E, and TERF1) could serve as a noninvasive diagnostic index for GC, and the combination of them could potentially be used as a predictor of the overall GC survival rate. PMID:26598640

  2. Recent advances in biomarker discovery in solid organ transplant by proteomics

    PubMed Central

    Sigdel, Tara K; Sarwal, Minnie M

    2012-01-01

    The identification and clinical use of more sensitive and specific biomarkers in the field of solid organ transplantation is an urgent need in medicine. Solid organ transplantation has seen improvements in the short-term survival of transplanted organs due to recent advancements in immunosuppressive therapy. However, the currently available methods of allograft monitoring are not optimal. Recent advancements in assaying methods for biomolecules such as genes, mRNA and proteins have helped to identify surrogate biomarkers that can be used to monitor the transplanted organ. These high-throughput ‘omic’ methods can help researchers to significantly speed up the identification and the validation steps, which are crucial factors for biomarker discovery efforts. Still, the progress towards identifying more sensitive and specific biomarkers remains a great deal slower than expected. In this article, we have evaluated the current status of biomarker discovery using proteomics tools in different solid organ transplants in recent years. This article summarizes recent reports and current status, along with the hurdles in efficient biomarker discovery of protein biomarkers using proteomics approaches. Finally, we will touch upon personalized medicine as a future direction for better management of transplanted organs, and provide what we think could be a recipe for success in this field. PMID:22087656

  3. CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics

    PubMed Central

    Coon, Joshua J.; Zürbig, Petra; Dakna, Mohammed; Dominiczak, Anna F.; Decramer, Stéphane; Fliser, Danilo; Frommberger, Moritz; Golovko, Igor; Good, David M.; Herget-Rosenthal, Stefan; Jankowski, Joachim; Julian, Bruce A.; Kellmann, Markus; Kolch, Walter; Massy, Ziad; Novak, Jan; Rossing, Kasper; Schanstra, Joost P.; Schiffer, Eric; Theodorescu, Dan; Vanholder, Raymond; Weissinger, Eva M.; Mischak, Harald; Schmitt-Kopplin, Philippe

    2010-01-01

    Owing to its availability, ease of collection, and correlation with pathophysiology of diseases, urine is an attractive source for clinical proteomics. However, many proteomic studies have had only limited clinical impact, due to factors such as modest numbers of subjects, absence of disease controls, small numbers of defined biomarkers, and diversity of analytical platforms. Therefore, it is difficult to merge biomarkers from different studies into a broadly applicable human urinary proteome database. Ideally, the methodology for defining the biomarkers should combine a reasonable analysis time with high resolution, thereby enabling the profiling of adequate samples and recognition of sufficient features to yield robust diagnostic panels. Capillary electrophoresis coupled to mass spectrometry (CE-MS), which was used to analyze urine samples from healthy subjects and patients with various diseases, is a suitable approach for this task. The database of these datasets compiled from the urinary peptides enabled the diagnosis, classification, and monitoring of a wide range of diseases. CE-MS exhibits excellent performance for biomarker discovery and allows subsequent biomarker sequencing independent of the separation platform. This approach may elucidate the pathogenesis of many diseases, and better define especially renal and urological disorders at the molecular level. PMID:20130789

  4. Identification of cancer protein biomarkers using proteomic techniques

    SciTech Connect

    Mor, Gil G; Ward, David C; Bray-Ward, Patricia

    2015-03-10

    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.

  5. Identification of cancer protein biomarkers using proteomic techniques

    DOEpatents

    Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

    2010-02-23

    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.

  6. Plasma Proteomics Biomarkers in Alzheimer's Disease: Latest Advances and Challenges.

    PubMed

    Perneczky, Robert; Guo, Liang-Hao

    2016-01-01

    The recent paradigm shift towards a more biologically oriented definition of Alzheimer's disease (AD) in clinical settings increases the need for sensitive biomarkers that can be applied in population-based settings. Blood plasma is easily accessible and contains a large number of proteins related to cerebral processes. It is therefore an ideal candidate for AD biomarker discovery. The present chapter provides an overview of the current research landscape in relation to blood-based AD biomarkers. Both clinical and methodological issues are covered. A brief summary is given on two relevant laboratory techniques to ascertain blood biomarker changes due to AD; methodological and clinical challenges in the field are also discussed. PMID:26235089

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

    SciTech Connect

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

    2008-11-15

    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)

  8. Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges

    PubMed Central

    2013-01-01

    Tremendous efforts have been made over the past few decades to discover novel cancer biomarkers for use in clinical practice. However, a striking discrepancy exists between the effort directed toward biomarker discovery and the number of markers that make it into clinical practice. One of the confounding issues in translating a novel discovery into clinical practice is that quite often the scientists working on biomarker discovery have limited knowledge of the analytical, diagnostic, and regulatory requirements for a clinical assay. This review provides an introduction to such considerations with the aim of generating more extensive discussion for study design, assay performance, and regulatory approval in the process of translating new proteomic biomarkers from discovery into cancer diagnostics. We first describe the analytical requirements for a robust clinical biomarker assay, including concepts of precision, trueness, specificity and analytical interference, and carryover. We next introduce the clinical considerations of diagnostic accuracy, receiver operating characteristic analysis, positive and negative predictive values, and clinical utility. We finish the review by describing components of the FDA approval process for protein-based biomarkers, including classification of biomarker assays as medical devices, analytical and clinical performance requirements, and the approval process workflow. While we recognize that the road from biomarker discovery, validation, and regulatory approval to the translation into the clinical setting could be long and difficult, the reward for patients, clinicians and scientists could be rather significant. PMID:24088261

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

    PubMed Central

    Gaudreau, Pierre-Olivier; Stagg, John; Soulières, Denis; Saad, Fred

    2016-01-01

    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. PMID:27168728

  10. Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

    PubMed Central

    Wan-Ibrahim, Wan I; Singh, Vivek A; Hashim, Onn H; Abdul-Rahman, Puteri S

    2015-01-01

    Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed. PMID:26581086

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

    PubMed

    Gaudreau, Pierre-Olivier; Stagg, John; Soulières, Denis; Saad, Fred

    2016-01-01

    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. PMID:27168728

  12. Analytical Validation Considerations of Multiplex Mass-Spectrometry-Based Proteomic Platforms for Measuring Protein Biomarkers

    PubMed Central

    2015-01-01

    Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein–protein interaction networks and signaling pathways underlying the disease), “staggers” to make a significant impact with only an average ∼1.5 protein biomarkers per year approved by the FDA over the past 15–20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years. PMID:25171765

  13. Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

    PubMed

    Boja, Emily S; Fehniger, Thomas E; Baker, Mark S; Marko-Varga, György; Rodriguez, Henry

    2014-12-01

    Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years. PMID:25171765

  14. Proteomic profiling of cerebrospinal fluid identifies biomarkers for amyotrophic lateral sclerosis

    PubMed Central

    Ranganathan, Srikanth; Williams, Eric; Ganchev, Philip; Gopalakrishnan, Vanathi; Lacomis, David; Urbinelli, Leo; Newhall, Kristyn; Cudkowicz, Merit E.; Brown, Robert H.; Bowser, Robert

    2006-01-01

    Amyotrophic lateral sclerosis (ALS) is characterized by degeneration of motor neurons. We tested the hypothesis that proteomic analysis will identify protein biomarkers that provide insight into disease pathogenesis and are diagnostically useful. To identify ALS specific biomarkers, we compared the proteomic profile of cerebrospinal fluid (CSF) from ALS and control subjects using surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). We identified 30 mass ion peaks with statistically significant (p < 0.01) differences between control and ALS subjects. Initial analysis with a rule-learning algorithm yielded biomarker panels with diagnostic predictive value as subsequently assessed using an independent set of coded test subjects. Three biomarkers were identified that are either decreased (transthyretin, cystatin C) or increased (carboxy-terminal fragment of neuroendocrine protein 7B2) in ALS CSF. We validated the SELDI-TOF-MS results for transthyretin and cystatin C by immunoblot and immunohistochemistry using commercially available antibodies. These findings identify a panel of CSF protein biomarkers for ALS. PMID:16313519

  15. Candidate-based proteomics in the search for biomarkers of cardiovascular disease

    PubMed Central

    Anderson, Leigh

    2005-01-01

    The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

  16. Identification of prosaposin and transgelin as potential biomarkers for gallbladder cancer using quantitative proteomics

    PubMed Central

    Sahasrabuddhe, Nandini A.; Barbhuiya, Mustafa A.; Bhunia, Shushruta; Subbannayya, Tejaswini; Gowda, Harsha; Advani, Jayshree; Shrivastav, Braj R.; Navani, Sanjay; Leal, Pamela; Roa, Juan Carlos; Chaerkady, Raghothama; Gupta, Sanjeev; Chatterjee, Aditi; Pandey, Akhilesh; Tiwari, Pramod K.

    2015-01-01

    Gallbladder cancer is an uncommon but lethal malignancy with particularly high incidence in Chile, India, Japan and China. There is a paucity of unbiased large-scale studies investigating molecular basis of gallbladder cancer. To systematically identify differentially regulated proteins in gallbladder cancer, iTRAQ-based quantitative proteomics of gallbladder cancer was carried out using Fourier transform high resolution mass spectrometry. Of the 2575 proteins identified, proteins upregulated in gallbladder cancer included several lysosomal proteins such as prosaposin, cathepsin Z and cathepsin H. Downregulated proteins included serine protease HTRA1 and transgelin, which have been reported to be downregulated in several other cancers. Novel biomarker candidates including prosaposin and transgelin were validated to be upregulated and downregulated, respectively, in gallbladder cancer using tissue microarrays. Our study provides the first large scale proteomic characterization of gallbladder cancer which will serve as a resource for future discovery of biomarkers for gallbladder cancer. PMID:24657443

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

    PubMed Central

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn; Zhang, Zhen-Yu; Gu, Yu-Mei; Kuznetsova, Tatiana; Nkuipou-Kenfack, Esther; Mischak, Harald; Staessen, Jan A.

    2016-01-01

    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 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 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. Conclusion 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. PMID:27308822

  18. Proteomic profiling of human sera for discovery of potential biomarkers to monitor abstinence from alcohol abuse

    PubMed Central

    Lai, Xianyin; Liangpunsakul, Suthat; Li, Kaigang; Witzmann, Frank A.

    2015-01-01

    Although numerous biomarkers or biomarker candidates have been discovered to detect levels of drinking and intervals of time after last drinking episode, only a few biomarkers have been applied to monitor abstinence in a longer interval (≥ 6 weeks) from alcohol abuse. Considering sample sources, sensitivity, and specificity, new biomarkers from blood with better accuracy are needed. To address this, serum proteomic profiles were compared between pre- and post- treatment samples from subjects seeking treatment for alcohol abuse and dependence in an intensive 6-week daily outpatient program using high-abundance plasma protein immunodepletion and LC-MS/MS techniques. Protein identification, quantification, candidate biomarker selection, and prioritization analyses were carried out. Among the 246 quantified serum proteins, abundance of 13 and 45 proteins in female and male subjects were significantly changed (p ≤ 0.05), respectively. Of these biomarker candidate proteins, 2 (female) and 8 (male) proteins were listed in category 1, with high area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, and fold change. In summary, several new biomarker candidates have been identified to monitor abstinence from alcohol abuse. PMID:25475211

  19. Integration of metabolomics and proteomics in multiple sclerosis: From biomarkers discovery to personalized medicine.

    PubMed

    Del Boccio, Piero; Rossi, Claudia; di Ioia, Maria; Cicalini, Ilaria; Sacchetta, Paolo; Pieragostino, Damiana

    2016-04-01

    Personalized medicine is the science of individualized prevention and therapy. In the last decade, advances in high-throughput approaches allowed the development of proteomic and metabolomic studies in evaluating the association of genetic and phenotypic variability with disease sensitivity and analgesic response. These considerations have more value in case of multiple sclerosis (MuS), a multifactorial disease with high heterogeneity in clinical course and treatment response. In this review, we reported and updated about proteomic and metabolomic studies for the research of new candidate biomarkers in MuS, and difficulties in their clinical applications. We focused especially on the description of both "omics" approaches that, once integrated, may synergically describe pathophysiology conditions. To prove this assumption, we rebuilt interaction between proteins and metabolites described in the literature as potential biomarkers for MuS, and a pathway analysis of these molecules was performed. The result of such speculation demonstrated a strong convergence of proteomic and metabolomic results in this field, showing also a poorness of available tools for incorporating "omics" approaches. In conclusion, the integration of Metabolomics and Proteomics may allow a more complete characterization of such a heterogeneous disease, providing further insights into personalized healthcare. PMID:27061322

  20. Potential biomarkers associated with diabetic glomerulopathy through proteomics.

    PubMed

    Hsu, Yung-Chien; Lei, Chen-Chou; Ho, Cheng; Shih, Ya-Hsueh; Lin, Chun-Liang

    2015-01-01

    Diabetic nephropathy (DN) is characterized by the development of progressive glomerulosclerotic lesions gradually leading to an increasing loss of functioning kidney parenchyma. Relatively little proteomic research of isolated glomeruli of experimental animal models has been done so far. Isolated glomerular proteomics is an innovative tool that potentially detects simultaneous expressions of glomeruli in diabetic pathological contexts. We compared the isolated glomerular profiles of rats with and without diabetes. The proteins in the aliquots of glomeruli were subjected to two-dimensional gel electrophoresis. The protein spots were matched and quantified using an imaging analysis system. The peptide mass fingerprints were identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry and a bioinformation search. We found that diabetes increased collagen type I and collagen type IV levels in diabetic glomeruli when compared to normal control group using Dynabeads. We found that rats with diabetes had significantly higher abundance of the Protein disulfide isomerase associated 3, Aspartoacylase-3,3-hydroxymethyl-3-methylglutaryl-Coenzyme A lyase, Lactamase beta 2 and Agmat protein. However, diabetic glomeruli in rats had significantly lower levels of the Regucalcin, rCG52140, Aldo-keto reductase family 1, Peroxiredoxin 1, and l-arginine: glycine amidinotransferase. These proteins of interest were reported to modulate disturbances in the homeostasis of endoplasmic reticulum stress, disturbance of inflammatory and fibrinogenic activities, impairing endothelial function, and dysregulation in the antioxidation capacity/oxidative stress in several tissue types under pathological contexts. Taken together, our high-throughput isolated glomerular proteomic findings indicated that multiple pathological reactions presumably occurred in DN. PMID:26364511

  1. ProfileDB: a resource for proteomics and cross-omics biomarker discovery.

    PubMed

    Bauer, Chris; Glintschert, Alexander; Schuchhardt, Johannes

    2014-05-01

    The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:24270047

  2. Cerebrospinal fluid proteomics and protein biomarkers in frontotemporal lobar degeneration: Current status and future perspectives.

    PubMed

    Oeckl, Patrick; Steinacker, Petra; Feneberg, Emily; Otto, Markus

    2015-07-01

    Frontotemporal lobar degeneration (FTLD) comprises a spectrum of rare neurodegenerative diseases with an estimated prevalence of 15-22 cases per 100,000 persons including the behavioral variant of frontotemporal dementia (bvFTD), progressive non-fluent aphasia (PNFA), semantic dementia (SD), FTD with motor neuron disease (FTD-MND), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). The pathogenesis of the diseases is still unclear and clinical diagnosis of FTLD is hampered by overlapping symptoms within the FTLD subtypes and with other neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Intracellular protein aggregates in the brain are a major hallmark of FTLD and implicate alterations in protein metabolism or function in the disease's pathogenesis. Cerebrospinal fluid (CSF) which surrounds the brain can be used to study changes in neurodegenerative diseases and to identify disease-related mechanisms or neurochemical biomarkers for diagnosis. In the present review, we will give an overview of the current literature on proteomic studies in CSF of FTLD patients. Reports of targeted and unbiased proteomic approaches are included and the results are discussed in regard of their informative value about disease pathology and the suitability to be used as diagnostic biomarkers. Finally, we will give some future perspectives on CSF proteomics and a list of candidate biomarkers which might be interesting for validation in further studies. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology. PMID:25526887

  3. Urinary proteomic shotgun approach for identification of potential acute rejection biomarkers in renal transplant recipients

    PubMed Central

    2012-01-01

    Background Acute rejection (AR) episodes in renal transplant recipients are suspected when plasma creatinine is elevated and other potential causes out ruled. Graft biopsies are however needed for definite diagnosis. Non-invasive AR-biomarkers is an unmet clinical need. The urinary proteome is an interesting source in the search for such a biomarker in this population. Methods In this proof of principle study, serial urine samples in the early post transplant phase from 6 patients with biopsy verified acute rejections and 6 age-matched controls without clinical signs of rejection were analyzed by shotgun proteomics. Results Eleven proteins fulfilled predefined criteria for regulation in association with AR. They presented detectable regulation already several days before clinical suspicion of AR (increased plasma creatinine). The regulated proteins could be grouped by their biological function; proteins related to growth and proteins related to immune response. Growth-related proteins (IGFBP7, Vasorin, EGF and Galectin-3-binding protein) were significantly up-regulated in association with AR (P = 0.03) while proteins related to immune response (MASP2, C3, CD59, Ceruloplasmin, PiGR and CD74) tended to be up-regulated ( P = 0.13). Conclusion The use of shotgun proteomics provides a robust and sensitive method for identification of potentially predictive urinary biomarkers of AR. Further validation of the current findings is needed to establish their potential clinical role with regards to clinical AR diagnosis. Trial registration ClinicalTrials.gov number NCT00139009 PMID:23369437

  4. Biomarkers for pancreatic cancer: Recent achievements in proteomics and genomics through classical and multivariate statistical methods

    PubMed Central

    Marengo, Emilio; Robotti, Elisa

    2014-01-01

    Pancreatic cancer (PC) is one of the most aggressive and lethal neoplastic diseases. A valid alternative to the usual invasive diagnostic tools would certainly be the determination of biomarkers in peripheral fluids to provide less invasive tools for early diagnosis. Nowadays, biomarkers are generally investigated mainly in peripheral blood and tissues through high-throughput omics techniques comparing control vs pathological samples. The results can be evaluated by two main strategies: (1) classical methods in which the identification of significant biomarkers is accomplished by monovariate statistical tests where each biomarker is considered as independent from the others; and (2) multivariate methods, taking into consideration the correlations existing among the biomarkers themselves. This last approach is very powerful since it allows the identification of pools of biomarkers with diagnostic and prognostic performances which are superior to single markers in terms of sensitivity, specificity and robustness. Multivariate techniques are usually applied with variable selection procedures to provide a restricted set of biomarkers with the best predictive ability; however, standard selection methods are usually aimed at the identification of the smallest set of variables with the best predictive ability and exhaustivity is usually neglected. The exhaustive search for biomarkers is instead an important alternative to standard variable selection since it can provide information about the etiology of the pathology by producing a comprehensive set of markers. In this review, the most recent applications of the omics techniques (proteomics, genomics and metabolomics) to the identification of exploratory biomarkers for PC will be presented with particular regard to the statistical methods adopted for their identification. The basic theory related to classical and multivariate methods for identification of biomarkers is presented and then, the most recent applications in

  5. Targeted proteomics for biomarker discovery and validation of hepatocellular carcinoma in hepatitis C infected patients

    PubMed Central

    Mustafa, Gul M; Larry, Denner; Petersen, John R; Elferink, Cornelis J

    2015-01-01

    Hepatocellular carcinoma (HCC)-related mortality is high because early detection modalities are hampered by inaccuracy, expense and inherent procedural risks. Thus there is an urgent need for minimally invasive, highly specific and sensitive biomarkers that enable early disease detection when therapeutic intervention remains practical. Successful therapeutic intervention is predicated on the ability to detect the cancer early. Similar unmet medical needs abound in most fields of medicine and require novel methodological approaches. Proteomic profiling of body fluids presents a sensitive diagnostic tool for early cancer detection. Here we describe such a strategy of comparative proteomics to identify potential serum-based biomarkers to distinguish high-risk chronic hepatitis C virus infected patients from HCC patients. In order to compensate for the extraordinary dynamic range in serum proteins, enrichment methods that compress the dynamic range without surrendering proteome complexity can help minimize the problems associated with many depletion methods. The enriched serum can be resolved using 2D-difference in-gel electrophoresis and the spots showing statistically significant changes selected for identification by liquid chromatography-tandem mass spectrometry. Subsequent quantitative verification and validation of these candidate biomarkers represent an obligatory and rate-limiting process that is greatly enabled by selected reaction monitoring (SRM). SRM is a tandem mass spectrometry method suitable for identification and quantitation of target peptides within complex mixtures independent on peptide-specific antibodies. Ultimately, multiplexed SRM and dynamic multiple reaction monitoring can be utilized for the simultaneous analysis of a biomarker panel derived from support vector machine learning approaches, which allows monitoring a specific disease state such as early HCC. Overall, this approach yields high probability biomarkers for clinical validation in

  6. Biomarker discovery for inflammatory bowel disease, using proteomic serum profiling.

    PubMed

    Meuwis, Marie-Alice; Fillet, Marianne; Geurts, Pierre; de Seny, Dominique; Lutteri, Laurence; Chapelle, Jean-Paul; Bours, Vincent; Wehenkel, Louis; Belaiche, Jacques; Malaise, Michel; Louis, Edouard; Merville, Marie-Paule

    2007-05-01

    Crohn's disease and ulcerative colitis known as inflammatory bowel diseases (IBD) are chronic immuno-inflammatory pathologies of the gastrointestinal tract. These diseases are multifactorial, polygenic and of unknown etiology. Clinical presentation is non-specific and diagnosis is based on clinical, endoscopic, radiological and histological criteria. Novel markers are needed to improve early diagnosis and classification of these pathologies. We performed a study with 120 serum samples collected from patients classified in 4 groups (30 Crohn, 30 ulcerative colitis, 30 inflammatory controls and 30 healthy controls) according to accredited criteria. We compared protein sera profiles obtained with a Surface Enhanced Laser Desorption Ionization-Time of Flight-Mass Spectrometer (SELDI-TOF-MS). Data analysis with univariate process and a multivariate statistical method based on multiple decision trees algorithms allowed us to select some potential biomarkers. Four of them were identified by mass spectrometry and antibody based methods. Multivariate analysis generated models that could classify samples with good sensitivity and specificity (minimum 80%) discriminating groups of patients. This analysis was used as a tool to classify peaks according to differences in level on spectra through the four categories of patients. Four biomarkers showing important diagnostic value were purified, identified (PF4, MRP8, FIBA and Hpalpha2) and two of these: PF4 and Hpalpha2 were detected in sera by classical methods. SELDI-TOF-MS technology and use of the multiple decision trees method led to protein biomarker patterns analysis and allowed the selection of potential individual biomarkers. Their downstream identification may reveal to be helpful for IBD classification and etiology understanding. PMID:17258689

  7. Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

    PubMed Central

    Atrih, A; Mudaliar, M A V; Zakikhani, P; Lamont, D J; Huang, J T-J; Bray, S E; Barton, G; Fleming, S; Nabi, G

    2014-01-01

    Background: Proteomics-based approaches for biomarker discovery are promising strategies used in cancer research. We present state-of-art label-free quantitative proteomics method to assess proteome of renal cell carcinoma (RCC) compared with noncancer renal tissues. Methods: Fresh frozen tissue samples from eight primary RCC lesions and autologous adjacent normal renal tissues were obtained from surgically resected tumour-bearing kidneys. Proteins were extracted by complete solubilisation of tissues using filter-aided sample preparation (FASP) method. Trypsin digested proteins were analysed using quantitative label-free proteomics approach followed by data interpretation and pathways analysis. Results: A total of 1761 proteins were identified and quantified with high confidence (MASCOT ion score threshold of 35 and P-value <0.05). Of these, 596 proteins were identified as differentially expressed between cancer and noncancer tissues. Two upregulated proteins in tumour samples (adipose differentiation-related protein and Coronin 1A) were further validated by immunohistochemistry. Pathway analysis using IPA, KOBAS 2.0, DAVID functional annotation and FLink tools showed enrichment of many cancer-related biological processes and pathways such as oxidative phosphorylation, glycolysis and amino acid synthetic pathways. Conclusions: Our study identified a number of differentially expressed proteins and pathways using label-free proteomics approach in RCC compared with normal tissue samples. Two proteins validated in this study are the focus of on-going research in a large cohort of patients. PMID:24548857

  8. Proteomic profiling in MPTP monkey model for early Parkinson disease biomarker discovery.

    PubMed

    Lin, Xiangmin; Shi, Min; Masilamoni, Jeyaraj Gunasingh; Dator, Romel; Movius, James; Aro, Patrick; Smith, Yoland; Zhang, Jing

    2015-07-01

    Identification of reliable and robust biomarkers is crucial to enable early diagnosis of Parkinson disease (PD) and monitoring disease progression. While imperfect, the slow, chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced non-human primate animal model system of parkinsonism is an abundant source of pre-motor or early stage PD biomarker discovery. Here, we present a study of a MPTP rhesus monkey model of PD that utilizes complementary quantitative iTRAQ-based proteomic, glycoproteomics and phosphoproteomics approaches. We compared the glycoprotein, non-glycoprotein, and phosphoprotein profiles in the putamen of asymptomatic and symptomatic MPTP-treated monkeys as well as saline injected controls. We identified 86 glycoproteins, 163 non-glycoproteins, and 71 phosphoproteins differentially expressed in the MPTP-treated groups. Functional analysis of the data sets inferred the biological processes and pathways that link to neurodegeneration in PD and related disorders. Several potential biomarkers identified in this study have already been translated for their usefulness in PD diagnosis in human subjects and further validation investigations are currently under way. In addition to providing potential early PD biomarkers, this comprehensive quantitative proteomic study may also shed insights regarding the mechanisms underlying early PD development. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology. PMID:25617661

  9. Proteomic profiling in MPTP monkey model for early Parkinson disease biomarker discovery

    PubMed Central

    Lin, Xiangmin; Shi, Min; Gunasingh Masilamoni, Jeyaraj; Dator, Romel; Movius, James; Aro, Patrick; Smith, Yoland; Zhang, Jing

    2015-01-01

    Identification of reliable and robust biomarkers is crucial to enable early diagnosis of Parkinson disease (PD) and monitoring disease progression. While imperfect, the slow, chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced non-human primate animal model system of parkinsonism is an abundant source of pre-motor or early stage PD biomarker discovery. Here, we present a study of a MPTP rhesus monkey model of PD that utilizes complementary quantitative iTRAQ-based proteomic, glycoproteomics and phosphoproteomics approaches. We compared the glycoprotein, non-glycoprotein, and phosphoprotein profiles in the putamen of asymptomatic and symptomatic MPTP-treated monkeys as well as saline injected controls. We identified 86 glycoproteins, 163 non-glycoproteins, and 71 phosphoproteins differentially expressed in the MPTP-treated groups. Functional analysis of the data sets inferred the biological processes and pathways that link to neurodegeneration in PD and related disorders. Several potential biomarkers identified in this study have already been translated for their usefulness in PD diagnosis in human subjects and further validation investigations are currently under way. In addition to providing potential early PD biomarkers, this comprehensive quantitative proteomic study may also shed insights regarding the mechanisms underlying early PD development. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology. PMID:25617661

  10. Data Fusion in Metabolomics and Proteomics for Biomarker Discovery.

    PubMed

    Blanchet, Lionel; Smolinska, Agnieszka

    2016-01-01

    Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry. Each method has inherent advantages and drawbacks, but they are complementary in terms of biological information.The fusion of different measurements is a complex topic. We describe here a framework allowing combining multiple data sets, provided by different analytical platforms. For each platform, the relevant information is extracted in the first step. The obtained latent variables are then fused and further analyzed. The influence of the original variables is then calculated back and interpreted. PMID:26519180

  11. We are what we eat: food safety and proteomics.

    PubMed

    D'Alessandro, Angelo; Zolla, Lello

    2012-01-01

    In this review, we lead the reader through the evolution of proteomics application to the study of quality control in production processes of foods (including food of plant origin and transgenic plants in particular, but also meat, wine and beer, and milk) and food safety (screening for foodborne pathogens). These topics are attracting a great deal of attention, especially in recent years, when the international community has become increasingly aware of the central role of food quality and safety and their influence on the health of end-consumers. Early proteomics studies in the field of food research were mainly aimed at performing exploratory analyses of food (bovine, swine, chicken, or lamb meat, but also transgenic food such as genetically modified maize, for example) and beverages (wine), with the goal of improving the quality of the end-products. Recently, developments in the field of proteomics have also allowed the study of safety issues, as the technical advantages of sensitive techniques such as mass spectrometry have guaranteed a faster and improved individuation of food contaminating pathogens with unprecedented sensitivity and specificity. PMID:21992580

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

    PubMed Central

    Lee, Sun Eun; West, Keith P.; Cole, Robert N.; Schulze, Kerry J.; Christian, Parul; Wu, Lee Shu-Fune; Yager, James D.; Groopman, John; Ruczinski, Ingo

    2015-01-01

    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 inflammation for

  13. Proteome analysis of biomarkers in the cerebrospinal fluid of neuromyelitis optica patients

    PubMed Central

    Bai, Shumei; Guo, Xuxiao; Qin, Zhaoyu; Wang, Banqin; Li, Xiaohong; Qin, Yanjiang; Liu, Yi-Hsin

    2009-01-01

    Purpose To better understand the pathophysiological mechanisms underlying neuromyelitis optica (NMO), we developed a proteomics platform for biomarker discovery in the cerebrospinal fluid (CSF) of patients with NMO. Methods Two-dimensional electrophoresis (2-DE) and matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) were used to compare the CSF proteome of NMO patients with that of controls. A subsequent ELISA and western blot analysis were performed to verify the results of the proteomic analysis. Pathway Studio 5.0 software was used to determine possible functional interactions among these differentially expressed proteins. Results Using 2-DE and MALDI-TOF MS, we identified 11 differentially expressed proteins and two isoforms of these same proteins. The expression of four proteins was enhanced, whereas the expression of seven proteins was reduced in the NMO group in comparison to the control group. These differences in protein expression were confirmed by performing ELISA and western blot analyses (p<0.01). Protein network analyses revealed biologic interactions and cross-talks among these differentially expressed proteins. Conclusions Because of their unique expression profile in NMO CSFs, these proteins are candidate biomarkers for NMO. Thus, our findings may have important implications for both the diagnosis of NMO and the further understanding of its pathogenesis. PMID:19710940

  14. Proteomic and cytokine plasma biomarkers for predicting progression from colorectal adenoma to carcinoma in human patients.

