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

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

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

The Urine Proteome as a Biomarker of Radiation Injury

PubMed Central

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

2009-01-01

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

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

PubMed

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

2015-11-01

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

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

Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

PubMed

Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, 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

2013-12-06

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 toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

Molecular Diagnosis and Biomarker Identification on SELDI proteomics data by ADTBoost method.

PubMed

Wang, Lu-Yong; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

Clinical proteomics is an emerging field that will have great impact on molecular diagnosis, identification of disease biomarkers, drug discovery and clinical trials in the post-genomic era. Protein profiling in tissues and fluids in disease and pathological control and other proteomics techniques will play an important role in molecular diagnosis with therapeutics and personalized healthcare. We introduced a new robust diagnostic method based on ADTboost algorithm, a novel algorithm in proteomics data analysis to improve classification accuracy. It generates classification rules, which are often smaller and easier to interpret. This method often gives most discriminative features, which can be utilized as biomarkers for diagnostic purpose. Also, it has a nice feature of providing a measure of prediction confidence. We carried out this method in amyotrophic lateral sclerosis (ALS) disease data acquired by surface enhanced laser-desorption/ionization-time-of-flight mass spectrometry (SELDI-TOF MS) experiments. Our method is shown to have outstanding prediction capacity through the cross-validation, ROC analysis results and comparative study. Our molecular diagnosis method provides an efficient way to distinguish ALS disease from neurological controls. The results are expressed in a simple and straightforward alternating decision tree format or conditional format. We identified most discriminative peaks in proteomic data, which can be utilized as biomarkers for diagnosis. It will have broad application in molecular diagnosis through proteomics data analysis and personalized medicine in this post-genomic era.

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

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

PubMed

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

2014-03-01

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

Global Cell Proteome Profiling, Phospho-signaling and Quantitative 
Proteomics for Identification of New Biomarkers in Acute Myeloid 
Leukemia Patients

PubMed Central

Aasebø, Elise; Forthun, Rakel B.; Berven, Frode; Selheim, Frode; Hernandez-Valladares, Maria

2016-01-01

The identification of protein biomarkers for acute myeloid leukemia (AML) that could find applications in AML diagnosis and prognosis, treatment and the selection for bone marrow transplant requires substantial comparative analyses of the proteomes from AML patients. In the past years, several studies have suggested some biomarkers for AML diagnosis or AML classification using methods for sample preparation with low proteome coverage and low resolution mass spectrometers. However, most of the studies did not follow up, confirm or validate their candidates with more patient samples. Current proteomics methods, new high resolution and fast mass spectrometers allow the identification and quantification of several thousands of proteins obtained from few tens of μg of AML cell lysate. Enrichment methods for posttranslational modifications (PTM), such as phosphorylation, can isolate several thousands of site-specific phosphorylated peptides from AML patient samples, which subsequently can be quantified with high confidence in new mass spectrometers. While recent reports aiming to propose proteomic or phosphoproteomic biomarkers on the studied AML patient samples have taken advantage of the technological progress, the access to large cohorts of AML patients to sample from and the availability of appropriate control samples still remain challenging. PMID:26306748

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

Cancer.gov

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

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

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

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

PubMed

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

2008-06-18

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

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

PubMed

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

2010-07-01

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

Salivary proteomics and biomarkers in neurology and psychiatry.

PubMed

Wormwood, Kelly L; Aslebagh, Roshanak; Channaveerappa, Devika; Dupree, Emmalyn J; Borland, Megan M; Ryan, Jeanne P; Darie, Costel C; Woods, Alisa G

2015-10-01

Biomarkers are greatly needed in the fields of neurology and psychiatry, to provide objective and earlier diagnoses of CNS conditions. Proteomics and other omics MS-based technologies are tools currently being utilized in much recent CNS research. Saliva is an interesting alternative biomaterial for the proteomic study of CNS disorders, with several advantages. Collection is noninvasive and saliva has many proteins. It is easier to collect than blood and can be collected by professionals without formal medical training. For psychiatric and neurological patients, supplying a saliva sample is less anxiety-provoking than providing a blood sample, and is less embarrassing than producing a urine specimen. The use of saliva as a biomaterial has been researched for the diagnosis of and greater understanding of several CNS conditions, including neurodegenerative diseases, autism, and depression. Salivary biomarkers could be used to rule out nonpsychiatric conditions that are often mistaken for psychiatric/neurological conditions, such as fibromyalgia, and potentially to assess cognitive ability in individuals with compromised brain function. As MS and omics technology advances, the sensitivity and utility of assessing CNS conditions using distal human biomaterials such as saliva is becoming increasingly possible. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Urinary Proteomic Biomarkers for Diagnosis and Risk Stratification of Autosomal Dominant Polycystic Kidney Disease: A Multicentric Study

PubMed Central

Kistler, Andreas D.; Serra, Andreas L.; Siwy, Justyna; Poster, Diane; Krauer, Fabienne; Torres, Vicente E.; Mrug, Michal; Grantham, Jared J.; Bae, Kyongtae T.; Bost, James E.; Mullen, William; Wüthrich, Rudolf P.; Mischak, Harald; Chapman, Arlene B.

2013-01-01

Treatment options for autosomal dominant polycystic kidney disease (ADPKD) will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS), we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI). The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV) based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001) with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD. PMID:23326375

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

PubMed Central

Orton, Dennis J.; Doucette, Alan A.

2013-01-01

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

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

A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease.

PubMed

Skillbäck, Tobias; Mattsson, Niklas; Hansson, Karl; Mirgorodskaya, Ekaterina; Dahlén, Rahil; van der Flier, Wiesje; Scheltens, Philip; Duits, Floor; Hansson, Oskar; Teunissen, Charlotte; Blennow, Kaj; Zetterberg, Henrik; Gobom, Johan

2017-10-17

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

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

Impact of biomarker development on drug safety assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marrer, Estelle, E-mail: estelle.marrer@novartis.co; 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 andmore » '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.« less

Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

PubMed Central

Xu, Jingwen; Zhang, Shijun; Jiang, Haiqiang; Wang, Nan; Lin, Haiqing

2017-01-01

Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect. PMID:28408942

Characterization of the liver tissue interstitial fluid (TIF) proteome indicates potential for application in liver disease biomarker discovery.

PubMed

Sun, Wei; Ma, Jie; Wu, Songfeng; Yang, Dong; Yan, Yujuan; Liu, Kehui; Wang, Jinglan; Sun, Longqin; Chen, Ning; Wei, Handong; Zhu, Yunping; Xing, Baocai; Zhao, Xiaohang; Qian, Xiaohong; Jiang, Ying; He, Fuchu

2010-02-05

Tissue interstitial fluid (TIF) forms the interface between circulating body fluids and intracellular fluid. Pathological alterations of liver cells could be reflected in TIF, making it a promising source of liver disease biomarkers. Mouse liver TIF was extracted, separated by SDS-PAGE, analyzed by linear ion trap mass spectrometer, and 1450 proteins were identified. These proteins may be secreted, shed from membrane vesicles, or represent cellular breakdown products. They show different profiling patterns, quantities, and possibly modification/cleavage of intracellular proteins. The high solubility and even distribution of liver TIF supports its suitability for proteome analysis. Comparison of mouse liver TIF data with liver tissue and plasma proteome data identified major proteins that might be released from liver to plasma and serve as blood biomarkers of liver origin. This result was partially supported by comparison of human liver TIF data with human liver and plasma proteome data. Paired TIFs from tumor and nontumor liver tissues of a hepatocellular carcinoma patient were analyzed and the profile of subtracted differential proteins supports the potential for biomarker discovery in TIF. This study is the first analysis of the liver TIF proteome and provides a foundation for further application of TIF in liver disease biomarker discovery.

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

Proteomic analyses of host and pathogen responses during bovine mastitis.

PubMed

Boehmer, Jamie L

2011-12-01

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

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

PubMed

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

2016-03-30

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

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

DTIC Science & Technology

2012-07-01

1-0431 TITLE: Biomarker Discovery and Mechanistic Studies of Prostate Cancer Using Targeted Proteomic Approaches PRINCIPAL INVESTIGATOR...July 2012 2. REPORT TYPE Final 3. DATES COVERED (From - To) 1 July 2008 – 30 June 2012 4. TITLE AND SUBTITLE Biomarker Discovery and Mechanistic...Department of Defense Synergistic Idea Development Award W81XWH-08-1-0430 (to H.Z) and W81XWH-08-1-0431 (to N.K.), an NIH/NCRR COBRE grant 1P20RR020171 (to

Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

PubMed

Magdalinou, N K; Noyce, A J; Pinto, R; Lindstrom, E; Holmén-Larsson, J; Holtta, M; Blennow, K; Morris, H R; Skillbäck, T; Warner, T T; Lees, A J; Pike, I; Ward, M; Zetterberg, H; Gobom, J

2017-04-01

Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as

Salivary biomarker development using genomic, proteomic and metabolomic approaches

PubMed Central

2012-01-01

The use of saliva as a diagnostic sample provides a non-invasive, cost-efficient method of sample collection for disease screening without the need for highly trained professionals. Saliva collection is far more practical and safe compared with invasive methods of sample collection, because of the infection risk from contaminated needles during, for example, blood sampling. Furthermore, the use of saliva could increase the availability of accurate diagnostics for remote and impoverished regions. However, the development of salivary diagnostics has required technical innovation to allow stabilization and detection of analytes in the complex molecular mixture that is saliva. The recent development of cost-effective room temperature analyte stabilization methods, nucleic acid pre-amplification techniques and direct saliva transcriptomic analysis have allowed accurate detection and quantification of transcripts found in saliva. Novel protein stabilization methods have also facilitated improved proteomic analyses. Although candidate biomarkers have been discovered using epigenetic, transcriptomic, proteomic and metabolomic approaches, transcriptomic analyses have so far achieved the most progress in terms of sensitivity and specificity, and progress towards clinical implementation. Here, we review recent developments in salivary diagnostics that have been accomplished using genomic, transcriptomic, proteomic and metabolomic approaches. PMID:23114182

Combined analysis of transcriptome and proteome data as a tool for the identification of candidate biomarkers in renal cell carcinoma

PubMed Central

Seliger, Barbara; Dressler, Sven P.; Wang, Ena; Kellner, Roland; Recktenwald, Christian V.; Lottspeich, Friedrich; Marincola, Francesco M.; Baumgärtner, Maja; Atkins, Derek; Lichtenfels, Rudolf

2012-01-01

Results obtained from expression profilings of renal cell carcinoma using different “ome”-based approaches and comprehensive data analysis demonstrated that proteome-based technologies and cDNA microarray analyses complement each other during the discovery phase for disease-related candidate biomarkers. The integration of the respective data revealed the uniqueness and complementarities of the different technologies. While comparative cDNA microarray analyses though restricted to upregulated targets largely revealed genes involved in controlling gene/protein expression (19%) and signal transduction processes (13%), proteomics/PROTEOMEX-defined candidate biomarkers include enzymes of the cellular metabolism (36%), transport proteins (12%) and cell motility/structural molecules (10%). Candidate biomarkers defined by proteomics and PROTEOMEX are frequently shared, whereas the sharing rate between cDNA microarray and proteome-based profilings is limited. Putative candidate biomarkers provide insights into their cellular (dys)function and their diagnostic/prognostic value but still warrant further validation in larger patient numbers. Based on the fact that merely 3 candidate biomarkers were shared by all applied technologies, namely annexin A4, tubulin alpha-1A chain and ubiquitin carboxyl-terminal hydrolase L1 the analysis at a single hierarchical level of biological regulation seems to provide only limited results thus emphasizing the importance and benefit of performing rather combinatorial screenings which can complement the standard clinical predictors. PMID:19235166

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

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

2014-12-05

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.

Infectious Disease Proteome Biomarkers: Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, Charles L.

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 aimedmore » at determining critical alterations in host signaling pathways to identify therapeutics targeted against the host.« less

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

PubMed

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

2017-12-01

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

Mass spectrometry for biomarker development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Chaochao; Liu, Tao; Baker, Erin Shammel

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.

An integrated proteomics and metabolomics approach for defining oncofetal biomarkers in the colorectal cancer.

PubMed

Ma, Yanlei; Zhang, Peng; Wang, Feng; Liu, Weijie; Yang, Jianjun; Qin, Huanlong

2012-04-01

The present study was designed to search for potential diagnostic biomarkers in the serum of colorectal cancer (CRC). CRC is the third most common cancer worldwide, and its prognosis is poor at early stages. A panel of novel biomarkers is urgently needed for early diagnosis of CRC. An integrated proteomics and metabolomics approach was performed to define oncofetal biomarkers in CRC by protein and metabolite profiling of serum samples from CRC patients, healthy control adults, and fetus. The differentially expressed proteins were identified by a 2-D DIGE (2-Dimensional Difference Gel Electrophoresis) coupled with a Finnigan LTQ-based proteomics approach. Meanwhile, the serum metabolome was analyzed using gas chromatography-mass spectrometry integrated with a commercial mass spectral library for peak identification. Of the 28 identified proteins and the 34 analyzed metabolites, only 5 protein spots and 6 metabolites were significantly increased or decreased in both CRC and fetal serum groups compared with the healthy adult group. Data from supervised predictive models allowed a separation of 93.5% of CRC patients from the healthy controls using the 6 metabolites. Finally, correlation analysis was applied to establish quantitative linkages between the 5 individual metabolite 3-hydroxybutyric acid, L-valine, L-threonine, 1-deoxyglucose, and glycine and the 5 individual proteins MACF1, APOH, A2M, IGL@, and VDB. Furthermore, 10 potential oncofetal biomarkers were characterized and their potential for CRC diagnosis was validated. The integrated approach we developed will promote the translation of biomarkers with clinical value into routine clinical practice.

Synovial fluid proteomics in the pursuit of arthritis mediators: An evolving field of novel biomarker discovery.

PubMed

Mahendran, Shalini M; Oikonomopoulou, Katerina; Diamandis, Eleftherios P; Chandran, Vinod

Synovial fluid (SF) is a protein-rich fluid produced into the joint cavity by cells of the synovial membrane. Due to its direct contact with articular cartilage, surfaces of the bone, and the synoviocytes of the inner membrane, it provides a promising reflection of the biochemical state of the joint under varying physiological and pathophysiological conditions. This property of SF has been exploited within numerous studies in search of unique biomarkers of joint pathologies with the ultimate goal of developing minimally invasive clinical assays to detect and/or monitor disease states. Several proteomic methodologies have been employed to mine the SF proteome. From elementary immunoassays to high-throughput analyses using mass spectrometry-based techniques, each has demonstrated distinct advantages and disadvantages in the identification and quantification of SF proteins. This review will explore the role of SF in the elucidation of the arthritis proteome and the extent to which high-throughput techniques have facilitated the discovery and validation of protein biomarkers from osteoarthritis (OA), rheumatoid arthritis (RA), psoriatic arthritis (PsA), and juvenile idiopathic arthritis (JIA) patients.

Potential for proteomic approaches in determining efficacy biomarkers following administration of fish oils rich in omega-3 fatty acids: application in pancreatic cancers.

PubMed

Runau, Franscois; Arshad, Ali; Isherwood, John; Norris, Leonie; Howells, Lynne; Metcalfe, Matthew; Dennison, Ashley

2015-06-01

Pancreatic cancer is a disease with a significantly poor prognosis. Despite modern advances in other medical, surgical, and oncologic therapy, the outcome from pancreatic cancer has improved little over the last 40 years. To improve the management of this difficult disease, trials investigating the use of dietary and parenteral fish oils rich in omega-3 (ω-3) fatty acids, exhibiting proven anti-inflammatory and anticarcinogenic properties, have revealed favorable results in pancreatic cancers. Proteomics is the large-scale study of proteins that attempts to characterize the complete set of proteins encoded by the genome of an organism and that, with the use of sensitive mass spectrometric-based techniques, has allowed high-throughput analysis of the proteome to aid identification of putative biomarkers pertinent to given disease states. These biomarkers provide useful insight into potentially discovering new markers for early detection or elucidating the efficacy of treatment on pancreatic cancers. Here, our review identifies potential proteomic-based biomarkers in pancreatic cancer relating to apoptosis, cell proliferation, angiogenesis, and metabolic regulation in clinical studies. We also reviewed proteomic biomarkers from the administration of ω-3 fatty acids that act on similar anticarcinogenic pathways as above and reflect that proteomic studies on the effect of ω-3 fatty acids in pancreatic cancer will yield favorable results. © 2015 American Society for Parenteral and Enteral Nutrition.

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

PubMed Central

Barkla, Bronwyn J.

2016-01-01

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised. PMID:28248236

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

PubMed

Barkla, Bronwyn J

2016-09-08

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

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

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.

PubMed

Chen, Jin-Qiu; Wakefield, Lalage M; Goldstein, David J

2015-06-06

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

Exploring the human seminal plasma proteome: an unexplored gold mine of biomarker for male infertility and male reproduction disorder.

PubMed

Gilany, Kambiz; Minai-Tehrani, Arash; Savadi-Shiraz, Elham; Rezadoost, Hassan; Lakpour, Niknam

2015-01-01

The human seminal fluid is a complex body fluid. It is not known how many proteins are expressed in the seminal plasma; however in analog with the blood it is possible up to 10,000 proteins are expressed in the seminal plasma. The human seminal fluid is a rich source of potential biomarkers for male infertility and reproduction disorder. In this review, the ongoing list of proteins identified from the human seminal fluid was collected. To date, 4188 redundant proteins of the seminal fluid are identified using different proteomics technology, including 2-DE, SDS-PAGE-LC-MS/MS, MudPIT. However, this was reduced to a database of 2168 non-redundant protein using UniProtKB/Swiss-Prot reviewed database. The core concept of proteome were analyzed including pI, MW, Amino Acids, Chromosome and PTM distribution in the human seminal plasma proteome. Additionally, the biological process, molecular function and KEGG pathway were investigated using DAVID software. Finally, the biomarker identified in different male reproductive system disorder was investigated using proteomics platforms so far. In this study, an attempt was made to update the human seminal plasma proteome database. Our finding showed that human seminal plasma studies used to date seem to have converged on a set of proteins that are repeatedly identified in many studies and that represent only a small fraction of the entire human seminal plasma proteome.

Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm

PubMed Central

Burillo, Elena; Jorge, Inmaculada; Martínez-López, Diego; Camafeita, Emilio; Blanco-Colio, Luis Miguel; Trevisan-Herraz, Marco; Ezkurdia, Iakes; Egido, Jesús; Michel, Jean-Baptiste; Meilhac, Olivier; Vázquez, Jesús; Martin-Ventura, Jose Luis

2016-01-01

High-density lipoproteins (HDLs) are complex protein and lipid assemblies whose composition is known to change in diverse pathological situations. Analysis of the HDL proteome can thus provide insight into the main mechanisms underlying abdominal aortic aneurysm (AAA) and potentially detect novel systemic biomarkers. We performed a multiplexed quantitative proteomics analysis of HDLs isolated from plasma of AAA patients (N = 14) and control study participants (N = 7). Validation was performed by western-blot (HDL), immunohistochemistry (tissue), and ELISA (plasma). HDL from AAA patients showed elevated expression of peroxiredoxin-6 (PRDX6), HLA class I histocompatibility antigen (HLA-I), retinol-binding protein 4, and paraoxonase/arylesterase 1 (PON1), whereas α-2 macroglobulin and C4b-binding protein were decreased. The main pathways associated with HDL alterations in AAA were oxidative stress and immune-inflammatory responses. In AAA tissue, PRDX6 colocalized with neutrophils, vascular smooth muscle cells, and lipid oxidation. Moreover, plasma PRDX6 was higher in AAA (N = 47) than in controls (N = 27), reflecting increased systemic oxidative stress. Finally, a positive correlation was recorded between PRDX6 and AAA diameter. The analysis of the HDL proteome demonstrates that redox imbalance is a major mechanism in AAA, identifying the antioxidant PRDX6 as a novel systemic biomarker of AAA. PMID:27934969

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

Identification of novel biomarker and therapeutic target candidates for acute intracerebral hemorrhage by quantitative plasma proteomics.

PubMed

Li, Guo-Chun; Zhang, Lina; Yu, Ming; Jia, Haiyu; Tian, Ting; Wang, Junqin; Wang, Fuqiang; Zhou, Ling

2017-01-01

The systematic mechanisms of acute intracerebral hemorrhage are still unknown and unverified, although many recent researches have indicated the secondary insults. This study was aimed to disclose the pathological mechanism and identify novel biomarker and therapeutic target candidates by plasma proteome. Patients with AICH (n = 8) who demographically matched healthy controls (n = 4) were prospectively enrolled, and their plasma samples were obtained. The TMT-LC-MS/MS-based proteomics approach was used to quantify the differential proteome across plasma samples, and the results were analyzed by Ingenuity Pathway Analysis to explore canonical pathways and the relationship involved in the uploaded data. Compared with healthy controls, there were 31 differentially expressed proteins in the ICH group ( P  < 0.05), of which 21 proteins increased while 10 proteins decreased in abundance. These proteins are involved in 21 canonical pathways. One network with high confidence level was selected by the function network analysis, in which 23 proteins, P38MAPK and NFκB signaling pathways participated. Upstream regulator analysis found two regulators, IL6 and TNF, with an activation z -score. Seven biomarker candidates: APCS, FGB, LBP, MGMT, IGFBP2, LYZ, and APOA4 were found. Six candidate proteins were selected to assess the validity of the results by subsequent Western blotting analysis. Our analysis provided several intriguing pathways involved in ICH, like LXR/RXR activation, acute phase response signaling, and production of NO and ROS in macrophages pathways. The three upstream regulators: IL-6, TNF, LPS, and seven biomarker candidates: APCS, APOA4, FGB, IGFBP2, LBP, LYZ, and MGMT were uncovered. LPS, APOA4, IGFBP2, LBP, LYZ, and MGMT are novel potential biomarkers in ICH development. The identified proteins and pathways provide new perspectives to the potential pathological mechanism and therapeutic targets underlying ICH.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Tujin; Zhou, Jianying; Gritsenko, Marina A.

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 tomore » 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.« less

Microfluidic liquid chromatography system for proteomic applications and biomarker screening.