    PubMed

    Choi, Jung-Won; Liu, Hao; Shin, Dong Hoon; Yu, Gyeong Im; Hwang, Jae Seok; Kim, Eun Soo; Yun, Jong Won

    2013-08-01

    In the present study, we screened proteomic and cytokine biomarkers between patients with adenomatous polyps and colorectal cancer (CRC) in order to improve our understanding of the molecular mechanisms behind turmorigenesis and tumor progression in CRC. To this end, we performed comparative proteomic analysis of plasma proteins using a combination of 2DE and MS as well as profiled differentially regulated cytokines and chemokines by multiplex bead analysis. Proteomic analysis identified 11 upregulated and 13 downregulated plasma proteins showing significantly different regulation patterns with diagnostic potential for predicting progression from adenoma to carcinoma. Some of these proteins have not previously been implicated in CRC, including upregulated leucine-rich α-2-glycoprotein, hemoglobin subunit β, Ig α-2 chain C region, and complement factor B as well as downregulated afamin, zinc-α-2-glycoprotein, vitronectin, and α-1-antichymotrypsin. In addition, plasma levels of three cytokines/chemokines, including interleukin-8, interferon gamma-induced protein 10, and tumor necrosis factor α, were remarkably elevated in patients with CRC compared to those with adenomatous polyps. Although further clinical validation is required, these proteins and cytokines can be established as novel biomarkers for CRC and/or its progression from colon adenoma. PMID:23606366

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

    PubMed

    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

    2016-02-01

    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. PMID:26620284

  16. Proteomic analysis for early neurodegenerative biomarker detection in an animal model.

    PubMed

    Vincenzetti, Silvia; Nasuti, Cinzia; Fedeli, Donatella; Ricciutelli, Massimo; Pucciarelli, Stefania; Gabbianelli, Rosita

    2016-02-01

    The exposure to xenobiotics in the early stages of life represents the most important component in the etiology of many neurodegenerative disorders. Proteomic analysis of plasma and brain samples from early life treated animal model was performed in order to identify early biomarkers of neurodegeneration. Two-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry identified four proteins in the plasma of adolescent rats that deviated from the control group. Low expression levels of transthyretin and plasma transferrin, and the absence of long-chain fatty acid transport 1 were measured. On the other hand, the same proteomic approach was done on striatum of an adult rat model of neurodegeneration. Mitochondrial aspartate aminotransferase and voltage-dependent anion channel were under expressed, while mitochondrial malate dehydrogenase, myelin basic protein and ubiquitin-60S ribosomal protein L40 were absent in striatum of animal model compared to control group. Data show that early biomarkers for the diagnosis of neurodegeneration can be obtained by proteomic analysis, starting from adolescent age and the results highlight the time frame for the onset of neurodegeneration due to early exposure to xenobiotics. PMID:26631339

  17. Epigenetics and Proteomics Join Transcriptomics in the Quest for Tuberculosis Biomarkers

    PubMed Central

    Esterhuyse, Maria M.; Weiner, January; Caron, Etienne; Loxton, Andre G.; Iannaccone, Marco; Wagman, Chandre; Saikali, Philippe; Stanley, Kim; Wolski, Witold E.; Mollenkopf, Hans-Joachim; Schick, Matthias; Aebersold, Ruedi; Linhart, Heinz; Walzl, Gerhard

    2015-01-01

    ABSTRACT An estimated one-third of the world’s population is currently latently infected with Mycobacterium tuberculosis. Latent M. tuberculosis infection (LTBI) progresses into active tuberculosis (TB) disease in ~5 to 10% of infected individuals. Diagnostic and prognostic biomarkers to monitor disease progression are urgently needed to ensure better care for TB patients and to decrease the spread of TB. Biomarker development is primarily based on transcriptomics. Our understanding of biology combined with evolving technical advances in high-throughput techniques led us to investigate the possibility of additional platforms (epigenetics and proteomics) in the quest to (i) understand the biology of the TB host response and (ii) search for multiplatform biosignatures in TB. We engaged in a pilot study to interrogate the DNA methylome, transcriptome, and proteome in selected monocytes and granulocytes from TB patients and healthy LTBI participants. Our study provides first insights into the levels and sources of diversity in the epigenome and proteome among TB patients and LTBI controls, despite limitations due to small sample size. Functionally the differences between the infection phenotypes (LTBI versus active TB) observed in the different platforms were congruent, thereby suggesting regulation of function not only at the transcriptional level but also by DNA methylation and microRNA. Thus, our data argue for the development of a large-scale study of the DNA methylome, with particular attention to study design in accounting for variation based on gender, age, and cell type. PMID:26374119

  18. Identification of potential plasma biomarkers for esophageal squamous cell carcinoma by a proteomic method.

    PubMed

    Zhao, Jia; Fan, Yu-Xia; Yang, Yang; Liu, Dong-Lei; Wu, Kai; Wen, Feng-Biao; Zhang, Chun-Yang; Zhu, Deng-Yan; Zhao, Song

    2015-01-01

    Among malignant tumors, the mortality rate of esophageal squamous cell carcinoma (ESCC) ranks sixth in the world. Late-stage diagnosis of ESCC increases the mortality. Therefore, more effective biomarkers for early diagnosis of ESCC are necessary. Unfortunately, appropriate biomarkers for clinical diagnosis and prognosis have not been identified yet. However, recent progresses in quantitative proteomics have offered opportunities to identify plasma proteins as biomarkers for ESCC. In the present study, plasma samples were analyzed by differential in-gel electrophoresis (DIGE) and differentially expressed proteins were identified by matrix assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). A total of 31 proteins representing 12 unique gene products were identified, in which 16 proteins were up-regulated and 15 down-regulated in tumors. The up-regulated proteins were alpha-2-HS-glycoprotein (AHSG), leucine-rich alpha-2-glycoprotein (LRG), zinc-alpha-2-glycoprotein, alpha-1-antichymotrypsin, complement factor I and complement C4-B, whereas the down-regulated proteins were serum albumin, Ig alpha-2 chain C region, alpha-1-antitrypsin, fibrinogen gamma chain, haptoglobin and hemoglobin subunit alpha. Among all the differentially expressed proteins, AHSG and LRG were validated by ELISA. The results were consistent with the data from the proteomics results, further suggesting that AHSG and LRG may be employed as potential biomarkers for the early diagnosis of ESCC. In summary, this study was the first time to use DIGE combined MALDI-TOF/TOF platform to identify the potential plasma biomarkers for ESCC. The plasma AHSG and LRG showed great potential for ESCC screening. PMID:25973038

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

    PubMed Central

    Guryča, Vilém; Roeder, Daniel; Piraino, Paolo; Lamerz, Jens; Ducret, Axel; Langen, Hanno; Cutler, Paul

    2014-01-01

    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. PMID:24833342

  20. Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries.

    PubMed

    Guergova-Kuras, Mariana; Kurucz, István; Hempel, William; Tardieu, Nadège; Kádas, János; Malderez-Bloes, Carole; Jullien, Anne; Kieffer, Yann; Hincapie, Marina; Guttman, András; Csánky, Eszter; Dezso, Balázs; Karger, Barry L; Takács, László

    2011-12-01

    A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC. PMID:21947365

  1. Proteomic Identification of Biomarkers in the Cerebrospinal fluid (CSF) of Astrocytoma Patients

    PubMed Central

    Khwaja, Fatima W.; Reed, Matthew S.; Olson, Jeffrey J.; Schmotzer, Brian J.; Gillespie, G.Yancey; Guha, Abhijit; Groves, Morris D.; Kesari, Santosh; Pohl, Jan; Van Meir, Erwin G.

    2008-01-01

    The monitoring of changes in the protein composition of the cerebrospinal fluid (CSF) can be used as a sensitive indicator of central nervous system (CNS) pathology, yet its systematic application to analysis of CNS neoplasia has been limited. There is a pressing need for both a better understanding of gliomagenesis, and the development of reliable biomarkers of the disease. In this report, we used two proteomic techniques, two-dimensional gel electrophoresis (2-DE) and cleavable Isotope-Coded Affinity Tag (cICAT), to compare CSF proteomes in order to identify tumor and grade specific biomarkers in patients bearing brain tumors of differing histologies and grades. Retrospective analyses were performed on 60 samples derived from astrocytomas WHO grade II, III and IV, schwannomas, metastastic brain tumors, inflammatory samples and non-neoplastic controls. We identified 103 potential tumor-specific markers; of which 20 were high-grade astrocytoma-specific. These investigations allowed us to identify a spectrum of signature proteins that could differentiate between low (AII) and high-grade (AIV) astrocytoma, which may represent new diagnostic, prognostic and disease follow-up markers when used alone or in combination. These candidate biomarkers may also have functional properties that play a critical role in the development and malignant progression of human astrocytomas, thus possibly representing novel therapeutic targets for this highly lethal disease. PMID:17269713

  2. Introducing biomarker panel in esophageal, gastric, and colon cancers; a proteomic approach

    PubMed Central

    Zamanian–Azodi, Mona; Rezaei–Tavirani, Mostafa; Hasanzadeh, Hadi; Rahmati Rad, Sara; Dalilan, Sona

    2015-01-01

    Cancer research is an attractive field in molecular biology and medicine. By applying large-scale tools such as advanced genomics and proteomics, cancer diagnosis and treatment have been improved greatly. Cancers of esophagus, gastric, and colon accounted for major health problem globally. Biomarker panel could bring out the accuracy for cancer evaluation tests as it can suggest a group of candidate molecules specified to particular malignancy in a way that distinguishing malignant tumors from benign, differentiating from other diseases, and identifying each stages with high specificity and sensitivity. In this review, a systematic search of unique protein markers reported by several proteomic literatures are classified in their specific cancer type group as novel panels for feasible accurate malignancy diagnosis and treatment. About thousands of introduced proteins were studied; however, a small number of them belonged to a specific kind of malignancy. In conclusion, despite the fact that combinatorial biomarkers appear to be hopeful, more evaluation of them is crucial to achieve the suitable biomarker panel for clinical application. This effort needs more investigations and researches for finding a specific and sensitive panel. PMID:25584171

  3. Discovery of Lung Cancer Biomarkers by Profiling the Plasma Proteome with Monoclonal Antibody Libraries*

    PubMed Central

    Guergova-Kuras, Mariana; Kurucz, István; Hempel, William; Tardieu, Nadège; Kádas, János; Malderez-Bloes, Carole; Jullien, Anne; Kieffer, Yann; Hincapie, Marina; Guttman, András; Csánky, Eszter; Dezső, Balázs; Karger, Barry L.; Takács, László

    2011-01-01

    A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC. PMID:21947365

  4. Blood-Based Proteomic Biomarkers of Alzheimer’s Disease Pathology

    PubMed Central

    Baird, Alison L.; Westwood, Sarah; Lovestone, Simon

    2015-01-01

    The complexity of Alzheimer’s disease (AD) and its long prodromal phase poses challenges for early diagnosis and yet allows for the possibility of the development of disease modifying treatments for secondary prevention. It is, therefore, of importance to develop biomarkers, in particular, in the preclinical or early phases that reflect the pathological characteristics of the disease and, moreover, could be of utility in triaging subjects for preventative therapeutic clinical trials. Much research has sought biomarkers for diagnostic purposes by comparing affected people to unaffected controls. However, given that AD pathology precedes disease onset, a pathology endophenotype design for biomarker discovery creates the opportunity for detection of much earlier markers of disease. Blood-based biomarkers potentially provide a minimally invasive option for this purpose and research in the field has adopted various “omics” approaches in order to achieve this. This review will, therefore, examine the current literature regarding blood-based proteomic biomarkers of AD and its associated pathology. PMID:26635716

  5. Differential Secreted Proteome Approach in Murine Model for Candidate Biomarker Discovery in Colon Cancer

    PubMed Central

    Rangiah, Kannan; Tippornwong, Montri; Sangar, Vineet; Austin, David; Tétreault, Marie-Pier; Rustgi, Anil K.; Blair, Ian A.; Yu, Kenneth H.

    2009-01-01

    The complexity and heterogeneity of the plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. We used cell culture as a model system and identified differentially expressed, secreted proteins which may constitute serological biomarkers. A stable isotope labeling by amino acids in cell culture (SILAC) approach was used to label the entire secreted proteomes of the CT26 murine colon cancer cell line and normal young adult mouse colon (YAMC) cell line, thereby creating a stable isotope labeled proteome (SILAP) standard. This SILAP standard was added to unlabeled murine CT26 colon cancer cell or normal murine YAMC colon epithelial cell secreted proteome samples. A multidimensional approach combining isoelectric focusing (IEF), strong cation exchange (SCX) followed by reversed phase liquid chromatography was used for extensive protein and peptide separation. A total of 614 and 929 proteins were identified from the YAMC and CT26 cell lines, with 418 proteins common to both cell lines. Twenty highly abundant differentially expressed proteins from these groups were selected for liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS) analysis in sera. Differential secretion into the serum was observed for several proteins when Apcmin mice were compared with control mice. These findings were then confirmed by Western blot analysis. PMID:19769411

  6. Data from human salivary proteome – A resource of potential biomarkers for oral cancer

    PubMed Central

    Sivadasan, Priya; Kumar Gupta, Manoj; Sathe, Gajanan J.; Balakrishnan, Lavanya; Palit, Priyanka; Gowda, Harsha; Suresh, Amritha; Abraham Kuriakose, Moni; Sirdeshmukh, Ravi

    2015-01-01

    Salivary proteins are an important source for developing marker-based assays for oral cancers. To get an insight into the proteins present in human saliva, we applied multiple strategies involving affinity-based depletion of abundant proteins, fractionation of the resulting proteins or their tryptic peptides followed by LC–MS/MS analysis, using high resolution mass spectrometry. By integrating the protein identifications observed by us with those from similar workflows employed in earlier investigations, we compiled an updated salivary proteome. We have mapped the salivary proteome to the published data on differentially expressed proteins from oral cancer tissues and also for their secretory features using prediction tools, SignalP 4.1, TMHMM 2c and Exocarta. Proteotypic peptides for the subset of proteins implicated in oral cancer and mapped to any two of the prediction tools for secretory potential have been listed. The data here are related to the research article “Human saliva proteome – a resource of potential biomarkers for oral cancer” in the Journal of Proteomics [1]. PMID:26217819

  7. Biomarkers: Dynamic "Tools" for Health and Safety Risk Assessment

    EPA Science Inventory

    Today informational flow from biomarkers contributes importantly to various types of health effects research, risk assessment and risk management decisions that impact, or have the potential to impact, public health and safety. Therefore, dependent upon the nature of the health r...

  8. Human Seminal Plasma Proteome Study: A Search for Male Infertility Biomarkers

    PubMed Central

    Davalieva, K; Kiprijanovska, S; Noveski, P; Plaseski, T; Kocevska, B; Plaseska-Karanfilska, D

    2012-01-01

    Seminal plasma is a potential source of biomarkers for many disorders of the male reproductive system including male infertility. Knowledge of the peptide and protein components of seminal fluid is accumulating especially with the appearance of high-throughput MS-based techniques. Of special interest in the field of male infertility biomarkers, is the identification and characterization of differentially expressed proteins in seminal plasma of men with normal and impaired spermatogenesis. However, the data obtained until now is still quite heterogeneous and with small percentage of overlap between independent studies. Extensive comparative analysis of seminal plasma proteome is still needed in order to establish a potential link between seminal plasma proteins and male infertility. PMID:24052741

  9. Proteomics in food: Quality, safety, microbes, and allergens.

    PubMed

    Piras, Cristian; Roncada, Paola; Rodrigues, Pedro M; Bonizzi, Luigi; Soggiu, Alessio

    2016-03-01

    Food safety and quality and their associated risks pose a major concern worldwide regarding not only the relative economical losses but also the potential danger to consumer's health. Customer's confidence in the integrity of the food supply could be hampered by inappropriate food safety measures. A lack of measures and reliable assays to evaluate and maintain a good control of food characteristics may affect the food industry economy and shatter consumer confidence. It is imperative to create and to establish fast and reliable analytical methods that allow a good and rapid analysis of food products during the whole food chain. Proteomics can represent a powerful tool to address this issue, due to its proven excellent quantitative and qualitative drawbacks in protein analysis. This review illustrates the applications of proteomics in the past few years in food science focusing on food of animal origin with some brief hints on other types. Aim of this review is to highlight the importance of this science as a valuable tool to assess food quality and safety. Emphasis is also posed in food processing, allergies, and possible contaminants like bacteria, fungi, and other pathogens. PMID:26603968

  10. Development of a pharmaceutical hepatotoxicity biomarker panel using a discovery to targeted proteomics approach.

    PubMed

    Collins, Ben C; Miller, Christine A; Sposny, Alexandra; Hewitt, Phillip; Wells, Martin; Gallagher, William M; Pennington, Stephen R

    2012-08-01

    There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and

  11. Development of a Pharmaceutical Hepatotoxicity Biomarker Panel Using a Discovery to Targeted Proteomics Approach*

    PubMed Central

    Collins, Ben C.; Miller, Christine A.; Sposny, Alexandra; Hewitt, Phillip; Wells, Martin; Gallagher, William M.; Pennington, Stephen R.

    2012-01-01

    There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and

  12. Serum proteome changes in acromegalic patients following transsphenoidal surgery: novel biomarkers of disease activity

    PubMed Central

    Cruz-Topete, Diana; Christensen, Britt; Sackmann-Sala, Lucila; Okada, Shigeru; Jorgensen, Jens Otto L; Kopchick, John J

    2014-01-01

    Context Transsphenoidal adenomectomy is the primary treatment for acromegaly. However, assessment of the therapeutical outcome remains problematic since the existing biomarkers of disease activity frequently show discordant results. Objective To discover novel serum biomarkers of disease activity in acromegalic patients before and after surgery. Design Serum samples of eight newly diagnosed acromegaly patients before and after transsphenoidal surgery were analyzed for proteomic changes by two-dimensional gel electrophoresis. Protein spots displaying statistically significant changes, pre- versus post-surgery, were identified by mass spectrometry (MS), tandem MS (MS/MS), and western blot analysis. Results Six protein spots displaying decreased intensities after surgery were identified as transthyretin (two isoforms), haptoglobin a2, b-hemoglobin, and apolipoprotein A-1 (two isoforms). One protein spot, identified as complement C4B precursor, was increased after the surgery. Conclusions Seven serum protein spots were differentially expressed following surgery in acromegalic patients. The identified proteins represent potential novel biomarkers to assess the effectiveness of surgical treatment in acromegalic individuals. Future studies will validate the use of the identified proteins as biomarkers of disease activity after medical treatment of acromegaly. PMID:21059862

  13. Development of Diagnostic Biomarkers for Detecting Diabetic Retinopathy at Early Stages Using Quantitative Proteomics

    PubMed Central

    Jin, Jonghwa; Min, Hophil; Kim, Sang Jin; Oh, Sohee; Kim, Kyunggon; Yu, Hyeong Gon; Park, Taesung; Kim, Youngsoo

    2016-01-01

    Diabetic retinopathy (DR) is a common microvascular complication caused by diabetes mellitus (DM) and is a leading cause of vision impairment and loss among adults. Here, we performed a comprehensive proteomic analysis to discover biomarkers for DR. First, to identify biomarker candidates that are specifically expressed in human vitreous, we performed data-mining on both previously published DR-related studies and our experimental data; 96 proteins were then selected. To confirm and validate the selected biomarker candidates, candidates were selected, confirmed, and validated using plasma from diabetic patients without DR (No DR) and diabetics with mild or moderate nonproliferative diabetic retinopathy (Mi or Mo NPDR) using semiquantitative multiple reaction monitoring (SQ-MRM) and stable-isotope dilution multiple reaction monitoring (SID-MRM). Additionally, we performed a multiplex assay using 15 biomarker candidates identified in the SID-MRM analysis, which resulted in merged AUC values of 0.99 (No DR versus Mo NPDR) and 0.93 (No DR versus Mi and Mo NPDR). Although further validation with a larger sample size is needed, the 4-protein marker panel (APO4, C7, CLU, and ITIH2) could represent a useful multibiomarker model for detecting the early stages of DR. PMID:26665153

  14. An extended Markov blanket approach to proteomic biomarker detection from high-resolution mass spectrometry data.

    PubMed

    Oh, Jung Hun; Gurnani, Prem; Schorge, John; Rosenblatt, Kevin P; Gao, Jean X

    2009-03-01

    High-resolution matrix-assisted laser desorption/ionization time-of-flight mass spectrometry has recently shown promise as a screening tool for detecting discriminatory peptide/protein patterns. The major computational obstacle in finding such patterns is the large number of mass/charge peaks (features, biomarkers, data points) in a spectrum. To tackle this problem, we have developed methods for data preprocessing and biomarker selection. The preprocessing consists of binning, baseline correction, and normalization. An algorithm, extended Markov blanket, is developed for biomarker detection, which combines redundant feature removal and discriminant feature selection. The biomarker selection couples with support vector machine to achieve sample prediction from high-resolution proteomic profiles. Our algorithm is applied to recurrent ovarian cancer study that contains platinum-sensitive and platinum-resistant samples after treatment. Experiments show that the proposed method performs better than other feature selection algorithms. In particular, our algorithm yields good performance in terms of both sensitivity and specificity as compared to other methods. PMID:19126475

  15. A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva

    PubMed Central

    Kawahara, Rebeca; Bollinger, James G.; Rivera, César; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Paes Leme, Adriana F.; MacCoss, Michael J.

    2015-01-01

    Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC. PMID:26552850

  16. A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva.

    PubMed

    Kawahara, Rebeca; Bollinger, James G; Rivera, César; Ribeiro, Ana Carolina P; Brandão, Thaís Bianca; Paes Leme, Adriana F; MacCoss, Michael J

    2016-01-01

    Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC. PMID:26552850

  17. Prostate cancer serum biomarker discovery through proteomic analysis of alpha-2 macroglobulin protein complexes

    PubMed Central

    Burgess, Earle F.; Ham, Amy-Joan L.; Tabb, David L.; Billheimer, Dean; Roth, Bruce J.; Chang, Sam S.; Cookson, Michael S.; Hinton, Timothy J.; Cheek, Kristin L.; Hill, Salisha; Pietenpol, Jennifer A.

    2010-01-01

    Alpha-2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen-independent, metastatic prostate cancer and six control patients without malignancy were analyzed by immunoaffinity enrichment of A2M protein complexes and MS identification of associated proteins. Known A2M substrates were reproducibly identified from patient serum in both cohorts, as well as proteins previously undetected in human serum. One example is heat shock protein 90 alpha (HSP90α), which was identified only in the serum of cancer patients in this study. Using an ELISA, the presence of HSP90α in human serum was validated on expanded test cohorts and found to exist in higher median serum concentrations in prostate cancer (n = 18) relative to control (n = 13) patients (median concentrations 50.7 versus 27.6 ng/mL, respectively, p = 0.001). Our results demonstrate the technical feasibility of this approach and support the analysis of A2M protein complexes for proteomic-based serum biomarker discovery. PMID:20107526

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

    PubMed Central

    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

  19. A Proteomic Analysis of Eccrine Sweat: Implications for the Discovery of Schizophrenia Biomarker Proteins

    PubMed Central

    Raiszadeh, Michelle M.; Ross, Mark M.; Russo, Paul S.; Schaepper, Mary Ann H.; Zhou, Weidong; Deng, Jianghong; Ng, Daniel; Dickson, April; Dickson, Cindy; Strom, Monica; Osorio, Carolina; Soeprono, Thomas; Wulfkuhle, Julia D.; Kabbani, Nadine; Petricoin, Emanuel F.; Liotta, Lance A.; Kirsch, Wolff M.

    2012-01-01

    Liquid chromatography tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate, and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately two-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers. PMID:22256890

  20. Proteomic analysis of eccrine sweat: implications for the discovery of schizophrenia biomarker proteins.

    PubMed

    Raiszadeh, Michelle M; Ross, Mark M; Russo, Paul S; Schaepper, Mary Ann; Zhou, Weidong; Deng, Jianghong; Ng, Daniel; Dickson, April; Dickson, Cindy; Strom, Monica; Osorio, Carolina; Soeprono, Thomas; Wulfkuhle, Julia D; Petricoin, Emanuel F; Liotta, Lance A; Kirsch, Wolff M

    2012-04-01

    Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately 2-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers. PMID:22256890

  1. Proteomics-based safety evaluation of multi-walled carbon nanotubes

    SciTech Connect

    Haniu, Hisao; Matsuda, Yoshikazu; Takeuchi, Kenji; Kim, Yoong Ahm; Hayashi, Takuya; Endo, Morinobu

    2010-02-01

    This study evaluated the biological responses to multi-walled carbon nanotubes (MWCNTs). Human monoblastic leukemia cells (U937) were exposed to As-grown MWCNTs and MWCNTs that were thermally treated at 1800 deg. C (HTT1800) and 2800 deg. C (HTT2800). Cell proliferation was highly inhibited by As-grown but not HTT2800. However, both As-grown and HTT1800, which include some impurities, were cytotoxic. Proteomics analysis of MWCNT-exposed cells revealed 37 protein spots on 2-dimensional electrophoresis gels that significantly changed (p < 0.05) after exposure to HTT1800 with a little iron and 20 spots that changed after exposure to HTT2800. Peptide mass fingerprinting identified 45 proteins that included heat shock protein beta-1, neutral alpha-glucosidase AB, and DNA mismatch repair protein Msh2. These altered proteins play roles in metabolism, biosynthesis, response to stress, and cell differentiation. Although HTT2800 did not inhibit cell proliferation or cause cytotoxicity in vitro, some proteins related to the response to stress were changed. Moreover, DJ-1 protein, which is a biomarker of Parkinson's disease and is related to cancer, was identified after exposure to both MWCNTs. These results show that the cytotoxicity of MWCNTs depends on their impurities, such as iron, while MWCNTs themselves cause some biological responses directly and/or indirectly in vitro. Our proteomics-based approach for detecting biological responses to nanomaterials is a promising new method for detailed safety evaluations.

  2. Salivary Proteomic and Genomic Biomarkers for Primary Sjögren’s Syndrome

    PubMed Central

    Hu, Shen; Wang, Jianghua; Meijer, Jiska; Ieong, Sonya; Xie, Yongming; Yu, Tianwei; Zhou, Hui; Henry, Sharon; Vissink, Arjan; Pijpe, Justin; Kallenberg, Cees; Elashoff, David; Loo, Joseph A.; Wong, David T.

    2010-01-01

    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 Sjögren’s syndrome (SS). Methods Mass spectrometry and expression microarray profiling were used to identify candidate protein and mRNA biomarkers of primary SS in WS samples. Validation of the discovered mRNA and protein biomarkers was also demonstrated using real-time quantitative polymerase chain reaction and immunoblotting techniques. Results Sixteen WS proteins were found to be down-regulated and 25 WS proteins were found to be up-regulated in primary SS patients compared with matched healthy control subjects. These proteins reflected the damage of glandular cells and inflammation of the oral cavity system in patients with primary SS. In addition, 16 WS peptides (10 up-regulated and 6 down-regulated in primary SS) were found at significantly different levels (P <0.05) in primary SS patients and controls. Using stringent criteria (3-fold change; P <0.0005), 27 mRNA in saliva samples were found to be significantly up-regulated in the primary SS patients. Strikingly, 19 of 27 genes that were found to be overex-pressed were interferon-inducible or were related to lymphocyte filtration and antigen presentation known to be involved in the pathogenesis of primary SS. Conclusion Our preliminary study has indicated that WS from patients with primary SS contains molecular signatures that reflect damaged glandular cells and an activated immune response in this autoimmune disease. These candidate proteomic and genomic biomarkers may improve the clinical detection of primary SS once they have been further validated. We also found that WS contains more informative proteins, peptides, and mRNA, as compared with gland-specific saliva, that can be used in generating candidate biomarkers for the detection of primary SS. PMID:17968930

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

    PubMed

    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. PMID:26735893

  4. Top-down proteomic identification of protein biomarkers of food-borne pathogens using MALDI-TOF-TOF-MS/MS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This chapter describes a step-by-step protocol and discussion of top-down proteomic identification of protein biomarkers of food-borne pathogens using matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometry (MALDI-TOF-TOF-MS/MS) and web-based software developed in the Pro...

  5. Composite sequence proteomic analysis of protein biomarkers of Campylobacter coli, C. lari and C. concisus for bacterial identification

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Proteins biomarkers observed in the matrix-assisted laser desorption/ionization time-of-flight mass spectra (MALDI-TOF-MS) of cell lysates of three strains of Campylobacter coli, two strains of C. lari and one strain of C. concisus have been identified by "bottom-up" proteomic techniques. The signif...

  6. Amino Acid Sequence Determination of Protein Biomarkers of Campylobacter upsaliensis and C. helveticus by 'Composite' Sequence Proteomic Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We have identified the protein biomarkers observed in the matrix-assisted laser desorption/ionization time-of-flight mass spectra (MALDI-TOF-MS) of cell lysates of five different strains of Campylobacter upsaliensis and one strain of C. helveticus by proteomic techniques. Only one of these strains ...

  7. A Quantitative Proteomic Approach to Prion Disease Biomarker Research: Delving into the Glycoproteome

    PubMed Central

    Wei, Xin; Herbst, Allen; Ma, Di; Aiken, Judd; Li, Lingjun

    2011-01-01

    Mass spectrometry (MS) – based proteomic approaches have evolved as powerful tools for the discovery of biomarkers. However, the identification of potential protein biomarkers from biofluid samples is challenging because of the limited dynamic range of detection. Currently there is a lack of sensitive and reliable pre-mortem diagnostic test for prion diseases. Here, we describe the use of a combined MS-based approach for biomarker discovery in prion diseases from mouse plasma samples. To overcome the limited dynamic range of detection and sample complexity of plasma samples, we used lectin affinity chromatography and multi-dimensional separations to enrich and isolate glycoproteins at low abundance. Relative quantitation of a panel of proteins was obtained by a combination of isotopic labeling and validated by spectral counting. Overall 708 proteins were identified, 53 of which showed more than 2-fold increase in concentration whereas 58 exhibited more than 2-fold decrease. A few of the potential candidate markers were previously associated with prion or other neurodegenerative diseases. PMID:21469646

  8. Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer.

    PubMed

    Ma, Hong; Chen, Guilin; Guo, Mingquan

    2016-04-01

    Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers. PMID:26616366

  9. Glycoprotein biomarker panel for pancreatic cancer discovered by quantitative proteomics analysis.

    PubMed

    Nie, Song; Lo, Andy; Wu, Jing; Zhu, Jianhui; Tan, Zhijing; Simeone, Diane M; Anderson, Michelle A; Shedden, Kerby A; Ruffin, Mack T; Lubman, David M

    2014-04-01

    Pancreatic cancer is a lethal disease where specific early detection biomarkers would be very valuable to improve outcomes in patients. Many previous studies have compared biosamples from pancreatic cancer patients with healthy controls to find potential biomarkers. However, a range of related disease conditions can influence the performance of these putative biomarkers, including pancreatitis and diabetes. In this study, quantitative proteomics methods were applied to discover potential serum glycoprotein biomarkers that distinguish pancreatic cancer from other pancreas related conditions (diabetes, cyst, chronic pancreatitis, obstructive jaundice) and healthy controls. Aleuria aurantia lectin (AAL) was used to extract fucosylated glycoproteins and then both TMT protein-level labeling and label-free quantitative analysis were performed to analyze glycoprotein differences from 179 serum samples across the six different conditions. A total of 243 and 354 serum proteins were identified and quantified by label-free and TMT protein-level quantitative strategies, respectively. Nineteen and 25 proteins were found to show significant differences in samples between the pancreatic cancer and other conditions using the label-free and TMT strategies, respectively, with 7 proteins considered significant in both methods. Significantly different glycoproteins were further validated by lectin-ELISA and ELISA assays. Four candidates were identified as potential markers with profiles found to be highly complementary with CA 19-9 (p < 0.001). Obstructive jaundice (OJ) was found to have a significant impact on the performance of every marker protein, including CA 19-9. The combination of α-1-antichymotrypsin (AACT), thrombospondin-1 (THBS1), and haptoglobin (HPT) outperformed CA 19-9 in distinguishing pancreatic cancer from normal controls (AUC = 0.95), diabetes (AUC = 0.89), cyst (AUC = 0.82), and chronic pancreatitis (AUC = 0.90). A marker panel of AACT, THBS1, HPT, and CA 19

  10. Label-free proteomics identifies Calreticulin and GRP75/Mortalin as peripherally accessible protein biomarkers for spinal muscular atrophy

    PubMed Central

    2013-01-01

    Background Spinal muscular atrophy (SMA) is a neuromuscular disease resulting from mutations in the survival motor neuron 1 (SMN1) gene. Recent breakthroughs in preclinical research have highlighted several potential novel therapies for SMA, increasing the need for robust and sensitive clinical trial platforms for evaluating their effectiveness in human patient cohorts. Given that most clinical trials for SMA are likely to involve young children, there is a need for validated molecular biomarkers to assist with monitoring disease progression and establishing the effectiveness of therapies being tested. Proteomics technologies have recently been highlighted as a potentially powerful tool for such biomarker discovery. Methods We utilized label-free proteomics to identify individual proteins in pathologically-affected skeletal muscle from SMA mice that report directly on disease status. Quantitative fluorescent western blotting was then used to assess whether protein biomarkers were robustly changed in muscle, skin and blood from another mouse model of SMA, as well as in a small cohort of human SMA patient muscle biopsies. Results By comparing the protein composition of skeletal muscle in SMA mice at a pre-symptomatic time-point with the muscle proteome at a late-symptomatic time-point we identified increased expression of both Calreticulin and GRP75/Mortalin as robust indicators of disease progression in SMA mice. We report that these protein biomarkers were consistently modified in different mouse models of SMA, as well as across multiple skeletal muscles, and were also measurable in skin biopsies. Furthermore, Calreticulin and GRP75/Mortalin were measurable in muscle biopsy samples from human SMA patients. Conclusions We conclude that label-free proteomics technology provides a powerful platform for biomarker identification in SMA, revealing Calreticulin and GRP75/Mortalin as peripherally accessible protein biomarkers capable of reporting on disease progression in

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

    SciTech Connect

    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

  12. Investigation of biomarkers of bile tolerance in Lactobacillus casei using comparative proteomics.

    PubMed

    Hamon, Erwann; Horvatovich, Peter; Bisch, Magali; Bringel, Françoise; Marchioni, Eric; Aoudé-Werner, Dalal; Ennahar, Saïd

    2012-01-01

    The identification of cell determinants involved in probiotic features is a challenge in current probiotic research. In this work, markers of bile tolerance in Lactobacillus casei were investigated using comparative proteomics. Six L. casei strains were classified on the basis of their ability to grow in the presence of bile salts in vitro. Constitutive differences between whole cell proteomes of the most tolerant strain (L. casei Rosell-215), the most sensitive one (L. casei ATCC 334), and a moderately tolerant strain (L. casei DN-114 001) were investigated. The ascertained subproteome was further studied for the six strains in both standard and bile stressing conditions. Focus was on proteins whose expression levels were correlated with observed levels of bile tolerance in vitro, particularly those previously reported to be involved in the bile tolerance process of lactobacilli. Analysis revealed that 12 proteins involved in membrane modification (NagA, NagB, and RmlC), cell protection and detoxification (ClpL and OpuA), as well as central metabolism (Eno, GndA, Pgm, Pta, Pyk, Rp1l, and ThRS) were likely to be key determinants of bile tolerance in L. casei and may serve as potential biomarkers for phenotyping or screening purposes. The approach used enabled the correlation of expression levels of particular proteins with a specific probiotic trait. PMID:22040141

  13. Proteomic Analysis of Cerebrospinal Fluid in Pneumococcal Meningitis Reveals Potential Biomarkers Associated with Survival

    PubMed Central

    Goonetilleke, Upali R.; Scarborough, Matthew; Ward, Stephen A.; Gordon, Stephen B.

    2016-01-01

    Background Patients with pneumococcal meningitis often die or have severe neurological damage despite optimal antibiotic therapy. New or improved therapy is required. The delivery of new interventions will require an improved understanding of the disease pathogenesis. Our objective was to learn more about the pathophysiology of severe meningitis through the interpretation of differences in the proteomic profile of cerebrospinal fluid (CSF) from patients with meningitis. Methods Two-dimensional polyacrylamide gel electrophoresis of CSF from normal subjects (controls, n = 10) and patients with pneumococcal meningitis (n = 20) was analyzed. Spot differences were compared and identified between controls, nonsurvivors (n = 9), and survivors (n = 11). Results Protein concentration in CSF of patients with meningitis was 4-fold higher than in CSF of control subjects (7.0 mg/mL vs 0.23 mg/mL; P < .01). A mean of 2466 discrete protein spots was present in CSF of patients with meningitis. Thirty-four protein spots were differentially expressed in CSF of nonsurvivors, compared with survivors. None of these protein spots were observed in CSF of control subjects. Conclusions Proteomic screening of CSF yields potential biomarkers capable of differentiating control subjects from nonsurvivors and survivors of meningitis. Proteins involved in the inflammatory process and central metabolism were represented in the differentially expressed protein repertoire. PMID:20608875

  14. Proteomic Biomarkers for Acute Interstitial Lung Disease in Gefitinib-Treated Japanese Lung Cancer Patients

    PubMed Central

    Kawakami, Takao; Nagasaka, Keiko; Takami, Sachiko; Wada, Kazuya; Tu, Hsiao-Kun; Otsuji, Makiko; Kyono, Yutaka; Dobashi, Tae; Komatsu, Yasuhiko; Kihara, Makoto; Akimoto, Shingo; Peers, Ian S.; South, Marie C.; Higenbottam, Tim; Fukuoka, Masahiro; Nakata, Koichiro; Ohe, Yuichiro; Kudoh, Shoji; Clausen, Ib Groth; Nishimura, Toshihide; Marko-Varga, György; Kato, Harubumi

    2011-01-01

    Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10−25), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control. PMID:21799770

  15. In-depth Proteomic Analysis of Nonsmall Cell Lung Cancer to Discover Molecular Targets and Candidate Biomarkers*

    PubMed Central

    Kikuchi, Takefumi; Hassanein, Mohamed; Amann, Joseph M.; Liu, Qinfeng; Slebos, Robbert J. C.; Rahman, S. M. Jamshedur; Kaufman, Jacob M.; Zhang, Xueqiong; Hoeksema, Megan D.; Harris, Bradford K.; Li, Ming; Shyr, Yu; Gonzalez, Adriana L.; Zimmerman, Lisa J.; Liebler, Daniel C.; Massion, Pierre P.; Carbone, David P.

    2012-01-01

    Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy. PMID:22761400

  16. Detection of biomarkers of pathogenic Naegleria fowleri through mass spectrometry and proteomics.

    PubMed

    Moura, Hercules; Izquierdo, Fernando; Woolfitt, Adrian R; Wagner, Glauber; Pinto, Tatiana; del Aguila, Carmen; Barr, John R

    2015-01-01

    Emerging methods based on mass spectrometry (MS) can be used in the rapid identification of microorganisms. Thus far, these practical and rapidly evolving methods have mainly been applied to characterize prokaryotes. We applied matrix-assisted laser-desorption-ionization-time-of-flight mass spectrometry MALDI-TOF MS in the analysis of whole cells of 18 N. fowleri isolates belonging to three genotypes. Fourteen originated from the cerebrospinal fluid or brain tissue of primary amoebic meningoencephalitis patients and four originated from water samples of hot springs, rivers, lakes or municipal water supplies. Whole Naegleria trophozoites grown in axenic cultures were washed and mixed with MALDI matrix. Mass spectra were acquired with a 4700 TOF-TOF instrument. MALDI-TOF MS yielded consistent patterns for all isolates examined. Using a combination of novel data processing methods for visual peak comparison, statistical analysis and proteomics database searching we were able to detect several biomarkers that can differentiate all species and isolates studied, along with common biomarkers for all N. fowleri isolates. Naegleria fowleri could be easily separated from other species within the genus Naegleria. A number of peaks detected were tentatively identified. MALDI-TOF MS fingerprinting is a rapid, reproducible, high-throughput alternative method for identifying Naegleria isolates. This method has potential for studying eukaryotic agents. PMID:25231600

  17. Transcriptomic and Proteomic Investigation of HSP90A as a Potential Biomarker for HCC

    PubMed Central

    Zhou, Yi; Deng, Xiaofang; Zang, Ning; Li, Hongtao; Li, Gang; Li, Cuiping; He, Min

    2015-01-01

    Background Hepatocellular carcinoma (HCC) is the third most frequent cause of cancer-related death in adults. Despite recent advances in the clinical technologies, the screening and diagnostic efficacy for HCC remains poor. Discovering novel and reliable HCC biomarkers is urgently needed. Material/Methods We performed a transcriptome-proteome integrated assay to track the possible HCC biomarkers from the process of HCC-derived gene expression in malignant cells to its protein product released into serum. Results Our screening results demonstrated that heat shock protein 90A (HSP90A), which participates in the PI3K-Akt signaling pathway and many other cancer-related pathways, warrants further investigation. The expression of HSP90A was increased in the HCC cells, serum, and tissues. Immunohistochemistry analysis on 76 clinical tissue samples also suggested the relevance between HSP90A expression and HCC metastatic behavior. Conclusions These findings suggest a role for HSP90A in HCC pathogenesis and the potential use of HSP90A for the screening and diagnosis of this malignancy. PMID:26704341

  18. Identification and Characterization of Potential Biomarkers by Quantitative Tissue Proteomics of Primary Lung Adenocarcinoma.

    PubMed

    Hsu, Chiung-Hung; Hsu, Chia-Wei; Hsueh, Chuen; Wang, Chih-Liang; Wu, Yi-Cheng; Wu, Chih-Ching; Liu, Chin-Ching; Yu, Jau-Song; Chang, Yu-Sun; Yu, Chia-Jung

    2016-07-01

    Lung cancer is the leading cause of cancer-related death worldwide. Both diagnostic and prognostic biomarkers are urgently needed to increase patient survival. In this study, we identified/quantified 1763 proteins from paired adenocarcinoma (ADC) tissues with different extents of lymph node (LN) involvement using an iTRAQ-based quantitative proteomic analysis. Based on a bioinformatics analysis and literature search, we selected six candidates (ERO1L, PABPC4, RCC1, RPS25, NARS, and TARS) from a set of 133 proteins that presented a 1.5-fold increase in expression in ADC tumors without LN metastasis compared with adjacent normal tissues. These six proteins were further verified using immunohistochemical staining and Western blot analyses. The protein levels of these six candidates were higher in tumor tissues compared with adjacent normal tissues. The ERO1L and NARS levels were positively associated with LN metastasis. Importantly, ERO1L overexpression in patients with early-stage ADC was positively correlated with poor survival, suggesting that ERO1L overexpression in primary sites of early-stage cancer tissues indicates a high risk for cancer micrometastasis. Moreover, we found that knockdown of either ERO1L or NARS reduced the viability and migration ability of ADC cells. Our results collectively provide a potential biomarker data set for ADC diagnosis/prognosis and reveal novel roles of ERO1L and NARS in ADC progression. PMID:27161446

  19. In-depth Proteomic Analysis of Six Types of Exudative Pleural Effusions for Nonsmall Cell Lung Cancer Biomarker Discovery*

    PubMed Central

    Liu, Pei-Jun; Chen, Chi-De; Wang, Chih-Liang; Wu, Yi-Cheng; Hsu, Chia-Wei; Lee, Chien-Wei; Huang, Lien-Hung; Yu, Jau-Song; Chang, Yu-Sun; Wu, Chih-Ching; Yu, Chia-Jung

    2015-01-01

    Pleural effusion (PE), a tumor-proximal body fluid, may be a promising source for biomarker discovery in human cancers. Because a variety of pathological conditions can lead to PE, characterization of the relative PE proteomic profiles from different types of PEs would accelerate discovery of potential PE biomarkers specifically used to diagnose pulmonary disorders. Using quantitative proteomic approaches, we identified 772 nonredundant proteins from six types of exudative PEs, including three malignant PEs (MPE, from lung, breast, and gastric cancers), one lung cancer paramalignant PE, and two benign diseases (tuberculosis and pneumonia). Spectral counting was utilized to semiquantify PE protein levels. Principal component analysis, hierarchical clustering, and Gene Ontology of cellular process analyses revealed differential levels and functional profiling of proteins in each type of PE. We identified 30 candidate proteins with twofold higher levels (q<0.05) in lung cancer MPEs than in the two benign PEs. Three potential markers, MET, DPP4, and PTPRF, were further verified by ELISA using 345 PE samples. The protein levels of these potential biomarkers were significantly higher in lung cancer MPE than in benign diseases or lung cancer paramalignant PE. The area under the receiver-operator characteristic curve for three combined biomarkers in discriminating lung cancer MPE from benign diseases was 0.903. We also observed that the PE protein levels were more clearly discriminated in effusions in which the cytological examination was positive and that they would be useful in rescuing the false negative of cytological examination in diagnosis of nonsmall cell lung cancer-MPE. Western blotting analysis further demonstrated that MET overexpression in lung cancer cells would contribute to the elevation of soluble MET in MPE. Our results collectively demonstrate the utility of label-free quantitative proteomic approaches in establishing differential PE proteomes and

  20. Proteomic Analysis of Temporally Stimulated Ovarian Cancer Cells for Biomarker Discovery*

    PubMed Central

    Marzinke, Mark A.; Choi, Caitlin H.; Chen, Li; Shih, Ie-Ming; Chan, Daniel W.; Zhang, Hui

    2013-01-01

    While ovarian cancer remains the most lethal gynecological malignancy in the United States, there are no biomarkers available that are able to predict therapeutic responses to ovarian malignancies. One major hurdle in the identification of useful biomarkers has been the ability to obtain enough ovarian cancer cells from primary tissues diagnosed in the early stages of serous carcinomas, the most deadly subtype of ovarian tumor. In order to detect ovarian cancer in a state of hyperproliferation, we analyzed the implications of molecular signaling cascades in the ovarian cancer cell line OVCAR3 in a temporal manner, using a mass-spectrometry-based proteomics approach. OVCAR3 cells were treated with EGF1, and the time course of cell progression was monitored based on Akt phosphorylation and growth dynamics. EGF-stimulated Akt phosphorylation was detected at 12 h post-treatment, but an effect on proliferation was not observed until 48 h post-exposure. Growth-stimulated cellular lysates were analyzed for protein profiles between treatment groups and across time points using iTRAQ labeling and mass spectrometry. The protein response to EGF treatment was identified via iTRAQ analysis in EGF-stimulated lysates relative to vehicle-treated specimens across the treatment time course. Validation studies were performed on one of the differentially regulated proteins, lysosomal-associated membrane protein 1 (LAMP-1), in human tissue lysates and ovarian tumor tissue sections. Further, tissue microarray analysis was performed to demarcate LAMP-1 expression across different stages of epithelial ovarian cancers. These data support the use of this approach for the efficient identification of tissue-based markers in tumor development related to specific signaling pathways. LAMP-1 is a promising biomarker for studies of the progression of EGF-stimulated ovarian cancers and might be useful in predicting treatment responses involving tyrosine kinase inhibitors or EGF receptor monoclonal

  1. Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact.

    PubMed

    Coleman, Orla; Henry, Michael; McVey, Gerard; Clynes, Martin; Moriarty, Michael; Meleady, Paula

    2016-01-01

    Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy. PMID:26985644

  2. Novel serum biomarkers for erythropoietin use in humans: a proteomic approach.

    PubMed

    Christensen, Britt; Sackmann-Sala, Lucila; Cruz-Topete, Diana; Jørgensen, Jens Otto L; Jessen, Niels; Lundby, Carsten; Kopchick, John J

    2011-01-01

    Erythropoietin (Epo) is produced primarily in the kidneys upon low blood oxygen availability and stimulates erythropoiesis in the bone marrow. Recombinant human Epo (rHuEpo), a drug developed to increase arterial oxygen content in patients, is also illicitly used by athletes to improve their endurance performance. Therefore, a robust and sensitive test to detect its abuse is needed. The aim of the present study was to investigate potential human serum biomarkers of Epo abuse employing a proteomic approach. Eight healthy male subjects were injected subcutaneously with rHuEpo (5,000 IU) every second day for a 16-day period. Serum was collected before starting the treatment regime and again at days 8 and 16 during the treatment period. Samples were homogenized and proteins separated by two-dimensional gel electrophoresis (2DE). Spots that changed significantly in response to rHuEpo treatment were identified by mass spectrometry. Both the number of reticulocytes and erythrocytes increased throughout the study, leading to a significant increase in hematocrit and hemoglobin content. In addition, transferrin levels increased but the percentage of iron bound to transferrin and ferritin levels decreased. Out of 97 serum proteins, seven were found to decrease significantly at day 16 compared with pre-Epo administration, and were identified as four isoforms of haptoglobin, two isoforms of transferrin, and a mixture of hemopexin and albumin. In support, total serum haptoglobin levels were found to be significantly decreased at both days 8 and 16. Thus a 2DE proteomic approach for discovery of novel markers of Epo action appears feasible. PMID:20966191

  3. Dysbindin as a novel biomarker for pancreatic ductal adenocarcinoma identified by proteomic profiling.

    PubMed

    Guo, Xin; Lv, Xiaohui; Fang, Cheng; Lv, Xing; Wang, Fengsong; Wang, Dongmei; Zhao, Jun; Ma, Yueyun; Xue, Yu; Bai, Quan; Yao, Xuebiao; Chen, Yong

    2016-10-15

    Pancreatic adenocarcinoma (PDAC) is known to have a poor prognosis partly because of lack of effective biomarkers. In the test set, we investigated dysbindin (DTNBP1) as a potential biomarker for PDAC by comparing preoperative and postoperative serum mass spectrometry (MS) proteomic profilings. Of the included 50 PDAC patients, 42 (positivity of 84.0%) detected a lower MS peak in postoperative serums than preoperative ones which was then identified as dysbindin. In the verification set, receiver operating characteristics (ROC) were used to assess diagnostic efficiency. 550 participants were included in the verification set [250 with PDAC, 80 with benign biliary obstruction (BBO), 70 with chronic pancreatitis (CP) and 150 healthy donors (HD)]. Dysbindin was increased in PDAC patient sera than in all controls. ROC curves revealed the optimum diagnostic cutoff for dysbindin was 699.16 pg/ml [area under curve (AUC) 0.849 (95% CI 0.812-0.885), sensitivity 81.9% and specificity 84.7%]. Raised concentration of dysbindin in sera could differentiate PDAC from BBO, CP and HD. Moreover, dysbindin maintained its diagnostic accuracy for PDAC patients who were CA19-9 negative [AUC 0.875 (95% CI 0.804-0.945), sensitivity 83.0%, specificity 89.0%] and for patients with benign biliary obstruction [AUC 0.849 (95% CI 0.803-0.894), sensitivity 82.3%, specificity 84.0%].Our discovery of dysbindin may complement measurement of CA19-9 in the diagnosis of PDAC and help to discriminate PDAC from other pancreatic diseases or begin biliary obstruction. PMID:27281120

  4. Assessing Susceptibility to Age-related Macular Degeneration with Proteomic and Genomic Biomarkers*

    PubMed Central

    Gu, Jiayin; Pauer, Gayle J. T.; Yue, Xiuzhen; Narendra, Umadevi; Sturgill, Gwen M.; Bena, James; Gu, Xiaorong; Peachey, Neal S.; Salomon, Robert G.; Hagstrom, Stephanie A.; Crabb, John W.