PubMed

Lazar, Iulia M; Trisiripisal, Phichet; Sarvaiya, Hetal A

2006-08-01

A microfluidic liquid chromatography (LC) system for proteomic investigations that integrates all the necessary components for stand-alone operation, i.e., pump, valve, separation column, and electrospray interface, is described in this paper. The overall size of the LC device is small enough to enable the integration of two fully functional separation systems on a 3 in. x 1 in. glass microchip. A multichannel architecture that uses electroosmotic pumping principles provides the necessary functionality for eluent propulsion and sample valving. The flow rates generated within these chips are fully consistent with the requirements of nano-LC platforms that are routinely used in proteomic applications. The microfluidic device was evaluated for the analysis of a protein digest obtained from the MCF7 breast cancer cell line. The cytosolic protein extract was processed according to a shotgun protocol, and after tryptic digestion and prefractionation using strong cation exchange chromatography (SCX), selected sample subfractions were analyzed with conventional and microfluidic LC platforms. Using similar experimental conditions, the performance of the microchip LC was comparable to that obtained with benchtop instrumentation, providing an overlap of 75% in proteins that were identified by more than two unique peptides. The microfluidic LC analysis of a protein-rich SCX fraction enabled the confident identification of 77 proteins by using conventional data filtering parameters, of 39 proteins with p < 0.001, and of 5 proteins that are known to be cancer-specific biomarkers, demonstrating thus the potential applicability of these chips for future high-throughput biomarker screening applications.

Proteomics for the authentication of fish species.

PubMed

Mazzeo, Maria Fiorella; Siciliano, Rosa Anna

2016-09-16

Assessment of seafood authenticity and origin, mainly in the case of processed products (fillets, sticks, baby food) represents the crucial point to prevent fraudulent deceptions thus guaranteeing market transparency and consumers health. The most dangerous practice that jeopardies fish safety is intentional or unintentional mislabeling, originating from the substitution of valuable fish species with inferior ones. Conventional analytical methods for fish authentication are becoming inadequate to comply with the strict regulations issued by the European Union and with the increase of mislabeling due to the introduction on the market of new fish species and market globalization. This evidence prompts the development of high-throughput approaches suitable to identify unambiguous biomarkers of authenticity and screen a large number of samples with minimal time consumption. Proteomics provides suitable and powerful tools to investigate main aspects of food quality and safety and has given an important contribution in the field of biomarkers discovery applied to food authentication. This report describes the most relevant methods developed to assess fish identity and offers a perspective on their potential in the evaluation of fish quality and safety thus depicting the key role of proteomics in the authentication of fish species and processed products. The assessment of fishery products authenticity is a main issue in the control quality process as deceptive practices could imply severe health risks. Proteomics based methods could significantly contribute to detect falsification and frauds, thus becoming a reliable operative first-line testing resource in food authentication. Copyright © 2016 Elsevier B.V. All rights reserved.

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

Human body fluid proteome analysis

PubMed Central

Hu, Shen; Loo, Joseph A.; Wong, David T.

2010-01-01

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future. PMID:17083142

Human body fluid proteome analysis.

PubMed

Hu, Shen; Loo, Joseph A; Wong, David T

2006-12-01

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

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

PubMed

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

2015-06-01

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

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

Blood Sampling and Preparation Procedures for Proteomic Biomarker Studies of Psychiatric Disorders.

PubMed

Guest, Paul C; Rahmoune, Hassan

2017-01-01

A major challenge in proteomic biomarker discovery and validation for psychiatric diseases is the inherent biological complexity underlying these conditions. There are also many technical issues which hinder this process such as the lack of standardization in sampling, processing and storage of bio-samples in preclinical and clinical settings. This chapter describes a reproducible procedure for sampling blood serum and plasma that is specifically designed for maximizing data quality output in two-dimensional gel electrophoresis, multiplex immunoassay and mass spectrometry profiling studies.

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

PubMed

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

2017-07-01

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

Plasma proteomics for biomarker discovery: a study in blue.

PubMed

Di Girolamo, Francesco; Righetti, Pier Giorgio

2011-12-01

The performance of Cibacron Blue dye (HiTrapBlue or Affigel Blue) in depleting albumin from plasma, as a pre-treatment for biomarker searching in the low-abundance proteome, is here assessed. It is shown that (i) co-depletion of non-albumin species is an ever-present hazard; (ii) the only proper eluant able to release quantitatively the proteins bound to the dye is boiling 4% SDS-25 mM DTT, an ion shock (2 M NaCl) being quite ineffective in releasing the low-abundance species tightly bound to the dye moiety; (iii) the mechanism of dye-protein interaction, after an initial ion-ion docking, is a robust hydrophobic interaction, which progressively augments at lower and lower pH values; (iv) at pH 2.2 in the presence of 0.1% TFA, the blue resin behaves, for all practical purposes, just as a reverse-phase chromatography column, since all residual proteins present in plasma are completely harvested. However Cibacron Blue technology should not necessarily be discarded: As long as also the plasma fraction adsorbed is properly released and analyzed, together with the flow through, one should be able to perform a viable analysis of the low-abundance proteome. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic Candidate Biomarkers of Drug-Induced Nephrotoxicity in the Rat

PubMed Central

Rouse, Rodney; Siwy, Justyna; Mullen, William; Mischak, Harald; Metzger, Jochen; Hanig, Joseph

2012-01-01

Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10–20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity. PMID:22509332

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

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

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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

PubMed

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

2013-08-01

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

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

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics

PubMed Central

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

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients’ saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects (p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity. PMID:28326926

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

PubMed

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

2017-01-01

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

Top-Down Quantitative Proteomics Identified Phosphorylation of Cardiac Troponin I as a Candidate Biomarker for Chronic Heart Failure

PubMed Central

Zhang, Jiang; Guy, Moltu J.; Norman, Holly S.; Chen, Yi-Chen; Xu, Qingge; Dong, Xintong; Guner, Huseyin; Wang, Sijian; Kohmoto, Takushi; Young, Ken H.; Moss, Richard L.; Ge, Ying

2011-01-01

The rapid increase in the prevalence of chronic heart failure (CHF) worldwide underscores an urgent need to identify biomarkers for the early detection of CHF. Post-translational modifications (PTMs) are associated with many critical signaling events during disease progression and thus offer a plethora of candidate biomarkers. We have employed top-down quantitative proteomics methodology for comprehensive assessment of PTMs in whole proteins extracted from normal and diseased tissues. We have systematically analyzed thirty-six clinical human heart tissue samples and identified phosphorylation of cardiac troponin I (cTnI) as a candidate biomarker for CHF. The relative percentages of the total phosphorylated cTnI forms over the entire cTnI populations (%Ptotal) were 56.4±3.5%, 36.9±1.6%, 6.1±2.4%, and 1.0±0.6% for postmortem hearts with normal cardiac function (n=7), early-stage of mild hypertrophy (n=5), severe hypertrophy/dilation (n=4), and end-stage CHF (n=6), respectively. In fresh transplant samples, the %Ptotal of cTnI from non-failing donor (n=4), and end-stage failing hearts (n=10) were 49.5±5.9% and 18.8±2.9%, respectively. Top-down MS with electron capture dissociation unequivocally localized the altered phosphorylation sites to Ser22/23 and determined the order of phosphorylation/dephosphorylation. This study represents the first clinical application of top-down MS-based quantitative proteomics for biomarker discovery from tissues, highlighting the potential of PTM as disease biomarkers. PMID:21751783

Identification of serum biomarkers in dogs naturally infected with Babesia canis canis using a proteomic approach

PubMed Central

2014-01-01

Background Canine babesiosis is a tick-borne disease that is caused by the haemoprotozoan parasites of the genus Babesia. There are limited data on serum proteomics in dogs, and none of the effect of babesiosis on the serum proteome. The aim of this study was to identify the potential serum biomarkers of babesiosis using proteomic techniques in order to increase our understanding about disease pathogenesis. Results Serum samples were collected from 25 dogs of various breeds and sex with naturally occurring babesiosis caused by B. canis canis. Blood was collected on the day of admission (day 0), and subsequently on the 1st and 6th day of treatment. Two-dimensional electrophoresis (2DE) of pooled serum samples of dogs with naturally occurring babesiosis (day 0, day 1 and day 6) and healthy dogs were run in triplicate. 2DE image analysis showed 64 differentially expressed spots with p ≤ 0.05 and 49 spots with fold change ≥2. Six selected spots were excised manually and subjected to trypsin digest prior to identification by electrospray ionisation mass spectrometry on an Amazon ion trap tandem mass spectrometry (MS/MS). Mass spectrometry data was processed using Data Analysis software and the automated Matrix Science Mascot Daemon server. Protein identifications were assigned using the Mascot search engine to interrogate protein sequences in the NCBI Genbank database. A number of differentially expressed serum proteins involved in inflammation mediated acute phase response, complement and coagulation cascades, apolipoproteins and vitamin D metabolism pathway were identified in dogs with babesiosis. Conclusions Our findings confirmed two dominant pathogenic mechanisms of babesiosis, haemolysis and acute phase response. These results may provide possible serum biomarker candidates for clinical monitoring of babesiosis and this study could serve as the basis for further proteomic investigations in canine babesiosis. PMID:24885808

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

PubMed

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

2017-03-01

Background: Prevalent worldwide obesity is associated with increased incidence of nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome. The identification of noninvasive biomarkers for NAFLD is of recent interest. Because primary de novo lipogenesis occurs in chicken liver as in human liver, adult chickens with age-associated steatosis resembling human NAFLD is an appealing animal model. Objective: The objective of this study was to screen potential biomarkers in the chicken model for NAFLD by transcriptomic and proteomic analysis. Methods: Hy-Line W-36 laying hens were fed standard feed from 25 to 45 wk of age to induce fatty liver. They were killed every 4 wk, and liver and plasma were collected at each time point to assess fatty liver development and for transcriptomic and proteomic analysis. Next, selected biomarkers were confirmed in additional experiments by providing supplements of the hepatoprotective nutrients betaine [300, 600, or 900 parts per million (ppm) in vivo; 2 mM in vitro] or docosahexaenoic acid (DHA; 1% in vivo; 100 μM in vitro) to 30-wk-old Hy-Line W-36 laying hens for 4 mo and to Hy-Line W-36 chicken primary hepatocytes with oleic acid-induced steatosis. Liver or hepatocyte lipid contents and the expression of biomarkers were then examined. Results: Plasma acetoacetyl-CoA synthetase (AACS), dipeptidyl-peptidase 4 (DPP4), glutamine synthetase (GLUL), and glutathione S -transferase (GST) concentrations are well-established biomarkers for NAFLD. Selected biomarkers had significant positive associations with hepatic lipid deposition ( P < 0.001). Betaine (900 ppm in vivo; 2 mM in vitro) and DHA (1% in vivo; 100 μM in vitro) supplementation both resulted in lower steatosis accompanied by the reduced expression of selected biomarkers in vivo and in vitro ( P < 0.05). Conclusion: This study used adult laying hens to identify biomarkers for NAFLD and indicated that AACS, DPP4, GLUL, and GST could be considered to be potential diagnostic

A novel workflow combining plaque imaging, plaque and plasma proteomics identifies biomarkers of human coronary atherosclerotic plaque disruption.

PubMed

Lee, Regent; Fischer, Roman; Charles, Philip D; Adlam, David; Valli, Alessandro; Di Gleria, Katalin; Kharbanda, Rajesh K; Choudhury, Robin P; Antoniades, Charalambos; Kessler, Benedikt M; Channon, Keith M

2017-01-01

Atherosclerotic plaque rupture is the culprit event which underpins most acute vascular syndromes such as acute myocardial infarction. Novel biomarkers of plaque rupture could improve biological understanding and clinical management of patients presenting with possible acute vascular syndromes but such biomarker(s) remain elusive. Investigation of biomarkers in the context of de novo plaque rupture in humans is confounded by the inability to attribute the plaque rupture as the source of biomarker release, as plaque ruptures are typically associated with prompt down-stream events of myocardial necrosis and systemic inflammation. We developed a novel approach to identify potential biomarkers of plaque rupture by integrating plaque imaging, using optical coherence tomography, with both plaque and plasma proteomic analysis in a human model of angioplasty-induced plaque disruption. We compared two pairs of coronary plaque debris, captured by a FilterWire Device, and their corresponding control samples and found matrix metalloproteinase 9 (MMP9) to be significantly enriched in plaque. Plaque contents, as defined by optical coherence tomography, affect the systemic changes of MMP9. Disruption of lipid-rich plaque led to prompt elevation of plasma MMP9, whereas disruption of non-lipid-rich plaque resulted in delayed elevation of plasma MMP9. Systemic MMP9 elevation is independent of the associated myocardial necrosis and systemic inflammation (measured by Troponin I and C-reactive protein, respectively). This information guided the selection of a subset of subjects of for further label free proteomics analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). We discovered five novel, plaque-enriched proteins (lipopolysaccharide binding protein, Annexin A5, eukaryotic translocation initiation factor, syntaxin 11, cytochrome B5 reductase 3) to be significantly elevated in systemic circulation at 5 min after plaque disruption. This novel approach for biomarker

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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed Central

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

Translational Research and Plasma Proteomic in Cancer.

PubMed

Santini, Annamaria Chiara; Giovane, Giancarlo; Auletta, Adelaide; Di Carlo, Angelina; Fiorelli, Alfonso; Cito, Letizia; Astarita, Carlo; Giordano, Antonio; Alfano, Roberto; Feola, Antonia; Di Domenico, Marina

2016-04-01

Proteomics is a recent field of research in molecular biology that can help in the fight against cancer through the search for biomarkers that can detect this disease in the early stages of its development. Proteomic is a speedily growing technology, also thanks to the development of even more sensitive and fast mass spectrometry analysis. Although this technique is the most widespread for the discovery of new cancer biomarkers, it still suffers of a poor sensitivity and insufficient reproducibility, essentially due to the tumor heterogeneity. Common technical shortcomings include limitations in the sensitivity of detecting low abundant biomarkers and possible systematic biases in the observed data. Current research attempts are trying to develop high-resolution proteomic instrumentation for high-throughput monitoring of protein changes that occur in cancer. In this review, we describe the basic features of the proteomic tools which have proven to be useful in cancer research, showing their advantages and disadvantages. The application of these proteomic tools could provide early biomarkers detection in various cancer types and could improve the understanding the mechanisms of tumor growth and dissemination. © 2015 Wiley Periodicals, Inc.

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

PubMed

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

2015-11-06

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duijvesz, Diederick; Burnum-Johnson, Kristin E.; Gritsenko, Marina A.

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 cellsmore » (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

Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset.

PubMed

Metz, Thomas O; Qian, Wei-Jun; 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

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications.

PubMed

Jimenez, Connie R; Verheul, Henk M W

2014-01-01

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

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

PubMed Central

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

2017-01-01

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

Proteomic profiling for plasma biomarkers of tuberculosis progression.

PubMed

Liu, Qiuyue; Pan, Liping; Han, Fen; Luo, Baojian; Jia, Hongyan; Xing, Aiying; Li, Qi; Zhang, Zongde

2018-06-05

Severe pulmonary tuberculosis (STB) is a life‑threatening condition with high economic and social burden. The present study aimed to screen for distinct proteins in different stages of TB and identify biomarkers for a better understanding of TB progression and pathogenesis. Blood samples were obtained from 81 patients with STB, 80 with mild TB (MTB) and 50 healthy controls. Differentially expressed proteins were identified using liquid chromatography‑tandem mass spectrometry‑based label‑free quantitative proteomic analysis. Functional and pathway enrichment analyses were performed for the identified proteins. The expression of potential biomarkers was further validated by western blot analysis and enzyme‑linked immunosorbent assays. The accuracy, sensitivity and specificity for selected protein biomarkers in diagnosing STB were also evaluated. A total of 1,011 proteins were identified in all three groups, and 153 differentially expressed proteins were identified in patients with STB. These proteins were involved in 'cellular process', 'response to stimulus', 'apoptotic process', 'immune system process' and 'select metabolic process'. Significant differences in protein expression were detected in α‑1‑acid glycoprotein 2 (ORM2), interleukin‑36α (IL‑36α), S100 calcium binding protein A9 (S100‑A9), superoxide dismutase (SOD)1 in the STB group, compared with the MTB and control groups. The combination of plasma ORM2, IL‑36α, S100A9 and SOD1 levels achieved 90.00% sensitivity and 92.16% specificity to discriminate between patients with STB and MTB, and 89.66% sensitivity and 98.9% specificity to discriminate between patients with STB and healthy controls. ORM2, S100A9, IL‑36α and SOD1 were associated with the development of TB, and have the potential to distinguish between different stages of TB. Differential protein expression during disease progression may improve the current understanding of STB pathogenesis.

Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

PubMed Central

Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

2016-01-01

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

2014-01-01

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

PubMed

Marimuthu, Arivusudar; Chavan, Sandip; Sathe, Gajanan; Sahasrabuddhe, Nandini A; Srikanth, Srinivas M; Renuse, Santosh; Ahmad, Sartaj; Radhakrishnan, Aneesha; Barbhuiya, Mustafa A; Kumar, Rekha V; Harsha, H C; Sidransky, David; Califano, Joseph; Pandey, Akhilesh; Chatterjee, Aditi

2013-11-01

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome. Copyright © 2013 Elsevier B.V. All rights reserved.

Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program (DASP) sample subset

PubMed Central

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

2009-01-01

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted “-omics” approaches are under-utilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. Alpha-2-glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples. PMID:18092746

Marine proteomics: a critical assessment of an emerging technology.

PubMed

Slattery, Marc; Ankisetty, Sridevi; Corrales, Jone; Marsh-Hunkin, K Erica; Gochfeld, Deborah J; Willett, Kristine L; Rimoldi, John M

2012-10-26

The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for eco-physiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several "model species". Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.

Serum biomarkers of Burkholderia mallei infection elucidated by proteomic imaging of skin and lung abscesses.

PubMed

Glaros, Trevor G; Blancett, Candace D; Bell, Todd M; Natesan, Mohan; Ulrich, Robert G

2015-01-01

The bacterium Burkholderia mallei is the etiological agent of glanders, a highly contagious, often fatal zoonotic infectious disease that is also a biodefense concern. Clinical laboratory assays that analyze blood or other biological fluids are the highest priority because these specimens can be collected with minimal risk to the patient. However, progress in developing sensitive assays for monitoring B. mallei infection is hampered by a shortage of useful biomarkers. Reasoning that there should be a strong correlation between the proteomes of infected tissues and circulating serum, we employed imaging mass spectrometry (IMS) of thin-sectioned tissues from Chlorocebus aethiops (African green) monkeys infected with B. mallei to localize host and pathogen proteins that were associated with abscesses. Using laser-capture microdissection of specific regions identified by IMS and histology within the tissue sections, a more extensive proteomic analysis was performed by a technique that combined the physical separation capabilities of liquid chromatography (LC) with the sensitive mass analysis capabilities of mass spectrometry (LC-MS/MS). By examining standard formalin-fixed, paraffin-embedded tissue sections, this strategy resulted in the identification of several proteins that were associated with lung and skin abscesses, including the host protein calprotectin and the pathogen protein GroEL. Elevated levels of calprotectin detected by ELISA and antibody responses to GroEL, measured by a microarray of the bacterial proteome, were subsequently detected in the sera of C. aethiops, Macaca mulatta, and Macaca fascicularis primates infected with B. mallei. Our results demonstrate that a combination of multidimensional MS analysis of traditional histology specimens with high-content protein microarrays can be used to discover lead pairs of host-pathogen biomarkers of infection that are identifiable in biological fluids.

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

PubMed

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

2017-07-15

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

Current advances in esophageal cancer proteomics.

PubMed

Uemura, Norihisa; Kondo, Tadashi

2015-06-01

We review the current status of proteomics for esophageal cancer (EC) from a clinician's viewpoint. The ultimate goal of cancer proteomics is the improvement of clinical outcome. The proteome as a functional translation of the genome is a straightforward representation of genomic mechanisms that trigger carcinogenesis. Cancer proteomics has identified the mechanisms of carcinogenesis and tumor progression, detected biomarker candidates for early diagnosis, and provided novel therapeutic targets for personalized treatments. Our review focuses on three major topics in EC proteomics: diagnostics, treatment, and molecular mechanisms. We discuss the major histological differences between EC types, i.e., esophageal squamous cell carcinoma and adenocarcinoma, and evaluate the clinical significance of published proteomics studies, including promising diagnostic biomarkers and novel therapeutic targets, which should be further validated prior to launching clinical trials. Multi-disciplinary collaborations between basic scientists, clinicians, and pathologists should be established for inter-institutional validation. In conclusion, EC proteomics has provided significant results, which after thorough validation, should lead to the development of novel clinical tools and improvement of the clinical outcome for esophageal cancer patients. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Use of Proteomic and Hematology Biomarkers for Prediction of Hematopoietic Acute Radiation Syndrome Severity in Baboon Radiation Models.

PubMed

Blakely, William F; Bolduc, David L; Debad, Jeff; Sigal, George; Port, Matthias; Abend, Michael; Valente, Marco; Drouet, Michel; Hérodin, Francis

2018-07-01

Use of plasma proteomic and hematological biomarkers represents a promising approach to provide useful diagnostic information for assessment of the severity of hematopoietic acute radiation syndrome. Eighteen baboons were evaluated in a radiation model that underwent total-body and partial-body irradiations at doses of Co gamma rays from 2.5 to 15 Gy at dose rates of 6.25 cGy min and 32 cGy min. Hematopoietic acute radiation syndrome severity levels determined by an analysis of blood count changes measured up to 60 d after irradiation were used to gauge overall hematopoietic acute radiation syndrome severity classifications. A panel of protein biomarkers was measured on plasma samples collected at 0 to 28 d after exposure using electrochemiluminescence-detection technology. The database was split into two distinct groups (i.e., "calibration," n = 11; "validation," n = 7). The calibration database was used in an initial stepwise regression multivariate model-fitting approach followed by down selection of biomarkers for identification of subpanels of hematopoietic acute radiation syndrome-responsive biomarkers for three time windows (i.e., 0-2 d, 2-7 d, 7-28 d). Model 1 (0-2 d) includes log C-reactive protein (p < 0.0001), log interleukin-13 (p < 0.0054), and procalcitonin (p < 0.0316) biomarkers; model 2 (2-7 d) includes log CD27 (p < 0.0001), log FMS-related tyrosine kinase 3 ligand (p < 0.0001), log serum amyloid A (p < 0.0007), and log interleukin-6 (p < 0.0002); and model 3 (7-28 d) includes log CD27 (p < 0.0012), log serum amyloid A (p < 0.0002), log erythropoietin (p < 0.0001), and log CD177 (p < 0.0001). The predicted risk of radiation injury categorization values, representing the hematopoietic acute radiation syndrome severity outcome for the three models, produced least squares multiple regression fit confidences of R = 0.73, 0.82, and 0.75, respectively. The resultant algorithms support the proof of concept that plasma proteomic biomarkers can supplement

Respiratory Toxicity Biomarkers

EPA Science Inventory

The advancement in high throughput genomic, proteomic and metabolomic techniques have accelerated pace of lung biomarker discovery. A recent growth in the discovery of new lung toxicity/disease biomarkers have led to significant advances in our understanding of pathological proce...

Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis*

PubMed Central

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-01-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the

Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis.

PubMed

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-06-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the

BluePen Biomarkers LLC: integrated biomarker solutions

PubMed Central

Blair, Ian A; Mesaros, Clementina; Lilley, Patrick; Nunez, Matthew

2016-01-01

BluePen Biomarkers provides a unique comprehensive multi-omics biomarker discovery and validation platform. We can quantify, integrate and analyze genomics, proteomics, metabolomics and lipidomics biomarkers, alongside clinical data, demographics and other phenotypic data. A unique bio-inspired signal processing analytic approach is used that has the proven ability to identify biomarkers in a wide variety of diseases. The resulting biomarkers can be used for diagnosis, prognosis, mechanistic studies and predicting treatment response, in contexts from core research through clinical trials. BluePen Biomarkers provides an additional groundbreaking research goal: identifying surrogate biomarkers from different modalities. This not only provides new biological insights, but enables least invasive, least-cost tests that meet or exceed the predictive quality of current tests. PMID:28031971

The current status of clinical proteomics and the use of MRM and MRM(3) for biomarker validation.

PubMed

Lemoine, Jérôme; Fortin, Tanguy; Salvador, Arnaud; Jaffuel, Aurore; Charrier, Jean-Philippe; Choquet-Kastylevsky, Geneviève

2012-05-01

The transfer of biomarkers from the discovery field to clinical use is still, despite progress, on a road filled with pitfalls. Since the emergence of proteomics, thousands of putative biomarkers have been published, often with overlapping diagnostic capacities. The strengthening of the robustness of discovery technologies, particularly in mass spectrometry, has been followed by intense discussions on establishing well-defined evaluation procedures for the identified targets to ultimately allow the clinical validation and then the clinical use of some of these biomarkers. Some of the obstacles to the evaluation process have been the lack of the availability of quick and easy-to-develop, easy-to-use, robust, specific and sensitive alternative quantitative methods when immunoaffinity-based tests are unavailable. Multiple reaction monitoring (MRM; also called selected reaction monitoring) is currently proving its capabilities as a complementary or alternative technique to ELISA for large biomarker panel evaluation. Here, we present how MRM(3) can overcome the lack of specificity and sensitivity often encountered by MRM when tracking minor proteins diluted by complex biological matrices.

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

PubMed

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

2018-05-15

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

Effects of Three Commonly-used Diuretics on the Urinary Proteome

PubMed Central

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

2014-01-01

Biomarker is the measurable change associated with a physiological or pathophysiological process. Unlike blood which has mechanisms to keep the internal environment homeostatic, urine is more likely to reflect changes of the body. As a result, urine is likely to be a better biomarker source than blood. However, since the urinary proteome is affected by many factors, including diuretics, careful evaluation of those effects is necessary if urinary proteomics is used for biomarker discovery. Here, we evaluated the effects of three commonly-used diuretics (furosemide, F; hydrochlorothiazide, H; and spirolactone, S) on the urinary proteome in rats. Urine samples were collected before and after intragastric administration of diuretics at therapeutic doses and the proteomes were analyzed using label-free liquid chromatography–tandem mass spectrometry (LC–MS/MS). Based on the criteria of P ⩽ 0.05, a fold change ⩾2, a spectral count ⩾5, and false positive rate (FDR) ⩽1%, 14 proteins (seven for F, five for H, and two for S) were identified by Progenesis LC–MS. The human orthologs of most of these 14 proteins are stable in the healthy human urinary proteome, and ten of them are reported as disease biomarkers. Thus, our results suggest that the effects of diuretics deserve more attention in future urinary protein biomarker studies. Moreover, the distinct effects of diuretics on the urinary proteome may provide clues to the mechanisms of diuretics. PMID:24508280

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

PubMed

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

2014-06-01

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

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

Role of Proteomics in the Development of Personalized Medicine.

PubMed

Jain, Kewal K

2016-01-01

Advances in proteomic technologies have made import contribution to the development of personalized medicine by facilitating detection of protein biomarkers, proteomics-based molecular diagnostics, as well as protein biochips and pharmacoproteomics. Application of nanobiotechnology in proteomics, nanoproteomics, has further enhanced applications in personalized medicine. Proteomics-based molecular diagnostics will have an important role in the diagnosis of certain conditions and understanding the pathomechanism of disease. Proteomics will be a good bridge between diagnostics and therapeutics; the integration of these will be important for advancing personalized medicine. Use of proteomic biomarkers and combination of pharmacoproteomics with pharmacogenomics will enable stratification of clinical trials and improve monitoring of patients for development of personalized therapies. Proteomics is an important component of several interacting technologies used for development of personalized medicine, which is depicted graphically. Finally, cancer is a good example of applications of proteomic technologies for personalized management of cancer. © 2016 Elsevier Inc. All rights reserved.

NCI, NHLBI, FDA, AACC, and CMS Collaborate in Advancing Proteomics Regulatory Science | Office of Cancer Clinical Proteomics Research

Cancer.gov

Despite great strides in proteomics and the growing number of articles citing the discovery of potential biomarkers, the actual rate of introduction of Food and Drug Administration (FDA) approved protein analytes has been relatively unchanged over the past 10 years. One of reasons for the lack of new protein-based biomarkers approved has been a lack of information and understanding by the proteomics research community to the regulatory process used by the FDA. To address this issue, Dr.

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. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

Unlocking the proteomic information encoded in MALDI-TOF-MS data used for microbial identification and characterization.

PubMed

Fagerquist, Clifton K

2017-01-01

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is increasingly utilized as a rapid technique to identify microorganisms including pathogenic bacteria. However, little attention has been paid to the significant proteomic information encoded in the MS peaks that collectively constitute the MS 'fingerprint'. This review/perspective is intended to explore this topic in greater detail in the hopes that it may spur interest and further research in this area. Areas covered: This paper examines the recent literature on utilizing MALDI-TOF for bacterial identification. Critical works highlighting protein biomarker identification of bacteria, arguments for and against protein biomarker identification, proteomic approaches to biomarker identification, emergence of MALDI-TOF-TOF platforms and their use for top-down proteomic identification of bacterial proteins, protein denaturation and its effect on protein ion fragmentation, collision cross-sections and energy deposition during desorption/ionization are also explored. Expert commentary: MALDI-TOF and TOF-TOF mass spectrometry platforms will continue to provide chemical analyses that are rapid, cost-effective and high throughput. These instruments have proven their utility in the taxonomic identification of pathogenic bacteria at the genus and species level and are poised to more fully characterize these microorganisms to the benefit of clinical microbiology, food safety and other fields.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

PubMed

Sun, Huishan; Pan, Liping; Jia, Hongyan; Zhang, Zhiguo; Gao, Mengqiu; Huang, Mailing; Wang, Jinghui; Sun, Qi; Wei, Rongrong; Du, Boping; Xing, Aiying; Zhang, Zongde

2018-01-01

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients ( n = 15), compared with LTBI individuals ( n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set ( n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set ( n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic

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

PubMed

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

2014-09-09

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

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle.

PubMed

Zhang, Kai; Tang, Chaohua; Liang, Xiaowei; Zhao, Qingyu; Zhang, Junmin

2018-01-10

Salbutamol, a selective β 2 -agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

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.

Protein biomarkers of alcohol abuse

PubMed Central

Torrente, Mariana P; Freeman, Willard M; Vrana, Kent E

2012-01-01

Alcohol abuse can lead to a number of health and social issues. Our current inability to accurately assess long-term drinking behaviors is an important obstacle to its diagnosis and treatment. Biomarkers for chronic alcohol consumption have made a number of important advances but have yet to become highly accurate and as accepted as objective tests for other diseases. Thus, there is a crucial need for the development of more sensitive and specific markers of alcohol abuse. Recent advancements in proteomic technologies have greatly increased the potential for alcohol abuse biomarker discovery. Here, the authors review established and novel protein biomarkers for long-term alcohol consumption and the proteomic technologies that have been used in their study. PMID:22967079

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

PubMed

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

2014-01-01

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

Detection of Biomarkers of Pathogenic Naegleria fowleri Through Mass Spectrometry and Proteomics

PubMed Central

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

2017-01-01

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

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

PubMed Central

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

2012-01-01

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

Identification of EBP50 as a specific biomarker for carcinogens via the analysis of mouse lymphoma cellular proteome.

PubMed

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

2012-03-01

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

Effect of sex and RYR1 gene mutation on the muscle proteomic profile and main physiological biomarkers in pigs at slaughter.

PubMed

Oliván, Mamen; González, Joel; Bassols, Anna; Díaz, Fernando; Carreras, Ricard; Mainau, Eva; Arroyo, Laura; Peña, Raquel; Potes, Yaiza; Coto-Montes, Ana; Hollung, Kristin; Velarde, Antonio

2018-07-01

Gender and RYR1 gene mutation might have an effect on the muscle metabolic characteristics and on the animal's stress at slaughter, which could influence the process of muscle-to-meat conversion. Forty-eight pigs were distributed in a design including two factors: sex (male/female) and RYR1 genotype (NN/Nn). At slaughter, physiological blood biomarkers and muscle proteome were analyzed and carcass and meat quality traits were registered. Females had higher serum levels of glucose, urea, C-reactive protein "CRP", Pig-MAP and glutation-peroxidase "GPx" and lower levels of lactate, showed faster muscle pH decline and higher meat exudation. RYR1 mutation increased serum creatinine, creatine kinase and CRP and decreased GPx. The proteomic study highlighted significant effects of gender and RYR1 genotype on proteins related to fibre composition, antioxidant defense and post mortem glycolytic pathway, which correlate to differences of meat quality. This study provides interesting information on muscle biomarkers of the ultimate meat quality that are modulated by the animal's individual susceptibility to stress at slaughter. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

Parker, Carol E; Borchers, Christoph H

2014-06-01

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

Determination of burn patient outcome by large-scale quantitative discovery proteomics

PubMed Central

Finnerty, Celeste C.; Jeschke, Marc G.; Qian, Wei-Jun; Kaushal, Amit; Xiao, Wenzhong; Liu, Tao; Gritsenko, Marina A.; Moore, Ronald J.; Camp, David G.; Moldawer, Lyle L.; Elson, Constance; Schoenfeld, David; Gamelli, Richard; Gibran, Nicole; Klein, Matthew; Arnoldo, Brett; Remick, Daniel; Smith, Richard D.; Davis, Ronald; Tompkins, Ronald G.; Herndon, David N.

2013-01-01

Objective Emerging proteomics techniques can be used to establish proteomic outcome signatures and to identify candidate biomarkers for survival following traumatic injury. We applied high-resolution liquid chromatography-mass spectrometry (LC-MS) and multiplex cytokine analysis to profile the plasma proteome of survivors and non-survivors of massive burn injury to determine the proteomic survival signature following a major burn injury. Design Proteomic discovery study. Setting Five burn hospitals across the U.S. Patients Thirty-two burn patients (16 non-survivors and 16 survivors), 19–89 years of age, were admitted within 96 h of injury to the participating hospitals with burns covering >20% of the total body surface area and required at least one surgical intervention. Interventions None. Measurements and Main Results We found differences in circulating levels of 43 proteins involved in the acute phase response, hepatic signaling, the complement cascade, inflammation, and insulin resistance. Thirty-two of the proteins identified were not previously known to play a role in the response to burn. IL-4, IL-8, GM-CSF, MCP-1, and β2-microglobulin correlated well with survival and may serve as clinical biomarkers. Conclusions These results demonstrate the utility of these techniques for establishing proteomic survival signatures and for use as a discovery tool to identify candidate biomarkers for survival. This is the first clinical application of a high-throughput, large-scale LC-MS-based quantitative plasma proteomic approach for biomarker discovery for the prediction of patient outcome following burn, trauma or critical illness. PMID:23507713

Advances of Proteomic Sciences in Dentistry

PubMed Central

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

2016-01-01

Applications of proteomics tools revolutionized various biomedical disciplines such as genetics, molecular biology, medicine, and dentistry. The aim of this review is to highlight the major milestones in proteomics in dentistry during the last fifteen years. Human oral cavity contains hard and soft tissues and various biofluids including saliva and crevicular fluid. Proteomics has brought revolution in dentistry by helping in the early diagnosis of various diseases identified by the detection of numerous biomarkers present in the oral fluids. This paper covers the role of proteomics tools for the analysis of oral tissues. In addition, dental materials proteomics and their future directions are discussed. PMID:27187379

Advances of Proteomic Sciences in Dentistry.

PubMed

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

2016-05-13

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

Proteomic profiling of white muscle from freshwater catfish Rita rita.

PubMed

Mohanty, Bimal Prasanna; Mitra, Tandrima; Banerjee, Sudeshna; Bhattacharjee, Soma; Mahanty, Arabinda; Ganguly, Satabdi; Purohit, Gopal Krishna; Karunakaran, Dhanasekar; Mohanty, Sasmita

2015-06-01

Muscle tissues contribute 34-48 % of the total body mass in fish. Proteomic analysis enables better understanding of the skeletal muscle physiology and metabolism. A proteome map reflects the general fingerprinting of the fish species and has the potential to identify novel proteins which could serve as biomarkers for many aspects of aquaculture including fish physiology and growth, flesh quality, food safety and aquatic environmental monitoring. The freshwater catfish Rita rita of the family Bagridae inhabiting the tropical rivers and estuaries is an important food fish with high nutritive value and is also considered a species of choice in riverine pollution monitoring. Omics information that could enhance utility of this species in molecular research is meager. Therefore, in the present study, proteomic analysis of Rita rita muscle has been carried out and functional genomics data have been generated. A reference muscle proteome has been developed, and 23 protein spots, representing 18 proteins, have been identified by MALDI-TOF/TOF-MS and LC-MS/MS. Besides, transcript information on a battery of heat shock proteins (Hsps) has been generated. The functional genomics information generated could act as the baseline data for further molecular research on this species.

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

Randomized trial of glucosamine and chondroitin supplementation on inflammation and oxidative stress biomarkers and plasma proteomics profiles in healthy humans.

PubMed

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

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. 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. 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. 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. ClinicalTrials.gov NCT01682694.

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. © 2014 The Author(s) Journal of Eukaryotic Microbiology © 2014 International Society of Protistologists.

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

PubMed

Htun, Nay Min; Peter, Karlheinz

2014-10-01

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

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. Copyright © 2012 Elsevier B.V. All rights reserved.

Head and neck cancer: proteomic advances and biomarker achievements.

PubMed

Rezende, Taia Maria Berto; de Souza Freire, Mirna; Franco, Octávio Luiz

2010-11-01

Tumors of the head and neck comprise an important neoplasia group, the incidence of which is increasing in many parts of the world. Recent advances in diagnostic and therapeutic techniques for these lesions have yielded novel molecular targets, uncovered signal pathway dominance, and advanced early cancer detection. Proteomics is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the analysis of different types of samples. The proteomic profiles of different types of cancer have been studied, and this has provided remarkable advances in cancer understanding. This review covers recent advances for head and neck cancer; it encompasses the risk factors, pathogenesis, proteomic tools that can help in understanding cancer, and new proteomic findings in this type of cancer. Copyright © 2010 American Cancer Society.

Ovine subclinical mastitis: proteomic analysis of whey and milk fat globules unveils putative diagnostic biomarkers in milk.

PubMed

Chiaradia, Elisabetta; Valiani, Andrea; Tartaglia, Micaela; Scoppetta, Fausto; Renzone, Giovanni; Arena, Simona; Avellini, Luca; Benda, Simona; Gaiti, Alberto; Scaloni, Andrea

2013-05-27

Subclinical mastitis is one of the main causes of alteration in milk content and has a major impact on both animal welfare and economy in the dairy industry. A better knowledge is needed to understand the ovine mammary gland metabolism and its response to bacterial infection. In this study, the proteomic changes in ovine milk as a result of subclinical mastitis were investigated by comparing both whey and fat globule membrane profiles of samples from Staphylococcus chromogenes-positive individuals, with those from non-infected counterparts having high or low somatic cell count; the latter were used as control. 2-DE and combined MS procedures were utilized for this purpose. Although sample bromatological parameters were very similar, proteomic analysis highlighted significant differences between the three experimental groups. Most relevant changes were observed between samples of infected milk and control. Modifications related to the defense response of the mammary gland to the pathogen were evident, with important consequences on nutritional and technological properties of milk. On the other hand, quantitative protein changes between non-infected samples with low and high levels of somatic cells indicated that the latter may result as a consequence of a probable unpaired cellular metabolism due to cellular stress, hormonal variations or previous infections. Putative biomarkers useful for the monitoring of sheep mammary metabolism and for the careful management of ovine subclinical mastitis to avoid its clinical degeneration are proposed and discussed. Proteomics has been here applied to the differentiation of healthy and subclinical mastitic sheep milk samples, evidencing the response of the mammary gland to S. chromogenes infection. Presented results propose useful protein biomarkers for the detection of ewe mammary infection at its subclinical stages and, subsequently, mastitis recognition and treatment. Differently from bovine, these data confirm that the

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...

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

Novel biomarkers for cardiovascular risk assessment: current status and future directions.

PubMed

MacNamara, James; Eapen, Danny J; Quyyumi, Arshed; Sperling, Laurence

2015-09-01

Cardiovascular disease (CVD) is the leading cause of mortality in the modern world. Traditional risk algorithms may miss up to 20% of CVD events. Therefore, there is a need for new cardiac biomarkers. Many fields of research are dedicated to improving cardiac risk prediction, including genomics, transcriptomics and proteomics. To date, even the most promising biomarkers have only demonstrated modest associations and predictive ability. Few have undergone randomized control trials. A number of biomarkers are targets to new therapies aimed to reduce cardiovascular risk. Currently, some of the most promising risk prediction has been demonstrated with panels of multiple biomarkers. This article reviews the current state and future of proteomic biomarkers and aggregate biomarker panels.

Biomarkers intersect with the exposome

PubMed Central

Rappaport, Stephen M.

2016-01-01

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment. PMID:22672124

Mass spectrometry-based proteomics for translational research: a technical overview.

PubMed

Paulo, Joao A; Kadiyala, Vivek; Banks, Peter A; Steen, Hanno; Conwell, Darwin L

2012-03-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.

Mass Spectrometry-Based Proteomics for Translational Research: A Technical Overview

PubMed Central

Paulo, Joao A.; Kadiyala, Vivek; Banks, Peter A.; Steen, Hanno; Conwell, Darwin L.

2012-01-01

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease. PMID:22461744

Proteomics as a Tool for Biomarker Discovery

PubMed Central

Kohn, Elise C.; Azad, Nilofer; Annunziata, Christina; Dhamoon, Amit S.; Whiteley, Gordon

2007-01-01

Novel technologies are now being advanced for the purpose of identification and validation of new disease biomarkers. A reliable and useful clinical biomarker must a) come from a readily attainable source, such as blood or urine, b) have sufficient sensitivity to correctly identify affected individuals, c) have sufficient specificity to avoid incorrect labeling of unaffected persons, and d) result in a notable benefit for the patient through intervention, such as survival or life quality improvement. Despite these critical descriptors, the few available FDA-approved biomarkers for cancer do not completely fit this definition and their benefits are limited to a small number of cancers. Ovarian cancer exemplifies the need for a diagnostic biomarker of early stage disease. Symptoms are present but not specific to the disease, delaying diagnosis until an advanced and generally incurable stage in over 70% of affected women. As such, diagnostic intervention in the form of oopherectomy can be performed in the appropriate at-risk population if identified such as with a new accurate, sensitive, and specific biomarker. If early stage disease is identified, the requirement for survival and life quality improvement will be met. One of the new technologies applied to biomarker discovery is tour-de-force analysis of serum peptides and proteins. Optimization of mass spectrometry techniques coupled with advanced bioinformatics approaches has yielded informative biomarker signatures discriminating presence of cancer from unaffected in multiple studies from different groups. Validation and randomized outcome studies are needed to determine the true value of these new biomarkers in early diagnosis, and improved survival and quality of life. PMID:18057524

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

PubMed

Findeisen, Peter; Neumaier, Michael

2009-01-01

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

Cross-platform method for identifying candidate network biomarkers for prostate cancer.

PubMed

Jin, G; Zhou, X; Cui, K; Zhang, X-S; Chen, L; Wong, S T C

2009-11-01

Discovering biomarkers using mass spectrometry (MS) and microarray expression profiles is a promising strategy in molecular diagnosis. Here, the authors proposed a new pipeline for biomarker discovery that integrates disease information for proteins and genes, expression profiles in both genomic and proteomic levels, and protein-protein interactions (PPIs) to discover high confidence network biomarkers. Using this pipeline, a total of 474 molecules (genes and proteins) related to prostate cancer were identified and a prostate-cancer-related network (PCRN) was derived from the integrative information. Thus, a set of candidate network biomarkers were identified from multiple expression profiles composed by eight microarray datasets and one proteomics dataset. The network biomarkers with PPIs can accurately distinguish the prostate patients from the normal ones, which potentially provide more reliable hits of biomarker candidates than conventional biomarker discovery methods.