    2009-01-01

    Age-related macular degeneration (AMD) is a progressive disease and major cause of severe visual loss. Toward the discovery of tools for early identification of AMD susceptibility, we evaluated the combined predictive capability of proteomic and genomic AMD biomarkers. We quantified plasma carboxyethylpyrrole (CEP) oxidative protein modifications and CEP autoantibodies by ELISA in 916 AMD and 488 control donors. CEP adducts are uniquely generated from oxidation of docosahexaenoate-containing lipids that are abundant in the retina. Mean CEP adduct and autoantibody levels were found to be elevated in AMD plasma by ∼60 and ∼30%, respectively. The odds ratio for both CEP markers elevated was 3-fold greater or more in AMD than in control patients. Genotyping was performed for AMD risk polymorphisms associated with age-related maculopathy susceptibility 2 (ARMS2), high temperature requirement factor A1 (HTRA1), complement factor H, and complement C3, and the risk of AMD was predicted based on genotype alone or in combination with the CEP markers. The AMD risk predicted for those exhibiting elevated CEP markers and risk genotypes was 2–3-fold greater than the risk based on genotype alone. AMD donors carrying the ARMS2 and HTRA1 risk alleles were the most likely to exhibit elevated CEP markers. The results compellingly demonstrate higher mean CEP marker levels in AMD plasma over a broad age range. Receiver operating characteristic curves suggest that CEP markers alone can discriminate between AMD and control plasma donors with ∼76% accuracy and in combination with genomic markers provide up to ∼80% discrimination accuracy. Plasma CEP marker levels were altered slightly by several demographic and health factors that warrant further study. We conclude that CEP plasma biomarkers, particularly in combination with genomic markers, offer a potential early warning system for assessing susceptibility to this blinding, multifactorial disease. PMID:19202148

  5. Comprehensive maternal serum proteomics identifies the cytoskeletal proteins as non-invasive biomarkers in prenatal diagnosis of congenital heart defects

    PubMed Central

    Chen, Lizhu; Gu, Hui; Li, Jun; Yang, Ze-Yu; Sun, Xiao; Zhang, Li; Shan, Liping; Wu, Lina; Wei, Xiaowei; Zhao, Yili; Ma, Wei; Zhang, Henan; Cao, Songying; Huang, Tianchu; Miao, Jianing; Yuan, Zhengwei

    2016-01-01

    Congenital heart defects (CHDs) are the most common group of major birth defects. Presently there are no clinically used biomarkers for prenatally detecting CHDs. Here, we performed a comprehensive maternal serum proteomics assessment, combined with immunoassays, for the discovery of non-invasive biomarkers for prenatal diagnosis of CHDs. A total of 370 women were included in this study. An isobaric tagging for relative and absolute quantification (iTRAQ) proteomic approach was used first to compare protein profiles in pooled serum collected from women who had CHD-possessing or normal fetuses, and 47 proteins displayed significant differential expressions. Targeted verifications were performed on 11 proteins using multiple reaction monitoring mass spectrometry (MRM-MS), and the resultant candidate biomarkers were then further validated using ELISA analysis. Finally, we identified a biomarker panel composed of 4 cytoskeletal proteins capable of differentiating CHD-pregnancies from normal ones [with an area under the receiver operating characteristic curve (AUC) of 0.938, P < 0.0001]. The discovery of cytoskeletal protein changes in maternal serum not only could help us in prenatal diagnosis of CHDs, but also may shed new light on CHD embryogenesis studies. PMID:26750556

  6. The Discovery of Novel Genomic, Transcriptomic, and Proteomic Biomarkers in Cardiovascular and Peripheral Vascular Disease: The State of the Art

    PubMed Central

    de Franciscis, Stefano; Metzinger, Laurent; Serra, Raffaele

    2016-01-01

    Cardiovascular disease (CD) and peripheral vascular disease (PVD) are leading causes of mortality and morbidity in western countries and also responsible of a huge burden in terms of disability, functional decline, and healthcare costs. Biomarkers are measurable biological elements that reflect particular physiological or pathological states or predisposition towards diseases and they are currently widely studied in medicine and especially in CD. In this context, biomarkers can also be used to assess the severity or the evolution of several diseases, as well as the effectiveness of particular therapies. Genomics, transcriptomics, and proteomics have opened new windows on disease phenomena and may permit in the next future an effective development of novel diagnostic and prognostic medicine in order to better prevent or treat CD. This review will consider the current evidence of novel biomarkers with clear implications in the improvement of risk assessment, prevention strategies, and medical decision making in the field of CD. PMID:27298828

  7. Identification of potential biomarkers for predicting acute dermal irritation by proteomic analysis.

    PubMed

    Zhang, Qihao; Dai, Taoli; Zhang, Lei; Zhang, Minjing; Xiao, Xue; Hu, Hao; Zou, Ping; Liu, Xia; Xiang, Qi; Su, Zhijian; Huang, Yadong; He, Qing-Yu

    2011-11-01

    In vitro alternative tests aiming at replacing the traditional animal test for predicting the irritant potential of chemicals have been developed, but the assessment parameters or endpoints are still not sufficient for analysis. To discover novel endpoints for skin irritation responses, a proteomics approach was used to analyze the protein expression in human keratinocytes exposed to sodium lauryl sulfate in the present study. Among the 20 identified proteins with altered expression, small heat shock protein 27 (HSP27) and superoxide dismutase [Cu-Zn] were down-regulated while cofilin-1 was up-regulated significantly in response to the chemical challenge. Keratinocytes were exposed to acid and basic chemicals for further validation of the proteins. HSP27 displayed the most significant alteration both in mRNA and protein levels, accompanied by nuclear translocation. The irritation also induced an increased production of interleukin-1α in keratinocytes. These findings suggest that these proteins may be combinational biomarkers or additional endpoints for skin hazard assessment. Further investigation into the protein alterations would be helpful for the mechanistic understanding of skin irritation. PMID:21469165

  8. Gene Expression and Proteome Analysis as Sources of Biomarkers in Basal Cell Carcinoma

    PubMed Central

    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

  9. Autoantibody Profiling of Glioma Serum Samples to Identify Biomarkers Using Human Proteome Arrays

    PubMed Central

    Syed, Parvez; Gupta, Shabarni; Choudhary, Saket; Pandala, Narendra Goud; Atak, Apurva; Richharia, Annie; KP, Manubhai; Zhu, Heng; Epari, Sridhar; Noronha, Santosh B.; Moiyadi, Aliasgar; Srivastava, Sanjeeva

    2015-01-01

    The heterogeneity and poor prognosis associated with gliomas, makes biomarker identification imperative. Here, we report autoantibody signatures across various grades of glioma serum samples and sub-categories of glioblastoma multiforme using Human Proteome chips containing ~17000 full-length human proteins. The deduced sets of classifier proteins helped to distinguish Grade II, III and IV samples from the healthy subjects with 88, 89 and 94% sensitivity and 87, 100 and 73% specificity, respectively. Proteins namely, SNX1, EYA1, PQBP1 and IGHG1 showed dysregulation across various grades. Sub-classes of GBM, based on its proximity to the sub-ventricular zone, have been reported to have different prognostic outcomes. To this end, we identified dysregulation of NEDD9, a protein involved in cell migration, with probable prognostic potential. Another subcategory of patients where the IDH1 gene is mutated, are known to have better prognosis as compared to patients carrying the wild type gene. On a comparison of these two cohorts, we found STUB1 and YWHAH proteins dysregulated in Grade II glioma patients. In addition to common pathways associated with tumourigenesis, we found enrichment of immunoregulatory and cytoskeletal remodelling pathways, emphasizing the need to explore biochemical alterations arising due to autoimmune responses in glioma. PMID:26370624

  10. Gene Expression and Proteome Analysis as Sources of Biomarkers in Basal Cell Carcinoma.

    PubMed

    Lupu, Mihai; Caruntu, Constantin; Ghita, Mihaela Adriana; Voiculescu, Vlad; Voiculescu, Suzana; Rosca, Adrian E; Caruntu, Ana; Moraru, Liliana; Popa, Iris Maria; Calenic, Bogdan; Greabu, Maria; Costea, Daniela Elena

    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

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Predictive proteomic biomarkers for inflammatory bowel disease-associated cancer: Where are we now in the era of the next generation proteomics?

    PubMed Central

    Park, Jong-Min; Han, Na Young; Han, Young-Min; Chung, Mi Kyung; Lee, Hoo Keun; Ko, Kwang Hyun; Kim, Eun-Hee; Hahm, Ki Baik

    2014-01-01

    Recent advances in genomic medicine have opened up the possibility of tailored medicine that may eventually replace traditional “one-size-fits all” approaches to the treatment of inflammatory bowel disease (IBD). In addition to exploring the interactions between hosts and microbes, referred to as the microbiome, a variety of strategies that can be tailored to an individual in the coming era of personalized medicine in the treatment of IBD are being investigated. These include prompt genomic screening of patients at risk of developing IBD, the utility of molecular discrimination of IBD subtypes among patients diagnosed with IBD, and the discovery of proteome biomarkers to diagnose or predict cancer risks. Host genetic factors influence the etiology of IBD, as do microbial ecosystems in the human bowel, which are not uniform, but instead represent many different microhabitats that can be influenced by diet and might affect processes essential to bowel metabolism. Further advances in basic research regarding intestinal inflammation may reveal new insights into the role of inflammatory mediators, referred to as the inflammasome, and the macromolecular complex of metabolites formed by intestinal bacteria. Collectively, knowledge of the inflammasome and metagenomics will lead to the development of biomarkers for IBD that target specific pathogenic mechanisms involved in the spontaneous progress of IBD. In this review article, our recent results regarding the discovery of potential proteomic biomarkers using a label-free quantification technique are introduced and on-going projects contributing to either the discrimination of IBD subtypes or to the prediction of cancer risks are accompanied by updated information from IBD biomarker research. PMID:25309077

  13. The proteomics toolbox for agricultural research: precision biomarker discovery using genetics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The vast array of proteomics technologies can often leave investigators wondering which set of tools to use to address their biological question. Deciding which set of tools to apply requires knowledge of the biology of the system and of the subtleties of each proteomics approach. Proteomics appro...

  14. Proteomics of wound exudate in snake venom-induced pathology: search for biomarkers to assess tissue damage and therapeutic success.

    PubMed

    Rucavado, Alexandra; Escalante, Teresa; Shannon, John; Gutiérrez, José María; Fox, Jay W

    2011-04-01

    Tissue damage analysis by traditional laboratory techniques is problematic. Proteomic analysis of exudates collected from affected tissue constitutes a powerful approach to assess tissue alterations, since biomarkers associated with pathologies can be identified in very low concentrations. In this study we proteomically explore the pathological effects induced by the venom of the viperid snake Bothrops asper in the gastrocnemius muscle of mice. Predominant proteins identified in the exudates included intracellular proteins, plasma proteins, extracellular matrix proteins and cell membrane-associated proteins. The presence of such proteins indicates cytotoxicity, plasma exudation, extracellular matrix degradation and shedding of membrane proteins. Some of these proteins may represent useful biomarkers for myonecrosis and microvascular damage. The effect of fucoidan, an inhibitor of myotoxic phospholipases A(2), and batimastat, an inhibitor of metalloproteinases, on the pathological effects induced by B. asper venom were also investigated. Fucoidan reduced the presence of intracellular proteins in exudates, whereas batimastat reduced the amount of relevant extracellular matrix proteins. The combination of these inhibitors resulted in the abrogation of the most relevant pathological effects of this venom. Thus, proteomic analysis of exudates represents a valuable approach to assess the characteristics of tissue damage in pathological models and the success of therapeutic interventions. PMID:21306181

  15. Proteomic Profiling of Paraffin-Embedded Samples Identifies Metaplasia-Specific and Early-Stage Gastric Cancer Biomarkers

    PubMed Central

    Sousa, Josane F.; Ham, Amy-Joan L.; Whitwell, Corbin; Nam, Ki Taek; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Zhang, Bing; Li, Ming; LaFleur, Bonnie; Liebler, Daniel C.; Goldenring, James R.

    2013-01-01

    Early diagnosis and curative resection are the predominant factors associated with increased survival in patients with gastric cancer. However, most gastric cancer cases are still diagnosed at later stages. Since most pathologic specimens are archived as FFPE samples, the ability to use them to generate expression profiles can greatly improve cancer biomarker discovery. We sought to uncover new biomarkers for stomach preneoplastic metaplasias and neoplastic lesions by generating proteome profiles using FFPE samples. We combined peptide isoelectric focusing and liquid chromatography–tandem mass spectrometry analysis to generate proteomic profiles from FFPE samples of intestinal-type gastric cancer, metaplasia, and normal mucosa. The expression patterns of selected proteins were analyzed by immunostaining first in single tissue sections from normal stomach, metaplasia, and gastric cancer and later in larger tissue array cohorts. We detected 60 proteins up-regulated and 87 proteins down-regulated during the progression from normal mucosa to metaplasia to gastric cancer. Two of the up-regulated proteins, LTF and DMBT1, were validated as specific markers for spasmolytic polypeptide–expressing metaplasia and intestinal metaplasia, respectively. In cancers, significantly lower levels of DMBT1 or LTF correlated with more advanced disease and worse prognosis. Thus, proteomic profiling using FFPE samples has led to the identification of two novel markers for stomach metaplasias and gastric cancer prognosis. PMID:22944598

  16. Identification of haptoglobin peptide as a novel serum biomarker for lung squamous cell carcinoma by serum proteome and peptidome profiling.

    PubMed

    Okano, Tetsuya; Seike, Masahiro; Kuribayashi, Hidehiko; Soeno, Chie; Ishii, Takeo; Kida, Kozui; Gemma, Akihiko

    2016-03-01

    To date, a number of potential biomarkers for lung squamous cell cancer (SCC) have been identified; however, sensitive biomarkers are currently lacking to detect early stage SCC due to low sensitivity and specificity. In the present study, we compared the 7 serum proteomic profiles of 11 SCC patients, 7 chronic obstructive pulmonary disease (COPD) patients and 7 healthy smokers as controls to identify potential serum biomarkers associated with SCC and COPD. Two-dimensional difference gel electrophoresis (2D-DIGE) and mass-spectrometric analysis (MS) using an affinity column revealed two candidate proteins, haptoglobin (HP) and apolipoprotein 4, as biomarkers of SCC, and α-1-antichymotrypsin as a marker of COPD. The iTRAQ technique was also used to identify SCC-specific peptides. HP protein expression was significantly higher in SCC patients than in COPD patients. Furthermore, two HP protein peptides showed significantly higher serum levels in SCC patients than in COPD patients. We established novel polyclonal antibodies for the two HP peptides and subsequently a sandwich enzyme-linked immunosorbent assay (ELISA) for the quantification of these specific peptides in patient and control sera. The sensitivity of detection by ELISA of one HP peptide (HP216) was 70% of SCC patients, 40% of COPDs patients and 13% of healthy controls. We also measured CYFRA, a cytokeratin fragment clinically used as an SCC tumor marker, in all the 28 cases and found CYFRA was detected in only seven SCC cases. However, when the measurement of HP216 was combined with that of CYFRA, 100% (10 of 10 patients) of SCC cases were detected. Our proteomic profiling demonstrates that the SCC-specific HP peptide HP216 may potentially be used as a diagnostic biomarker for SCC. PMID:26783151

  17. Identification of haptoglobin peptide as a novel serum biomarker for lung squamous cell carcinoma by serum proteome and peptidome profiling

    PubMed Central

    OKANO, TETSUYA; SEIKE, MASAHIRO; KURIBAYASHI, HIDEHIKO; SOENO, CHIE; ISHII, TAKEO; KIDA, KOZUI; GEMMA, AKIHIKO

    2016-01-01

    To date, a number of potential biomarkers for lung squamous cell cancer (SCC) have been identified; however, sensitive biomarkers are currently lacking to detect early stage SCC due to low sensitivity and specificity. In the present study, we compared the 7 serum proteomic profiles of 11 SCC patients, 7 chronic obstructive pulmonary disease (COPD) patients and 7 healthy smokers as controls to identify potential serum biomarkers associated with SCC and COPD. Two-dimensional difference gel electrophoresis (2D-DIGE) and mass-spectrometric analysis (MS) using an affinity column revealed two candidate proteins, haptoglobin (HP) and apolipoprotein 4, as biomarkers of SCC, and α-1-antichymotrypsin as a marker of COPD. The iTRAQ technique was also used to identify SCC-specific peptides. HP protein expression was significantly higher in SCC patients than in COPD patients. Furthermore, two HP protein peptides showed significantly higher serum levels in SCC patients than in COPD patients. We established novel polyclonal antibodies for the two HP peptides and subsequently a sandwich enzyme-linked immunosorbent assay (ELISA) for the quantification of these specific peptides in patient and control sera. The sensitivity of detection by ELISA of one HP peptide (HP216) was 70% of SCC patients, 40% of COPDs patients and 13% of healthy controls. We also measured CYFRA, a cytokeratin fragment clinically used as an SCC tumor marker, in all the 28 cases and found CYFRA was detected in only seven SCC cases. However, when the measurement of HP216 was combined with that of CYFRA, 100% (10 of 10 patients) of SCC cases were detected. Our proteomic profiling demonstrates that the SCC-specific HP peptide HP216 may potentially be used as a diagnostic biomarker for SCC. PMID:26783151

  18. iTRAQ-Based Quantitative Proteomic Analysis Identified HSC71 as a Novel Serum Biomarker for Renal Cell Carcinoma

    PubMed Central

    Zhang, Yushi; Cai, Yi; Yu, Hongyan; Li, Hanzhong

    2015-01-01

    Renal cell carcinoma (RCC) is one of the most lethal urologic cancers and about 80% of RCC are of the clear-cell type (ccRCC). However, there are no serum biomarkers for the accurate diagnosis of RCC. In this study, we performed a quantitative proteomic analysis on serum samples from ccRCC patients and control group by using isobaric tag for relative and absolute quantitation (iTRAQ) labeling and LC-MS/MS analysis to access differentially expressed proteins. Overall, 16 proteins were significantly upregulated (ratio > 1.5) and 14 proteins were significantly downregulated (ratio < 0.67) in early-stage ccRCC compared to control group. HSC71 was selected and subsequently validated by Western blot in six independent sets of patients. ELISA subsequently confirmed HSC71 as a potential serum biomarker for distinguishing RCC from benign urologic disease with an operating characteristic curve (ROC) area under the curve (AUC) of 0.86 (95% confidence interval (CI), 0.76~0.96), achieving sensitivity of 87% (95% CI 69%~96%) at a specificity of 80% (95% CI 61~92%) with a threshold of 15 ng/mL. iTRAQ-based quantitative proteomic analysis led to identification of serum HSC71 as a novel serum biomarker of RCC, particularly useful in early diagnosis of ccRCC. PMID:26425554

  19. Assessment of Metabolomic and Proteomic Biomarkers in Detection and Prognosis of Progression of Renal Function in Chronic Kidney Disease

    PubMed Central

    Nkuipou-Kenfack, Esther; Duranton, Flore; Gayrard, Nathalie; Argilés, Àngel; Lundin, Ulrika; Weinberger, Klaus M.; Dakna, Mohammed; Delles, Christian; Mullen, William; Husi, Holger; Klein, Julie; Koeck, Thomas; Zürbig, Petra; Mischak, Harald

    2014-01-01

    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

  20. Proteomic analysis of synovial fluid as an analytical tool to detect candidate biomarkers for knee osteoarthritis

    PubMed Central

    Liao, Weixiong; Li, Zhongli; Zhang, Hao; Li, Ji; Wang, Ketao; Yang, Yimeng

    2015-01-01

    We conducted research to detect the proteomic profiles in synovial fluid (SF) from knee osteoarthritis (OA) patients to better understand the pathogenesis and aetiology of OA. Our long-term goal is to identify reliable candidate biomarkers for OA in SF. The SF proteins obtained from 10 knee OA patients and 10 non-OA patients (9 of whom were patients with a meniscus injury in the knee; 1 had a discoid meniscus in the knee, and all exhibited intact articular cartilage) were separated by two-dimensional electrophoresis (2-DE). The repeatability of the obtained protein spots regarding their intensity was tested via triplicate 2-DE of selected samples. The observed protein expression patterns were subjected to statistical analysis, and differentially expressed protein spots were identified via matrix-assisted laser desorption/ionisation-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). Our analyses showed low intrasample variability and clear intersample variation. Among the protein spots observed on the gels, there were 29 significant differences, of which 22 corresponded to upregulation and 7 to downregulation in the OA group. One of the upregulated protein spots was confirmed to be haptoglobin by mass spectrometry, and the levels of haptoglobin in SF are positively correlated with the severity of OA (r = 0.89, P < 0.001). This study showed that 2-DE could be used under standard conditions to screen SF samples and identify a small subset of proteins in SF that are potential markers associated with OA. Spots of interest identified by mass spectrometry, such as haptoglobin, may be associated with OA severity. PMID:26617706

  1. Identification of Biomarkers by Proteomics for Prenatal Screening for Neural Tube Defects.

    PubMed

    Shen, Guosong; He, Pingya; Du, Ying; Zhang, Su

    2016-01-01

    Neural tube defect (NTD) is a serious congenital defect, but current methods for identifying NTD are limited. We used proteomic analysis of maternal serum to identify NTD-specific proteins whose levels differed between women with NTD fetuses (n = 50) and those with healthy fetuses (n = 40). Three NTD-specific protein peaks (8,130.6, 15,941.7, and 3,960.3 m/z) were identified using MALDI-TOF-mass spectrophotemetry, and were included in a diagnostic model developed using Biomarker Patterns software. The model used cut-offs for the relative intensity of the three peaks to indicate if a case had or did not have NTD. The model identified 48 of the 50 NTD cases and 36 of the 40 control cases correctly, resulting in the sensitivity of 96.0% (48/50) and the specificity of 90.0% (36/40). The diagnostic model was also tested on 105 clinical cases at high risk for NTD, as determined by having high alpha-fetoprotein levels, resulting in the sensitivity of 100% (101/101) and the specificity of 75.0% (3/4). Using the International Protein Index database, we identified proteins with a molecular mass of 8,130.6 Da as ADP-ribosylation factor 1 and a protein similar to cold agglutinin FS-1 antibody light-chain. The 15,941.7-Da peak corresponded to vitamin K3 protein, and the identity of the 3,960.3-Da protein was unclear. Thus, this study developed a diagnostic model consisting of the three peaks which may be indicators of NTD. This new assay may be at least as accurate for diagnosing NTD compared with the commonly used clinical test that assesses alpha-fetoprotein levels. PMID:26806611

  2. Serum antibodies to the HPV16 proteome as biomarkers for head and neck cancer

    PubMed Central

    Anderson, K S; Wong, J; D'Souza, G; Riemer, A B; Lorch, J; Haddad, R; Pai, S I; Longtine, J; McClean, M; LaBaer, J; Kelsey, K T; Posner, M

    2011-01-01

    Background: Human papillomavirus (HPV) type 16 is associated with oropharyngeal carcinomas (OPC). Antibodies (Abs) to HPV16 E6 and E7 oncoproteins have been detected in patient sera; however, Abs to other early HPV-derived proteins have not been well explored. Methods: Antibodies to the HPV16 proteome were quantified using a novel multiplexed bead assay, using C-terminal GST-fusion proteins captured onto Luminex beads. Sera were obtained from untreated patients with OPC (N=40), partners of patients with HPV16+ OPC (N=11), and healthy controls (N=50). Results: Oropharyngeal carcinomas patients with known virus-like capsid particle+ Abs had elevated serum Abs to HPV16 E1, E2, E4, E6, and E7, and L1 antibody levels, but not E5. The ratios of specific median fluorescence intensity to p21-GST compared with controls were E1: 50.7 vs 2.1; E4: 14.6 vs 1.3; E6: 11.3 vs 2.4; E7: 43.1 vs 2.6; and L1: 10.3 vs 2.6 (each P⩽0.01). In a validation cohort, HPV16 E1, E2, and E7 antibody levels were significantly elevated compared with healthy control samples (P⩽0.02) and partners of OPC patients (P⩽0.01). Conclusion: Patients with HPV16+ OPC have detectable Abs to E1, E2, and E7 proteins, which are potential biomarkers for HPV-associated OPC. PMID:21654689

  3. Evaluation of Multi-Protein Immunoaffinity Subtraction for Plasma Proteomics and Candidate Biomarker Discovery Using Mass Spectrometry

    SciTech Connect

    Liu, Tao; Qian, Weijun; Mottaz, Heather M.; Gritsenko, Marina A.; Norbeck, Angela D.; Moore, Ronald J.; Purvine, Samuel O.; Camp, David G.; Smith, Richard D.

    2006-11-01

    The detection of low-abundance protein disease biomarkers from human blood poses significant challenges due to the high dynamic range of protein concentrations that span more than 10 orders of magnitude, as well as the extreme complexity of the serum/plasma proteome. Therefore, experimental strategies that include the removal of high-abundance proteins have been increasingly utilized in proteomic studies of serum, plasma, and other body fluids to enhance detection of low-abundance proteins and achieve broader proteome coverage. However, both the specificity and reproducibility of the high-abundance protein depletion process represent common concerns. Here, we report a detailed evaluation of the performance of two commercially available immunoaffinity subtraction systems commonly used in human serum/plasma proteome characterization by high resolution LC-MS/MS. One system uses mammalian IgG antibodies to remove six of the most abundant plasma proteins, and the other uses chicken immunoglobulin yolk (IgY) antibodies to remove twelve of the most abundant plasma proteins. Plasma samples were repeatedly processed using these two systems, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. Removal of target proteins by both immunoaffinity subtraction systems proved reproducible and efficient. Nontarget proteins, including spiked protein standards, were also observed to bind to the columns, but in a fairly reproducible manner. The results suggest that these multi-protein immunoaffinity subtraction systems are both highly effective and reproducible for removing high-abundance proteins and therefore, can be readily integrated into quantitative strategies to enhance detection of low-abundance proteins in biomarker discovery studies.

  4. Serum Proteomic Signature of Human Chagasic Patients for the Identification of Novel Potential Protein Biomarkers of Disease*

    PubMed Central

    Wen, Jian-Jun; Zago, M. Paola; Nuñez, Sonia; Gupta, Shivali; Burgos, Federico Nuñez; Garg, Nisha Jain

    2012-01-01

    Chagas disease is initiated upon infection by Trypanosoma cruzi. Among the health consequences is a decline in heart function, and the pathophysiological mechanisms underlying this manifestation are not well understood. To explore the possible mechanisms, we employed IgY LC10 affinity chromatography in conjunction with ProteomeLab PF2D and two-dimensional gel electrophoresis to resolve the proteome signature of high and low abundance serum proteins in chagasic patients. MALDI-TOF MS/MS analysis yielded 80 and 14 differentially expressed proteins associated with cardiomyopathy of chagasic and other etiologies, respectively. The extent of oxidative stress-induced carbonyl modifications of the differentially expressed proteins (n = 26) was increased and coupled with a depression of antioxidant proteins. Functional annotation of the top networks developed by ingenuity pathway analysis of proteome database identified dysregulation of inflammation/acute phase response signaling and lipid metabolism relevant to production of prostaglandins and arachidonic acid in chagasic patients. Overlay of the major networks identified prothrombin and plasminogen at a nodal position with connectivity to proteome signature indicative of heart disease (i.e., thrombosis, angiogenesis, vasodilatation of blood vessels or the aorta, and increased permeability of blood vessel and endothelial tubes), and inflammatory responses (e.g., platelet aggregation, complement activation, and phagocyte activation and migration). The detection of cardiac proteins (myosin light chain 2 and myosin heavy chain 11) and increased levels of vinculin and plasminogen provided a comprehensive set of biomarkers of cardiac muscle injury and development of clinical Chagas disease in human patients. These results provide an impetus for biomarker validation in large cohorts of clinically characterized chagasic patients. PMID:22543060

  5. From SOMAmer-Based Biomarker Discovery to Diagnostic and Clinical Applications: A SOMAmer-Based, Streamlined Multiplex Proteomic Assay

    PubMed Central

    Kraemer, Stephan; Vaught, Jonathan D.; Bock, Christopher; Gold, Larry; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Saccomano, Nicholas A.; Wilcox, Sheri K.; Zichi, Dom; Sanders, Glenn M.

    2011-01-01

    Recently, we reported a SOMAmer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar), rapid, can be highly multiplexed (upwards of 60 analytes), and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community. PMID:22022604

  6. Identification of five candidate lung cancer biomarkers by proteomics analysis of conditioned media of four lung cancer cell lines.