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

PubMed

Larkin, S E T; Johnston, H E; Jackson, T R; Jamieson, D G; Roumeliotis, T I; Mockridge, C I; Michael, A; Manousopoulou, A; Papachristou, E K; Brown, M D; Clarke, N W; Pandha, H; Aukim-Hastie, C L; Cragg, M S; Garbis, S D; Townsend, P A

2016-10-25

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6. Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

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

PubMed Central

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

2015-01-01

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

Proteomic Analysis of Saliva Identifies Potential Biomarkers for Orthodontic Tooth Movement

PubMed Central

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

2012-01-01

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

Exosomal Fetuin-A identified by proteomics: a novel urinary biomarker for detecting acute kidney injury

PubMed Central

Zhou, Hua; Pisitkun, Trairak; Aponte, Angel; Yuen, Peter S.T.; Hoffert, Jason D.; Yasuda, Hideo; Hu, Xuzhen; Chawla, Lakhmir; Shen, Rong-Fong; Knepper, Mark A.; Star., Robert A.

2008-01-01

Urinary exosomes containing apical membrane and intracellular fluid are normally secreted into the urine from all nephron segments, and may carry protein markers of renal dysfunction and structural injury. We aimed to discover biomarkers in urinary exosomes to detect acute kidney injury (AKI) which has a high mortality and morbidity. Animals were injected intravenously with cisplatin. Urinary exosomes were isolated by differential centrifugation. Protein changes were evaluated by two-dimensional difference in gel electrophoresis and changed proteins were identified by MALDI-TOF-TOF or LC-MS/MS. The identified candidate biomarkers were validated by western blotting in individual urine samples from rats subjected to cisplatin injection; bilateral ischemia and reperfusion (I/R); volume depletion (VD); and ICU patients with and without AKI. We identified 18 proteins that were increased and 9 proteins that were decreased 8 hr after cisplatin. Most of the candidates could not be validated by western blotting. However, exosomal Fetuin-A increased 52.5-fold at day 2 (1 day before serum creatinine increase and tubule damage) and remained elevated 51.5-fold at day 5 (peak renal injury) after cisplatin injection. By immuno-electron microscopy and elution studies, Fetuin-A was located inside urinary exosomes. Urinary Fetuin-A was increased 31.6-fold in the early phase (2~8hr) of ischemia/reperfusion, but not in prerenal azotemia. Urinary exosomal Fetuin-A also increased in three ICU patients with AKI compared to the patients without AKI. We conclude that 1) Proteomic analysis of urinary exosomes can provide biomarker candidates for the diagnosis of AKI; 2) Urinary Fetuin-A might be a predictive biomarker of structural renal injury. PMID:17021608

A Method for Label-Free, Differential Top-Down Proteomics.

PubMed

Ntai, Ioanna; Toby, Timothy K; LeDuc, Richard D; Kelleher, Neil L

2016-01-01

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

Bio-markers: traceability in food safety issues.

PubMed

Raspor, Peter

2005-01-01

Research and practice are focusing on development, validation and harmonization of technologies and methodologies to ensure complete traceability process throughout the food chain. The main goals are: scale-up, implementation and validation of methods in whole food chains, assurance of authenticity, validity of labelling and application of HACCP (hazard analysis and critical control point) to the entire food chain. The current review is to sum the scientific and technological basis for ensuring complete traceability. Tracing and tracking (traceability) of foods are complex processes due to the (bio)markers, technical solutions and different circumstances in different technologies which produces various foods (processed, semi-processed, or raw). Since the food is produced for human or animal consumption we need suitable markers to be stable and traceable all along the production chain. Specific biomarkers can have a function in technology and in nutrition. Such approach would make this development faster and more comprehensive and would make possible that food effect could be monitored with same set of biomarkers in consumer. This would help to develop and implement food safety standards that would be based on real physiological function of particular food component.

CSF proteomic fingerprints for HIV-associated cognitive impairment.

PubMed

Laspiur, Juliana Pérez; Anderson, Eric R; Ciborowski, Pawel; Wojna, Valerie; Rozek, Wojciech; Duan, Fenghai; Mayo, Raul; Rodríguez, Elaine; Plaud-Valentín, Marinés; Rodríguez-Orengo, José; Gendelman, Howard E; Meléndez, Loyda M

2007-12-01

Cognitive impairment remains a major complication of advanced human immunodeficiency virus (HIV) infection despite the widespread use of anti-retroviral therapy. Diagnosis is made by exclusion making biomarkers of great potential use. Thus, we used an integrated proteomics platform to assess cerebrospinal fluid protein profiles from 50 HIV-1 seropositive Hispanic women. Nine of 38 proteins identified were unique in those patients with cognitive impairment (CI). These proteins were linked to cell signaling, structural function, and antioxidant activities. This work highlights, in a preliminary manner, the utility of proteomic profiling for biomarker discovery for HIV-1 associated cognitive dysfunction.

CSF proteomic fingerprints for HIV- associated cognitive impairment

PubMed Central

Laspiur, Juliana Pérez; Anderson, Eric R.; Ciborowski, Pawel; Wojna, Valerie; Rozek, Wojciech; Duan, Fenghai; Mayo, Raul; Rodríguez, Elaine; Plaud-Valentín, Marinés; Rodríguez-Orengo, José; Gendelman, Howard E.; Meléndez, Loyda M.

2008-01-01

Cognitive impairment remains a major complication of advanced human immunodeficiency virus (HIV) infection despite the wide spread use of anti-retroviral therapy. Diagnosis is made by exclusion making biomarkers of great potential use. Thus, we used an integrated proteomics platform to assess cerebrospinal fluid protein profiles from 50 HIV-1 seropositive Hispanic women. Nine of 38 proteins identified were unique in those patients with cognitive impairment. These proteins were linked to cell signaling, structural function, and antioxidant activities. This work highlights, in a preliminary manner, the utility of proteomic profiling for biomarker discovery for HIV-1 associated cognitive dysfunction. PMID:17950469

The application of proteomics in different aspects of hepatocellular carcinoma research.

PubMed

Xing, Xiaohua; Liang, Dong; Huang, Yao; Zeng, Yongyi; Han, Xiao; Liu, Xiaolong; Liu, Jingfeng

2016-08-11

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, which is causing the second leading cancer-related death worldwide. With the significant advances of high-throughput protein analysis techniques, the proteomics offered an extremely useful and versatile analytical platform for biomedical researches. In recent years, different proteomic strategies have been widely applied in the various aspects of HCC studies, ranging from screening the early diagnostic and prognostic biomarkers to in-depth investigating the underlying molecular mechanisms. In this review, we would like to systematically summarize the current applications of proteomics in hepatocellular carcinoma study, and discuss the challenges of applying proteomics in study clinical samples, as well as discuss the possible application of proteomics in precision medicine. In this review, we have systematically summarized the current applications of proteomics in hepatocellular carcinoma study, ranging from screening biomarkers to in-depth investigating the underlying molecular mechanisms. In addition, we have discussed the challenges of applying proteomics in study clinical samples, as well as the possible applications of proteomics in precision medicine. We believe that this review would help readers to be better familiar with the recent progresses of clinical proteomics, especially in the field of hepatocellular carcinoma research. Copyright © 2016 Elsevier B.V. All rights reserved.

Translational plant proteomics: a perspective.

PubMed

Agrawal, Ganesh Kumar; Pedreschi, Romina; Barkla, Bronwyn J; Bindschedler, Laurence Veronique; Cramer, Rainer; Sarkar, Abhijit; Renaut, Jenny; Job, Dominique; Rakwal, Randeep

2012-08-03

Translational proteomics is an emerging sub-discipline of the proteomics field in the biological sciences. Translational plant proteomics aims to integrate knowledge from basic sciences to translate it into field applications to solve issues related but not limited to the recreational and economic values of plants, food security and safety, and energy sustainability. In this review, we highlight the substantial progress reached in plant proteomics during the past decade which has paved the way for translational plant proteomics. Increasing proteomics knowledge in plants is not limited to model and non-model plants, proteogenomics, crop improvement, and food analysis, safety, and nutrition but to many more potential applications. Given the wealth of information generated and to some extent applied, there is the need for more efficient and broader channels to freely disseminate the information to the scientific community. This article is part of a Special Issue entitled: Translational Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed

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

2018-05-02

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

The Role of Clinical Proteomics, Lipidomics, and Genomics in the Diagnosis of Alzheimer's Disease.

PubMed

Martins, Ian James

2016-03-31

The early diagnosis of Alzheimer's disease (AD) has become important to the reversal and treatment of neurodegeneration, which may be relevant to premature brain aging that is associated with chronic disease progression. Clinical proteomics allows the detection of various proteins in fluids such as the urine, plasma, and cerebrospinal fluid for the diagnosis of AD. Interest in lipidomics has accelerated with plasma testing for various lipid biomarkers that may with clinical proteomics provide a more reproducible diagnosis for early brain aging that is connected to other chronic diseases. The combination of proteomics with lipidomics may decrease the biological variability between studies and provide reproducible results that detect a community's susceptibility to AD. The diagnosis of chronic disease associated with AD that now involves genomics may provide increased sensitivity to avoid inadvertent errors related to plasma versus cerebrospinal fluid testing by proteomics and lipidomics that identify new disease biomarkers in body fluids, cells, and tissues. The diagnosis of AD by various plasma biomarkers with clinical proteomics may now require the involvement of lipidomics and genomics to provide interpretation of proteomic results from various laboratories around the world.

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

PubMed

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

2016-01-04

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

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

PubMed

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

2013-01-01

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

Application of Proteomic Approaches to Accelerate Drug Development for Psychiatric Disorders.

PubMed

Rahmoune, Hassan; Martins-de-Souza, Daniel; Guest, Paul C

2017-01-01

Proteomic-based biomarkers are now an integral part of the drug development process. This chapter covers the role of proteomic biomarker tests as useful tools for improving preclinical research and clinical development. One medical area that has been lagging behind this process is the study of psychiatric disorders, and this is most likely due to the complexity of these diseases. The potential of incorporating biomarkers in the clinical pipeline to improve decision-making, accelerate drug development, improve translation and reduce development costs is also discussed, with a focus on psychiatric diseases like schizophrenia. This chapter will also discuss the next steps that must be taken to keep moving this process forwards.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

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

PubMed

Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-10-01

The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

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

Consolidation of proteomics data in the Cancer Proteomics database.

PubMed

Arntzen, Magnus Ø; Boddie, Paul; Frick, Rahel; Koehler, Christian J; Thiede, Bernd

2015-11-01

Cancer is a class of diseases characterized by abnormal cell growth and one of the major reasons for human deaths. Proteins are involved in the molecular mechanisms leading to cancer, furthermore they are affected by anti-cancer drugs, and protein biomarkers can be used to diagnose certain cancer types. Therefore, it is important to explore the proteomics background of cancer. In this report, we developed the Cancer Proteomics database to re-interrogate published proteome studies investigating cancer. The database is divided in three sections related to cancer processes, cancer types, and anti-cancer drugs. Currently, the Cancer Proteomics database contains 9778 entries of 4118 proteins extracted from 143 scientific articles covering all three sections: cell death (cancer process), prostate cancer (cancer type) and platinum-based anti-cancer drugs including carboplatin, cisplatin, and oxaliplatin (anti-cancer drugs). The detailed information extracted from the literature includes basic information about the articles (e.g., PubMed ID, authors, journal name, publication year), information about the samples (type, study/reference, prognosis factor), and the proteomics workflow (Subcellular fractionation, protein, and peptide separation, mass spectrometry, quantification). Useful annotations such as hyperlinks to UniProt and PubMed were included. In addition, many filtering options were established as well as export functions. The database is freely available at http://cancerproteomics.uio.no. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Proteome analysis for identification of tumor-associated biomarkers in breast cancer].

PubMed

Wang, Xi; Liang, Wei-Jiang; Zhu, Zhen-Yu; Yang, Ming-Tian; Zeng, Yi-Xin

2004-11-01

Pre-symptomatic screening of early-stage breast cancer may greatly reduce tumor-related mortality. Some tumor markers, such as CA15-3 and CA27-29, are recommended only for monitoring therapy of advanced or relapsed breast cancer. This study was to find new biomarkers that could be used individually or in combination with an existing modality for cost-effective screening of breast cancer by proteome analysis. Protein expression differences among 128 serum samples of 64 breast cancer patients (19 of stage I, 24 of stage II, and 21 of stage III), 52 patients with benign breast diseases, and 12 healthy women were analyzed with IMAC3 and WCX2 Ciphergen ProteinChip Arrays. On WCX2 chip, a panel of 5 proteins (9 116, 8 905, 8 749, 9 470, and 9 692 Da) was selected based on their collective contribution to the optimal separation between breast cancer patients and both non-cancer patients and healthy women, and expression of another 2 proteins (9 405 and 6 424 Da) was different between patients with breast cancer of stage I and stage III. On IMAC3 chip, a panel of 9 proteins (5 236, 7 823, 7 464, 5 213, 5 334, 5 064, 5 374, 7 756, and 7 623 Da) was selected based on their collective contribution to the optimal separation between breast cancer patients and both non-cancer patients and healthy women, and expression of another 3 proteins (7 922, 4 641, and 5 910 Da) was different between patients with breast cancer of stage I and stage III. Protein expression in breast cancer patients is different from that in both non-cancer patients and healthy women, and those proteins with different expression may be used as new biomarkers in breast cancer.

Comparative proteomics lends insight into genotype-specific pathogenicity.

PubMed

Guarnieri, Michael T

2013-09-01

Comparative proteomic analyses have emerged as a powerful tool for the identification of unique biomarkers and mechanisms of pathogenesis. In this issue of Proteomics, Murugaiyan et al. utilize difference gel electrophoresis (DIGE) to examine differential protein expression between nonpathogenic and pathogenic genotypes of Prototheca zopfii, a causative agent in bovine enteritis and mastitis. Their findings provide insights into molecular mechanisms of infection and evolutionary adaptation of pathogenic genotypes, demonstrating the power of comparative proteomic analyses. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Embryology in the era of proteomics.

PubMed

Katz-Jaffe, Mandy G; McReynolds, Susanna

2013-03-15

Proteomic technologies have begun providing evidence that viable embryos possess unique protein profiles. Some of these potential protein biomarkers have been identified as extracellular and could be used in the development of a noninvasive quantitative method for embryo assessment. The field of assisted reproductive technologies would benefit from defining the human embryonic proteome and secretome, thereby expanding our current knowledge of embryonic cellular processes. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes.

PubMed

Wen, Li; Liu, Ye-Fang; Jiang, Cen; Zeng, Shao-Qian; Su, Yue; Wu, Wen-Jun; Liu, Xi-Yang; Wang, Jian; Liu, Ying; Su, Chen; Li, Bai-Xue; Feng, Quan-Sheng

2018-03-08

Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.

Proteomics of ovarian cancer: functional insights and clinical applications

DOE PAGES

Elzek, Mohamed A.; Rodland, Karin D.

2015-03-04

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification ofmore » aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics’ contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. In conclusion, we propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.« less

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

PubMed

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

2017-06-01

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

Proteomic analysis of first trimester maternal serum to identify candidate biomarkers potentially predictive of spontaneous preterm birth.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2018-04-30

Spontaneous preterm birth (sPTB) remains a major clinical dilemma; current diagnostics and interventions have not reduced the rate of this serious healthcare burden. This study characterizes differential protein profiles and post-translational modifications (PTMs) in first trimester maternal serum using a refined top-down approach coupling two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) to directly compare subsequent term and preterm labour events and identify marked protein differences. 30 proteoforms were found to be significantly increased or decreased in the sPTB group including 9 phosphoproteins and 11 glycoproteins. Changes occurred in proteins associated with immune and defence responses. We identified protein species that are associated with several clinically relevant biological processes, including interrelated biological networks linked to regulation of the complement cascade and coagulation pathways, immune modulation, metabolic processes and cell signalling. The finding of altered proteoforms in maternal serum from pregnancies that delivered preterm suggests these as potential early biomarkers of sPTB and also possible mediators of the disorder. Identifying changes in protein profiles is critical in the study of cell biology, and disease treatment and prevention. Identifying consistent changes in the maternal serum proteome during early pregnancy, including specific protein PTMs (e.g. phosphorylation, glycosylation), is likely to provide better opportunities for prediction, intervention and prevention of preterm birth. This is the first study to examine first trimester maternal serum using a highly refined top-down proteomic analytical approach based on high resolution 2DE coupled with mass spectrometry to directly compare preterm (<37 weeks) and preterm (≥37 weeks) events and identify select protein differences between these conditions. As such, the data present a promising avenue for translation of biomarker discovery to a

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

PubMed

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

2015-10-01

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

Characterization of the rat cerebrospinal fluid proteome following acute cerebral ischemia using an aptamer-based proteomic technology.

PubMed

Simats, Alba; García-Berrocoso, Teresa; Ramiro, Laura; Giralt, Dolors; Gill, Natalia; Penalba, Anna; Bustamante, Alejandro; Rosell, Anna; Montaner, Joan

2018-05-21

The limited accessibility to the brain has turned the cerebrospinal fluid (CSF) into a valuable source that may contribute to the complete understanding of the stroke pathophysiology. Here we have described the CSF proteome in the hyper-acute phase of cerebral ischemia by performing an aptamer-based proteomic assay (SOMAscan) in CSF samples collected before and 30 min after male Wistar rats had undergone a 90 min Middle Cerebral Artery Occlusion (MCAO) or sham-surgery. Proteomic results indicated that cerebral ischemia acutely increased the CSF levels of 716 proteins, mostly overrepresented in leukocyte chemotaxis and neuronal death processes. Seven promising candidates were further evaluated in rat plasma and brain (CKB, CaMK2A, CaMK2B, CaMK2D, PDXP, AREG, CMPK). The 3 CaMK2 family-members and CMPK early decreased in the infarcted brain area and, together with AREG, co-localized with neurons. Conversely, CKB levels remained consistent after the insult and specifically matched with astrocytes. Further exploration of these candidates in human plasma revealed the potential of CKB and CMPK to diagnose stroke, while CaMK2B and CMPK resulted feasible biomarkers of functional stroke outcome. Our findings provided insights into the CSF proteome following cerebral ischemia and identified new outstanding proteins that might be further considered as potential biomarkers of stroke.

A comparative proteomic analysis of bile for biomarkers of cholangiocarcinoma.

PubMed

Laohaviroj, Marut; Potriquet, Jeremy; Jia, Xinying; Suttiprapa, Sutas; Chamgramol, Yaovalux; Pairojkul, Chawalit; Sithithaworn, Paiboon; Mulvenna, Jason; Sripa, Banchob

2017-06-01

Cholangiocarcinoma is a primary malignant tumor of the bile duct epithelium. Cholangiocarcinoma is usually detected at an advanced stage when successful treatment is no longer possible. As the tumor originates from the bile duct epithelium, bile is an ideal source of tumor biomarkers for cholangiocarcinoma. In this study, we used a quantitative proteomics approach to identify potential tumor-associated proteins in the bile fluid of six cholangiocarcinoma patients. Three different gross-appearance tumor types were used in the analysis: mass-forming type ( n = 2), periductal infiltrating type ( n = 2), and intraductal growth type ( n = 2). Two bile samples from non-cancerous patients were used as controls. Isobaric labeling, coupled with Tandem mass spectrometry, was used to quantify protein levels in the bile of cholangiocarcinoma and control patients. In all, 63 proteins were significantly increased in cholangiocarcinoma bile compared to normal bile. Alpha-1-antitrypsin was one of the overexpressed proteins that increased in cholangiocarcinoma bile samples. Immunohistochemical analysis revealed that alpha-1-antitrypsin was detected in 177 (50%) of 354 cholangiocarcinoma tissues from our Tissue Bank. Immunoblotting of 54 cholangiocarcinoma bile samples showed that alpha-1-antitrypsin was positive in 38 (70%) samples. Fecal enzyme-linked immunosorbent assay showed that alpha-1-antitrypsin level was able to distinguish cholangiocarcinoma patients from normal individuals. In conclusion, alpha-1-antitrypsin is a potential marker for early diagnosis of cholangiocarcinoma.

Affordable proteomics: the two-hybrid systems.

PubMed

Gillespie, Marc

2003-06-01

Numerous proteomic methodologies exist, but most require a heavy investment in expertise and technology. This puts these approaches out of reach for many laboratories and small companies, rarely allowing proteomics to be used as a pilot approach for biomarker or target identification. Two proteomic approaches, 2D gel electrophoresis and the two-hybrid systems, are currently available to most researchers. The two-hybrid systems, though accommodating to large-scale experiments, were originally designed as practical screens, that by comparison to current proteomics tools were small-scale, affordable and technically feasible. The screens rapidly generated data, identifying protein interactions that were previously uncharacterized. The foundation for a two-hybrid proteomic investigation can be purchased as separate kits from a number of companies. The true power of the technique lies not in its affordability, but rather in its portability. The two-hybrid system puts proteomics back into laboratories where the output of the screens can be evaluated by researchers with experience in the particular fields of basic research, cancer biology, toxicology or drug development.

Biomarkers of systemic inflammation in farmers with musculoskeletal disorders; a plasma proteomic study.

PubMed

Ghafouri, Bijar; Carlsson, Anders; Holmberg, Sara; Thelin, Anders; Tagesson, Christer

2016-05-10

Farmers have an increased risk for musculoskeletal disorders (MSD) such as osteoarthritis of the hip, low back pain, and neck and upper limb complaints. The underlying mechanisms are not fully understood. Work-related exposures and inflammatory responses might be involved. Our objective was to identify plasma proteins that differentiated farmers with MSD from rural referents. Plasma samples from 13 farmers with MSD and rural referents were included in the investigation. Gel based proteomics was used for protein analysis and proteins that differed significantly between the groups were identified by mass spectrometry. In total, 15 proteins differed significantly between the groups. The levels of leucine-rich alpha-2-glycoprotein, haptoglobin, complement factor B, serotransferrin, one isoform of kininogen, one isoform of alpha-1-antitrypsin, and two isoforms of hemopexin were higher in farmers with MSD than in referents. On the other hand, the levels of alpha-2-HS-glycoprotein, alpha-1B-glycoprotein, vitamin D- binding protein, apolipoprotein A1, antithrombin, one isoform of kininogen, and one isoform of alpha-1-antitrypsin were lower in farmers than in referents. Many of the identified proteins are known to be involved in inflammation. Farmers with MSD had altered plasma levels of protein biomarkers compared to the referents, indicating that farmers with MSD may be subject to a more systemic inflammation. It is possible that the identified differences of proteins may give clues to the biochemical changes occurring during the development and progression of MSD in farmers, and that one or several of these protein biomarkers might eventually be used to identify and prevent work-related MSD.

A decade of plant proteomics and mass spectrometry: translation of technical advancements to food security and safety issues.

PubMed

Agrawal, Ganesh Kumar; Sarkar, Abhijit; Righetti, Pier Giorgio; Pedreschi, Romina; Carpentier, Sebastien; Wang, Tai; Barkla, Bronwyn J; Kohli, Ajay; Ndimba, Bongani Kaiser; Bykova, Natalia V; Rampitsch, Christof; Zolla, Lello; Rafudeen, Mohamed Suhail; Cramer, Rainer; Bindschedler, Laurence Veronique; Tsakirpaloglou, Nikolaos; Ndimba, Roya Janeen; Farrant, Jill M; Renaut, Jenny; Job, Dominique; Kikuchi, Shoshi; Rakwal, Randeep

2013-01-01

Tremendous progress in plant proteomics driven by mass spectrometry (MS) techniques has been made since 2000 when few proteomics reports were published and plant proteomics was in its infancy. These achievements include the refinement of existing techniques and the search for new techniques to address food security, safety, and health issues. It is projected that in 2050, the world's population will reach 9-12 billion people demanding a food production increase of 34-70% (FAO, 2009) from today's food production. Provision of food in a sustainable and environmentally committed manner for such a demand without threatening natural resources, requires that agricultural production increases significantly and that postharvest handling and food manufacturing systems become more efficient requiring lower energy expenditure, a decrease in postharvest losses, less waste generation and food with longer shelf life. There is also a need to look for alternative protein sources to animal based (i.e., plant based) to be able to fulfill the increase in protein demands by 2050. Thus, plant biology has a critical role to play as a science capable of addressing such challenges. In this review, we discuss proteomics especially MS, as a platform, being utilized in plant biology research for the past 10 years having the potential to expedite the process of understanding plant biology for human benefits. The increasing application of proteomics technologies in food security, analysis, and safety is emphasized in this review. But, we are aware that no unique approach/technology is capable to address the global food issues. Proteomics-generated information/resources must be integrated and correlated with other omics-based approaches, information, and conventional programs to ensure sufficient food and resources for human development now and in the future. © 2013 Wiley Periodicals, Inc.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

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

2016-10-18

The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

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.

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.

Development of a Targeted Urine Proteome Assay for kidney diseases.

PubMed

Cantley, Lloyd G; Colangelo, Christopher M; Stone, Kathryn L; Chung, Lisa; Belcher, Justin; Abbott, Thomas; Cantley, Jennifer L; Williams, Kenneth R; Parikh, Chirag R

2016-01-01

Since human urine is the most readily available biofluid whose proteome changes in response to disease, it is a logical sample for identifying protein biomarkers for kidney diseases. Potential biomarkers were identified by using a multiproteomics workflow to compare urine proteomes of kidney transplant patients with immediate and delayed graft function. Differentially expressed proteins were identified, and corresponding stable isotope labeled internal peptide standards were synthesized for scheduled MRM. The Targeted Urine Proteome Assay (TUPA) was then developed by identifying those peptides for which there were at least two transitions for which interference in a urine matrix across 156 MRM runs was <30%. This resulted in an assay that monitors 224 peptides from 167 quantifiable proteins. TUPA opens the way for using a robust mass spectrometric technology, MRM, for quantifying and validating biomarkers from among 167 urinary proteins. This approach, while developed using differentially expressed urinary proteins from patients with delayed versus immediate graft function after kidney transplant, can be expanded to include differentially expressed urinary proteins in multiple kidney diseases. Thus, TUPA could provide a single assay to help diagnose, prognose, and manage many kidney diseases. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comprehensive proteomic analysis of bovine spermatozoa of varying fertility rates and identification of biomarkers associated with fertility.

PubMed

Peddinti, Divyaswetha; Nanduri, Bindu; Kaya, Abdullah; Feugang, Jean M; Burgess, Shane C; Memili, Erdogan

2008-02-22

Male infertility is a major problem for mammalian reproduction. However, molecular details including the underlying mechanisms of male fertility are still not known. A thorough understanding of these mechanisms is essential for obtaining consistently high reproductive efficiency and to ensure lower cost and time-loss by breeder. Using high and low fertility bull spermatozoa, here we employed differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT) and identified 125 putative biomarkers of fertility. We next used quantitative Systems Biology modeling and canonical protein interaction pathways and networks to show that high fertility spermatozoa differ from low fertility spermatozoa in four main ways. Compared to sperm from low fertility bulls, sperm from high fertility bulls have higher expression of proteins involved in: energy metabolism, cell communication, spermatogenesis, and cell motility. Our data also suggests a hypothesis that low fertility sperm DNA integrity may be compromised because cell cycle: G2/M DNA damage checkpoint regulation was most significant signaling pathway identified in low fertility spermatozoa. This is the first comprehensive description of the bovine spermatozoa proteome. Comparative proteomic analysis of high fertility and low fertility bulls, in the context of protein interaction networks identified putative molecular markers associated with high fertility phenotype.

Comprehensive proteomic analysis of bovine spermatozoa of varying fertility rates and identification of biomarkers associated with fertility

PubMed Central

Peddinti, Divyaswetha; Nanduri, Bindu; Kaya, Abdullah; Feugang, Jean M; Burgess, Shane C; Memili, Erdogan

2008-01-01

Background Male infertility is a major problem for mammalian reproduction. However, molecular details including the underlying mechanisms of male fertility are still not known. A thorough understanding of these mechanisms is essential for obtaining consistently high reproductive efficiency and to ensure lower cost and time-loss by breeder. Results Using high and low fertility bull spermatozoa, here we employed differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT) and identified 125 putative biomarkers of fertility. We next used quantitative Systems Biology modeling and canonical protein interaction pathways and networks to show that high fertility spermatozoa differ from low fertility spermatozoa in four main ways. Compared to sperm from low fertility bulls, sperm from high fertility bulls have higher expression of proteins involved in: energy metabolism, cell communication, spermatogenesis, and cell motility. Our data also suggests a hypothesis that low fertility sperm DNA integrity may be compromised because cell cycle: G2/M DNA damage checkpoint regulation was most significant signaling pathway identified in low fertility spermatozoa. Conclusion This is the first comprehensive description of the bovine spermatozoa proteome. Comparative proteomic analysis of high fertility and low fertility bulls, in the context of protein interaction networks identified putative molecular markers associated with high fertility phenotype. PMID:18294385

Characterization of Foodborne Strains of Staphylococcus aureus by Shotgun Proteomics: Functional Networks, Virulence Factors and Species-Specific Peptide Biomarkers

PubMed Central

Carrera, Mónica; Böhme, Karola; Gallardo, José M.; Barros-Velázquez, Jorge; Cañas, Benito; Calo-Mata, Pilar

2017-01-01

In the present work, we applied a shotgun proteomics approach for the fast and easy characterization of 20 different foodborne strains of Staphylococcus aureus (S. aureus), one of the most recognized foodborne pathogenic bacteria. A total of 644 non-redundant proteins were identified and analyzed via an easy and rapid protein sample preparation procedure. The results allowed the differentiation of several proteome datasets from the different strains (common, accessory, and unique datasets), which were used to determine relevant functional pathways and differentiate the strains into different Euclidean hierarchical clusters. Moreover, a predicted protein-protein interaction network of the foodborne S. aureus strains was created. The whole confidence network contains 77 nodes and 769 interactions. Most of the identified proteins were surface-associated proteins that were related to pathways and networks of energy, lipid metabolism and virulence. Twenty-seven virulence factors were identified, and most of them corresponded to autolysins, N-acetylmuramoyl-L-alanine amidases, phenol-soluble modulins, extracellular fibrinogen-binding proteins and virulence factor EsxA. Potential species-specific peptide biomarkers were screened. Twenty-one species-specific peptide biomarkers, belonging to eight different proteins (nickel-ABC transporter, N-acetylmuramoyl-L-alanine amidase, autolysin, clumping factor A, gram-positive signal peptide YSIRK, cysteine protease/staphopain, transcriptional regulator MarR, and transcriptional regulator Sar-A), were proposed to identify S. aureus. These results constitute the first major dataset of peptides and proteins of foodborne S. aureus strains. This repository may be useful for further studies, for the development of new therapeutic treatments for S. aureus food intoxications and for microbial source-tracking in foodstuffs. PMID:29312172

Keratin 17 in premalignant and malignant squamous lesions of the cervix: proteomic discovery and immunohistochemical validation as a diagnostic and prognostic biomarker

PubMed Central

Escobar-Hoyos, Luisa F; Yang, Jie; Zhu, Jiawen; Cavallo, Julie-Ann; Zhai, Haiyan; Burke, Stephanie; Koller, Antonius; Chen, Emily I; Shroyer, Kenneth R

2014-01-01

Most previously described immunohistochemical markers of cervical high-grade squamous intraepithelial lesion (HSIL) and squamous cell carcinoma may help to improve diagnostic accuracy but have a minimal prognostic value. The goals of the current study were to identify and validate novel candidate biomarkers that could potentially improve diagnostic and prognostic accuracy for cervical HSIL and squamous cell carcinoma. Microdissected tissue sections from formalin-fixed paraffin-embedded normal ectocervical squamous mucosa, low-grade squamous intraepithelial lesion (LSIL), HSIL and squamous cell carcinoma sections were analyzed by mass spectrometry-based shotgun proteomics for biomarker discovery. The diagnostic specificity of candidate biomarkers was subsequently evaluated by immunohistochemical analysis of tissue microarrays. Among 1750 proteins identified by proteomic analyses, keratin 4 (KRT4) and keratin 17 (KRT17) showed reciprocal patterns of expression in the spectrum of cases ranging from normal ectocervical squamous mucosa to squamous cell carcinoma. Immunohistochemical studies confirmed that KRT4 expression was significantly decreased in squamous cell carcinoma compared with the other diagnostic categories. By contrast, KRT17 expression was significantly increased in HSIL and squamous cell carcinoma compared with normal ectocervical squamous mucosa and LSIL. KRT17 was also highly expressed in immature squamous metaplasia and in endocervical reserve cells but was generally not detected in mature squamous metaplasia. Furthermore, high levels of KRT17 expression were significantly associated with poor survival of squamous cell carcinoma patients (Hazard ratio = 14.76, P = 0.01). In summary, both KRT4 and KRT17 expressions are related to the histopathology of the cervical squamous mucosa; KRT17 is highly overexpressed in immature squamous metaplasia, in HSIL, and in squamous cell carcinoma and the level of KRT17 in squamous cell carcinoma may help to identify

Statistical Analysis of Variation in the Human Plasma Proteome

DOE PAGES

Corzett, Todd H.; Fodor, Imola K.; Choi, Megan W.; ...

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where onemore » human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.« less

Statistical analysis of variation in the human plasma proteome.

PubMed

Corzett, Todd H; Fodor, Imola K; Choi, Megan W; Walsworth, Vicki L; Turteltaub, Kenneth W; McCutchen-Maloney, Sandra L; Chromy, Brett A

2010-01-01

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.

PubMed

Ellis, Matthew J; Gillette, Michael; Carr, Steven A; Paulovich, Amanda G; Smith, Richard D; Rodland, Karin K; Townsend, R Reid; Kinsinger, Christopher; Mesri, Mehdi; Rodriguez, Henry; Liebler, Daniel C

2013-10-01

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium is applying the latest generation of proteomic technologies to genomically annotated tumors from The Cancer Genome Atlas (TCGA) program, a joint initiative of the NCI and the National Human Genome Research Institute. By providing a fully integrated accounting of DNA, RNA, and protein abnormalities in individual tumors, these datasets will illuminate the complex relationship between genomic abnormalities and cancer phenotypes, thus producing biologic insights as well as a wave of novel candidate biomarkers and therapeutic targets amenable to verification using targeted mass spectrometry methods. ©2013 AACR.

Biomarkers in prostate cancer: what’s new?

PubMed Central

Sartori, David A.; Chan, Daniel W.

2014-01-01

Purpose of review This review is intended to provide an overview of the current state of biomarkers for prostate cancer (PCa), with a focus on biomarkers approved by the US Food and Drug Administration (FDA) as well as biomarkers available from Clinical Laboratory Improvement Amendment (CLIA)-certified clinical laboratories within the last 1–2 years. Recent findings During the past 2 years, two biomarkers have been approved by the US FDA. These include proPSA as part of the Prostate Health Index (phi) by Beckman Coulter, Inc and PCA3 as Progensa by Gen Probe, Inc. With the advances in genomic and proteomic technologies, several new CLIA-based laboratory-developed tests have become available. Examples are Oncotype DX from Genomics Health, Inc, and Prolaris from Myriad Genetics, Inc. In most cases, these new tests are based on a combination of multiple genomic or proteomic biomarkers. Summary Several new tests, as discussed in this review, have become available during the last 2 years. Although the intended use of most of these tests is to distinguish PCa from benign prostatic conditions with better sensitivity and specificity than prostate-specific antigen, studies have shown that some of them may also be useful in the differentiation of aggressive from nonaggressive forms of PCa. PMID:24626128

Tear film proteome in age-related macular degeneration.

PubMed

Winiarczyk, Mateusz; Kaarniranta, Kai; Winiarczyk, Stanisław; Adaszek, Łukasz; Winiarczyk, Dagmara; Mackiewicz, Jerzy

2018-06-01

Age-related macular degeneration (AMD) is the main reason for blindness in elderly people in the developed countries. Current screening protocols have limitations in detecting the early signs of retinal degeneration. Therefore, it would be desirable to find novel biomarkers for early detection of AMD. Development of novel biomarkers would help in the prevention, diagnostics, and treatment of AMD. Proteomic analysis of tear film has shown promise in this research area. If an optimal set of biomarkers could be obtained from accessible body fluids, it would represent a reliable way to monitor disease progression and response to novel therapies. Tear films were collected on Schirmer strips from a total of 22 patients (8 with wet AMD, 6 with dry AMD, and 8 control individuals). 2D electrophoresis was used to separate tear film proteins prior to their identification with matrix-assisted laser desorption/ionization time of flight spectrometer (MALDI-TOF/TOF) and matching with functional databases. A total of 342 proteins were identified. Most of them were previously described in various proteomic studies concerning AMD. Shootin-1, histatin-3, fidgetin-like protein 1, SRC kinase signaling inhibitor, Graves disease carrier protein, actin cytoplasmic 1, prolactin-inducible protein 1, and protein S100-A7A were upregulated in the tear film samples isolated from AMD patients and were not previously linked with this disease in any proteomic analysis. The upregulated proteins supplement our current knowledge of AMD pathogenesis, providing evidence that certain specific proteins are expressed into the tear film in AMD. As far we are aware, this is the first study to have undertaken a comprehensive in-depth analysis of the human tear film proteome in AMD patients.

Proteomics in investigation of cancer metastasis: functional and clinical consequences and methodological challenges.

PubMed

Maryáš, Josef; Faktor, Jakub; Dvořáková, Monika; Struhárová, Iva; Grell, Peter; Bouchal, Pavel

2014-03-01

Metastases are responsible for most of the cases of death in patients with solid tumors. There is thus an urgent clinical need of better understanding the exact molecular mechanisms and finding novel therapeutics targets and biomarkers of metastatic disease of various tumors. Metastases are formed in a complicated biological process called metastatic cascade. Up to now, proteomics has enabled the identification of number of metastasis-associated proteins and potential biomarkers in cancer tissues, microdissected cells, model systems, and secretomes. Expression profiles and biological role of key proteins were confirmed in verification and functional experiments. This communication reviews these observations and analyses the methodological aspects of the proteomics approaches used. Moreover, it reviews contribution of current proteomics in the field of functional characterization and interactome analysis of proteins involved in various events in metastatic cascade. It is evident that ongoing technical progress will further increase proteome coverage and sample capacity of proteomics technologies, giving complex answers to clinical and functional questions asked. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomarkers in rheumatic diseases: how can they facilitate diagnosis and assessment of disease activity?

PubMed

Mohan, Chandra; Assassi, Shervin

2015-11-26

Serological and proteomic biomarkers can help clinicians diagnose rheumatic diseases earlier and assess disease activity more accurately. These markers have been incorporated into the recently revised classification criteria of several diseases to enable early diagnosis and timely initiation of treatment. Furthermore, they also facilitate more accurate subclassification and more focused monitoring for the detection of certain disease manifestations, such as lung and renal involvement. These biomarkers can also make the assessment of disease activity and treatment response more reliable. Simultaneously, several new serological and proteomic biomarkers have become available in the routine clinical setting--for example, a protein biomarker panel for rheumatoid arthritis and a myositis antibody panel for dermatomyositis and polymyositis. This review will focus on commercially available antibody and proteomic biomarkers in rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis (scleroderma), dermatomyositis and polymyositis, and axial spondyloarthritis (including ankylosing spondylitis). It will discuss how these markers can facilitate early diagnosis as well as more accurate subclassification and assessment of disease activity in the clinical setting. The ultimate goal of current and future biomarkers in rheumatic diseases is to enable early detection of these diseases and their clinical manifestations, and to provide effective monitoring and treatment regimens that are tailored to each patient's needs and prognosis. © BMJ Publishing Group Ltd 2015.

Differential proteomics of human seminal plasma: A potential target for searching male infertility marker proteins.

PubMed

Tomar, Anil Kumar; Sooch, Balwinder Singh; Singh, Sarman; Yadav, Savita

2012-04-01

The clinical fertility tests, available in the market, fail to define the exact cause of male infertility in almost half of the cases and point toward a crucial need of developing better ways of infertility investigations. The protein biomarkers may help us toward better understanding of unknown cases of male infertility that, in turn, can guide us to find better therapeutic solutions. Many clinical attempts have been made to identify biomarkers of male infertility in sperm proteome but only few studies have targeted seminal plasma. Human seminal plasma is a rich source of proteins that are essentially required for development of sperm and successful fertilization. This viewpoint article highlights the importance of human seminal plasma proteome in reproductive physiology and suggests that differential proteomics integrated with functional analysis may help us in searching potential biomarkers of male infertility. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Affinity Proteomics in the mountains: Alpbach 2015.

PubMed

Taussig, Michael J

2016-09-25

The 2015 Alpbach Workshop on Affinity Proteomics, organised by the EU AFFINOMICS consortium, was the 7th workshop in this series. As in previous years, the focus of the event was the current state of affinity methods for proteome analysis, including complementarity with mass spectrometry, progress in recombinant binder production methods, alternatives to classical antibodies as affinity reagents, analysis of proteome targets, industry focus on biomarkers, and diagnostic and clinical applications. The combination of excellent science with Austrian mountain scenery and winter sports engender an atmosphere that makes this series of workshops exceptional. The articles in this Special Issue represent a cross-section of the presentations at the 2015 meeting. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolomics, Nutrition, and Potential Biomarkers of Food Quality, Intake, and Health Status.

PubMed

Sébédio, Jean-Louis

Diet, dietary patterns, and other environmental factors such as exposure to toxins are playing an important role in the prevention/development of many diseases, like obesity, type 2 diabetes, and consequently on the health status of individuals. A major challenge nowadays is to identify novel biomarkers to detect as early as possible metabolic dysfunction and to predict evolution of health status in order to refine nutritional advices to specific population groups. Omics technologies such as genomics, transcriptomics, proteomics, and metabolomics coupled with statistical and bioinformatics tools have already shown great potential in this research field even if so far only few biomarkers have been validated. For the past two decades, important analytical techniques have been developed to detect as many metabolites as possible in human biofluids such as urine, blood, and saliva. In the field of food science and nutrition, many studies have been carried out for food authenticity, quality, and safety, as well as for food processing. Furthermore, metabolomic investigations have been carried out to discover new early biomarkers of metabolic dysfunction and predictive biomarkers of developing pathologies (obesity, metabolic syndrome, type-2 diabetes, etc.). Great emphasis is also placed in the development of methodologies to identify and validate biomarkers of nutrients exposure. © 2017 Elsevier Inc. All rights reserved.

Biomarkers in localized prostate cancer

PubMed Central

Ferro, Matteo; Buonerba, Carlo; Terracciano, Daniela; Lucarelli, Giuseppe; Cosimato, Vincenzo; Bottero, Danilo; Deliu, Victor M; Ditonno, Pasquale; Perdonà, Sisto; Autorino, Riccardo; Coman, Ioman; De Placido, Sabino; Di Lorenzo, Giuseppe; De Cobelli, Ottavio

2016-01-01

Biomarkers can improve prostate cancer diagnosis and treatment. Accuracy of prostate-specific antigen (PSA) for early diagnosis of prostate cancer is not satisfactory, as it is an organ- but not cancer-specific biomarker, and it can be improved by using models that incorporate PSA along with other test results, such as prostate cancer antigen 3, the molecular forms of PSA (proPSA, benign PSA and intact PSA), as well as kallikreins. Recent reports suggest that new tools may be provided by metabolomic studies as shown by preliminary data on sarcosine. Additional molecular biomarkers have been identified by the use of genomics, proteomics and metabolomics. We review the most relevant biomarkers for early diagnosis and management of localized prostate cancer. PMID:26768791

Urinary Biomarkers of Brain Diseases

PubMed Central

An, Manxia; Gao, Youhe

2016-01-01

Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome. PMID:26751805

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.

PubMed

Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan; Chen, Emily I

2016-11-01

Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulkarni, Shilpa; Koller, Antonius; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24more » and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially

Nonclinical safety biomarkers of drug-induced vascular injury: current status and blueprint for the future.