    PubMed

    Planque, Chris; Kulasingam, Vathany; Smith, Chris R; Reckamp, Karen; Goodglick, Lee; Diamandis, Eleftherios P

    2009-12-01

    Detection of lung cancer at an early stage is necessary for successful therapy and improved survival rates. We performed a bottom-up proteomics analysis using a two-dimensional LC-MS/MS strategy on the conditioned media of four lung cancer cell lines of different histological backgrounds (non-small cell lung cancer: H23 (adenocarcinoma), H520 (squamous cell carcinoma), and H460 (large cell carcinoma); small cell lung cancer: H1688) to identify secreted or membrane-bound proteins that could be useful as novel lung cancer biomarkers. Proteomics analysis of the four conditioned media allowed identification of 1,830 different proteins (965, 871, 726, and 847 from H1688, H23, H460, and H520, respectively). All proteins were assigned a subcellular localization, and 38% were classified as extracellular or membrane-bound. We successfully identified the internal control proteins (also detected by ELISA), kallikrein-related peptidases 14 and 11, and IGFBP2. We also identified known or putative lung cancer tumor markers such as squamous cell carcinoma antigen, carcinoembryonic antigen, chromogranin A, creatine kinase BB, progastrin-releasing peptide, neural cell adhesion molecule, and tumor M2-PK. To select the most promising candidates for validation, we performed tissue specificity assays, functional classifications, literature searches for association to cancer, and a comparison of our proteome with the proteome of lung-related diseases and serum. Five novel lung cancer candidates, ADAM-17, osteoprotegerin, pentraxin 3, follistatin, and tumor necrosis factor receptor superfamily member 1A were preliminarily validated in the serum of patients with lung cancer and healthy controls. Our results demonstrate the utility of this cell culture proteomics approach to identify secreted and shed proteins that are potentially useful as serological markers for lung cancer. PMID:19776420

  7. Identification of Five Candidate Lung Cancer Biomarkers by Proteomics Analysis of Conditioned Media of Four Lung Cancer Cell Lines*

    PubMed Central

    Planque, Chris; Kulasingam, Vathany; Smith, Chris R.; Reckamp, Karen; Goodglick, Lee; Diamandis, Eleftherios P.

    2009-01-01

    Detection of lung cancer at an early stage is necessary for successful therapy and improved survival rates. We performed a bottom-up proteomics analysis using a two-dimensional LC-MS/MS strategy on the conditioned media of four lung cancer cell lines of different histological backgrounds (non-small cell lung cancer: H23 (adenocarcinoma), H520 (squamous cell carcinoma), and H460 (large cell carcinoma); small cell lung cancer: H1688) to identify secreted or membrane-bound proteins that could be useful as novel lung cancer biomarkers. Proteomics analysis of the four conditioned media allowed identification of 1,830 different proteins (965, 871, 726, and 847 from H1688, H23, H460, and H520, respectively). All proteins were assigned a subcellular localization, and 38% were classified as extracellular or membrane-bound. We successfully identified the internal control proteins (also detected by ELISA), kallikrein-related peptidases 14 and 11, and IGFBP2. We also identified known or putative lung cancer tumor markers such as squamous cell carcinoma antigen, carcinoembryonic antigen, chromogranin A, creatine kinase BB, progastrin-releasing peptide, neural cell adhesion molecule, and tumor M2-PK. To select the most promising candidates for validation, we performed tissue specificity assays, functional classifications, literature searches for association to cancer, and a comparison of our proteome with the proteome of lung-related diseases and serum. Five novel lung cancer candidates, ADAM-17, osteoprotegerin, pentraxin 3, follistatin, and tumor necrosis factor receptor superfamily member 1A were preliminarily validated in the serum of patients with lung cancer and healthy controls. Our results demonstrate the utility of this cell culture proteomics approach to identify secreted and shed proteins that are potentially useful as serological markers for lung cancer. PMID:19776420

  8. Randomized Trial of Glucosamine and Chondroitin Supplementation on Inflammation and Oxidative Stress Biomarkers and Plasma Proteomics Profiles in Healthy Humans

    PubMed Central

    Navarro, Sandi L.; White, Emily; Kantor, Elizabeth D.; Zhang, Yuzheng; Rho, Junghyun; Song, Xiaoling; Milne, Ginger L.; Lampe, Paul D.; Lampe, Johanna W.

    2015-01-01

    Background Glucosamine and chondroitin are popular non-vitamin dietary supplements used for osteoarthritis. Long-term use is associated with lower incidence of colorectal and lung cancers and with lower mortality; however, the mechanism underlying these observations is unknown. In vitro and animal studies show that glucosamine and chondroitin inhibit NF-kB, a central mediator of inflammation, but no definitive trials have been done in healthy humans. Methods We conducted a randomized, double-blind, placebo-controlled, cross-over study to assess the effects of glucosamine hydrochloride (1500 mg/d) plus chondroitin sulfate (1200 mg/d) for 28 days compared to placebo in 18 (9 men, 9 women) healthy, overweight (body mass index 25.0–32.5 kg/m2) adults, aged 20–55 y. We examined 4 serum inflammatory biomarkers: C-reactive protein (CRP), interleukin 6, and soluble tumor necrosis factor receptors I and II; a urinary inflammation biomarker: prostaglandin E2-metabolite; and a urinary oxidative stress biomarker: F2-isoprostane. Plasma proteomics on an antibody array was performed to explore other pathways modulated by glucosamine and chondroitin. Results Serum CRP concentrations were 23% lower after glucosamine and chondroitin compared to placebo (P = 0.048). There were no significant differences in other biomarkers. In the proteomics analyses, several pathways were significantly different between the interventions after Bonferroni correction, the most significant being a reduction in the “cytokine activity” pathway (P = 2.6 x 10-16), after glucosamine and chondroitin compared to placebo. Conclusion Glucosamine and chondroitin supplementation may lower systemic inflammation and alter other pathways in healthy, overweight individuals. This study adds evidence for potential mechanisms supporting epidemiologic findings that glucosamine and chondroitin are associated with reduced risk of lung and colorectal cancer. Trial Registration ClinicalTrials.gov NCT01682694 PMID

  9. Metabolomic and proteomic biomarkers for III-V semiconductors: Chemical-specific porphyrinurias and proteinurias

    SciTech Connect

    Fowler, Bruce A. . E-mail: bxf9@cdc.gov; Conner, Elizabeth A.; Yamauchi, Hiroshi

    2005-08-07

    A pressing need exists to develop and validate molecular biomarkers to assess the early effects of chemical agents, both individually and in mixtures. This is particularly true for new and chemically intensive industries such as the semiconductor industry. Previous studies from this laboratory and others have demonstrated element-specific alterations of the heme biosynthetic pathway for the III-V semiconductors gallium arsenide (GaAs) and indium arsenide (InAs) with attendant increased urinary excretion of specific heme precursors. These data represent an example of a metabolomic biomarker to assess chemical effects early, before clinical disease develops. Previous studies have demonstrated that the intratracheal or subcutaneous administration of GaAs and InAs particles to hamsters produces the induction of the major stress protein gene families in renal proximal tubule cells. This was monitored by 35-S methionine labeling of gene products followed by two-dimensional gel electrophoresis after exposure to InAs particles. The present studies examined whether these effects were associated with the development of compound-specific proteinuria after 10 or 30 days following subcutaneous injection of GaAs or InAs particles in hamsters. The results of these studies demonstrated the development of GaAs- and InAs-specific alterations in renal tubule cell protein expression patterns that varied at 10 and 30 days. At the 30-day point, cells in hamsters that received InAs particles showed marked attenuation of protein expression, suggesting inhibition of the stress protein response. These changes were associated with GaAs and InAs proteinuria patterns as monitored by two-dimensional gel electrophoresis and silver staining. The intensity of the protein excretion patterns increased between the 10- and 30-day points and was most pronounced for animals in the 30-day InAs treatment group. No overt morphologic signs of cell death were seen in renal tubule cells of these animals

  10. Exploring the potential of the platelet membrane proteome as a source of peripheral biomarkers for Alzheimer's disease

    PubMed Central

    2013-01-01

    Introduction Peripheral biomarkers to diagnose Alzheimer's disease (AD) have not been established. Given parallels between neuron and platelet biology, we hypothesized platelet membrane-associated protein changes may differentiate patients clinically defined with probable AD from noncognitive impaired controls. Methods Purified platelets, confirmed by flow cytometry were obtained from individuals before fractionation by ultracentrifugation. Following a comparison of individual membrane fractions by SDS-PAGE for general proteome uniformity, equal protein weight from the membrane fractions for five representative samples from AD and five samples from controls were pooled. AD and control protein pools were further divided into molecular weight regions by one-dimensional SDS-PAGE, prior to digestion in gel. Tryptic peptides were analyzed by reverse-phase liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Ionized peptide intensities were averaged for each identified protein in the two pools, thereby measuring relative protein abundance between the two membrane protein pools. Log2-transformed ratio (AD/control) of protein abundances fit a normal distribution, thereby permitting determination of significantly changed protein abundances in the AD pool. Results We report a comparative analysis of the membrane-enriched platelet proteome between patients with mild to moderate AD and cognitively normal, healthy subjects. A total of 144 proteins were determined significantly altered in the platelet membrane proteome from patients with probable AD. In particular, secretory (alpha) granule proteins were dramatically reduced in AD. Of these, we confirmed significant reduction of thrombospondin-1 (THBS1) in the AD platelet membrane proteome by immunoblotting. There was a high protein-protein connectivity of proteins in other pathways implicated by proteomic changes to the proteins that define secretory granules. Conclusions Depletion of secretory granule proteins

  11. Proteomic identification of alpha-2-HS-glycoprotein as a plasma biomarker of hypopharyngeal squamous cell carcinoma.

    PubMed

    Tian, Wen-Dong; Li, Jun-Zheng; Hu, Shui-Wang; Peng, Xiao-Wei; Li, Gang; Liu, Xiong; Chen, Huai-Hong; Xu, Xia; Li, Xiang-Ping

    2015-01-01

    Hypopharyngeal squamous cell carcinoma (HSCC) has very poor prognosis compared with other head and neck squamous cell carcinomas. Late-stage diagnosis of HSCC increases mortality. Therefore, more effective biomarkers for early diagnosis of HSCC are necessary. Unfortunately, appropriate biomarkers for clinical diagnosis and prognosis have not been identified yet. However, recent progresses in quantitative proteomics have offered opportunities to identify plasma proteins as biomarkers for HSCC. In the present study, plasma samples were analyzed by two-dimensional differential gel electrophoresis (2D-DIGE), and differentially expressed proteins were identified by matrix assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). A total of 26 proteins representing 12 unique gene products were identified. The up-regulation proteins were alpha-2-HS-glycoprotein (AHSG), complement C4-B, haptoglobin, C-reactive protein, and ceruloplasmin, whereas the down-regulation proteins were serum albumin, angiotensinogen, alpha-1-antichymotrypsin, Ig gamma-3 chain C region, fibrinogen gamma chain, apolipoprotein A-I, and Ig kappa chain C region. Among all the differentially expressed proteins, AHSG was validated by western blot and ELISA. The results were consistent with the data from 2D-DIGE, further suggesting that AHSG may be employed as a potential biomarker for the early diagnosis of HSCC. In summary, this study was the first to use 2D-DIGE and MALDI-TOF/TOF platform to identify the potential plasma biomarkers for HSCC. The plasma AHSG showed great potential for HSCC screening. PMID:26464644

  12. Identification of Cardiac Myosin-binding Protein C as a Candidate Biomarker of Myocardial Infarction by Proteomics Analysis*

    PubMed Central

    Jacquet, Sebastien; Yin, Xiaoke; Sicard, Pierre; Clark, James; Kanaganayagam, Gajen S.; Mayr, Manuel; Marber, Michael S.

    2009-01-01

    Acute myocardial infarction (AMI) is a common cause of death for which effective treatments are available provided that diagnosis is rapid. The current diagnostic gold standards are circulating cardiac troponins I and T. However, their slow release delays diagnosis, and their persistence limits their utility in the identification of reinfarction. The aim was to identify candidate biomarkers of AMI. Isolated mouse hearts were perfused with oxygenated protein-free buffer, and coronary effluent was collected after ischemia or during matched normoxic perfusion. Effluents were analyzed using proteomics approaches based on one- or two-dimensional initial separation. Of the 459 proteins identified after ischemia with one-dimensional separation, 320 were not detected in the control coronary effluent. Among these were all classic existing biomarkers of AMI. We also identified the cardiac isoform of myosin-binding protein C in its full-length form and as a 40-kDa degradation product. This protein was not detected in the other murine organs examined, increased markedly with even trivial myocardial infarction, and could be detected in the plasma after myocardial infarction in vivo, a profile compatible with a biomarker of AMI. Two-dimensional fluorescence DIGE of ischemic and control coronary effluents identified more than 200 asymmetric spots verified by swapping dyes. Once again existing biomarkers of injury were confirmed as well as posttranslational modifications of antioxidant proteins such as peroxiredoxins. Perfusing hearts with protein-free buffers provides a platform of graded ischemic injury that allows detailed analysis of protein release and identification of candidate cardiac biomarkers like myosin-binding protein C. PMID:19721077

  13. Proteomic identification of alpha-2-HS-glycoprotein as a plasma biomarker of hypopharyngeal squamous cell carcinoma

    PubMed Central

    Tian, Wen-Dong; Li, Jun-Zheng; Hu, Shui-Wang; Peng, Xiao-Wei; Li, Gang; Liu, Xiong; Chen, Huai-Hong; Xu, Xia; Li, Xiang-Ping

    2015-01-01

    Hypopharyngeal squamous cell carcinoma (HSCC) has very poor prognosis compared with other head and neck squamous cell carcinomas. Late-stage diagnosis of HSCC increases mortality. Therefore, more effective biomarkers for early diagnosis of HSCC are necessary. Unfortunately, appropriate biomarkers for clinical diagnosis and prognosis have not been identified yet. However, recent progresses in quantitative proteomics have offered opportunities to identify plasma proteins as biomarkers for HSCC. In the present study, plasma samples were analyzed by two-dimensional differential gel electrophoresis (2D-DIGE), and differentially expressed proteins were identified by matrix assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). A total of 26 proteins representing 12 unique gene products were identified. The up-regulation proteins were alpha-2-HS-glycoprotein (AHSG), complement C4-B, haptoglobin, C-reactive protein, and ceruloplasmin, whereas the down-regulation proteins were serum albumin, angiotensinogen, alpha-1-antichymotrypsin, Ig gamma-3 chain C region, fibrinogen gamma chain, apolipoprotein A-I, and Ig kappa chain C region. Among all the differentially expressed proteins, AHSG was validated by western blot and ELISA. The results were consistent with the data from 2D-DIGE, further suggesting that AHSG may be employed as a potential biomarker for the early diagnosis of HSCC. In summary, this study was the first to use 2D-DIGE and MALDI-TOF/TOF platform to identify the potential plasma biomarkers for HSCC. The plasma AHSG showed great potential for HSCC screening. PMID:26464644

  14. Rapid Identification of Protein Biomarkers of E. coli O157:H7 by MALDI-TOF-TOF Mass Spectrometry and Top-Down Proteomics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We have identified six protein biomarkers from two strains of E. coli O157:H7 and one non-pathogenic E. coli strain by matrix-assisted laser desorption/ionization (MALDI) time-of-flight/time-of-flight tandem mass spectrometry (TOF/TOF-MS/MS) and top-down proteomics. Mature, intact proteins were ext...

  15. Response to cold acclimation in diapause pupae of Hyles euphorbiae (Lepidoptera: Sphingidae): candidate biomarker identification using proteomics.

    PubMed

    Stuckas, H; Mende, M B; Hundsdoerfer, A K

    2014-08-01

    The distribution range of Hyles euphorbiae covers distinct climates across the Palaearctic. Previous investigations showed a correlation between mitochondrial DNA identity of populations and climatic conditions related to winter; however, the lack of biomarkers hampers investigations to test whether geographically distinct populations do show specific molecular responses to low temperatures or whether they possess specific genetic identity at loci functionally related to cold response. The present study was designed to identify candidate protein biomarkers and biological processes that are associated with cold acclimation of overwintering H. euphorbiae diapause pupae. Specimens taken from a single central European population were gradually cooled from 20 °C to -2 °C over 36 days and 12 differentially abundant proteins were identified. In addition, DeepSuperSAGE sequencing technology was applied to study differentially regulated genes. There was incongruence between differentially abundant proteins and differentially expressed genes, but functional characteristics of regulated proteins and analyses of gene ontology term enrichment among differentially regulated genes pointed to activation of the same biological processes, e.g. oxidative stress response. As proteins represent biologically active molecules, candidate biomarkers derived from proteomics are considered well suited to explore intraspecific patterns of local adaptation to different climates. PMID:24628883

  16. Quantitative proteomics analysis to identify diffuse axonal injury biomarkers in rats using iTRAQ coupled LC-MS/MS.

    PubMed

    Zhang, Peng; Zhu, Shisheng; Li, Yongguo; Zhao, Minzhu; Liu, Meng; Gao, Jun; Ding, Shijia; Li, Jianbo

    2016-02-01

    Diffuse axonal injury (DAI) is fairly common during a traumatic brain injury (TBI) and is associated with high mortality. Making an early diagnosis, appropriate therapeutic decisions, and an accurate prognostic evaluation of patients with DAI still pose difficulties for clinicians. The detailed mechanisms of axonal injury after head trauma have yet to be clearly defined and no reliable biomarkers are available for early DAI diagnosis. Therefore, this study employed an established DAI animal model in conjunction with an isobaric tag for relative and absolute quantification (iTRAQ)-based protein identification/quantification approach. Alterations in rat cerebral protein expression were quantified using iTRAQ coupled LC-MS/MS, with differentially expressed proteins between the control groups, sham and sham-injured, and the injury groups, animals that died immediately post-injury and those sacrificed at 1h, 6h, 1d, 3d and 7d post-injury, identified. A total of 1858 proteins were identified and quantified and comparative analysis identified ten candidate proteins that warranted further examination. Of the ten candidate DAI biomarkers, four proteins, citrate synthase (CS), synaptosomal-associated protein 25 (Snap25), microtubule-associated protein 1B (MAP1B) and Rho-associated protein kinase 2 (Rock2), were validated by subsequent Western blot and immunohistochemistry analyses. Our studies not only identified several novel biomarkers that may provide insight into the pathophysiological mechanisms of DAI, but also demonstrated the feasibility of iTRAQ-based quantitative proteomic analysis in cerebral tissue research. PMID:26710722

  17. IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomic biomarker discovery

    SciTech Connect

    Shi, Tujin; Zhou, Jianying; Gritsenko, Marina A.; Hossain, Mahmud; Camp, David G.; Smith, Richard D.; Qian, Weijun

    2012-02-01

    Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up to 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.

  18. Searching for the noninvasive biomarker Holy Grail: Are urine proteomics the answer?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recently, biobehavioral nursing scientists have focused their attention on the search for biomarkers or biological signatures to identify patients at risk for various health problems and poor disease outcomes. In response to the national impetus for biomarker discovery, the measurement of biological...

  19. Feasibility of investigating differential proteomic expression in depression: implications for biomarker development in mood disorders.

    PubMed

    Frye, M A; Nassan, M; Jenkins, G D; Kung, S; Veldic, M; Palmer, B A; Feeder, S E; Tye, S J; Choi, D S; Biernacka, J M

    2015-01-01

    The objective of this study was to determine whether proteomic profiling in serum samples can be utilized in identifying and differentiating mood disorders. A consecutive sample of patients with a confirmed diagnosis of unipolar (UP n=52) or bipolar depression (BP-I n=46, BP-II n=49) and controls (n=141) were recruited. A 7.5-ml blood sample was drawn for proteomic multiplex profiling of 320 proteins utilizing the Myriad RBM Discovery Multi-Analyte Profiling platform. After correcting for multiple testing and adjusting for covariates, growth differentiation factor 15 (GDF-15), hemopexin (HPX), hepsin (HPN), matrix metalloproteinase-7 (MMP-7), retinol-binding protein 4 (RBP-4) and transthyretin (TTR) all showed statistically significant differences among groups. In a series of three post hoc analyses correcting for multiple testing, MMP-7 was significantly different in mood disorder (BP-I+BP-II+UP) vs controls, MMP-7, GDF-15, HPN were significantly different in bipolar cases (BP-I+BP-II) vs controls, and GDF-15, HPX, HPN, RBP-4 and TTR proteins were all significantly different in BP-I vs controls. Good diagnostic accuracy (ROC-AUC⩾0.8) was obtained most notably for GDF-15, RBP-4 and TTR when comparing BP-I vs controls. While based on a small sample not adjusted for medication state, this discovery sample with a conservative method of correction suggests feasibility in using proteomic panels to assist in identifying and distinguishing mood disorders, in particular bipolar I disorder. Replication studies for confirmation, consideration of state vs trait serial assays to delineate proteomic expression of bipolar depression vs previous mania, and utility studies to assess proteomic expression profiling as an advanced decision making tool or companion diagnostic are encouraged. PMID:26645624

  20. The distinctive gastric fluid proteome in gastric cancer reveals a multi-biomarker diagnostic profile

    PubMed Central

    Kon, Oi Lian; Yip, Tai-Tung; Ho, Meng Fatt; Chan, Weng Hoong; Wong, Wai Keong; Tan, Soo Yong; Ng, Wai Har; Kam, Siok Yuen; Eng, Alvin KH; Ho, Patrick; Viner, Rosa; Ong, Hock Soo; Kumarasinghe, M Priyanthi

    2008-01-01

    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 < 0.01). Multimarker clustering showed two distinctive proteomic profiles independent of age and ethnicity. Eighteen of 19 cancer samples clustered together (sensitivity 95%) while 27/36 of non-cancer samples clustered in a second group. Nine non-cancer samples that clustered with cancer samples included 5 pre-malignant lesions (1 adenomatous polyp and 4 intestinal metaplasia). Validation using a second sample set showed the sensitivity and specificity to be 88% and 93%, respectively. Positive predictive value of the combined data was 0.80. Selected peptide sequencing identified pepsinogen C and pepsin A activation peptide as significantly down-regulated and alpha-defensin as significantly up-regulated. 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. PMID:18950519

  1. Environmental monitoring of Domingo Rubio stream (Huelva Estuary, SW Spain) by combining conventional biomarkers and proteomic analysis in Carcinus maenas.

    PubMed

    Montes Nieto, Rafael; García-Barrera, Tamara; Gómez-Ariza, José-Luis; López-Barea, Juan

    2010-02-01

    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. PMID:19815320

  2. Identification of HSPA8 as a candidate biomarker for endometrial carcinoma by using iTRAQ-based proteomic analysis

    PubMed Central

    Shan, Nianchun; Zhou, Wei; Zhang, Shufen; Zhang, Yu

    2016-01-01

    Although there are advances in diagnostic, predictive, and therapeutic strategies, discovering protein biomarker for early detection is required for improving the survival rate of the patients with endometrial carcinoma. In this study, we identify proteins that are differentially expressed between the Stage I endometrial carcinoma and the normal pericarcinous tissues by using isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic analysis. Totally, we screened 1,266 proteins. Among them, 103 proteins were significantly overexpressed, and 30 were significantly downexpressed in endometrial carcinoma. Using the bioinformatics analysis, we identified a list of proteins that might be closely associated with endometrial carcinoma, including CCT7, HSPA8, PCBP2, LONP1, PFN1, and EEF2. We validated the gene overexpression of these molecules in the endometrial carcinoma tissues and found that HSPA8 was most significantly upregulated. We further validated the overexpression of HSPA8 by using immunoblot analysis. Then, HSPA8 siRNA was transferred into the endometrial cancer cells RL-95-2 and HEC-1B. The depletion of HSPA8 siRNAs significantly reduced cell proliferation, promoted cell apoptosis, and suppressed cell growth in both cell lines. Taken together, HSPA8 plays a vital role in the development of endometrial carcinoma. HSPA8 is a candidate biomarker for early diagnosis and therapy of Stage I endometrial carcinoma. PMID:27110132

  3. Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation

    PubMed Central

    2010-01-01

    Background To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Methods Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Results Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Conclusions Coronin-1C could be a candidate biomarker to predict HCC invasive behavior. PMID:20181269

  4. Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

    PubMed Central

    Beretov, Julia; Wasinger, Valerie C.; Millar, Ewan K. A.; Schwartz, Peter; Graham, Peter H.; Li, Yong

    2015-01-01

    Introduction Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression. Method We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20). Results Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively. Conclusions Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns

  5. SILAC-based quantitative proteomic approach to identify potential biomarkers from the esophageal squamous cell carcinoma secretome

    PubMed Central

    Kashyap, Manoj Kumar; Harsha, HC; Renuse, Santosh; Pawar, Harsh; Sahasrabuddhe, Nandini A; Kim, Min-Sik; Marimuthu, Arivusudar; Keerthikumar, Shivakumar; Muthusamy, Babylakshmi; Kandasamy, Kumaran; Subbannayya, Yashwanth; Prasad, Thottethodi Subrahmanya Keshava; Mahmood, Riaz; Chaerkady, Raghothama; Meltzer, Stephen J; Kumar, Rekha V; Rustgi, Anil K

    2010-01-01

    The identification of secreted proteins that are differentially expressed between non-neoplastic and esophageal squamous cell carcinoma (ESCC) cells can provide potential biomarkers of ESCC. We used a SILAC-based quantitative proteomic approach to compare the secretome of ESCC cells with that of non-neoplastic esophageal squamous epithelial cells. Proteins were resolved by SDS-PAGE and tandem mass spectrometry analysis (LC-MS/MS) of in-gel trypsindigested peptides was carried out on a high-accuracy qTOF mass spectrometer. In total, we identified 441 proteins in the combined secretomes, including 120 proteins with ≥ 2-fold upregulation in the ESCC secretome vs. that of non-neoplastic esophageal squamous epithelial cells. In this study, several potential protein biomarkers previously known to be increased in ESCC including matrix metalloproteinase 1, transferrin receptor and transforming growth factor beta-induced 68 kDa were identified as overexpressed in the ESCC-derived secretome. In addition, we identified several novel proteins that have not been previously reported to be associated with ESCC. Among the novel candidate proteins identified, protein disulfide isomerase family a member 3 (PDIA3), GDP dissociation inhibitor 2 (GDI2) and lectin galactoside binding soluble 3 binding protein (LGALS3BP) were further validated by immunoblot analysis and immunohistochemical labeling using tissue microarrays. This tissue microarray analysis showed overexpression of protein disulfide isomerase family a member 3, GDP dissociation inhibitor 2 and lectin galactoside binding soluble 3 binding protein in 93, 93 and 87% of 137 ESCC cases, respectively. Hence, we conclude that these potential biomarkers are excellent candidates for further evaluation to test their role and efficacy in the early detection of ESCC. PMID:20686364

  6. Statistical considerations of optimal study design for human plasma proteomics and biomarker discovery.

    PubMed

    Zhou, Cong; Simpson, Kathryn L; Lancashire, Lee J; Walker, Michael J; Dawson, Martin J; Unwin, Richard D; Rembielak, Agata; Price, Patricia; West, Catharine; Dive, Caroline; Whetton, Anthony D

    2012-04-01

    A mass spectrometry-based plasma biomarker discovery workflow was developed to facilitate biomarker discovery. Plasma from either healthy volunteers or patients with pancreatic cancer was 8-plex iTRAQ labeled, fractionated by 2-dimensional reversed phase chromatography and subjected to MALDI ToF/ToF mass spectrometry. Data were processed using a q-value based statistical approach to maximize protein quantification and identification. Technical (between duplicate samples) and biological variance (between and within individuals) were calculated and power analysis was thereby enabled. An a priori power analysis was carried out using samples from healthy volunteers to define sample sizes required for robust biomarker identification. The result was subsequently validated with a post hoc power analysis using a real clinical setting involving pancreatic cancer patients. This demonstrated that six samples per group (e.g., pre- vs post-treatment) may provide sufficient statistical power for most proteins with changes>2 fold. A reference standard allowed direct comparison of protein expression changes between multiple experiments. Analysis of patient plasma prior to treatment identified 29 proteins with significant changes within individual patient. Changes in Peroxiredoxin II levels were confirmed by Western blot. This q-value based statistical approach in combination with reference standard samples can be applied with confidence in the design and execution of clinical studies for predictive, prognostic, and/or pharmacodynamic biomarker discovery. The power analysis provides information required prior to study initiation. PMID:22338609

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

    NASA Astrophysics Data System (ADS)

    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.

  8. Proteomic Biomarkers for Ageing the Mosquito Aedes aegypti to Determine Risk of Pathogen Transmission

    PubMed Central

    Hugo, Leon E.; Monkman, James; Dave, Keyur A.; Wockner, Leesa F.; Birrell, Geoff W.; Norris, Emma L.; Kienzle, Vivian J.; Sikulu, Maggy T.; Ryan, Peter A.; Gorman, Jeffery J.; Kay, Brian H.