PubMed

Mikaelian, Igor; Cameron, Mark; Dalmas, Deidre A; Enerson, Bradley E; Gonzalez, Raymond J; Guionaud, Silvia; Hoffmann, Peter K; King, Nicholas M P; Lawton, Michael P; Scicchitano, Marshall S; Smith, Holly W; Thomas, Roberta A; Weaver, James L; Zabka, Tanja S

2014-06-01

Better biomarkers are needed to identify, characterize, and/or monitor drug-induced vascular injury (DIVI) in nonclinical species and patients. The Predictive Safety Testing Consortium (PSTC), a precompetitive collaboration of pharmaceutical companies and the U.S. Food and Drug Administration (FDA), formed the Vascular Injury Working Group (VIWG) to develop and qualify translatable biomarkers of DIVI. The VIWG focused its research on acute DIVI because early detection for clinical and nonclinical safety monitoring is desirable. The VIWG developed a strategy based on the premise that biomarkers of DIVI in rat would be translatable to humans due to the morphologic similarity of vascular injury between species regardless of mechanism. The histomorphologic lexicon for DIVI in rat defines degenerative and adaptive findings of the vascular endothelium and smooth muscles, and characterizes inflammatory components. We describe the mechanisms of these changes and their associations with candidate biomarkers for which advanced analytical method validation was completed. Further development is recommended for circulating microRNAs, endothelial microparticles, and imaging techniques. Recommendations for sample collection and processing, analytical methods, and confirmation of target localization using immunohistochemistry and in situ hybridization are described. The methods described are anticipated to aid in the identification and qualification of translational biomarkers for DIVI. © 2014 by The Author(s).

Mammalian plasma membrane proteins as potential biomarkers and drug targets.

PubMed

Rucevic, Marijana; Hixson, Douglas; Josic, Djuro

2011-06-01

Defining the plasma membrane proteome is crucial to understand the role of plasma membrane in fundamental biological processes. Change in membrane proteins is one of the first events that take place under pathological conditions, making plasma membrane proteins a likely source of potential disease biomarkers with prognostic or diagnostic potential. Membrane proteins are also potential targets for monoclonal antibodies and other drugs that block receptors or inhibit enzymes essential to the disease progress. Despite several advanced methods recently developed for the analysis of hydrophobic proteins and proteins with posttranslational modifications, integral membrane proteins are still under-represented in plasma membrane proteome. Recent advances in proteomic investigation of plasma membrane proteins, defining their roles as diagnostic and prognostic disease biomarkers and as target molecules in disease treatment, are presented. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel ageing-biomarker discovery using data-intensive technologies.

PubMed

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

2015-11-01

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

Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matheis, Katja A., E-mail: katja.matheis@boehringer-ingelheim.com; Com, Emmanuelle; High-Throughput Proteomics Core Facility OUEST-genopole

2011-04-15

The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with 'omics' data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinicalmore » chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.« less

Value of biomarkers in osteoarthritis: current status and perspectives

PubMed Central

Lotz, M; Martel-Pelletier, J; Christiansen, C; Brandi, M-L; Bruyère, O; Chapurlat, R; Collette, J; Cooper, C; Giacovelli, G; Kanis, J A; Karsdal, M A; Kraus, V; Lems, W F; Meulenbelt, I; Pelletier, J-P; Raynauld, J-P; Reiter-Niesert, S; Rizzoli, R; Sandell, L J; Van Spil, W E; Reginster, J-Y

2013-01-01

Osteoarthritis affects the whole joint structure with progressive changes in cartilage, menisci, ligaments and subchondral bone, and synovial inflammation. Biomarkers are being developed to quantify joint remodelling and disease progression. This article was prepared following a working meeting of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis convened to discuss the value of biochemical markers of matrix metabolism in drug development in osteoarthritis. The best candidates are generally molecules or molecular fragments present in cartilage, bone or synovium and may be specific to one type of joint tissue or common to them all. Many currently investigated biomarkers are associated with collagen metabolism in cartilage or bone, or aggrecan metabolism in cartilage. Other biomarkers are related to non-collagenous proteins, inflammation and/or fibrosis. Biomarkers in osteoarthritis can be categorised using the burden of disease, investigative, prognostic, efficacy of intervention, diagnostic and safety classification. There are a number of promising candidates, notably urinary C-terminal telopeptide of collagen type II and serum cartilage oligomeric protein, although none is sufficiently discriminating to differentiate between individual patients and controls (diagnostic) or between patients with different disease severities (burden of disease), predict prognosis in individuals with or without osteoarthritis (prognostic) or perform so consistently that it could function as a surrogate outcome in clinical trials (efficacy of intervention). Future avenues for research include exploration of underlying mechanisms of disease and development of new biomarkers; technological development; the ‘omics’ (genomics, metabolomics, proteomics and lipidomics); design of aggregate scores combining a panel of biomarkers and/or imaging markers into single diagnostic algorithms; and investigation into the relationship between biomarkers and

Connecting Brain Proteomics with Behavioural Neuroscience in Translational Animal Models of Neuropsychiatric Disorders.

PubMed

Sarnyai, Zoltán; Guest, Paul C

2017-01-01

Modelling psychiatric disorders in animals has been hindered by several challenges related to our poor understanding of the disease causes. This chapter describes recent advances in translational research which may lead to animal models and relevant proteomic biomarkers that can be informative about disease mechanisms and potential new therapeutic targets. The review focuses on the behavioural and molecular correlates in models of schizophrenia and major depressive disorder, as guided by recently established Research Domain Criteria (RDoC). This approach is based on providing proteomic data for aetiologically driven, behaviourally well-characterised animal models to link discovered biomarker candidates with the human disease.

Proteomics of the Human Placenta: Promises and Realities

PubMed Central

Robinson, J.M.; Ackerman, W.E.; Kniss, D.A.; Takizawa, T.; Vandré, D.D.

2015-01-01

Proteomics is an area of study that sets as its ultimate goal the global analysis of all of the proteins expressed in a biological system of interest. However, technical limitations currently hamper proteome-wide analyses of complex systems. In a more practical sense, a desired outcome of proteomics research is the translation of large protein data sets into formats that provide meaningful information regarding clinical conditions (e.g., biomarkers to serve as diagnostic and/or prognostic indicators of disease). Herein, we discuss placental proteomics by describing existing studies, pointing out their strengths and weaknesses. In so doing, we strive to inform investigators interested in this area of research about the current gap between hyperbolic promises and realities. Additionally, we discuss the utility of proteomics in discovery-based research, particularly as regards the capacity to unearth novel insights into placental biology. Importantly, when considering under studied systems such as the human placenta and diseases associated with abnormalities in placental function, proteomics can serve as a robust ‘shortcut’ to obtaining information unlikely to be garnered using traditional approaches. PMID:18222537

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

PubMed Central

Xu, Huajun; Zheng, Xiaojiao; Jia, Wei; Yin, Shankai

2015-01-01

Abstract Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA. PMID:26448002

Redox Proteomics Applied to the Thiol Secretome.

PubMed

Ghezzi, Pietro; Chan, Philippe

2017-03-01

Secreted proteins are important both as signaling molecules and potential biomarkers. Recent Advances: Protein can undergo different types of oxidation, both in physiological conditions or under oxidative stress. Several redox proteomics techniques have been successfully applied to the identification of glutathionylated proteins, an oxidative post-translational modification consisting in the formation of a mixed disulfide between a protein cysteine and glutathione. Redox proteomics has also been used to study other forms of protein oxidation. Because of the highest proportion of free cysteines in the cytosol, redox proteomics of protein thiols has focused, so far, on intracellular proteins. However, plasma proteins, such as transthyretin and albumin, have been described as glutathionylated or cysteinylated. The present review discusses the redox state of protein cysteines in relation to their cellular distribution. We describe the various approaches used to detect secreted glutathionylated proteins, the only thiol modification studied so far in secreted proteins, and the specific problems presented in the study of the secretome. This review focusses on glutathionylated proteins secreted under inflammatory conditions and that may act as soluble mediators (cytokines). Future studies on the redox secretome (including other forms of oxidation) might identify new soluble mediators and biomarkers of oxidative stress. Antioxid. Redox Signal. 26, 299-312.

Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

PubMed Central

Dasilva, Noelia; Díez, Paula; Matarraz, Sergio; González-González, María; Paradinas, Sara; Orfao, Alberto; Fuentes, Manuel

2012-01-01

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors. PMID:22438764

Meeting Report--NASA Radiation Biomarker Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straume, Tore; Amundson, Sally A,; Blakely, William F.

2008-05-01

A summary is provided of presentations and discussions from the NASA Radiation Biomarker Workshop held September 27-28, 2007, at NASA Ames Research Center in Mountain View, California. Invited speakers were distinguished scientists representing key sectors of the radiation research community. Speakers addressed recent developments in the biomarker and biotechnology fields that may provide new opportunities for health-related assessment of radiation-exposed individuals, including for long-duration space travel. Topics discussed include the space radiation environment, biomarkers of radiation sensitivity and individual susceptibility, molecular signatures of low-dose responses, multivariate analysis of gene expression, biomarkers in biodefense, biomarkers in radiation oncology, biomarkers and triagemore » following large-scale radiological incidents, integrated and multiple biomarker approaches, advances in whole-genome tiling arrays, advances in mass-spectrometry proteomics, radiation biodosimetry for estimation of cancer risk in a rat skin model, and confounding factors. Summary conclusions are provided at the end of the report.« less

Forensic proteomics for the evaluation of the post-mortem decay in bones.

PubMed

Procopio, Noemi; Williams, Anna; Chamberlain, Andrew T; Buckley, Michael

2018-04-15

Current methods for evaluation the of post-mortem interval (PMI) of skeletal remains suffer from poor accuracy due to the great number of variables that affect the diagenetic process and to the lack of specific guidelines to address this issue. During decomposition, proteins can undergo cumulative decay over the time, resulting in a decrease in the range and abundance of proteins present (i.e., the proteome) in different tissues as well as in an increase of post-translational modifications occurring in these proteins. In this study, we investigate the applicability of bone proteomic analyses to simulated forensic contexts, looking for specific biomarkers that may help the estimation of PMI, as well as evaluate a previously discovered marker for the estimation of biological age. We noticed a reduction of particular plasma and muscle proteins with increasing PMIs, as well as an increased deamidation of biglycan, a protein with a role in modulating bone growth and mineralization. We also corroborated our previous results regarding the use of fetuin-A as a potential biomarker for the estimation of age-at-death, demonstrating the applicability and the great potential that proteomics may have towards forensic sciences. The estimation of the post-mortem interval has a key role in forensic investigations, however nowadays it still suffers from poor reliability, especially when body tissues are heavily decomposed. Here we propose for the first time the application of bone proteomics to the estimation of the time elapsed since death and found several new potential biomarkers to address this, demonstrating the applicability of proteomic analyses to forensic sciences. Copyright © 2018. Published by Elsevier B.V.

Platelet proteomics: from discovery to diagnosis.

PubMed

Looße, Christina; Swieringa, Frauke; Heemskerk, Johan W M; Sickmann, Albert; Lorenz, Christin

2018-05-22

Platelets are the smallest cells within the circulating blood with key roles in physiological haemostasis and pathological thrombosis regulated by the onset of activating/inhibiting processes via receptor responses and signalling cascades. Areas covered: Proteomics as well as genomic approaches have been fundamental in identifying and quantifying potential targets for future diagnostic strategies in the prevention of bleeding and thrombosis, and uncovering the complexity of platelet functions in health and disease. In this article, we provide a critical overview on current functional tests used in diagnostics and the future perspectives for platelet proteomics in clinical applications. Expert commentary: Proteomics represents a valuable tool for the identification of patients with diverse platelet associated defects. In-depth validation of identified biomarkers, e.g. receptors, signalling proteins, post-translational modifications, in large cohorts is decisive for translation into routine clinical diagnostics.

Proteomics in pharmaceutical research and development.

PubMed

Cutler, Paul; Voshol, Hans

2015-08-01

In the 20 years since its inception, the evolution of proteomics in pharmaceutical industry has mirrored the developments within academia and indeed other industries. From initial enthusiasm and subsequent disappointment in global protein expression profiling, pharma research saw the biggest impact when relating to more focused approaches, such as those exploring the interaction between proteins and drugs. Nowadays, proteomics technologies have been integrated in many areas of pharmaceutical R&D, ranging from the analysis of therapeutic proteins to the monitoring of clinical trials. Here, we review the development of proteomics in the drug discovery process, placing it in a historical context as well as reviewing the current status in light of the contributions to this special issue, which reflect some of the diverse demands of the drug and biomarker pipelines. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-11-01

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

New serum biomarkers for detection of tuberculosis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.

PubMed

Liu, Ji-Yan; Jin, Lei; Zhao, Meng-Yuan; Zhang, Xin; Liu, Chi-Bo; Zhang, Yu-Xiang; Li, Fu-Jian; Zhou, Jian-Min; Wang, Hua-Jun; Li, Ji-Cheng

2011-10-01

New technologies for the early detection of tuberculosis (TB) are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. The aim of the present study was to screen for the potential protein biomarkers in serum for the diagnosis of TB using proteomic fingerprint technology. Proteomic fingerprint technology combining protein chips with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to profile the serum proteins from 50 patients with TB, 25 patients with lung disease other than TB, and 25 healthy volunteers. The protein fingerprint expression of all the serum samples and the resulting profiles between TB and control groups were analyzed with the Biomarker Wizard system. A total of 30 discriminating m/z peaks were detected that were related to TB (p<0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the three biomarkers (2024, 8007, and 8598 Da) generated excellent separation between the TB and control groups. The sensitivity was 84.0% and the specificity was 86.0%. Blind test data indicated a sensitivity of 80.0% and a specificity of 84.2%. The data suggested a potential application of SELDI-TOF MS as an effective technology to profile serum proteome, and with pattern analysis, a diagnostic model comprising three potential biomarkers was indicated to differentiate people with TB and healthy controls rapidly and precisely.

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

PubMed

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

2018-04-02

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

Current trends in quantitative proteomics - an update.

PubMed

Li, H; Han, J; Pan, J; Liu, T; Parker, C E; Borchers, C H

2017-05-01

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Cerebrospinal Fluid Biomarkers for Huntington's Disease.

PubMed

Byrne, Lauren M; Wild, Edward J

2016-01-01

Cerebrospinal fluid (CSF) is enriched in brain-derived components and represents an accessible and appealing means of interrogating the CNS milieu to study neurodegenerative diseases and identify biomarkers to facilitate the development of novel therapeutics. Many such CSF biomarkers have been proposed for Huntington's disease (HD) but none has been validated for clinical trial use. Across many studies proposing dozens of biomarker candidates, there is a notable lack of statistical power, consistency, rigor and validation. Here we review proposed CSF biomarkers including neurotransmitters, transglutaminase activity, kynurenine pathway metabolites, oxidative stress markers, inflammatory markers, neuroendocrine markers, protein markers of neuronal death, proteomic approaches and mutant huntingtin protein itself. We reflect on the need for large-scale, standardized CSF collections with detailed phenotypic data to validate and qualify much-needed CSF biomarkers for clinical trial use in HD.

Mixed-mode ion exchange-based integrated proteomics technology for fast and deep plasma proteome profiling.

PubMed

Xue, Lu; Lin, Lin; Zhou, Wenbin; Chen, Wendong; Tang, Jun; Sun, Xiujie; Huang, Peiwu; Tian, Ruijun

2018-06-09

Plasma proteome profiling by LC-MS based proteomics has drawn great attention recently for biomarker discovery from blood liquid biopsy. Due to standard multi-step sample preparation could potentially cause plasma protein degradation and analysis variation, integrated proteomics sample preparation technologies became promising solution towards this end. Here, we developed a fully integrated proteomics sample preparation technology for both fast and deep plasma proteome profiling under its native pH. All the sample preparation steps, including protein digestion and two-dimensional fractionation by both mixed-mode ion exchange and high-pH reversed phase mechanism were integrated into one spintip device for the first time. The mixed-mode ion exchange beads design achieved the sample loading at neutral pH and protein digestion within 30 min. Potential sample loss and protein degradation by pH changing could be voided. 1 μL of plasma sample with depletion of high abundant proteins was processed by the developed technology with 12 equally distributed fractions and analyzed with 12 h of LC-MS gradient time, resulting in the identification of 862 proteins. The combination of the Mixed-mode-SISPROT and data-independent MS method achieved fast plasma proteome profiling in 2 h with high identification overlap and quantification precision for a proof-of-concept study of plasma samples from 5 healthy donors. We expect that the Mixed-mode-SISPROT become a generally applicable sample preparation technology for clinical oriented plasma proteome profiling. Copyright © 2018 Elsevier B.V. All rights reserved.

Personalized medicine beyond genomics: alternative futures in big data-proteomics, environtome and the social proteome.

PubMed

Özdemir, Vural; Dove, Edward S; Gürsoy, Ulvi K; Şardaş, Semra; Yıldırım, Arif; Yılmaz, Şenay Görücü; Ömer Barlas, I; Güngör, Kıvanç; Mete, Alper; Srivastava, Sanjeeva

2017-01-01

No field in science and medicine today remains untouched by Big Data, and psychiatry is no exception. Proteomics is a Big Data technology and a next generation biomarker, supporting novel system diagnostics and therapeutics in psychiatry. Proteomics technology is, in fact, much older than genomics and dates to the 1970s, well before the launch of the international Human Genome Project. While the genome has long been framed as the master or "elite" executive molecule in cell biology, the proteome by contrast is humble. Yet the proteome is critical for life-it ensures the daily functioning of cells and whole organisms. In short, proteins are the blue-collar workers of biology, the down-to-earth molecules that we cannot live without. Since 2010, proteomics has found renewed meaning and international attention with the launch of the Human Proteome Project and the growing interest in Big Data technologies such as proteomics. This article presents an interdisciplinary technology foresight analysis and conceptualizes the terms "environtome" and "social proteome". We define "environtome" as the entire complement of elements external to the human host, from microbiome, ambient temperature and weather conditions to government innovation policies, stock market dynamics, human values, political power and social norms that collectively shape the human host spatially and temporally. The "social proteome" is the subset of the environtome that influences the transition of proteomics technology to innovative applications in society. The social proteome encompasses, for example, new reimbursement schemes and business innovation models for proteomics diagnostics that depart from the "once-a-life-time" genotypic tests and the anticipated hype attendant to context and time sensitive proteomics tests. Building on the "nesting principle" for governance of complex systems as discussed by Elinor Ostrom, we propose here a 3-tiered organizational architecture for Big Data science such as

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation.

PubMed

Hulme, Charlotte H; Wilson, Emma L; Fuller, Heidi R; Roberts, Sally; Richardson, James B; Gallacher, Pete; Peffers, Mandy J; Shirran, Sally L; Botting, Catherine H; Wright, Karina T

2018-05-02

Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI

Proteomics in bone research

PubMed Central

Zhang, Hengwei; Recker, Robert; Lee, Wai-Nang Paul; Xiao, Gary Guishan

2010-01-01

Osteoporosis is prevalent among the elderly and is a major cause of bone fracture in this population. Bone integrity is maintained by the dynamic processes of bone resorption and bone formation (bone remodeling). Osteoporosis results when there is an imbalance of the two counteracting processes. Bone mineral density, measured by dual-energy x-ray absorptiometry has been the primary method to assess fracture risk for decades. Recent studies demonstrated that measurement of bone turnover markers allows for a dynamic assessment of bone remodeling, while imaging techniques, such as dual-energy x-ray absorptiometry, do not. The application of proteomics has permitted discoveries of new, sensitive, bone turnover markers, which provide unique information for clinical diagnosis and treatment of patients with bone diseases. This review summarizes the recent findings of proteomic studies on bone diseases, properties of mesenchymal stem cells with high expansion rates and osteoblast and osteoclast differentiation, with emphasis on the role of quantitative proteomics in the study of signaling dynamics, biomarkers and discovery of therapeutic targets. PMID:20121480

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

Genomics and proteomics in liver fibrosis and cirrhosis

PubMed Central

2012-01-01

Genomics and proteomics have become increasingly important in biomedical science in the past decade, as they provide an opportunity for hypothesis-free experiments that can yield major insights not previously foreseen when scientific and clinical questions are based only on hypothesis-driven approaches. Use of these tools, therefore, opens new avenues for uncovering physiological and pathological pathways. Liver fibrosis is a complex disease provoked by a range of chronic injuries to the liver, among which are viral hepatitis, (non-) alcoholic steatohepatitis and autoimmune disorders. Some chronic liver patients will never develop fibrosis or cirrhosis, whereas others rapidly progress towards cirrhosis in a few years. This variety can be caused by disease-related factors (for example, viral genotype) or host-factors (genetic/epigenetic). It is vital to establish accurate tools to identify those patients at highest risk for disease severity or progression in order to determine who are in need of immediate therapies. Moreover, there is an urgent imperative to identify non-invasive markers that can accurately distinguish mild and intermediate stages of fibrosis. Ideally, biomarkers can be used to predict disease progression and treatment response, but these studies will take many years due to the requirement for lengthy follow-up periods to assess outcomes. Current genomic and proteomic research provides many candidate biomarkers, but independent validation of these biomarkers is lacking, and reproducibility is still a key concern. Thus, great opportunities and challenges lie ahead in the field of genomics and proteomics, which, if successful, could transform the diagnosis and treatment of chronic fibrosing liver diseases. PMID:22214245

Urinary Biomarkers of Brain Diseases.

PubMed

An, Manxia; Gao, Youhe

2015-12-01

Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome. Copyright © 2016 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Protein biomarker validation via proximity ligation assays.

PubMed

Blokzijl, A; Nong, R; Darmanis, S; Hertz, E; Landegren, U; Kamali-Moghaddam, M

2014-05-01

The ability to detect minute amounts of specific proteins or protein modifications in blood as biomarkers for a plethora of human pathological conditions holds great promise for future medicine. Despite a large number of plausible candidate protein biomarkers published annually, the translation to clinical use is impeded by factors such as the required size of the initial studies, and limitations of the technologies used. The proximity ligation assay (PLA) is a versatile molecular tool that has the potential to address some obstacles, both in validation of biomarkers previously discovered using other techniques, and for future routine clinical diagnostic needs. The enhanced specificity of PLA extends the opportunities for large-scale, high-performance analyses of proteins. Besides advantages in the form of minimal sample consumption and an extended dynamic range, the PLA technique allows flexible assay reconfiguration. The technology can be adapted for detecting protein complexes, proximity between proteins in extracellular vesicles or in circulating tumor cells, and to address multiple post-translational modifications in the same protein molecule. We discuss herein requirements for biomarker validation, and how PLA may play an increasing role in this regard. We describe some recent developments of the technology, including proximity extension assays, the use of recombinant affinity reagents suitable for use in proximity assays, and the potential for single cell proteomics. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

Enrichment of low-molecular-weight proteins from biofluids for biomarker discovery.

PubMed

Chertov, Oleg; Simpson, John T; Biragyn, Arya; Conrads, Thomas P; Veenstra, Timothy D; Fisher, Robert J

2005-01-01

The dramatic progress in mass spectrometry-based methods of protein identification has triggered a new quest for disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and its variant surface-enhanced laser desorption/ionization mass spectrometry, provide effective means to explore the less studied information slice of the human serum proteome -- low-molecular-weight proteins and peptides. These low-molecular-weight proteins and peptides are promising for the detection of important biomarkers. Due to the significant experimental problems imposed by high-abundance and high-molecular-weight proteins, it is important to effectively remove these species prior to mass spectrometry analysis of the low-molecular-weight serum and plasma proteomes. In this review, the advantages afforded by recently introduced methods for prefractionation of serum, as they pertain to the detection and identification of biomarkers, will be discussed.

Proteomic Analysis of the Human Skin Proteome after In Vivo Treatment with Sodium Dodecyl Sulphate

PubMed Central

Parkinson, Erika; Skipp, Paul; Aleksic, Maja; Garrow, Andrew; Dadd, Tony; Hughes, Michael; Clough, Geraldine; O′Connor, C. David

2014-01-01

Background Skin has a variety of functions that are incompletely understood at the molecular level. As the most accessible tissue in the body it often reveals the first signs of inflammation or infection and also represents a potentially valuable source of biomarkers for several diseases. In this study we surveyed the skin proteome qualitatively using gel electrophoresis, liquid chromatography tandem mass spectrometry (GeLC-MS/MS) and quantitatively using an isobaric tagging strategy (iTRAQ) to characterise the response of human skin following exposure to sodium dodecyl sulphate (SDS). Results A total of 653 skin proteins were assigned, 159 of which were identified using GeLC-MS/MS and 616 using iTRAQ, representing the most comprehensive proteomic study in human skin tissue. Statistical analysis of the available iTRAQ data did not reveal any significant differences in the measured skin proteome after 4 hours exposure to the model irritant SDS. Conclusions This study represents the first step in defining the critical response to an irritant at the level of the proteome and provides a valuable resource for further studies at the later stages of irritant exposure. PMID:24849295

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

PubMed

Wimmer, Helge; Gundacker, Nina C; Griss, Johannes; Haudek, Verena J; Stättner, Stefan; Mohr, Thomas; Zwickl, Hannes; Paulitschke, Verena; Baron, David M; Trittner, Wolfgang; Kubicek, Markus; Bayer, Editha; Slany, Astrid; Gerner, Christopher

2009-06-01

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database-assisted interpretation strategy based on proteome profiles of primary cells. Both 2-D-PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2-D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2-D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self-designed SQL database (CPL/MUW - database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type-specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna-database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Toxicoproteomics: serum proteomic pattern diagnostics for early detection of drug induced cardiac toxicities and cardioprotection.

PubMed

Petricoin, Emanuel F; Rajapaske, Vinodh; Herman, Eugene H; Arekani, Ali M; Ross, Sally; Johann, Donald; Knapton, Alan; Zhang, J; Hitt, Ben A; Conrads, Thomas P; Veenstra, Timothy D; Liotta, Lance A; Sistare, Frank D

2004-01-01

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry which communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity based processes as cascades of reinforcing information percolate through the system and become reflected in changing proteomic information content of the circulation. Serum Proteomic Pattern Diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. While this approach has shown tremendous promise in early detection of cancers, detection of drug-induced toxicity may also be possible with this same technology. Analysis of serum from rat models of anthracycline and anthracenedione induced cardiotoxicity indicate the potential clinical utility of diagnostic proteomic patterns where low molecular weight peptides and protein fragments may have higher accuracy than traditional biomarkers of cardiotoxicity such as troponins. These fragments may one day be harvested by circulating nanoparticles designed to absorb, enrich and amplify the diagnostic biomarker repertoire generated even at the critical initial stages of toxicity.

Label-free proteome of water buffalo (Bubalus bubalis) seminal plasma.

PubMed

Brito, Mayara F; Auler, Patrícia A; Tavares, Guilherme C; Rezende, Cristiana P; Almeida, Gabriel M F; Pereira, Felipe L; Leal, Carlos A G; Moura, Arlindo de Alencar; Figueiredo, Henrique C P; Henry, Marc

2018-06-11

The study aimed to describe the Bubalus bubalis seminal plasma proteome using a label-free shotgun UDMS E approach. A total of 859 nonredundant proteins were identified across five biological replicates with stringent identification. Proteins specifically related to sperm maturation and protection, capacitation, fertilization and metabolic activity were detected in the buffalo seminal fluid. In conclusion, we provide a comprehensive proteomic profile of buffalo seminal plasma, which establishes a foundation for further studies designed to understand regulation of sperm function and discovery of novel biomarkers for fertility. MS data are available in the ProteomeXchange with identifier PXD003728. © 2018 Blackwell Verlag GmbH.

AgHalo: A Facile Fluorogenic Sensor to Detect Drug-Induced Proteome Stress.

PubMed

Liu, Yu; Fares, Matthew; Dunham, Noah P; Gao, Zi; Miao, Kun; Jiang, Xueyuan; Bollinger, Samuel S; Boal, Amie K; Zhang, Xin

2017-07-17

Drug-induced proteome stress that involves protein aggregation may cause adverse effects and undermine the safety profile of a drug. Safety of drugs is regularly evaluated using cytotoxicity assays that measure cell death. However, these assays provide limited insights into the presence of proteome stress in live cells. A fluorogenic protein sensor is reported to detect drug-induced proteome stress prior to cell death. An aggregation prone Halo-tag mutant (AgHalo) was evolved to sense proteome stress through its aggregation. Detection of such conformational changes was enabled by a fluorogenic ligand that fluoresces upon AgHalo forming soluble aggregates. Using 5 common anticancer drugs, we exemplified detection of differential proteome stress before any cell death was observed. Thus, this sensor can be used to evaluate drug safety in a regime that the current cytotoxicity assays cannot cover and be generally applied to detect proteome stress induced by other toxins. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteomic evaluation of sheep serum proteins

PubMed Central

2012-01-01

Background The applications of proteomic strategies to ovine medicine remain limited. The definition of serum proteome may be a good tool to identify useful protein biomarkers for recognising sub-clinical conditions and overt disease in sheep. Findings from bovine species are often directly translated for use in ovine medicine. In order to characterize normal protein patterns and improve knowledge of molecular species-specific characteristics, we generated a two-dimensional reference map of sheep serum. The possible application of this approach was tested by analysing serum protein patterns in ewes with mild broncho-pulmonary disease, which is very common in sheep and in the peripartum period which is a stressful time, with a high incidence of infectious and parasitic diseases. Results This study generated the first reference 2-DE maps of sheep serum. Overall, 250 protein spots were analyzed, and 138 identified. Compared with healthy sheep, serum protein profiles of animals with rhino-tracheo-bronchitis showed a significant decrease in protein spots identified as transthyretin, apolipoprotein A1 and a significant increase in spots identified as haptoglobin, endopin 1b and alpha1B glycoprotein. In the peripartum period, haptoglobin, alpha-1-acid glycoprotein, apolipoprotein A1 levels rose, while transthyretin content dropped. Conclusions This study describes applications of proteomics in putative biomarker discovery for early diagnosis as well as for monitoring the physiological and metabolic situations critical for ovine welfare. PMID:22630135

The Impact of the Glomerular Filtration Rate on the Human Plasma Proteome.

PubMed

Christensson, Anders; Ash, Jessica A; DeLisle, Robert K; Gaspar, Fraser W; Ostroff, Rachel; Grubb, Anders; Lindström, Veronica; Bruun, Laila; Williams, Steve A

2018-05-01

The application of proteomics in chronic kidney disease (CKD) can potentially uncover biomarkers and pathways that are predictive of disease. Within this context, this study examines the relationship between the human plasma proteome and glomerular filtration rate (GFR) as measured by iohexol clearance in a cohort from Sweden (n = 389; GFR range: 8-100 mL min -1 /1.73 m 2 ). A total of 2893 proteins are quantified using a modified aptamer assay. A large proportion of the proteome is associated with GFR, reinforcing the concept that CKD affects multiple physiological systems (individual protein-GFR correlations listed here). Of these, cystatin C shows the most significant correlation with GFR (rho = -0.85, p = 1.2 × 10 -97 ), establishing strong validation for the use of this biomarker in CKD diagnostics. Among the other highly significant protein markers are insulin-like growth factor-binding protein 6, neuroblastoma suppressor of tumorigenicity 1, follistatin-related protein 3, trefoil factor 3, and beta-2 microglobulin. These proteins may indicate an imbalance in homeostasis across a variety of cellular processes, which may be underlying renal dysfunction. Overall, this study represents the most extensive characterization of the plasma proteome and its relation to GFR to date, and suggests the diagnostic and prognostic value of proteomics for CKD across all stages. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Differential proteomic profiling of primary and recurrent chordomas.

PubMed

Chen, Su; Xu, Wei; Jiao, Jian; Jiang, Dongjie; Liu, Jian; Chen, Tenghui; Wan, Zongmiao; Xu, Leqin; Zhou, Zhenhua; Xiao, Jianru

2015-05-01

Chordomas are locally destructive tumors with high rates of recurrence and a poor prognosis. The mechanisms involved in chordoma recurrence remain largely unknown. In the present study, we examined the proteomic profile of a chordoma primary tumor (CSO) and a recurrent tumor (CSR) through mass spectrum in a chordoma patient who underwent surgery. Bioinformatic analysis of the profile showed that 359 proteins had a significant expression difference and 21 pathways had a striking alteration between the CSO and the CSR. The CSR showed a significant increase in carbohydrate metabolism. Immunohistochemistry (IHC) confirmed that the cancer stem cell marker activated leukocyte cell adhesion molecule (ALCAM or CD166) expression level was higher in the recurrent than that in the primary tumor. The present study analyzed the proteomic profile change between CSO and CSR and identified a new biomarker ALCAM in recurrent chordomas. This finding sheds light on unraveling the pathophysiology of chordoma recurrence and on exploring more effective prognostic biomarkers and targeted therapies against this devastating disease.

Renal Cancer Biomarkers | NCI Technology Transfer Center | TTC

Cancer.gov

The National Cancer Institute's Laboratory of Proteomics and Analytical Technologies is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize diagnostic, therapeutic and prognostic cancer biomarkers from clinical specimens.

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

PubMed

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

2015-02-01

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

Proteomic analysis of acetaminophen-induced hepatotoxicity and identification of heme oxygenase 1 as a potential plasma biomarker of liver injury

PubMed Central

Gao, Yuan; Cao, Zhijun; Yang, Xi; Abdelmegeed, Mohamed A.; Sun, Jinchun; Chen, Si; Beger, Richard D.; Davis, Kelly; Salminen, William F.; Song, Byoung-Joon; Mendrick, Donna L.; Yu, Li-Rong

2017-01-01

Purpose Overdose of acetaminophen (APAP) is a major cause of acute liver failure. This study was aimed to identify pathways related to hepatotoxicity and potential biomarkers of liver injury. Experimental design Rats were treated with low (100 mg/kg) and high (1250 mg/kg) doses of APAP, and liver tissues at 6 and 24 h post-treatment were analyzed using a proteomic approach of 16O/18O labeling and 2D-LC-MS/MS. Results Molecular pathways evolved progressively from scattered and less significant perturbations to more focused and significant alterations in a dose- and time-dependent manner upon APAP treatment. Imbalanced expression of hemeoxygenase 1 (HMOX1) and biliverdin reductase A (BLVRA) was associated with hepatotoxicity. Protein abundance changes of a total of 31 proteins were uniquely correlated to liver damage, among which a dramatic increase of HMOX1 levels in plasma was observed. Liver injury-associated significant elevation of plasma HMOX1 was further validated in mice treated with APAP. Conclusions and clinical relevance This study unveiled molecular changes associated with APAP-induced liver toxicity at the pathway levels and identified HMOX1 as a potential plasma biomarker of liver injury. PMID:27634590

Comparative proteomics in alkaptonuria provides insights into inflammation and oxidative stress.

PubMed

Braconi, Daniela; Bernardini, Giulia; Paffetti, Alessandro; Millucci, Lia; Geminiani, Michela; Laschi, Marcella; Frediani, Bruno; Marzocchi, Barbara; Santucci, Annalisa

2016-12-01

Alkaptonuria (AKU) is an ultra-rare inborn error of metabolism associated with a defective catabolism of phenylalanine and tyrosine leading to increased systemic levels of homogentisic acid (HGA). Excess HGA is partly excreted in the urine, partly accumulated within the body and deposited onto connective tissues under the form of an ochronotic pigment, leading to a range of clinical manifestations. No clear genotype/phenotype correlation was found in AKU, and today there is the urgent need to identify biomarkers able to monitor AKU progression and evaluate response to treatment. With this aim, we provided the first proteomic study on serum and plasma samples from alkaptonuric individuals showing pathological SAA, CRP and Advanced Oxidation Protein Products (AOPP) levels. Interesting similarities with proteomic studies on other rheumatic diseases were highlighted together with proteome alterations supporting the existence of oxidative stress and inflammation in AKU. Potential candidate biomarkers to assess disease severity, monitor disease progression and evaluate response to treatment were identified as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Use of Proteomics in Assisted Reproduction.

PubMed

Kosteria, Ioanna; Anagnostopoulos, Athanasios K; Kanaka-Gantenbein, Christina; Chrousos, George P; Tsangaris, George T

2017-01-01

Despite the explosive increase in the use of Assisted Reproductive Technologies (ART) over the last 30 years, their success rates remain suboptimal. Proteomics is a rapidly-evolving technology-driven science that has already been widely applied in the exploration of human reproduction and fertility, providing useful insights into its physiology and leading to the identification of numerous proteins that may be potential biomarkers and/or treatment targets of a successful ART pregnancy. Here we present a brief overview of the techniques used in proteomic analyses and attempt a comprehensive presentation of recent data from mass spectrometry-based proteomic studies in humans, regarding all components of ARTs, including the male and female gamete, the derived zygote and embryo, the endometrium and, finally, the ART offspring both pre- and postnatally. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The State of the Human Proteome in 2013 as viewed through PeptideAtlas: Comparing the Kidney, Urine, and Plasma Proteomes for the Biology and Disease-driven Human Proteome Project

PubMed Central

Farrah, Terry; Deutsch, Eric W.; Omenn, Gilbert S.; Sun, Zhi; Watts, Julian D.; Yamamoto, Tadashi; Shteynberg, David; Harris, Micheleen M.; Moritz, Robert L.

2014-01-01

The kidney, urine, and plasma proteomes are intimately related: proteins and metabolic waste products are filtered from the plasma by the kidney and excreted via the urine, while kidney proteins may be secreted into the circulation or released into the urine. Shotgun proteomics datasets derived from human kidney, urine, and plasma samples were collated and processed using a uniform software pipeline, and relative protein abundances were estimated by spectral counting. The resulting PeptideAtlas builds yielded 4005, 2491, and 3553 nonredundant proteins at 1% FDR for the kidney, urine, and plasma proteomes, respectively—for kidney and plasma, the largest high-confidence protein sets to date. The same pipeline applied to all available human data yielded a 2013 Human PeptideAtlas build containing 12,644 nonredundant proteins and at least one peptide for each of ~14,000 Swiss-Prot entries, an increase over 2012 of ~7.5% of the predicted human proteome. We demonstrate that abundances are correlated between plasma and urine, examine the most abundant urine proteins not derived from either plasma or kidney, and consider the biomarker potential of proteins associated with renal decline. This analysis forms part of the Biology and Disease-driven Human Proteome Project (B/D-HPP) and a contribution to the Chromosome-centric Human Proteome Project (C-HPP) special issue. PMID:24261998

Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach.

PubMed

Kumar, Bhowmik Salil; Lee, Young-Joo; Yi, Hong Jae; Chung, Bong Chul; Jung, Byung Hwa

2010-02-19

In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg(-1) day(-1) or 250 mg kg(-1) day(-1) for a period of 7 days (n=4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers. Copyright 2009 Elsevier B.V. All rights reserved.

Quantitative proteomics of bronchoalveolar lavage fluid in lung adenocarcinoma.

PubMed

Almatroodi, Saleh A; McDonald, Christine F; Collins, Allison L; Darby, Ian A; Pouniotis, Dodie S

2015-01-01

The most commonly reported primary lung cancer subtype is adenocarcinoma, which is associated with a poor prognosis and short survival. Proteomic studies on human body fluids such as bronchoalveolar lavage fluid (BALF) have become essential methods for biomarker discovery, examination of tumor pathways and investigation of potential treatments. This study used quantitative proteomics to investigate the up-regulation of novel proteins in BALF from patients with primary lung adenocarcinoma in order to identify potential biomarkers. BALF samples from individuals with and without primary lung adenocarcinoma were analyzed using liquid chromatography-mass spectrometry. One thousand and one hundred proteins were identified, 33 of which were found to be consistently overexpressed in all lung adenocarcinoma samples compared to non-cancer controls. A number of overexpressed proteins have been previously shown to be related to lung cancer progression including S100-A8, annexin A1, annexin A2, thymidine phosphorylase and transglutaminase 2. The overexpression of a number of specific proteins in BALF from patients with primary lung adenocarcinoma may be used as a potential biomarker for lung adenocarcinoma. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

Sample handling for mass spectrometric proteomic investigations of human sera.

PubMed

West-Nielsen, Mikkel; Høgdall, Estrid V; Marchiori, Elena; Høgdall, Claus K; Schou, Christian; Heegaard, Niels H H

2005-08-15

Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers while less effort has been invested in devising standard procedures for sample preparation and storage in relation to model building based on complex sets of mass spectrometric (MS) data. Thus, development of standardized methods for collection and storage of patient samples together with standards for transportation and handling of samples are needed. This requires knowledge about how sample processing affects MS-based proteome analyses and thereby how nonbiological biased classification errors are avoided. In this study, we characterize the effects of sample handling, including clotting conditions, storage temperature, storage time, and freeze/thaw cycles, on MS-based proteomics of human serum by using principal components analysis, support vector machine learning, and clustering methods based on genetic algorithms as class modeling and prediction methods. Using spiking to artificially create differentiable sample groups, this integrated approach yields data that--even when working with sample groups that differ more than may be expected in biological studies--clearly demonstrate the need for comparable sampling conditions for samples used for modeling and for the samples that are going into the test set group. Also, the study emphasizes the difference between class prediction and class comparison studies as well as the advantages and disadvantages of different modeling methods.

Defining the Adipose Tissue Proteome of Dairy Cows to Reveal Biomarkers Related to Peripartum Insulin Resistance and Metabolic Status.

PubMed

Zachut, Maya

2015-07-02

Adipose tissue is a central regulator of metabolism in dairy cows; however, little is known about the association between various proteins in adipose tissue and the metabolic status of peripartum cows. Therefore, the objectives were to (1) examine total protein expression in adipose tissue of dairy cows and (2) identify biomarkers in adipose that are linked to insulin resistance and to cows' metabolic status. Adipose tissue biopsies were obtained from eight multiparous cows at -17 and +4 days relative to parturition. Proteins were analyzed by intensity-based, label-free, quantitative shotgun proteomics (nanoLC-MS/MS). Cows were divided into groups with insulin-resistant (IR) and insulin-sensitive (IS) adipose according to protein kinase B phosphorylation following insulin stimulation. Cows with IR adipose lost more body weight postpartum compared with IS cows. Differential expression of 143 out of 586 proteins was detected in prepartum versus postpartum adipose. Comparing IR to IS adipose revealed differential expression of 18.9% of the proteins; those related to lipolysis (hormone-sensitive lipase, perilipin, monoglycerol lipase) were increased in IR adipose. In conclusion, we found novel biomarkers related to IR in adipose and to metabolic status that could be used to characterize high-yielding dairy cows that are better adapted to peripartum metabolic stress.

High-throughput serum proteomics for the identification of protein biomarkers of mortality in older men

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orwoll, Eric S.; Wiedrick, Jack; Jacobs, Jon

The biological perturbations associated with incident mortality are not well elucidated, and there are limited biomarkers for the prediction of mortality. We used a novel high throughput proteomics approach to identify serum peptides and proteins associated with 5 year mortality in community dwelling men age >65 years who participated in a longitudinal observational study of musculoskeletal aging (Osteoporotic Fractures in Men: MrOS). In a discovery phase, serum specimens collected at baseline in 2473 men were analyzed using liquid chromatography-ion mobility-mass spectrometry, and incident mortality in the subsequent 5 years was ascertained by tri-annual questionnaire. Rigorous statistical methods were utilized tomore » identify 56 peptides (31 proteins) that were associated with 5-year mortality. In an independent replication phase, selected reaction monitoring was used to examine 21 of those peptides in baseline serum from 750 additional men; 81% of those peptides remained significantly associated with mortality. Mortality-associated proteins included a variety involved in inflammation or complement activation; several have been previously linked to mortality (e.g. C reactive protein, alpha 1-antichymotrypsin) and others are not previously known to be associated with mortality. Other novel proteins of interest included pregnancy-associated plasma protein, VE cadherin, leucine-rich α-2 glycoprotein 1, vinculin, vitronectin, mast/stem cell growth factor receptor and Saa4. A panel of peptides improved the predictive value of a commonly used clinical predictor of mortality. Overall, these results suggest that complex inflammatory pathways, and proteins in other pathways, are linked to 5-year mortality risk. This work may serve to identify novel biomarkers for near term mortality.« less

Innovative biomarkers in psychiatric disorders: a major clinical challenge in psychiatry.