    2013-01-01

    Biomarkers of the age of mosquitoes are required to determine the risk of transmission of various pathogens as each pathogen undergoes a period of extrinsic incubation in the mosquito host. Using the 2-D Difference Gel Electrophoresis (2-D DIGE) procedure, we investigated the abundance of up to 898 proteins from the Yellow Fever and dengue virus vector, Aedes aegypti, during ageing. By applying a mixed-effects model of protein expression, we identified five common patterns of abundance change during ageing and demonstrated an age-related decrease in variance for four of these. This supported a search for specific proteins with abundance changes that remain tightly associated with ageing for use as ageing biomarkers. Using MALDI-TOF/TOF mass spectrometry we identified ten candidate proteins that satisfied strict biomarker discovery criteria (identified in two out of three multivariate analysis procedures and in two cohorts of mosquitoes). We validated the abundances of the four most suitable candidates (Actin depolymerising factor; ADF, Eukaryotic initiation factor 5A; eIF5A, insect cuticle protein Q17LN8, and Anterior fat body protein; AFP) using semi-quantitative Western analysis of individual mosquitoes of six ages. The redox-response protein Manganese superoxide dismutase (SOD2) and electron shuttling protein Electron transfer oxidoreductase (ETO) were subject to post-translational modifications affecting their charge states with potential effects on function. For the four candidates we show remarkably consistent decreases in abundance during ageing, validating initial selections. In particular, the abundance of AFP is an ideal biomarker candidate for whether a female mosquito has lived long enough to be capable of dengue virus transmission. We have demonstrated proteins to be a suitable class of ageing biomarkers in mosquitoes and have identified candidates for epidemiological studies of dengue and the evaluation of new disease reduction projects targeting

  9. A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma.

    PubMed

    Ahn, Yeong Hee; Shin, Park Min; Oh, Na Ree; Park, Gun Wook; Kim, Hoguen; Yoo, Jong Shin

    2012-09-18

    Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression. PMID:22789673

  10. Solvent interaction analysis as a proteomic approach to structure-based biomarker discovery and clinical diagnostics.

    PubMed

    Zaslavsky, Boris Y; Uversky, Vladimir N; Chait, Arnon

    2016-01-01

    Proteins have several measurable features in biological fluids that may change under pathological conditions. The current disease biomarker discovery is mostly based on protein concentration in the sample as the measurable feature. Changes in protein structures, such as post-translational modifications and in protein-partner interactions are known to accompany pathological processes. Changes in glycosylation profiles are well-established for many plasma proteins in various types of cancer and other diseases. The solvent interaction analysis method is based on protein partitioning in aqueous two-phase systems and is highly sensitive to changes in protein structure and protein-protein- and protein-partner interactions while independent of the protein concentration in the biological sample. It provides quantitative index: partition coefficient representing changes in protein structure and interactions with partners. The fundamentals of the method are presented with multiple examples of applications of the method to discover and monitor structural protein biomarkers as disease-specific diagnostic indicators. PMID:26558960

  11. Meningiomas and Proteomics: Focus on New Potential Biomarkers and Molecular Pathways.

    PubMed

    Abbritti, Rosaria Viola; Polito, Francesca; Cucinotta, Maria; Lo Giudice, Claudio; Caffo, Maria; Tomasello, Chiara; Germanò, Antonino; Aguennouz, Mohammed

    Meningiomas are one of the most common tumors affecting the central nervous system, exhibiting a great heterogeneity in grading, treatment and molecular background. This article provides an overview of the current literature regarding the molecular aspect of meningiomas. Analysis of potential biomarkers in serum, cerebrospinal fluid (CSF) and pathological tissues was reported. Applying bioinformatic methods and matching the common proteic profile, arising from different biological samples, we highlighted the role of nine proteins, particularly related to tumorigenesis and grading of meningiomas: serpin peptidase inhibitor alpha 1, ceruloplasmin, hemopexin, albumin, C3, apolipoprotein, haptoglobin, amyloid-P-component serum and alpha-1-beta-glycoprotein. These proteins and their associated pathways, including complement and coagulation cascades, plasma lipoprotein particle remodeling and lipid metabolism could be considered possible diagnostic, prognostic biomarkers, and eventually therapeutic targets. Further investigations are needed to better characterize the role of these proteins and pathways in meningiomas. The role of new therapeutic strategies are also discussed. PMID:27566655

  12. Proteomics analysis of urine reveals acute phase response proteins as candidate diagnostic biomarkers for prostate cancer.

    PubMed

    Davalieva, Katarina; Kiprijanovska, Sanja; Komina, Selim; Petrusevska, Gordana; Zografska, Natasha Chokrevska; Polenakovic, Momir

    2015-01-01

    Despite the overall success of prostate specific antigen (PSA) in screening and detection of prostate cancer (PCa), its use has been limited due to the lack of specificity. The principal driving goal currently within PCa research is to identify non-invasive biomarker(s) for early detection of aggressive tumors with greater sensitivity and specificity than PSA. In this study, we focused on identification of non-invasive biomarkers in urine with higher specificity than PSA. We tested urine samples from PCa and benign prostatic hyperplasia (BPH) patients by 2-D DIGE coupled with MS and bioinformatics analysis. Statistically significant (p < 0.05), 1.8 fold variation or more in abundance, showed 41 spots, corresponding to 23 proteins. The Ingenuity Pathway Analysis showed significant association with the Acute Phase Response Signaling pathway. Nine proteins with differential abundances were included in this pathway: AMBP, APOA1, FGA, FGG, HP, ITIH4, SERPINA1, TF and TTR. The expression pattern of 4 acute phase response proteins differed from the defined expression in the canonical pathway. The urine levels of TF, AMPB and HP were measured by immunoturbidimetry in an independent validation set. The concentration of AMPB in urine was significantly higher in PCa while levels of TF and HP were opposite (p < 0.05). The AUC for the individual proteins ranged from 0.723 to 0.754. The combination of HP and AMBP yielded the highest accuracy (AUC = 0.848), greater than PSA. The proposed biomarker set is quickly quantifiable and economical with potential to improve the sensitivity and specificity of PCa detection. PMID:25653573

  13. 2D gel blood serum biomarkers reveal differential clinical proteomics of the neurodegenerative diseases.

    PubMed

    Sheta, Essam A; Appel, Stanley H; Goldknopf, Ira L

    2006-02-01

    This review addresses the challenges of neuroproteomics and recent progress in biomarkers and tests for neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. The review will discuss how the application of quantitative 2D gel electrophoresis, combined with appropriate single-variable and multivariate biostatistics, allows for selection of disease-specific serum biomarkers. It will also address how the use of large cohorts of specifically targeted patient blood serum samples and complimentary age-matched controls, in parallel with the use of selected panels of these biomarkers, are being applied to the development of blood tests to specifically address unmet pressing needs in the differential diagnosis of these diseases, and to provide potential avenues for mechanism-based drug targeting and treatment monitoring. While exploring recent findings in this area, the review discusses differences in critical pathways of immune/inflammation and amyloid formation between Parkinson's disease and amyotrophic lateral sclerosis, as well as discernable synergistic relationships between these pathways that are revealed by this approach. The potential for pathway measurement in blood tests for differential diagnosis, disease burden and therapeutic monitoring is also outlined. PMID:16445350

  14. Serum Proteomic Changes after Randomized Prolonged Erythropoietin Treatment and/or Endurance Training: Detection of Novel Biomarkers

    PubMed Central

    Christensen, Britt; Ludvigsen, Maja; Nellemann, Birgitte; Kopchick, John J.; Honoré, Bent; Jørgensen, Jens Otto L.

    2015-01-01

    Introduction 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. Trial Design 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. Methods 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. Results 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. Conclusion An isoform of haptoglobin/haptoglobin related protein could be a new anti-doping marker and merits further research. Trial Registration ClinicalTrials.gov NCT01320449 PMID:25679398

  15. Identification and Validation of Loa loa Microfilaria-Specific Biomarkers: a Rational Design Approach Using Proteomics and Novel Immunoassays

    PubMed Central

    Drame, Papa M.; Meng, Zhaojing; Bennuru, Sasisekhar; Herrick, Jesica A.; Veenstra, Timothy D.

    2016-01-01

    ABSTRACT Immunoassays are currently needed to quantify Loa loa microfilariae (mf). To address this need, we have conducted proteomic and bioinformatic analyses of proteins present in the urine of a Loa mf-infected patient and used this information to identify putative biomarkers produced by L. loa mf. In total, 70 of the 15,444 described putative L. loa proteins were identified. Of these 70, 18 were L. loa mf specific, and 2 of these 18 (LOAG_16297 and LOAG_17808) were biologically immunogenic. We developed novel reverse luciferase immunoprecipitation system (LIPS) immunoassays to quantify these 2 proteins in individual plasma samples. Levels of these 2 proteins in microfilaremic L. loa-infected patients were positively correlated to mf densities in the corresponding blood samples (r = 0.71 and P < 0.0001 for LOAG_16297 and r = 0.61 and P = 0.0002 for LOAG_17808). For LOAG_16297, the levels in plasma were significantly higher in Loa-infected (geometric mean [GM], 0.045 µg/ml) than in uninfected (P < 0.0001), Wuchereria bancrofti-infected (P = 0.0005), and Onchocerca volvulus-infected (P < 0.0001) individuals, whereas for LOAG_17808 protein, they were not significantly different between Loa-infected (GM, 0.123 µg/ml) and uninfected (P = 0.06) and W. bancrofti-infected (P = 0.32) individuals. Moreover, only LOAG_16297 showed clear discriminative ability between L. loa and the other potentially coendemic filariae. Indeed, the specificity of the LOAG_16297 reverse LIPS assay was 96% (with a sensitivity of 77%). Thus, LOAG_16297 is a very promising biomarker that will be exploited in a quantitative point-of-care immunoassay for determination of L. loa mf densities. PMID:26884435

  16. Clinical Proteomics Identifies Urinary CD14 as a Potential Biomarker for Diagnosis of Stable Coronary Artery Disease

    PubMed Central

    Lee, Min-Yi; Huang, Chun-Hao; Kuo, Chao-Jen; Lin, Chen-Lung Steve; Lai, Wen-Ter; Chiou, Shyh-Horng

    2015-01-01

    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. PMID:25668619

  17. Development of micro immunosensors to study genomic and proteomic biomarkers related to cancer and Alzheimer's disease

    NASA Astrophysics Data System (ADS)

    Prabhulkar, Shradha

    A report from the National Institutes of Health defines a disease biomarker as a "characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." Early diagnosis is a crucial factor for incurable disease such as cancer and Alzheimer's disease (AD). During the last decade researchers have discovered that biochemical changes caused by a disease can be detected considerably earlier as compared to physical manifestations/symptoms. In this dissertation electrochemical detection was utilized as the detection strategy as it offers high sensitivity/specificity, ease of operation, and capability of miniaturization and multiplexed detection. Electrochemical detection of biological analytes is an established field, and has matured at a rapid pace during the last 50 years and adapted itself to advances in micro/nanofabrication procedures. Carbon fiber microelectrodes were utilized as the platform sensor due to their high signal to noise ratio, ease and low-cost of fabrication, biocompatibility, and active carbon surface which allows conjugation with biorecognition moieties. This dissertation specifically focuses on the detection of 3 extensively validated biomarkers for cancer and AD. Firstly, vascular endothelial growth factor (VEGF) a cancer biomarker was detected using a one-step, reagentless immunosensing strategy. The immunosensing strategy allowed a rapid and sensitive means of VEGF detection with a detection limit of about 38 pg/mL with a linear dynamic range of 0--100 pg/mL. Direct detection of AD-related biomarker amyloid beta (Abeta) was achieved by exploiting its inherent electroactivity. The quantification of the ratio of Abeta1-40/42 (or Abeta ratio) has been established as a reliable test to diagnose AD through human clinical trials. Triple barrel carbon fiber microelectrodes were used to simultaneously detect Abeta1-40 and Abeta1-42 in

  18. Identification of novel, therapy-responsive protein biomarkers in a mouse model of Duchenne muscular dystrophy by aptamer-based serum proteomics

    PubMed Central

    Coenen-Stass, Anna M. L.; McClorey, Graham; Manzano, Raquel; Betts, Corinne A.; Blain, Alison; Saleh, Amer F.; Gait, Michael J.; Lochmüller, Hanns; Wood, Matthew J. A.; Roberts, Thomas C.

    2015-01-01

    There is currently an urgent need for biomarkers that can be used to monitor the efficacy of experimental therapies for Duchenne Muscular Dystrophy (DMD) in clinical trials. Identification of novel protein biomarkers has been limited due to the massive complexity of the serum proteome and the presence of a small number of very highly abundant proteins. Here we have utilised an aptamer-based proteomics approach to profile 1,129 proteins in the serum of wild-type and mdx (dystrophin deficient) mice. The serum levels of 96 proteins were found to be significantly altered (P < 0.001, q < 0.01) in mdx mice. Additionally, systemic treatment with a peptide-antisense oligonucleotide conjugate designed to induce Dmd exon skipping and recover dystrophin protein expression caused many of the differentially abundant serum proteins to be restored towards wild-type levels. Results for five leading candidate protein biomarkers (Pgam1, Tnni3, Camk2b, Cycs and Adamts5) were validated by ELISA in the mouse samples. Furthermore, ADAMTS5 was found to be significantly elevated in human DMD patient serum. This study has identified multiple novel, therapy-responsive protein biomarkers in the serum of the mdx mouse with potential utility in DMD patients. PMID:26594036

  19. Identifying Biomarkers and Mechanisms of Toxic Metal Stress with Global Proteomics

    SciTech Connect

    Miller, Susan M.

    2012-04-16

    Hg is a wide-spread contaminant in the environment and is toxic in all of its various forms. Data suggest that RHg+ and Hg2+ are toxic in two ways. At low levels, Hg species appear to disrupt membrane-bound respiration causing a burst of reactive oxygen species (ROS) that further damage the cell. At higher Hg concentrations, RHg+ and Hg2+ may form adducts with cysteine- and selenocysteine-containing proteins in all cellular compartments resulting in their inactivation. Although these mechansims for toxicity are generally accepted, the most sensitive targets associated with these mechanisms are not well understood. In this collaborative project involving three laboratories at three institutions, the overall goal was to develop of a mass spectrometry-based global proteomics methodology that could be used to identify Hg-adducted (and ideally, ROS-damaged) proteins in order to address these types of questions. The two objectives of this overall collaborative project were (1) to identify, quantify, and compare ROS- and Hg-damaged proteins in cells treated with various Hg species and concentrations to test this model for two mechanisms of Hg toxicity, and (2) to define the cellular roles of the ubiquitous bacterial mercury resistance (mer) locus with regards to how the proteins of this pathway interact to protect other cell proteins from Hg damage. The specific objectives and accomplishments of the Miller lab in this project included: (1) Development of algorithms for analysis of the Hg-proteomic mass spectrometry data to identify mercury adducted peptides and other trends in the data. (2) Investigation of the role of mer operon proteins in scavenging Hg(II) from other mer pathway proteins as a means of protecting cellular proteins from damage.

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

    PubMed

    Ye, Hui; Mandal, Rakesh; Catherman, Adam; Thomas, Paul M; Kelleher, Neil L; Ikonomidou, Chrysanthy; Li, Lingjun

    2014-01-01

    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. PMID:24710523

  1. Identification of Candidate Serum Biomarkers for Schistosoma mansoni Infected Mice Using Multiple Proteomic Platforms

    PubMed Central

    Kardoush, Manal I.

    2016-01-01

    Background Schistosomiasis is an important helminth infection of humans. There are few reliable diagnostic biomarkers for early infection, for recurrent infection or to document successful treatment. In this study, we compared serum protein profiles in uninfected and infected mice to identify disease stage-specific biomarkers. Methods Serum collected from CD1 mice infected with 50–200 Schistosoma mansoni cercariae were analyzed before infection and at 3, 6 and 12 weeks post-infection using three mass spectrometric (MS) platforms. Results Using SELDI-TOF MS, 66 discriminating m/z peaks were detected between S. mansoni infected mice and healthy controls. Used in various combinations, these peaks could 1) reliably diagnose early-stage disease, 2) distinguish between acute and chronic infection and 3) diagnose S. mansoni infection regardless the parasite burden. The most important contributors to these diagnostic algorithms were peaks at 3.7, 13 and 46 kDa. Employing sample fractionation and differential gel electrophoresis, we analyzed gel slices either by MALDI-TOF MS or Velos Orbitrap MS. The former yielded eight differentially-expressed host proteins in the serum at different disease stages including transferrin and alpha 1- antitrypsin. The latter suggested the presence of a surprising number of parasite-origin proteins in the serum during both the acute (n = 200) and chronic (n = 105) stages. The Orbitrap platform also identified many differentially-expressed host-origin serum proteins during the acute and chronic stages (296 and 220 respectively). The presence of one of the schistosome proteins, glutathione S transferase (GST: 25 KDa), was confirmed by Western Blot. This study provides proof-of-principle for an approach that can yield a large number of novel candidate biomarkers for Schistosoma infection. PMID:27138990

  2. A Proteomic Approach Identifies Candidate Early Biomarkers to Predict Severe Dengue in Children

    PubMed Central

    Nhi, Dang My; Huy, Nguyen Tien; Ohyama, Kaname; Kimura, Daisuke; Lan, Nguyen Thi Phuong; Uchida, Leo; Thuong, Nguyen Van; Nhon, Cao Thi My; Phuc, Le Hong; Mai, Nguyen Thi; Mizukami, Shusaku; Bao, Lam Quoc; Doan, Nguyen Ngoc; Binh, Nguyen Van Thanh; Quang, Luong Chan; Karbwang, Juntra; Yui, Katsuyuki; Morita, Kouichi; Huong, Vu Thi Que; Hirayama, Kenji

    2016-01-01

    Background Severe dengue with severe plasma leakage (SD-SPL) is the most frequent of dengue severe form. Plasma biomarkers for early predictive diagnosis of SD-SPL are required in the primary clinics for the prevention of dengue death. Methodology Among 63 confirmed dengue pediatric patients recruited, hospital based longitudinal study detected six SD-SPL and ten dengue with warning sign (DWS). To identify the specific proteins increased or decreased in the SD-SPL plasma obtained 6–48 hours before the shock compared with the DWS, the isobaric tags for relative and absolute quantification (iTRAQ) technology was performed using four patients each group. Validation was undertaken in 6 SD-SPL and 10 DWS patients. Principal findings Nineteen plasma proteins exhibited significantly different relative concentrations (p<0.05), with five over-expressed and fourteen under-expressed in SD-SPL compared with DWS. The individual protein was classified to either blood coagulation, vascular regulation, cellular transport-related processes or immune response. The immunoblot quantification showed angiotensinogen and antithrombin III significantly increased in SD-SPL whole plasma of early stage compared with DWS subjects. Even using this small number of samples, antithrombin III predicted SD-SPL before shock occurrence with accuracy. Conclusion Proteins identified here may serve as candidate predictive markers to diagnose SD-SPL for timely clinical management. Since the number of subjects are small, so further studies are needed to confirm all these biomarkers. PMID:26895439

  3. Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

    PubMed Central

    Gao, Yan; Zhao, Lingyu; Liu, Liying; Qin, Yannan; Wang, Xiaofei; Song, Tusheng; Huang, Chen

    2014-01-01

    Objective To investigate discriminating protein patterns and serum biomarkers between clear cell renal cell carcinoma (ccRCC) patients and healthy controls, as well as between paired pre- and post-operative ccRCC patients. Methods We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with ccRCC. A total of 162 serum samples were analyzed in this study, among which there were 58 serum samples from ccRCC patients, 40 from additional paired pre- and post-operative ccRCC patients (n = 20), and 64 from healthy volunteers as healthy controls. ClinProTools software identified several distinct markers between ccRCC patients and healthy controls, as well as between pre- and post-operative patients. Results Patients with ccRCC could be identified with a mean sensitivity of 88.38% and a mean specificity of 91.67%. Of 67 m/z peaks that differed among the ccRCC, healthy controls, pre- and post-operative ccRCC patients, 24 were significantly different (P<0.05). Three candidate peaks, which were upregulated in ccRCC group and showed a tendency to return to healthy control values after surgery, were identified as peptide regions of RNA-binding protein 6 (RBP6), tubulin beta chain (TUBB), and zinc finger protein 3 (ZFP3) with the m/z values of 1466.98, 1618.22, and 5905.23, respectively. Conclusion MB-MALDI-TOF-MS method could generate serum peptidome profiles of ccRCC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy. PMID:25368985

  4. Investigation of proteomic biomarkers in in vivo hepatotoxicity study of rat liver: toxicity differentiation in hepatotoxicants.

    PubMed

    Yamamoto, Toshinori; Kikkawa, Rie; Yamada, Hiroshi; Horii, Ikuo

    2006-02-01

    We investigated the overall protein expression profiles in the in vivo hepatotoxicity of rats induced by four well-recognized hepatotoxicants. Acetaminophen (APAP), amiodarone (AMD), tetracycline (TC) and carbon tetrachloride (CTC) were administered to male rats by gavages and the liver at 24 hr post-dosing was applied to the proteomic experiment. Blood biochemistry and histopathology were examined to identify specific changes related to the compounds given. Protein expression in the liver was investigated by 2-dimensional gel electrophoresis (2DE), and spots showing a significantly different expression in treated versus control group were excised from gels and identified by Q-Tof mass spectrometer. They were well characterized based on their functions related to the mechanisms of toxicity of the compounds. Among them, we focused on the 8 proteins that were affected by all 4 compounds examined. Proteins related to oxidative stress response such as carbonic anhydrase III (CA3) and 60kDa heat shock protein (HSP60), and energy metabolism such as adenylate kinase 4 (AK4) were found. Moreover, hierarchical clustering analysis using 2D-gel spots information revealed the possibility to differentiate the groups based on their toxicity levels such as severity of liver damage. These results suggested that assessing the effects of hepatotoxicants on protein expression is worth trying to screen candidate compounds at the developmental stage of drugs. PMID:16538043

  5. Proteomic identification of prognostic tumour biomarkers, using chemotherapy-induced cancer-associated fibroblasts

    PubMed Central

    Peiris-Pagès, Maria; Smith, Duncan L.; Győrffy, Balázs; Sotgia, Federica; Lisanti, Michael P.

    2015-01-01

    Cancer cells grow in highly complex stromal microenvironments, which through metabolic remodelling, catabolism, autophagy and inflammation nurture them and are able to facilitate metastasis and resistance to therapy. However, these changes in the metabolic profile of stromal cancer-associated fibroblasts and their impact on cancer initiation, progression and metastasis are not well-known. This is the first study to provide a comprehensive proteomic portrait of the azathioprine and taxol-induced catabolic state on human stromal fibroblasts, which comprises changes in the expression of metabolic enzymes, myofibroblastic differentiation markers, antioxidants, proteins involved in autophagy, senescence, vesicle trafficking and protein degradation, and inducers of inflammation. Interestingly, many of these features are major contributors to the aging process. A catabolic stroma signature, generated with proteins found differentially up-regulated in taxol-treated fibroblasts, strikingly correlates with recurrence, metastasis and poor patient survival in several solid malignancies. We therefore suggest the inhibition of the catabolic state in healthy cells as a novel approach to improve current chemotherapy efficacies and possibly avoid future carcinogenic processes. PMID:26539730

  6. PTRF/Cavin-1 and MIF Proteins Are Identified as Non-Small Cell Lung Cancer Biomarkers by Label-Free Proteomics

    PubMed Central

    Gámez-Pozo, Angelo; Sánchez-Navarro, Iker; Calvo, Enrique; Agulló-Ortuño, María Teresa; López-Vacas, Rocío; Díaz, Esther; Camafeita, Emilio; Nistal, Manuel; Madero, Rosario; Espinosa, Enrique; López, Juan Antonio; Vara, Juan Ángel Fresno

    2012-01-01

    With the completion of the human genome sequence, biomedical sciences have entered in the “omics” era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer. PMID:22461895

  7. Proteome Biomarkers in Xylem Reveal Pierce’s Disease Tolerance in Grape

    PubMed Central

    Katam, Ramesh; Chibanguza, Kundai; Latinwo, Lekan M; Smith, Danyel

    2016-01-01

    Pierce’s disease (PD) is a significant threat to grape cultivation and industry. The disease caused by bacterium Xylella fastidiosa clogs xylem vessels resulting in wilting of the plant. PD-tolerant grape genotypes are believed to produce certain novel components in xylem tissue that help them to combat invading pathogens. Research has been aimed at characterizing the uniquely expressed xylem proteins by PD-tolerant genotypes. The objectives were to i) compare and characterize Vitis xylem proteins differentially expressed in PD-tolerant and PD-susceptible cultivars and, ii) identify xylem proteins uniquely expressed in PD-tolerant genotypes. A high throughput two-dimensional gel electrophoresis of xylem proteins from three Vitis species identified more than 200 proteins with pls 3.0 to 9.0 and molecular weights of 20 to 75 kDa. The differentially expressed proteins were then excised and analyzed with MALDI/TOF mass spectrometer. The mass spectra were collected and protein identification was performed against the Viridiplantae database using Matrix Science algorithm. Proteins were mapped to the universal protein resource to study gene ontology. Comparative analysis of the xylem proteome of three species indicated the highest number of proteins in muscadine grape, followed by Florida hybrid bunch and bunch grape. These proteins were all associated with disease resistance, energy metabolism, protein processing and degradation, biosynthesis, stress related functions, cell wall biogenesis, signal transduction, and ROS detoxification. Furthermore, β-1, 3-glucanase, 10-deacetyl baccatin III-10-O-acetyl transferase-like, COP9, and aspartyl protease nepenthesin precursor proteins were found to be uniquely expressed in PD-tolerant muscadine grape, while they are absent in PD-susceptible bunch grape. Data suggests that muscadine and Florida hybrid bunch grapes express novel proteins in xylem to overcome pathogen attack while bunch grape lacks this capability, making them

  8. Proteomic profiling in multiple sclerosis clinical courses reveals potential biomarkers of neurodegeneration.

    PubMed

    Liguori, Maria; Qualtieri, Antonio; Tortorella, Carla; Direnzo, Vita; Bagalà, Angelo; Mastrapasqua, Mariangela; Spadafora, Patrizia; Trojano, Maria

    2014-01-01

    The aim of our project was to perform an exploratory analysis of the cerebrospinal fluid (CSF) proteomic profiles of Multiple Sclerosis (MS) patients, collected in different phases of their clinical course, in order to investigate the existence of peculiar profiles characterizing the different MS phenotypes. The study was carried out on 24 Clinically Isolated Syndrome (CIS), 16 Relapsing Remitting (RR) MS, 11 Progressive (Pr) MS patients. The CSF samples were analysed using the Matrix Assisted Laser Desorption Ionisation Time Of Flight (MALDI-TOF) mass spectrometer in linear mode geometry and in delayed extraction mode (m/z range: 1000-25000 Da). Peak lists were imported for normalization and statistical analysis. CSF data were correlated with demographic, clinical and MRI parameters. The evaluation of MALDI-TOF spectra revealed 348 peak signals with relative intensity ≥ 1% in the study range. The peak intensity of the signals corresponding to Secretogranin II and Protein 7B2 were significantly upregulated in RRMS patients compared to PrMS (p<0.05), whereas the signals of Fibrinogen and Fibrinopeptide A were significantly downregulated in CIS compared to PrMS patients (p<0.04). Additionally, the intensity of the Tymosin β4 peak was the only signal to be significantly discriminated between the CIS and RRMS patients (p = 0.013). Although with caution due to the relatively small size of the study populations, and considering that not all the findings remained significant after adjustment for multiple comparisons, in our opinion this mass spectrometry evaluation confirms that this technique may provide useful and important information to improve our understanding of the complex pathogenesis of MS. PMID:25098164

  9. Identification of PCSK9 as a novel serum biomarker for the prenatal diagnosis of neural tube defects using iTRAQ quantitative proteomics

    PubMed Central

    An, Dong; Wei, Xiaowei; Li, Hui; Gu, Hui; Huang, Tianchu; Zhao, Guifeng; Liu, Bo; Wang, Weilin; Chen, Lizhu; Ma, Wei; Zhang, Henan; Cao, Songying; Yuan, Zhengwei

    2015-01-01

    To identify candidate serum molecule biomarkers for the non-invasive early prenatal diagnosis of neural tube defects (NTDs), we employed an iTRAQ-based quantitative proteomic approach to analyze the proteomic changes in serum samples from embryonic day (E) 11 and E13 pregnant rats with spina bifida aperta (SBA) induced by all-trans retinoic acid. Among the 390 proteins identified, 40 proteins at E11 and 26 proteins at E13 displayed significant differential expression in the SBA groups. We confirmed 5 candidate proteins by ELISA. We observed the space-time expression changes of proprotein convertase subtilisin/kexin type 9 (PCSK9) at different stages of fetal development, including a marked decrease in the sera of NTD pregnancies and gradual increase in the sera of normal pregnancies with embryonic development. PCSK9 demonstrated the diagnostic efficacy of potential NTD biomarkers [with an area under the receiver operating characteristic curve of 0.763, 95% CI: 065–0.88]. Additionally, PCSK9 expression in the spinal cords and placentas of SBA rat fetuses was markedly decreased. PCSK9 could serve as a novel molecular biomarker for the non-invasive prenatal screening of NTDs and may be involved in the pathogenesis of NTDs at critical periods of fetal development. PMID:26691006

  10. Biomarker Candidate Identification in Yersinia Pestis Using Organism-Wide Semiquantitative Proteomics

    SciTech Connect

    Hixson, Kim K.; Adkins, Joshua N.; Baker, Scott E.; Moore, Ronald J.; Smith, Richard D.; McCutchen-Maloney, Sandra L.; Lipton, Mary S.

    2006-11-03

    Yersinia pestis, the causative agent of plague, is listed by the CDC as a level A select pathogen. To better enable detection, intervention and treatment of Y. pestis infections, it is necessary to understand its protein expression under conditions that promote or inhibit virulence. To this end, we have utilized a novel combination of the accurate mass and time tag methodology of mass spectrometry and clustering analysis using OmniViz™ to compare the protein abundance changes of 992 identified proteins under four growth conditions. Temperature and Ca2+ concentration were used to trigger virulence associated protein expression fundamental to the low calcium response. High-resolution liquid chromatography and electrospray ionization mass spectrometry were utilized to determine protein identity and abundance on the genome-wide level. The cluster analyses revealed, in a rapid visual platform, the reproducibility of the current method as well as relevant protein abundance changes of expected and novel proteins relating to a specific growth condition and sub-cellular location. Using this method, 89 proteins were identified as having a similar abundance change profile to 29 known virulence associated proteins, providing additional biomarker candidates for future detection and vaccine development strategies.

  11. Pathway Analysis of Proteomics Profiles in Rabies Infection: Towards Future Biomarkers?

    PubMed

    Mehta, Shraddha; Sreenivasamurthy, Sreelakshmi; Banerjee, Shefali; Mukherjee, Sandeepan; Prasad, Keshava; Chowdhary, Abhay

    2016-02-01

    Rabies is a zoonotic viral disease that invariably leads to fatal encephalitis, which can be prevented provided post-exposure prophylaxis is initiated timely. Ante-mortem diagnostic tests are inconclusive, and rabies is nontreatable once the clinical signs appear. A large number of host factors are responsible for the altered neuronal functions observed in rabies; however their precise role remains uninvestigated. We therefore used two-dimensional electrophoresis and mass spectrometry analysis to identify differentially expressed host proteins in an experimental murine model of rabies. We identified 143 proteins corresponding to 45 differentially expressed spots (p < 0.05) in neuronal tissues of Swiss albino mice in response to infection with neurovirulent rabies strains. Time series analyses revealed that a majority of the alterations occur at 4 to 6 days post infection, in particular affecting the host's cytoskeletal architecture. Extensive pathway analysis and protein interaction studies using the bioinformatic tools such as Ingenuity Pathway Analysis and STRING revealed novel pathways and molecules (e.g., protein ubiquitination) unexplored hitherto. Further activation/inhibition studies of these pathway molecular leads would be relevant to identify novel biomarkers and mechanism-based therapeutics for rabies, a disease that continues to severely impact global health. PMID:26871867

  12. Proteomic biomarkers predicting lymph node involvement in serum of cervical cancer patients. Limitations of SELDI-TOF MS

    PubMed Central

    2012-01-01

    Background Lymph node status is not part of the staging system for cervical cancer, but provides important information for prognosis and treatment. We investigated whether lymph node status can be predicted with proteomic profiling. Material & methods Serum samples of 60 cervical cancer patients (FIGO I/II) were obtained before primary treatment. Samples were run through a HPLC depletion column, eliminating the 14 most abundant proteins ubiquitously present in serum. Unbound fractions were concentrated with spin filters. Fractions were spotted onto CM10 and IMAC30 surfaces and analyzed with surface-enhanced laser desorption time of flight (SELDI-TOF) mass spectrometry (MS). Unsupervised peak detection and peak clustering was performed using MASDA software. Leave-one-out (LOO) validation for weighted Least Squares Support Vector Machines (LSSVM) was used for prediction of lymph node involvement. Other outcomes were histological type, lymphvascular space involvement (LVSI) and recurrent disease. Results LSSVM models were able to determine LN status with a LOO area under the receiver operating characteristics curve (AUC) of 0.95, based on peaks with m/z values 2,698.9, 3,953.2, and 15,254.8. Furthermore, we were able to predict LVSI (AUC 0.81), to predict recurrence (AUC 0.92), and to differentiate between squamous carcinomas and adenocarcinomas (AUC 0.88), between squamous and adenosquamous carcinomas (AUC 0.85), and between adenocarcinomas and adenosquamous carcinomas (AUC 0.94). Conclusions Potential markers related with lymph node involvement were detected, and protein/peptide profiling support differentiation between various subtypes of cervical cancer. However, identification of the potential biomarkers was hampered by the technical limitations of SELDI-TOF MS. PMID:22694804

  13. A proteomics-based identification of putative biomarkers for disease in bovine milk.

    PubMed

    van Altena, S E C; de Klerk, B; Hettinga, K A; van Neerven, R J J; Boeren, S; Savelkoul, H F J; Tijhaar, E J

    2016-06-01

    The objective of this study was to identify and characterize potential biomarkers for disease resistance in bovine milk that can be used to indicate dairy cows at risk to develop future health problems. We selected high- and low-resistant cows i.e. cows that were less or more prone to develop diseases according to farmers' experience and notifications in the disease registration data. The protein composition of milk serum samples of these high- and low-resistant cows were compared using NanoLC-MS/MS. In total 78 proteins were identified and quantified of which 13 were significantly more abundant in low-resistant cows than high-resistant cows. Quantification of one of these proteins, lactoferrin (LF), by ELISA in a new and much larger set of full fat milk samples confirmed higher LF levels in low- versus high-resistant cows. These high- and low-resistant cows were selected based on comprehensive disease registration and milk recording data, and absence of disease for at least 4 weeks. Relating the experienced diseases to LF levels in milk showed that lameness was associated with higher LF levels in milk. Analysis of the prognostic value of LF showed that low-resistant cows with higher LF levels in milk had a higher risk of being culled within one year after testing than high-resistant cows. In conclusion, LF in milk are higher in low-resistant cows, are associated with lameness and may be a prognostic marker for risk of premature culling. PMID:27185258

  14. The search for biomarkers of human embryo developmental potential in IVF: a comprehensive proteomic approach.

    PubMed

    Nyalwidhe, Julius; Burch, Tanya; Bocca, Silvina; Cazares, Lisa; Green-Mitchell, Shamina; Cooke, Marissa; Birdsall, Paige; Basu, Gaurav; Semmes, O John; Oehninger, Sergio

    2013-04-01

    The objective of these studies was to identify differentially expressed peptides/proteins in the culture media of embryos grown during in vitro fertilization (IVF) treatment to establish their value as biomarkers predictive of implantation potential and live birth. Micro-droplets of embryo culture media from IVF patients (conditioned) and control media maintained under identical culture conditions were collected and frozen at -80°C on Days 2-3 of in vitro development prior to analysis. The embryos were transferred on Day 3. The peptides were affinity purified based on their physico-chemical properties and profiled by mass spectrometry for differential expression. The identified proteins were further characterized by western blot and ELISA, and absolute quantification was achieved by multiple reaction monitoring (MRM). We identified up to 14 differentially regulated peptides after capture using paramagnetic beads with different affinities. These differentially expressed peptides were used to generate genetic algorithms (GAs) with a recognition capability of 71-84% for embryo transfer cycles resulting in pregnancy and 75-89% for those with failed implantation. Several peptides were further identified as fragments of Apolipoprotein A-1, which showed consistent and significantly reduced expression in the embryo media samples from embryo transfer cycles resulting in viable pregnancies. Western blot and ELISA, as well as quantitative MRM results, were confirmatory. These results demonstrated that peptide/protein profiles from the culture medium during early human in vitro development can discriminate embryos with highest and lowest implantation competence following uterine transfer. Further prospective studies are needed to establish validated thresholds for clinical application. PMID:23247814

  15. Multiomics approach to identify novel biomarkers for dilated cardiomyopathy: Proteome and transcriptome analyses of 4C30 dilated cardiomyopathy mouse model.

    PubMed

    Nishigori, Mitsuhiro; Yagi, Hiroaki; Mochiduki, Akikazu; Minamino, Naoto

    2016-11-01

    Dilated cardiomyopathy (DCM) is an intractable disease, without any radical treatment option other than cardiac transplantation. Additionally, biomarkers to determine progressive staging are not yet available. Irrespective of the diversity of causative gene mutations, the phenotype of DCM is rather common. Therefore, it is plausible to determine DCM staging in terms of variations in protein and mRNA levels. In this study, we performed proteome and transcriptome analysis of the left ventricle of 4C30 DCM model mice showing mild and severe phenotypes at 12 and 24 weeks (wk) after birth, respectively. Proteomic analyses results showed 109 proteins that increased and 133 others that decreased among 1874 detected proteins. We selected biomarker candidates by confirming consistent alterations in protein levels at 12 and 24 wk, and mRNA levels at 12 wk, and narrowed these down based on the requirement that they should be detectable in blood. Finally, we selected six biomarker candidates based on sustained or augmented alteration at 24 wk and confirmed their definite alterations in the left ventricle by quantitative polymerase chain reaction, western blot analysis, and multiple reaction monitoring (MRM). To assess the validity of this strategy, we measured plasma concentrations of the six candidates by MRM method and identified two proteins (FTL1 and GRP78) that demonstrated significant elevation in the 4C30 mice plasma. Taken together, a multiomics strategy comparing tissue expression levels of proteins and mRNAs between diseased and control groups, with appropriate confirmation, is a promising approach for the discovery of new biomarkers. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 491-502, 2016. PMID:26799926

  16. A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer.

    PubMed

    Tang, Hsin-Yao; Beer, Lynn A; Chang-Wong, Tony; Hammond, Rachel; Gimotty, Phyllis; Coukos, George; Speicher, David W

    2012-02-01

    Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients. PMID:22032327

  17. Mass Spectrometry-Based Proteomic Study Makes High-Density Lipoprotein a Biomarker for Atherosclerotic Vascular Disease

    PubMed Central

    Yang, Chao-Yuh; Tsai, Fuu-Jen; Lin, Shih-Yi

    2015-01-01

    High-density lipoprotein (HDL) is a lipid and protein complex that consists of apolipoproteins and lower level HDL-associated enzymes. HDL dysfunction is a factor in atherosclerosis and decreases patient survival. Mass spectrometry- (MS-) based proteomics provides a high throughput approach for analyzing the composition and modifications of complex HDL proteins in diseases. HDL can be separated according to size, surface charge, electronegativity, or apoprotein composition. MS-based proteomics on subfractionated HDL then allows investigation of lipoprotein roles in diseases. Herein, we review recent developments in MS-based quantitative proteomic techniques, HDL proteomics and lipoprotein modifications in diseases, and HDL subfractionation studies. We also discuss future directions and perspectives in MS-based proteomics on HDL. PMID:26090384

  18. A comparative proteomic study of plasma in feline pancreatitis and pancreatic carcinoma using 2-dimensional gel electrophoresis to identify diagnostic biomarkers: A pilot study

    PubMed Central

    Meachem, Melissa D.; Snead, Elisabeth R.; Kidney, Beverly A.; Jackson, Marion L.; Dickinson, Ryan; Larson, Victoria; Simko, Elemir

    2015-01-01

    While pancreatitis is now recognized as a common ailment in cats, the diagnosis remains challenging due to discordant results and suboptimal sensitivity of ultrasound and specific feline pancreatic lipase (Spec fPL) assay. Pancreatitis also shares similar clinical features with pancreatic carcinoma, a rare but aggressive disease with a grave prognosis. The objective of this pilot study was to compare the plasma proteomes of normal healthy cats (n = 6), cats with pancreatitis (n = 6), and cats with pancreatic carcinoma (n = 6) in order to identify potential new biomarkers of feline pancreatic disease. After plasma protein separation by 2-dimensional gel electrophoresis, protein spots were detected by Coomassie Brilliant Blue G-250 staining and identified by mass spectrometry. Alpha-1-acid glycoprotein (AGP), apolipoprotein-A1 (Apo-A1), and apolipoprotein-A1 precursor (Pre Apo-A1) appeared to be differentially expressed, which suggests the presence of a systemic acute-phase response and alteration of lipid metabolism in cats with pancreatic disease. Future studies involving greater case numbers are needed in order to assess the utility of these proteins as potential biomarkers. More sensitive proteomic techniques may also be helpful in detecting significant but low-abundance proteins. PMID:26130850

  19. The Identification of Novel Potential Injury Mechanisms and Candidate Biomarkers in Renal Allograft Rejection by Quantitative Proteomics*

    PubMed Central

    Sigdel, Tara K.; Salomonis, Nathan; Nicora, Carrie D.; Ryu, Soyoung; He, Jintang; Dinh, Van; Orton, Daniel J.; Moore, Ronald J.; Hsieh, Szu-Chuan; Dai, Hong; Thien-Vu, Minh; Xiao, Wenzhong; Smith, Richard D.; Qian, Wei-Jun; Camp, David G.; Sarwal, Minnie M.

    2014-01-01

    Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a “hub” protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of

  20. Mass spectrometry for biomarker development

    SciTech Connect

    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.

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

    PubMed Central

    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

  2. Identification of RAB2A and PRDX1 as the potential biomarkers for oral squamous cell carcinoma using mass spectrometry-based comparative proteomic approach.

    PubMed

    Dey, Kaushik Kumar; Pal, Ipsita; Bharti, Rashmi; Dey, Goutam; Kumar, B N Prashanth; Rajput, Shashi; Parekh, Aditya; Parida, Sheetal; Halder, Priyanka; Kulavi, Indranil; Mandal, Mahitosh

    2015-12-01

    Despite the recent advances in diagnostic and therapeutic strategies, oral squamous cell carcinoma (OSCC) remains a major health burden. Protein biomarker discovery for early detection will help to improve patient survival rate in OSCC. Mass spectrometry-based proteomics has emerged as an excellent approach for detection of protein biomarkers in various types of cancers. In the current study, we have used 4-Plex isobaric tags for relative and absolute quantitation (iTRAQ)-based shotgun quantitative proteomic approach to identify proteins that are differentially expressed in cancerous tissues compared to normal tissues. The high-resolution mass spectrometric analysis resulted in identifying 2,074 proteins, among which 288 proteins were differentially expressed. Further, it was noticed that 162 proteins were upregulated, while 125 proteins were downregulated in OSCC-derived cancer tissue samples as compared to the adjacent normal tissues. We identified some of the known molecules which were reported earlier in OSCC such as MMP-9 (8.4-fold), ZNF142 (5.6-fold), and S100A7 (3.5-fold). Apart from this, we have also identified some novel signature proteins which have not been reported earlier in OSCC including ras-related protein Rab-2A isoform, RAB2A (4.6-fold), and peroxiredoxin-1, PRDX1 (2.2-fold). The immunohistochemistry-based validation using tissue microarray slides in OSCC revealed overexpression of the RAB2A and PRDX1 gene in 80 and 68 % of the tested clinical cases, respectively. This study will not only serve as a resource of candidate biomarkers but will contribute towards the existing knowledge on the role of the candidate molecules towards disease progression and therapeutic potential. PMID:26159854

  3. Association of potential salivary biomarkers with diabetic retinopathy and its severity in type-2 diabetes mellitus: a proteomic analysis by mass spectrometry

    PubMed Central

    Subrayan, Visvaraja

    2016-01-01

    Aim/hypothesis: The aim of our study was to characterize the human salivary proteome and determine the changes in protein expression in two different stages of diabetic retinopathy with type-2 diabetes mellitus: (1) with non-proliferative diabetic retinopathy (NPDR) and (2) with proliferative diabetic retinopathy (PDR). Type-2 diabetes mellitus without diabetic retinopathy (XDR) was designated as control. Method: In this study, 45 saliva samples were collected (15 samples from XDR control group, 15 samples from NPDR disease group and 15 samples from PDR disease group). Salivary proteins were extracted, reduced, alkylated, trypsin digested and labeled with an isobaric tag for relative and absolute quantitation (iTRAQ) before being analyzed by an Orbitrap fusion tribrid mass spectrometer. Protein annotation, fold change calculation and statistical analysis were interrogated by Proteome Discoverer. Biological pathway analysis was performed by Ingenuity Pathway Analysis. Data are available via ProteomeXchange with identifiers PXD003723–PX003725. Results: A total of 315 proteins were identified from the salivary proteome and 119 proteins were found to be differentially expressed. The differentially expressed proteins from the NPDR disease group and the PDR disease group were assigned to respective canonical pathways indicating increased Liver X receptor/Retinoid X receptor (LXR/RXR) activation, Farnesoid X receptor/Retinoid X receptor (FXR/RXR) activation, acute phase response signaling, sucrose degradation V and regulation of actin-based motility by Rho in the PDR disease group compared to the NPDR disease group. Conclusions/Interpretation: Progression from non-proliferative to proliferative retinopathy in type-2 diabetic patients is a complex multi-mechanism and systemic process. Furthermore, saliva was shown to be a feasible alternative sample source for diabetic retinopathy biomarkers. PMID:27280065

  4. Urine Proteome Analysis Reflects Atherosclerotic Disease in an ApoE−/− Mouse Model and Allows the Discovery of New Candidate Biomarkers in Mouse and Human Atherosclerosis*

    PubMed Central

    von zur Muhlen, Constantin; Schiffer, Eric; Sackmann, Christine; Zürbig, Petra; Neudorfer, Irene; Zirlik, Andreas; Htun, Nay; Iphöfer, Alexander; Jänsch, Lothar; Mischak, Harald; Bode, Christoph; Chen, Yung C.; Peter, Karlheinz

    2012-01-01

    Noninvasive diagnosis of atherosclerosis via single biomarkers has been attempted but remains elusive. However, a previous polymarker or pattern approach of urine polypeptides in humans reflected coronary artery disease with high accuracy. The aim of the current study is to use urine proteomics in ApoE−/− mice to discover proteins with pathophysiological roles in atherogenesis and to identify urinary polypeptide patterns reflecting early stages of atherosclerosis. Urine of ApoE−/− mice either on high fat diet (HFD) or chow diet was collected over 12 weeks; urine of wild type mice on HFD was used to exclude diet-related proteome changes. Capillary electrophoresis coupled to mass spectrometry (CE-MS) of samples identified 16 polypeptides specific for ApoE−/− mice on HFD. In a blinded test set, these polypeptides allowed identification of atherosclerosis at a sensitivity of 90% and specificity of 100%, as well as monitoring of disease progression. Sequencing of the discovered polypeptides identified fragments of α1-antitrypsin, epidermal growth factor (EGF), kidney androgen-regulated protein, and collagen. Using immunohistochemistry, α1-antitrypsin, EGF, and collagen type I were shown to be highly expressed in atherosclerotic plaques of ApoE−/− mice on HFD. Urinary excretion levels of collagen and α1-antitrypsin fragments also significantly correlated with intraplaque collagen and α1-antitrypsin content, mirroring plaque protein expression in the urine proteome. To provide further confirmation that the newly identified proteins are relevant in humans, the presence of collagen type I, α1-antitrypsin, and EGF was also confirmed in human atherosclerotic disease. Urine proteome analysis in mice exemplifies the potential of a novel multimarker approach for the noninvasive detection of atherosclerosis and monitoring of disease progression. Furthermore, this approach represents a novel discovery tool for the identification of proteins relevant in murine

  5. Urine proteome analysis reflects atherosclerotic disease in an ApoE-/- mouse model and allows the discovery of new candidate biomarkers in mouse and human atherosclerosis.

    PubMed

    von zur Muhlen, Constantin; Schiffer, Eric; Sackmann, Christine; Zürbig, Petra; Neudorfer, Irene; Zirlik, Andreas; Htun, Nay; Iphöfer, Alexander; Jänsch, Lothar; Mischak, Harald; Bode, Christoph; Chen, Yung C; Peter, Karlheinz

    2012-07-01

    Noninvasive diagnosis of atherosclerosis via single biomarkers has been attempted but remains elusive. However, a previous polymarker or pattern approach of urine polypeptides in humans reflected coronary artery disease with high accuracy. The aim of the current study is to use urine proteomics in ApoE(-/-) mice to discover proteins with pathophysiological roles in atherogenesis and to identify urinary polypeptide patterns reflecting early stages of atherosclerosis. Urine of ApoE(-/-) mice either on high fat diet (HFD) or chow diet was collected over 12 weeks; urine of wild type mice on HFD was used to exclude diet-related proteome changes. Capillary electrophoresis coupled to mass spectrometry (CE-MS) of samples identified 16 polypeptides specific for ApoE(-/-) mice on HFD. In a blinded test set, these polypeptides allowed identification of atherosclerosis at a sensitivity of 90% and specificity of 100%, as well as monitoring of disease progression. Sequencing of the discovered polypeptides identified fragments of α(1)-antitrypsin, epidermal growth factor (EGF), kidney androgen-regulated protein, and collagen. Using immunohistochemistry, α(1)-antitrypsin, EGF, and collagen type I were shown to be highly expressed in atherosclerotic plaques of ApoE(-/-) mice on HFD. Urinary excretion levels of collagen and α(1)-antitrypsin fragments also significantly correlated with intraplaque collagen and α(1)-antitrypsin content, mirroring plaque protein expression in the urine proteome. To provide further confirmation that the newly identified proteins are relevant in humans, the presence of collagen type I, α(1)-antitrypsin, and EGF was also confirmed in human atherosclerotic disease. Urine proteome analysis in mice exemplifies the potential of a novel multimarker approach for the noninvasive detection of atherosclerosis and monitoring of disease progression. Furthermore, this approach represents a novel discovery tool for the identification of proteins relevant in

  6. Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program sample subset

    SciTech Connect

    Metz, Thomas O.; Qian, Weijun; Jacobs, Jon M.; Gritsenko, Marina A.; Moore, Ronald J.; Polpitiya, Ashoka D.; Monroe, Matthew E.; Camp, David G.; mueller, Patricia W.; Smith, Richard D.

    2008-02-01

    Objective. Before biomarkers predictive of type 1 diabetes can be evaluated in proficiency evaluations, they must be identified and validated in initial, exploratory studies. Hypothesis-driven comparative studies may be performed to identify candidate biomarkers but are limited to the current knowledge of metabolic, signaling, and inflammatory pathways in the context of type 1 diabetes. Alternatively, untargeted “-omics” approaches may be employed in profiling studies to identify candidate biomarkers of type 1 diabetes.

  7. Identification of phosphorylated MYL12B as a potential plasma biomarker for septic acute kidney injury using a quantitative proteomic approach.

    PubMed

    Wu, Fan; Dong, Xiu-Juan; Li, Yan-Yan; Zhao, Yan; Xu, Qiu-Lin; Su, Lei

    2015-01-01

    Acute kidney injury (AKI) is a common and increasingly encountered complication in hospitalized patients with critical illness in intensive care units (ICU). According to the etiology, Sepsis-induced AKI (SAKI) is a leading contributor to AKI and significantly has very poor prognosis, which might be related to the late detection when the elevation of BUN and serum creatinine (SCr) is used. Many genes are up-regulated in the damaged kidney with the corresponding protein products appearing in plasma and urine. Some of these are candidate biomarkers for more timely diagnosis of SAKI. Therefore, extensive research efforts over this past decade have been directed at the discovery and validation of novel SAKI biomarkers to detect injury prior to changes in kidney function, a number of serum and urinary proteins, including NGAL, KIM-1, cystatin-C, IL-18, and L-FABP, have been identified for predicting SAKI before a rise in BUN and serum creatinine in several experimental and clinical trainings. Unfortunately, an ideal biomarker of SAKI with highly sensitivity and specificity has not been identified yet. Recent progresses in quantitative proteomics have offered opportunities to discover biomarkers for SAKI. In the present study, kidney tissue samples from SAKI mice were analyzed by two-dimensional differential gel electrophoresis (2D-DIGE), and 4 up-regulated proteins, which were actin (ACTB), myosin regulatory light chain 12B (MYL12B), myosin regulatory light polypeptide 9 (MYL9), and myosin regulatory light chain 12A (MYL12A) were identified by matrix assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). Among all the varied proteins, MYL12B was validated by western blot. Interestingly, there was no change between the SAKI and control kidney tissues, however, phosphorylated MYL12B was detected to be consistent with the proteomics data. Furthermore, phosphorylated MYL12B was found similarly to be increased in SAKI plasma

  8. Identification of phosphorylated MYL12B as a potential plasma biomarker for septic acute kidney injury using a quantitative proteomic approach

    PubMed Central

    Wu, Fan; Dong, Xiu-Juan; Li, Yan-Yan; Zhao, Yan; Xu, Qiu-Lin; Su, Lei

    2015-01-01

    Acute kidney injury (AKI) is a common and increasingly encountered complication in hospitalized patients with critical illness in intensive care units (ICU). According to the etiology, Sepsis-induced AKI (SAKI) is a leading contributor to AKI and significantly has very poor prognosis, which might be related to the late detection when the elevation of BUN and serum creatinine (SCr) is used. Many genes are up-regulated in the damaged kidney with the corresponding protein products appearing in plasma and urine. Some of these are candidate biomarkers for more timely diagnosis of SAKI. Therefore, extensive research efforts over this past decade have been directed at the discovery and validation of novel SAKI biomarkers to detect injury prior to changes in kidney function, a number of serum and urinary proteins, including NGAL, KIM-1, cystatin-C, IL-18, and L-FABP, have been identified for predicting SAKI before a rise in BUN and serum creatinine in several experimental and clinical trainings. Unfortunately, an ideal biomarker of SAKI with highly sensitivity and specificity has not been identified yet. Recent progresses in quantitative proteomics have offered opportunities to discover biomarkers for SAKI. In the present study, kidney tissue samples from SAKI mice were analyzed by two-dimensional differential gel electrophoresis (2D-DIGE), and 4 up-regulated proteins, which were actin (ACTB), myosin regulatory light chain 12B (MYL12B), myosin regulatory light polypeptide 9 (MYL9), and myosin regulatory light chain 12A (MYL12A) were identified by matrix assisted laser desorption ionization-time of flight/time of flight mass spectrometry (MALDI-TOF/TOF MS). Among all the varied proteins, MYL12B was validated by western blot. Interestingly, there was no change between the SAKI and control kidney tissues, however, phosphorylated MYL12B was detected to be consistent with the proteomics data. Furthermore, phosphorylated MYL12B was found similarly to be increased in SAKI plasma

  9. S100A8 is identified as a biomarker of HPV18-infected oral squamous cell carcinomas by suppression subtraction hybridization, clinical proteomics analysis, and immunohistochemistry staining.

    PubMed

    Lo, Wan-Yu; Lai, Chien-Chen; Hua, Chun-Hung; Tsai, Ming-Hsui; Huang, Shiuan-Yi; Tsai, Chang-Hai; Tsai, Fuu-Jen

    2007-06-01

    The purpose of this work is to differentiate between the Human papillomaviruses 18 positive (HPV18+) and negative (HPV18-) oral squamous cell carcinomas (OSCC) in oral cancer patients with cancer-associated oral habits (betel quid chewing, cigarette smoking, and alcohol drinking). Both gene and protein expression profiles of HPV18+ and HPV18- OSCC were compared: we then further explored the biological effect of HPV in oral cancer. Suppression subtraction hybridization (SSH), clinical proteomics analysis, and immunohistochemistry (IHC) staining were carried out in the HPV18+ and HPV18- OSCC groups. HPV typing detection revealed that 11 OSCC tissues from 82 patients were positive for HPV18. The SSH experiment showed that 4 cancer-associated genes were highly transcribed within 11 cDNA libraries of HPV18+ OSCC, including poly(ADP-ribose)polymerase I (PARP1), replication protein A2 (RPA2), S100A8, and S100A2. Clinical proteomics analysis indicated that there was over 10-fold overexpression of Stratifin, F-actin capping protein alpha-1 subunit (CapZ alpha-1), Apolipoprotein A-1 (ApoA-1), Heat-shock protein 27 (HSP27), Arginase-1, p16INK4A, and S100 calcium-binding protein A8 (S100A8) in HPV18+ OSCC. Interestingly, the results from SSH and protemics analysis showed that S100A8 was overexpressed in HPV18+ OSCC. Moreover, IHC staining demonstrated that S100A8 was up-regulated in HPV18+ OSCC tissues. Our results suggest that S100A8 plays an important role in oral carcinogenesis following HPV18 infection; therefore, S100A8 may be a powerful biomarker of HPV18 as well as a potential therapeutic target for HPV18+ OSCC patients. The study is the first to identify S100A8 as a biomarker in HPV-associated cancer. Furthermore, this is also the first study to discover a biomarker by combining SSH, clinical proteomics, and IHC stain analysis in oral cancer-associated research. PMID:17451265

  10. Safety, tolerability, and biomarkers of the treatment of mice with aerosolized Toll-like receptor ligands

    PubMed Central

    Alfaro, Victoria Y.; Goldblatt, David L.; Valverde, Gabriella R.; Munsell, Mark F.; Quinton, Lee J.; Walker, Adam K.; Dantzer, Robert; Varadhachary, Atul; Scott, Brenton L.; Evans, Scott E.; Tuvim, Michael J.; Dickey, Burton F.

    2014-01-01

    We have previously discovered a synergistically therapeutic combination of two Toll-like receptor ligands, an oligodeoxynucleotide (ODN) and Pam2CSK4. Aerosolization of these ligands stimulates innate immunity within the lungs to prevent pneumonia from bacterial and viral pathogens. Here we examined the safety and tolerability of this treatment in mice, and characterized the expression of biomarkers of innate immune activation. We found that neutrophils appeared in lung lavage fluid 4 h after treatment, reached a peak at 48 h, and resolved by 7 days. The peak of neutrophil influx was accompanied by a small increase in lung permeability. Despite the abundance of neutrophils in lung lavage fluid, only rare neutrophils were visible histopathologically in the interstitium surrounding bronchi and veins and none were visible in alveolar airspaces. The cytokines interleukin 6 (IL-6), tumour necrosis factor, and Chemokine (C-X-C motif) ligand 2 rose several hundred-fold in lung lavage fluid 4 h after treatment in a dose-dependent and synergistic manner, providing useful biomarkers of lung activation. IL-6 rose fivefold in serum with delayed kinetics compared to its rise in lavage fluid, and might serve as a systemic biomarker of immune activation of the lungs. The dose–response relationship of lavage fluid cytokines was preserved in mice that underwent myeloablative treatment with cytosine arabinoside to model the treatment of hematologic malignancy. There were no overt signs of distress in mice treated with ODN/Pam2CSK4 in doses up to eightfold the therapeutic dose, and no changes in temperature, respiratory rate, or behavioral signs of sickness including sugar water preference, food disappearance, cage exploration or social interaction, though there was a small degree of transient weight loss. We conclude that treatment with aerosolized ODN/Pam2CSK4 is well tolerated in mice, and that innate immune activation of the lungs can be monitored by the measurement of

  11. Biomarker Candidates of Chlamydophila pneumoniae Proteins and Protein Fragments Identified by Affinity-Proteomics Using FTICR-MS and LC-MS/MS

    NASA Astrophysics Data System (ADS)

    Susnea, Iuliana; Bunk, Sebastian; Wendel, Albrecht; Hermann, Corinna; Przybylski, Michael

    2011-04-01

    We report here an affinity-proteomics approach that combines 2D-gel electrophoresis and immunoblotting with high performance mass spectrometry to the identification of both full length protein antigens and antigenic fragments of Chlamydophila pneumoniae (C. pneumoniae). The present affinity-mass spectrometry approach effectively utilized high resolution FTICR mass spectrometry and LC-tandem-MS for protein identification, and enabled the identification of several new highly antigenic C. pneumoniae proteins that were not hitherto reported or previously detected only in other Chlamydia species, such as Chlamydia trachomatis. Moreover, high resolution affinity-MS provided the identification of several neo-antigenic protein fragments containing N- and C-terminal, and central domains such as fragments of the membrane protein Pmp21 and the secreted chlamydial proteasome-like factor (Cpaf), representing specific biomarker candidates.

  12. Label-free proteomic analysis of the hydrophobic membrane protein complement in articular chondrocytes: a technique for identification of membrane biomarkers

    PubMed Central

    Matta, Csaba; Zhang, Xiaofei; Liddell, Susan; Smith, Julia R.; Mobasheri, Ali

    2015-01-01

    Abstract Context: There is insufficient knowledge about the chondrocyte membranome and its molecular composition. Objective: To develop a Triton X-114 based separation technique using nanoLC-MS/MS combined with shotgun proteomics to identify chondrocyte membrane proteins. Materials and methods: Articular chondrocytes from equine metacarpophalangeal joints were separated into hydrophobic and hydrophilic fractions; trypsin-digested proteins were analysed by nanoLC-MS/MS. Results: A total of 315 proteins were identified. The phase extraction method yielded a high proportion of membrane proteins (56%) including CD276, S100-A6 and three VDAC isoforms. Discussion: Defining the chondrocyte membranome is likely to reveal new biomarker targets for conventional and biological drug discovery. PMID:26864288

  13. Identification of toxicological biomarkers of di(2-ethylhexyl) phthalate in proteins secreted by HepG2 cells using proteomic analysis.

    PubMed

    Choi, Seonyoung; Park, So-Young; Jeong, Ji; Cho, Eunkyung; Phark, Sohee; Lee, Min; Kwak, Dongsub; Lim, Ji-Youn; Jung, Woon-Won; Sul, Donggeun

    2010-05-01

    The effects of di(2-ethylhexyl) phthalate (DEHP) on proteins secreted by HepG2 cells were studied using a proteomic approach. HepG2 cells were exposed to various concentrations of DEHP (0, 2.5, 5, 10, 25, 50, 100, and 250 microM) for 24 or 48 h. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) and comet assays were then conducted to determine the cytotoxicity and genotoxicity of DEHP, respectively. The MTT assay showed that 10 microM DEHP was the maximum concentration that did not cause cell death. In addition, the DNA damage in HepG2 cells exposed to DEHP was found to increase in a dose- and time-dependent fashion. Proteomic analysis using two different pI ranges (4-7 and 6-9) and large size 2-DE revealed the presence of 2776 protein spots. A total of 35 (19 up- and 16 down-regulated) proteins were identified as biomarkers of DEHP by ESI-MS/MS. Several differentiated protein groups were also found. Proteins involved in apoptosis, transportation, signaling, energy metabolism, and cell structure and motility were found to be up- or down-regulated. Among these, the identities of cystatin C, Rho GDP inhibitor, retinol binding protein 4, gelsolin, DEK protein, Raf kinase inhibitory protein, triose phosphate isomerase, cofilin-1, and haptoglobin-related protein were confirmed by Western blot assay. Therefore, these proteins could be used as potential biomarkers of DEHP and human disease associated with DEHP. PMID:20198640

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

    PubMed Central

    Hollingsworth, Alan B.; Gordon, Kelly; Silver, Michael; Mulpuri, Rao; Letsios, Elias; Reese, David E.

    2016-01-01

    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 combinatorial

  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.

    PubMed

    Henderson, Meredith C; Hollingsworth, Alan B; Gordon, Kelly; Silver, Michael; Mulpuri, Rao; Letsios, Elias; Reese, David E

    2016-01-01

    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 combinatorial

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

    PubMed

    Tonry, Claire L; Leacy, Emma; Raso, Cinzia; Finn, Stephen P; Armstrong, John; Pennington, Stephen R

    2016-01-01

    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. PMID:27438858

  17. Proteomics of bronchial biopsies: galectin-3 as a predictive biomarker of airway remodelling modulation in omalizumab-treated severe asthma patients.

    PubMed

    Mauri, Pierluigi; Riccio, Anna Maria; Rossi, Rossana; Di Silvestre, Dario; Benazzi, Louise; De Ferrari, Laura; Dal Negro, Roberto Walter; Holgate, Stephen T; Canonica, Giorgio Walter

    2014-11-01

    Asthma is a chronic inflammatory disease. Reticular basement membrane (RBM) thickening is considered feature of airway remodelling (AR) particularly in severe asthma (SA). Omalizumab, mAb to IgE is effective in SA and can modulate AR. Herein we describe protein profiles of bronchial biopsies to detect biomarkers of anti-IgE effects on AR and to explain potential mechanisms/pathways. We defined the bronchial biopsy protein profiles, before and after treatment. Unsupervised clustering of baseline proteomes resulted in very good agreement with the morphometric analysis of AR. Protein profiles of omalizumab responders (ORs) were significantly different from those of non-omalizumab responders (NORs). The major differences between ORs and NORs lied to smooth muscle and extra cellular matrix proteins. Notably, an IgE-binding protein (galectin-3) was reliable, stable and predictive biomarker of AR modulation. Omalizumab down-regulated bronchial smooth muscle proteins in SA. These findings suggest that omalizumab may exert disease-modifying effects on remodelling components. PMID:25194755

  18. iTRAQ-Based Proteomics Screen identifies LIPOCALIN-2 (LCN-2) as a potential biomarker for colonic lateral-spreading tumors.

    PubMed

    Wang, Xianfei; Li, Aimin; Guo, Yubin; Wang, Yadong; Zhao, Xinhua; Xiang, Li; Han, Zelong; Li, Yue; Xu, Wen; Zhuang, Kangmin; Yan, Qun; Zhong, Jietao; Xiong, Jing; Liu, Side

    2016-01-01

    The improvement and implementation of a colonoscopy technique has led to increased detection of laterally spreading tumors (LSTs), which are presumed to constitute an aggressive type of colonic neoplasm. Early diagnosis and treatment of LSTs is clinically challenging. To overcome this problem, we employed iTRAQ to identify LST-specific protein biomarkers potentially involved in LST progression. In this study, we identified 2,001 differentially expressed proteins in LSTs using iTRAQ-based proteomics technology. Lipocalin-2 (LCN-2) was the most up-regulated protein. LSTs expression levels of LCN-2 and matrix metallopeptidase-9 (MMP-9) showed positive correlation with worse pathological grading, and up-regulation of these proteins in LSTs was also reflected in serum. Furthermore, LCN-2 protein overexpression was positively correlated with MMP-9 protein up-regulation in the tumor tissue and serum of LST patients (former rs = 0.631, P = 0.000; latter rs = 0.815, P = 0.000). Our results suggest that LCN-2 constitutes a potential biomarker for LST disease progression and might be a novel therapeutic target in LSTs. PMID:27339395

  19. Fibrinogen Alpha Chain Precursor and Apolipoprotein A-I in Urine as Biomarkers for Noninvasive Diagnosis of Calcium Oxalate Nephrolithiasis: A Proteomics Study

    PubMed Central

    Zhu, Wei; Liu, Min; Wang, Guang-Chun; Peng, Bo; Yan, Yang; Che, Jian-Ping; Ma, Qing-Wei; Yao, Xu-Dong; Zheng, Jun-Hua

    2014-01-01

    Calcium oxalate nephrolithiasis is the most common urological disease, but noninvasive and convenient methods of diagnosis are rarely available. Objective. The present study aimed to identify potential urine biomarkers for noninvasive diagnosis of CaOx nephrolithiasis. Methodology. Urine samples from 72 patients with CaOx nephrolithiasis and 30 healthy controls were collected and proteomics analysis was performed using matrix-assisted laser desorption/ionization-time of flight-mass spectrometer (MALDI-TOF-MS). Results. Thirteen proteins/peptides displayed statistically significant differences. The peptides of m/z 1207.23 and 2773.86 were selected by the genetic algorithm (GA) to build a possible diagnostic model. The area under the curve of m/z 1207.23 and 2773.86 was 0.936 and 0.987, respectively. The diagnostic model in distinguishing patients and healthy subjects showed 100% sensitivity and specificity. The peak at m/z 2773.86 was identified as fibrinogen alpha chain (FGA) with the sequence G.EGDFLAEGGGVR.G, and the peak at m/z 2773.86 was identified as apolipoprotein A-I (apoA-I) with the sequence L.PVLESFKVSFLSALEEYTKKLNTQ. Conclusion. The study results strongly suggested that urinary FGA and apoA-I are highly sensitive and specific biomarkers for noninvasive diagnosis of CaOx nephrolithiasis. PMID:25147800

  20. iTRAQ-Based Proteomics Screen identifies LIPOCALIN-2 (LCN-2) as a potential biomarker for colonic lateral-spreading tumors

    PubMed Central

    Wang, Xianfei; Li, Aimin; Guo, Yubin; Wang, Yadong; Zhao, Xinhua; Xiang, Li; Han, Zelong; Li, Yue; Xu, Wen; Zhuang, Kangmin; Yan, Qun; Zhong, Jietao; Xiong, Jing; Liu, Side

    2016-01-01

    The improvement and implementation of a colonoscopy technique has led to increased detection of laterally spreading tumors (LSTs), which are presumed to constitute an aggressive type of colonic neoplasm. Early diagnosis and treatment of LSTs is clinically challenging. To overcome this problem, we employed iTRAQ to identify LST-specific protein biomarkers potentially involved in LST progression. In this study, we identified 2,001 differentially expressed proteins in LSTs using iTRAQ-based proteomics technology. Lipocalin-2 (LCN-2) was the most up-regulated protein. LSTs expression levels of LCN-2 and matrix metallopeptidase-9 (MMP-9) showed positive correlation with worse pathological grading, and up-regulation of these proteins in LSTs was also reflected in serum. Furthermore, LCN-2 protein overexpression was positively correlated with MMP-9 protein up-regulation in the tumor tissue and serum of LST patients (former rs = 0.631, P = 0.000; latter rs = 0.815, P = 0.000). Our results suggest that LCN-2 constitutes a potential biomarker for LST disease progression and might be a novel therapeutic target in LSTs. PMID:27339395

  1. Proteomics-based identification and validation of novel plasma biomarkers phospholipid transfer protein and mannan-binding lectin serine protease-1 in age-related macular degeneration

    PubMed Central

    Kim, Hye-Jung; Ahn, Seong Joon; Woo, Se Joon; Hong, Hye Kyoung; Suh, Eui Jin; Ahn, Jeeyun; Park, Ji Hyun; Ryoo, Na-Kyung; Lee, Ji Eun; Kim, Ki Woong; Park, Kyu Hyung; Lee, Cheolju

    2016-01-01

    Age-related macular degeneration (AMD) is a major cause of severe, progressive visual loss among the elderly. There are currently no established serological markers for the diagnosis of AMD. In this study, we carried out a large-scale quantitative proteomics analysis to identify plasma proteins that could serve as potential AMD biomarkers. We found that the plasma levels of phospholipid transfer protein (PLTP) and mannan-binding lectin serine protease (MASP)-1 were increased in AMD patients relative to controls. The receiver operating characteristic curve based on data from an independent set of AMD patients and healthy controls had an area under the curve of 0.936 for PLTP and 0.716 for MASP-1, revealing excellent discrimination between the two groups. A proteogenomic combination model that incorporated PLTP and MASP-1 along with two known risk genotypes of age-related maculopathy susceptibility 2 and complement factor H genes further enhanced discriminatory power. Additionally, PLTP and MASP-1 mRNA and protein expression levels were upregulated in retinal pigment epithelial cells upon exposure to oxidative stress in vitro. These results indicate that PLTP and MASP-1 can serve as plasma biomarkers for the early diagnosis and treatment of AMD, which is critical for preventing AMD-related blindness. PMID:27605007

  2. Proteomics-based identification and validation of novel plasma biomarkers phospholipid transfer protein and mannan-binding lectin serine protease-1 in age-related macular degeneration.

    PubMed

    Kim, Hye-Jung; Ahn, Seong Joon; Woo, Se Joon; Hong, Hye Kyoung; Suh, Eui Jin; Ahn, Jeeyun; Park, Ji Hyun; Ryoo, Na-Kyung; Lee, Ji Eun; Kim, Ki Woong; Park, Kyu Hyung; Lee, Cheolju

    2016-01-01

    Age-related macular degeneration (AMD) is a major cause of severe, progressive visual loss among the elderly. There are currently no established serological markers for the diagnosis of AMD. In this study, we carried out a large-scale quantitative proteomics analysis to identify plasma proteins that could serve as potential AMD biomarkers. We found that the plasma levels of phospholipid transfer protein (PLTP) and mannan-binding lectin serine protease (MASP)-1 were increased in AMD patients relative to controls. The receiver operating characteristic curve based on data from an independent set of AMD patients and healthy controls had an area under the curve of 0.936 for PLTP and 0.716 for MASP-1, revealing excellent discrimination between the two groups. A proteogenomic combination model that incorporated PLTP and MASP-1 along with two known risk genotypes of age-related maculopathy susceptibility 2 and complement factor H genes further enhanced discriminatory power. Additionally, PLTP and MASP-1 mRNA and protein expression levels were upregulated in retinal pigment epithelial cells upon exposure to oxidative stress in vitro. These results indicate that PLTP and MASP-1 can serve as plasma biomarkers for the early diagnosis and treatment of AMD, which is critical for preventing AMD-related blindness. PMID:27605007

  3. Identification of S100A9 as Biomarker of Responsiveness to the Methotrexate/Etanercept Combination in Rheumatoid Arthritis Using a Proteomic Approach

    PubMed Central

    Obry, Antoine; Lequerré, Thierry; Hardouin, Julie; Boyer, Olivier; Fardellone, Patrice; Philippe, Peggy; Le Loët, Xavier; Cosette, Pascal; Vittecoq, Olivier

    2014-01-01

    Objectives One way to optimize the drug prescription in rheumatoid arthritis (RA) is to identify predictive biomarkers of drug responsiveness. Here, we investigated the potential "theranostic" value of proteins of the S100 family by monitoring levels of both S100A8 and S100A9 in blood samples from RA patients. Design For proteomic analysis, peripheral blood mononuclear cells (PBMC) and serum samples were collected in patients prior to initiation of the methotrexate/etanercept (MTX/ETA) combination. Firstly, relative mass spectrometry (MS) quantification focusing on S100A8 and S100A9 proteins was carried out from PBMCs samples to identify potential biomarkers. The same approach was also performed from serum samples from responder (R) and non responder (NR) patients. Finally, to confirm these results, an absolute quantification of S100A8, S100A9 proteins and calprotectin (heterodimer of S100A8/S100A9) was carried out on the serum samples using ELISA. Results MS analyses revealed that both S100A8 and S100A9 proteins were significantly accumulated in PBMC from responders. In contrast to PBMC, only the S100A9 protein was significantly overexpressed in the serum of R patients. Absolute quantification by ELISA confirmed this result and pointed out a similar expression level of S100A8 protein and calprotectin in sera from both R and NR groups. Thus, the S100A9 protein revealed to be predictive of MTX/ETA responsiveness, contrarily to parameters of inflammation and auto-antibodies which did not allow significant discrimination. Conclusion This is the first report of an overexpression of S100A9 protein in both PBMCs and serum of patients with subsequent response to the MTX/ETA combination. This protein thus represents an interesting biomarker candidate of therapeutic response in RA. PMID:25546405

  4. Proteomic profiling of a mouse model of acute intestinal Apc deletion leads to identification of potential novel biomarkers of human colorectal cancer (CRC).

    PubMed

    Hammoudi, Abeer; Song, Fei; Reed, Karen R; Jenkins, Rosalind E; Meniel, Valerie S; Watson, Alastair J M; Pritchard, D Mark; Clarke, Alan R; Jenkins, John R

    2013-10-25

    Colorectal cancer (CRC) is the fourth most common cause of cancer-related death worldwide. Accurate non-invasive screening for CRC would greatly enhance a population's health. Adenomatous polyposis coli (Apc) gene mutations commonly occur in human colorectal adenomas and carcinomas, leading to Wnt signalling pathway activation. Acute conditional transgenic deletion of Apc in murine intestinal epithelium (AhCre(+)Apc(fl)(/)(fl)) causes phenotypic changes similar to those found during colorectal tumourigenesis. This study comprised a proteomic analysis of murine small intestinal epithelial cells following acute Apc deletion to identify proteins that show altered expression during human colorectal carcinogenesis, thus identifying proteins that may prove clinically useful as blood/serum biomarkers of colorectal neoplasia. Eighty-one proteins showed significantly increased expression following iTRAQ analysis, and validation of nine of these by Ingenuity Pathaway Analysis showed they could be detected in blood or serum. Expression was assessed in AhCre(+)Apc(fl)(/)(fl) small intestinal epithelium by immunohistochemistry, western blot and quantitative real-time PCR; increased nucelolin concentrations were also detected in the serum of AhCre(+)Apc(fl)(/)(fl) and Apc(Min)(/)(+) mice by ELISA. Six proteins; heat shock 60kDa protein 1, Nucleolin, Prohibitin, Cytokeratin 18, Ribosomal protein L6 and DEAD (Asp-Glu-Ala-Asp) box polypeptide 5,were selected for further investigation. Increased expression of 4 of these was confirmed in human CRC by qPCR. In conclusion, several novel candidate biomarkers have been identified from analysis of transgenic mice in which the Apc gene was deleted in the intestinal epithelium that also showed increased expression in human CRC. Some of these warrant further investigation as potential serum-based biomarkers of human CRC. PMID:23998936

  5. iTRAQ and multiple reaction monitoring as proteomic tools for biomarker search in cerebrospinal fluid of patients with Parkinson's disease dementia.

    PubMed

    Lehnert, Stefan; Jesse, Sarah; Rist, Wolfgang; Steinacker, Petra; Soininen, Hilkka; Herukka, Sanna-Kaisa; Tumani, Hayrettin; Lenter, Martin; Oeckl, Patrick; Ferger, Boris; Hengerer, Bastian; Otto, Markus

    2012-04-01

    About 30% of patients with Parkinson's disease (PD) develop Parkinson's disease dementia (PDD) in the course of the disease. Until now, diagnosis is based on clinical and neuropsychological examinations, since so far there is no laboratory marker. In this study we aimed to find a neurochemical marker which would allow a risk assessment for the development of a dementia in PD patients. For this purpose, we adopted a gel-free proteomic approach (iTRAQ-method) to identify biomarker-candidates in the cerebrospinal fluid (CSF) of patients with PD, PDD and non-demented controls (NDC). Validation of these candidates was then carried out by multiple-reaction-monitoring (MRM) optimised for CSF. Using the iTRAQ-approach, we were able to identify 16 differentially regulated proteins. Fourteen out of these 16 proteins could then be followed-up simultaneously in our optimised MRM-measurement protocol. However only Tyrosine-kinase-non-receptor-type 13 and Netrin-G1 differed significantly between PDD and NDC cohorts. In addition, a significant difference was found for Golgin-160 and Apolipoprotein B-100 between PD and NDC. Apart from possible pathophysiological considerations, we propose that Tyrosine-kinase non-receptor-type 13 and Netrin G1 are biomarker candidates for the development of a Parkinson's disease dementia. Furthermore we suggest that iTRAQ and MRM are valuable tools for the discovery of biomarker in cerebrospinal fluid. However further validation studies need to be done with larger patient cohorts and other proteins need to be checked as well. PMID:22327139

  6. Proteomic analysis of serum proteins in triple transgenic Alzheimer's disease mice: implications for identifying biomarkers for use to screen potential candidate therapeutic drugs for early Alzheimer's disease.

    PubMed

    Sui, Xiaojing; Ren, Xiaohu; Huang, Peiwu; Li, Shuiming; Ma, Quan; Ying, Ming; Ni, Jiazuan; Liu, Jianjun; Yang, Xifei

    2014-01-01

    Alzheimer's disease (AD) is the most common fatal neurodegenerative disease affecting the elderly worldwide. There is an urgent need to identify novel biomarkers of early AD. This study aims to search for potential early protein biomarkers in serum from a triple transgenic (PS1M146V/APPSwe/TauP301L) mouse model. Proteomic analysis via two-dimensional fluorescence difference gel electrophoresis was performed on serum samples from wild-type (WT) and triple transgenic mice that were treated with or without coenzyme Q10 (CoQ10) (800 mg/kg body weight/day), a powerful endogenous antioxidant displaying therapeutic benefits against AD pathology and cognitive impairment in multiple AD mouse models, for a period of three months beginning at two months of age. A total of 15 differentially expressed serum proteins were identified between the WT and AD transgenic mice. The administration of CoQ10 was found to alter the changes in the differentially expressed serum proteins by upregulating 10 proteins and down-regulating 10 proteins. Among the proteins modulated by CoQ10, clusterin and α-2-macroglobulin were validated via ELISA assay. These findings revealed significant changes in serum proteins in the AD mouse model at an early pathological stage and demonstrated that administration of CoQ10 could modulate these changes in serum proteins. Our study suggested that these differentially expressed serum proteins could serve as potential protein biomarkers of early AD and that screening for potential candidate AD therapeutic drugs and monitoring of therapeutic effects could be performed via measurement of the changes in these differentially expressed serum proteins. PMID:24496070

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

    PubMed Central

    Abunimer, Ayman; Smith, Krista; Wu, Tsung-Jung; Lam, Phuc; Simonyan, Vahan; Mazumder, Raja

    2014-01-01

    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. PMID:24705329

  8. Proteomics and the search for welfare and stress biomarkers in animal production in the one-health context.

    PubMed

    Marco-Ramell, A; de Almeida, A M; Cristobal, S; Rodrigues, P; Roncada, P; Bassols, A

    2016-06-21

    Stress and welfare are important factors in animal production in the context of growing production optimization and scrutiny by the general public. In a context in which animal and human health are intertwined aspects of the one-health concept it is of utmost importance to define the markers of stress and welfare. These are important tools for producers, retailers, regulatory agents and ultimately consumers to effectively monitor and assess the welfare state of production animals. Proteomics is the science that studies the proteins existing in a given tissue or fluid. In this review we address this topic by showing clear examples where proteomics has been used to study stress-induced changes at various levels. We adopt a multi-species (cattle, swine, small ruminants, poultry, fish and shellfish) approach under the effect of various stress inducers (handling, transport, management, nutritional, thermal and exposure to pollutants) clearly demonstrating how proteomics and systems biology are key elements to the study of stress and welfare in farm animals and powerful tools for animal welfare, health and productivity. PMID:26931796

  9. Web-based software for rapid "top-down" proteomic identification of protein biomarkers with implications for bacterial identification

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We have developed web-based software for the rapid identification of protein biomarkers of bacterial microorganisms. Proteins from bacterial cell lysates were ionized by matrix-assisted laser desorption/ionization (MALDI), mass-isolated and fragmented using a time-of-flight/time-of-flight (TOF-TOF)...

  10. 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.

    PubMed

    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. PMID:25454514