PubMed

Lozupone, Madia; Seripa, Davide; Stella, Eleonora; La Montagna, Maddalena; Solfrizzi, Vincenzo; Quaranta, Nicola; Veneziani, Federica; Cester, Alberto; Sardone, Rodolfo; Bonfiglio, Caterina; Giannelli, Gianluigi; Bisceglia, Paola; Bringiotti, Roberto; Daniele, Antonio; Greco, Antonio; Bellomo, Antonello; Logroscino, Giancarlo; Panza, Francesco

2017-09-01

Currently, the diagnosis of psychiatric illnesses is based upon DSM-5 criteria. Although endophenotype-specificity for a particular disorder is discussed, the identification of objective biomarkers is ongoing for aiding diagnosis, prognosis, or clinical response to treatment. We need to improve the understanding of the biological abnormalities in psychiatric illnesses across conventional diagnostic boundaries. The present review investigates the innovative post-genomic knowledge used for psychiatric illness diagnostics and treatment response, with a particular focus on proteomics. Areas covered: This review underlines the contribution that psychiatric innovative biomarkers have reached in relation to diagnosis and theragnosis of psychiatric illnesses. Furthermore, it encompasses a reliable representation of their involvement in disease through proteomics, metabolomics/pharmacometabolomics and lipidomics techniques, including the possible role that gut microbiota and CYP2D6 polimorphisms may play in psychiatric illnesses. Expert opinion: Etiologic heterogeneity, variable expressivity, and epigenetics may impact clinical manifestations, making it difficult for a single measurement to be pathognomonic for multifaceted psychiatric disorders. Academic, industry, or government's partnerships may successfully identify and validate new biomarkers so that unfailing clinical tests can be developed. Proteomics, metabolomics, and lipidomics techniques are considered to be helpful tools beyond neuroimaging and neuropsychology for the phenotypic characterization of brain diseases.

Identification of aldolase A as a potential diagnostic biomarker for colorectal cancer based on proteomic analysis using formalin-fixed paraffin-embedded tissue.

PubMed

Yamamoto, Tetsushi; Kudo, Mitsuhiro; Peng, Wei-Xia; Takata, Hideyuki; Takakura, Hideki; Teduka, Kiyoshi; Fujii, Takenori; Mitamura, Kuniko; Taga, Atsushi; Uchida, Eiji; Naito, Zenya

2016-10-01

Colorectal cancer (CRC) is one of the most common cancers worldwide, and many patients are already at an advanced stage when they are diagnosed. Therefore, novel biomarkers for early detection of colorectal cancer are required. In this study, we performed a global shotgun proteomic analysis using formalin-fixed and paraffin-embedded (FFPE) CRC tissue. We identified 84 candidate proteins whose expression levels were differentially expressed in cancer and non-cancer regions. A label-free semiquantitative method based on spectral counting and gene ontology (GO) analysis led to a total of 21 candidate proteins that could potentially be detected in blood. Validation studies revealed cyclophilin A, annexin A2, and aldolase A mRNA and protein expression levels were significantly higher in cancer regions than in non-cancer regions. Moreover, an in vitro study showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cells compared to normal colon epithelium. These findings suggest that decreased aldolase A in blood may be a novel biomarker for the early detection of CRC.

Search for novel circulating cancer chemopreventive biomarkers of dietary rice bran intervention in Apc(Min) mice model of colorectal carcinogenesis, using proteomic and metabolic profiling strategies.

PubMed

Norris, Leonie; Malkar, Aditya; Horner-Glister, Emma; Hakimi, Amirmansoor; Ng, Leong L; Gescher, Andreas J; Creaser, Colin; Sale, Stewart; Jones, Donald J L

2015-09-01

There is strong epidemiological evidence indicating that consumption by humans of whole-grain foods including rice bran may be associated with a low incidence of cancer, especially in the colorectum. Molecular processes associated with cancer development may be retarded by fiber consumption. Consequently, intervention with dietary fiber might be suitable as a cancer chemoprevention strategy in high-risk populations. Here, we searched for putative molecular mechanism-based efficacy biomarkers of rice fiber consumption in the plasma of mice characterized by a genetic propensity to develop gastrointestinal adenomas. The hypothesis was tested that metabolic and proteomic changes in blood reflect the chemopreventive activity of rice bran. Apc(Min) mice received diet supplemented with rice bran at 5, 15, and 30%. Blood and tissue samples were taken. Plasma was subjected to MS-based proteomic and metabolic profiling analyses as well as assessment of hematocrit values. Gastrointestinal tracts were removed and adenomas were counted and their size was measured so that total tumor burden could be calculated. The hypothesis was tested that metabolic and proteomic changes in blood reflect chemopreventive activity. Rice bran consumption reduced adenoma burden and number in a dose-related fashion when compared to controls. Metabolic profiling data demonstrated strong clustering of the groups indicating that metabolic pathways are perturbed. Proteomic analysis identified adiponectin as a molecule that was significantly altered, which may play a role in tumor suppression. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

PubMed

Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk

2016-05-01

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hui; Shi, Tujin; Qian, Wei-Jun

2015-12-04

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

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

PubMed

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

2016-01-01

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Intraluminal proteome and peptidome of human urinary extracellular vesicles.

PubMed

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

2015-06-01

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

Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery.

PubMed

Prieto, DaRue A; Chan, King C; Johann, Donald J; Ye, Xiaoying; Whitely, Gordon; Blonder, Josip

2017-01-01

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

Application of proteomics in research on traditional Chinese medicine.

PubMed

Suo, Tongchuan; Wang, Haixia; Li, Zheng

2016-09-01

Traditional Chinese medicine (TCM) is a widely used complementary alternative medicine approach. Although many aspects of its effectiveness have been approved clinically, rigorous scientific techniques are highly required to translate the promises from TCM into powerful modern therapies. In this respect, proteomics is useful because of its ability to unveil the underlying target proteins and/or protein biomarkers. In this review, we summarize the recent interplay between proteomics and research on TCM, ranging from exploration of the medicinal materials to the biological basis of TCM concepts, and from pathological studies to pharmacological investigations. We show that proteomic analyses provide preliminary biological evidence of the promises in TCM, and the integration of proteomics with other omics and bioinformatics offers a comprehensive methodology to address the complications of TCM. Expert commentary: Currently, only limited information can be obtained regarding TCM issues and thus more work is required to resolve the ambiguity. As such, more collaborations between proteomics and other techniques (other omics, network pharmacology, etc.) are essential for deciphering the underlying biological basis in TCM topics.

Anthelmintic metabolism in parasitic helminths: proteomic insights.

PubMed

Brophy, Peter M; MacKintosh, Neil; Morphew, Russell M

2012-08-01

Anthelmintics are the cornerstone of parasitic helminth control. Surprisingly, understanding of the biochemical pathways used by parasitic helminths to detoxify anthelmintics is fragmented, despite the increasing global threat of anthelmintic resistance within the ruminant and equine industries. Reductionist biochemistry has likely over-estimated the enzymatic role of glutathione transferases in anthelmintic metabolism and neglected the potential role of the cytochrome P-450 superfamily (CYPs). Proteomic technologies offers the opportunity to support genomics, reverse genetics and pharmacokinetics, and provide an integrated insight into both the cellular mechanisms underpinning response to anthelmintics and also the identification of biomarker panels for monitoring the development of anthelmintic resistance. To date, there have been limited attempts to include proteomics in anthelmintic metabolism studies. Optimisations of membrane, post-translational modification and interaction proteomic technologies in helminths are needed to especially study Phase I CYPs and Phase III ABC transporter pumps for anthelmintics and their metabolites.

Identification of IGFBP2 and IGFBP3 As Compensatory Biomarkers for CA19-9 in Early-Stage Pancreatic Cancer Using a Combination of Antibody-Based and LC-MS/MS-Based Proteomics

PubMed Central

Yoneyama, Toshihiro; Ohtsuki, Sumio; Honda, Kazufumi; Kobayashi, Makoto; Iwasaki, Motoki; Uchida, Yasuo; Okusaka, Takuji; Nakamori, Shoji; Shimahara, Masashi; Ueno, Takaaki; Tsuchida, Akihiko; Sata, Naohiro; Ioka, Tatsuya; Yasunami, Yohichi; Kosuge, Tomoo; Kaneda, Takashi; Kato, Takao; Yagihara, Kazuhiro; Fujita, Shigeyuki; Huang, Wilber; Yamada, Tesshi; Tachikawa, Masanori; Terasaki, Tetsuya

2016-01-01

Pancreatic cancer is one of the most lethal tumors, and reliable detection of early-stage pancreatic cancer and risk diseases for pancreatic cancer is essential to improve the prognosis. As 260 genes were previously reported to be upregulated in invasive ductal adenocarcinoma of pancreas (IDACP) cells, quantification of the corresponding proteins in plasma might be useful for IDACP diagnosis. Therefore, the purpose of the present study was to identify plasma biomarkers for early detection of IDACP by using two proteomics strategies: antibody-based proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. Among the 260 genes, we focused on 130 encoded proteins with known function for which antibodies were available. Twenty-three proteins showed values of the area under the curve (AUC) of more than 0.8 in receiver operating characteristic (ROC) analysis of reverse-phase protein array (RPPA) data of IDACP patients compared with healthy controls, and these proteins were selected as biomarker candidates. We then used our high-throughput selected reaction monitoring or multiple reaction monitoring (SRM/MRM) methodology, together with an automated sample preparation system, micro LC and auto analysis system, to quantify these candidate proteins in plasma from healthy controls and IDACP patients on a large scale. The results revealed that insulin-like growth factor-binding protein (IGFBP)2 and IGFBP3 have the ability to discriminate IDACP patients at an early stage from healthy controls, and IGFBP2 appeared to be increased in risk diseases of pancreatic malignancy, such as intraductal papillary mucinous neoplasms (IPMNs). Furthermore, diagnosis of IDACP using the combination of carbohydrate antigen 19–9 (CA19-9), IGFBP2 and IGFBP3 is significantly more effective than CA19-9 alone. This suggests that IGFBP2 and IGFBP3 may serve as compensatory biomarkers for CA19-9. Early diagnosis with this marker combination may improve the prognosis of

Development of Biomarkers for Screening Hepatocellular Carcinoma Using Global Data Mining and Multiple Reaction Monitoring

PubMed Central

Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases. PMID:23717429

Development of biomarkers for screening hepatocellular carcinoma using global data mining and multiple reaction monitoring.

PubMed

Kim, Hyunsoo; Kim, Kyunggon; Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases.

Translational safety biomarkers of colonic barrier integrity in the rat.

PubMed

Erkens, Tim; Bueters, Ruud; van Heerden, Marjolein; Cuyckens, Filip; Vreeken, Rob; Goeminne, Nick; Lammens, Lieve

2018-05-20

The intestinal barrier controls intestinal permeability, and its disruption has been associated with multiple diseases. Therefore, preclinical safety biomarkers monitoring barrier integrity are essential during the development of drugs targeting the intestines, particularly if starting treatment early after onset of disease. Classical toxicology endpoints are not sensitive enough and therefore our objective was to identify non-invasive markers enabling early in vivo detection of colonic barrier perturbation. Male Sprague-Dawley rats were dosed intracolonically via the rectum, using sodium caprate or ibuprofen as tool compounds to alter barrier integrity. Several potentially translational biomarkers and probe molecules related to permeability, inflammation or tissue damage were evaluated, using various analytical platforms, including immunoassays, targeted metabolomics and highly sensitive ultra-performance liquid chromatography-tandem mass spectrometry. Several markers were identified that allow early in vivo detection of colonic barrier integrity changes, before histopathological evidence of tissue damage. The most promising permeability markers identified were plasma fluorescein isothiocyanate-dextran 4000 and a lactulose/mannitol/sucralose mixture in urine. These markers showed maximum increases over 100-fold or approximately 10-50-fold, respectively. Intracolonic administration of the above probe molecules outperformed oral administration and inflammatory or other biomarkers, such as α 2 -macroglobulin, calprotectin, cytokines, prostaglandins and a panel of metabolic molecules to identify early and subtle changes in barrier integrity. However, optimal timing of probe administration and sample collection is important for all markers evaluated. Inclusion of these probe molecules in preclinical toxicity studies might aid in risk assessment and the design of a clinical biomarker plan, as several of these markers have translational potential. Copyright © 2018 John

Capillary electrophoresis interfaced with a mass spectrometer (CE-MS): technical considerations and applicability for biomarker studies in animals.

PubMed

Albalat, Amaya; Husi, Holger; Siwy, Justyna; Nally, Jarlath E; McLauglin, Mark; Eckersall, Peter D; Mullen, William

2014-02-01

Proteomics is a growing field that has the potential to be applied to many biology-related disciplines. However, the study of the proteome has proven to be very challenging due to its high level of complexity when compared to genome and transcriptome data. In order to analyse this level of complexity, high resolution separation of peptides/proteins are needed together with high resolution analysers. Currently, liquid chromatography and capillary electrophoresis (CE) are the two most widely used separation techniques that can be coupled on-line with a mass spectrometer (MS). In CE, proteins/ peptides are separated according to their size, charge and shape leading to high resolving power. Although further progress in the area of sensitivity, throughput and proteome coverage are expected, MS-based proteomics have developed to a level at which they are habitually applied to study a wide range of biological questions. The aim of this review is to present CE-MS as a proteomic analytical platform for biomarker research that could be used in farm animal and veterinary studies. This is a MS-analytical platform that has been widely used for biomarker research in the biomedical field but its application in animal proteomic studies is relatively novel. The review will focus on introducing the CE-MS platform and the primary considerations for its application to biomarker research. Furthermore, current applications but more importantly potential application in the field of farm animals and veterinary science will be presented and discussed.

Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

PubMed

Borrebaeck, Carl A K

2017-03-01

Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

An effect size filter improves the reproducibility in spectral counting-based comparative proteomics.

PubMed

Gregori, Josep; Villarreal, Laura; Sánchez, Alex; Baselga, José; Villanueva, Josep

2013-12-16

The microarray community has shown that the low reproducibility observed in gene expression-based biomarker discovery studies is partially due to relying solely on p-values to get the lists of differentially expressed genes. Their conclusions recommended complementing the p-value cutoff with the use of effect-size criteria. The aim of this work was to evaluate the influence of such an effect-size filter on spectral counting-based comparative proteomic analysis. The results proved that the filter increased the number of true positives and decreased the number of false positives and the false discovery rate of the dataset. These results were confirmed by simulation experiments where the effect size filter was used to evaluate systematically variable fractions of differentially expressed proteins. Our results suggest that relaxing the p-value cut-off followed by a post-test filter based on effect size and signal level thresholds can increase the reproducibility of statistical results obtained in comparative proteomic analysis. Based on our work, we recommend using a filter consisting of a minimum absolute log2 fold change of 0.8 and a minimum signal of 2-4 SpC on the most abundant condition for the general practice of comparative proteomics. The implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of the results obtained among independent laboratories and MS platforms. Quality control analysis of microarray-based gene expression studies pointed out that the low reproducibility observed in the lists of differentially expressed genes could be partially attributed to the fact that these lists are generated relying solely on p-values. Our study has established that the implementation of an effect size post-test filter improves the statistical results of spectral count-based quantitative proteomics. The results proved that the filter increased the number of true positives whereas decreased

Prohibitin as an oxidative stress biomarker in the eye

PubMed Central

Lee, Hyunju; Arnouk, Hilal; Sripathi, Srinivas; Chen, Ping; Zhang, Ruonan; Hunt, Richard C.; Hrushesky, William J. M.; Chung, Hyewon; Lee, Sung Haeng; Jahng, Wan Jin

2016-01-01

Identification of biomarker proteins in the retina and the retinal pigment epithelium (RPE) under oxidative stress may imply new insights into signaling mechanisms of retinal degeneration at the molecular level. Proteomic data from an in vivo mice model in constant light and an in vitro oxidative stress model are compared to controls under normal conditions. Our proteomic study shows that prohibitin is involved in oxidative stress signaling in the retina and RPE. The identity of prohibitin in the retina and the RPE was studied using 2D electrophoresis, immunohistochemistry, western blot, and mass spectrometry analysis. Comparison of expression levels with apoptotic markers as well as translocation between mitochondria and the nucleus imply that the regulation of prohibitin is an early signaling event in the RPE and retina under oxidative stress. Immunohistochemical analysis of murine aged and diabetic eyes further suggests that the regulation of prohibitin in the RPE/retina is related to aging- and diabetes-induced oxidative stress. Our proteomic approach implies that prohibitin in the RPE and the retina could be a new biomarker protein of oxidative stress in aging and diabetes. PMID:20832420

Prohibitin as an oxidative stress biomarker in the eye.

PubMed

Lee, Hyunju; Arnouk, Hilal; Sripathi, Srinivas; Chen, Ping; Zhang, Ruonan; Bartoli, Manuela; Hunt, Richard C; Hrushesky, William J M; Chung, Hyewon; Lee, Sung Haeng; Jahng, Wan Jin

2010-12-01

Identification of biomarker proteins in the retina and retinal pigment epithelium (RPE) under oxidative stress may imply new insights into signaling mechanisms of retinal degeneration at the molecular level. Proteomic data from an in vivo mice model in constant light and an in vitro oxidative stress model are compared to controls under normal conditions. Our proteomic study shows that prohibitin is involved in oxidative stress signaling in the retina and RPE. The identity of prohibitin in the retina and RPE was studied using 2D electrophoresis, immunohistochemistry, western blot, and mass spectrometry analysis. Comparison of expression levels with apoptotic markers as well as translocation between mitochondria and the nucleus imply that the regulation of prohibitin is an early signaling event in the RPE and retina under oxidative stress. Immunohistochemical analysis of murine aged and diabetic eyes further suggests that the regulation of prohibitin in the RPE/retina is related to aging- and diabetes-induced oxidative stress. Our proteomic approach implies that prohibitin in the RPE and the retina could be a new biomarker protein of oxidative stress in aging and diabetes. Copyright © 2010 Elsevier B.V. All rights reserved.

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.

Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013.

PubMed

Viglio, Simona; Stolk, Jan; Iadarola, Paolo; Giuliano, Serena; Luisetti, Maurizio; Salvini, Roberta; Fumagalli, Marco; Bardoni, Anna

2014-01-22

To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

Targeting human pathogenic bacteria by siderophores: A proteomics review.

PubMed

Ferreira, Daniela; Seca, Ana M L; C G A, Diana; Silva, Artur M S

2016-08-11

Human bacterial infections are still a major public health problem throughout the world. Therefore it is fundamental to understand how pathogenic bacteria interact with their human host and to develop more advanced drugs or vaccines in response to the increasing bacterial resistance. Since iron is essential to bacterial survival and growth inside the host tissues, these microorganisms have developed highly efficient iron-acquisition systems; the most common one involves the secretion of iron chelators into the extracellular environment, known as siderophores, and the corresponding siderophore-membrane receptors or transporters responsible for the iron uptake. In the past few decades, several biochemical methods and genetic screens have been employed to track down and identify these iron-scavenging molecules. However, compared with the previous "static" approaches, proteomic identification is revealing far more molecules through full protein mapping and becoming more rapid and selective, leading the scientific and medical community to consider standardizing proteomic tools for clinical biomarker detection of bacterial infectious diseases. In this review, we focus on human pathogenic Gram-negative bacteria and discuss the importance of siderophores in their virulence and the available proteomic strategies to identify siderophore-related proteins and their expression level under different growth conditions. The promising use of siderophore antibiotics to overcome bacterial resistance and the future of proteomics in the routine clinical care are also mentioned. Proteomic strategies to identify siderophore-related proteins and their expression level can be helpful to control and/or find a cure of infectious deseases especially if related with multidrug resistance. Siderophores are low-molecular-weight compounds produced by bacteria which can become clinical biomarkers and/or antibiotics used mainly in "Trojan horse" type strategies. Due to the above mention we think

Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics.

PubMed

Dittrich, Julia; Ceglarek, Uta

2017-01-01

The increasing number of peptide and protein biomarker candidates requires expeditious and reliable quantification strategies. The utilization of liquid chromatography coupled to quadrupole tandem mass spectrometry (LC-MS/MS) for the absolute quantitation of plasma proteins and peptides facilitates the multiplexed verification of tens to hundreds of biomarkers from smallest sample quantities. Targeted proteomics assays derived from bottom-up proteomics principles rely on the identification and analysis of proteotypic peptides formed in an enzymatic digestion of the target protein. This protocol proposes a procedure for the establishment of a targeted absolute quantitation method for middle- to high-abundant plasma proteins waiving depletion or enrichment steps. Essential topics as proteotypic peptide identification and LC-MS/MS method development as well as sample preparation and calibration strategies are described in detail.

Proteomic profiling of eccrine sweat reveals its potential as a diagnostic biofluid for active tuberculosis.

PubMed

Adewole, Olanisun Olufemi; Erhabor, Greg Efosa; Adewole, Temitayo Oluwatoyin; Ojo, Abiodun Oluwasesan; Oshokoya, Harriet; Wolfe, Lisa M; Prenni, Jessica E

2016-05-01

Excessive sweating is a common symptom of the disease and an unexplored biofluid for TB diagnosis; we conducted a proof-of-concept study to identify potential diagnostic biomarkers of active TB in eccrine sweat. We performed a global proteomic profile of eccrine sweat sampled from patients with active pulmonary TB, other lung diseases (non-TB disease), and healthy controls. A comparison of proteomics between Active-TB, Non-TB, and Healthy Controls was done in search for potential biomarkers of active TB. Sweat specimens were pooled from 32 active TB patients, 27 patients with non-TB diseases, and 24 apparently healthy controls, all were negative for HIV. Over 100 unique proteins were identified in the eccrine sweat of all three groups. Twenty-six proteins were exclusively detected in the sweat of patients with active TB while the remaining detected proteins overlapped between three groups. Gene ontology evaluation indicated that the proteins detected uniquely in sweat of active TB patients were involved in immune response and auxiliary protein transport. Gene products for cellular components (e.g. ribosomes) were detected only in active TB patients. Data are available via ProteomeXchange with identifier PXD003224. Proteomics of sweat from active TB patients is a viable approach for biomarker identification, which could be used to develop a nonsputum-based test for detection of active TB. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

SELDI PROTEINCHIP-BASED LIVER BIOMARKERS IN FUNGICIDE EXPOSED ZEBRAFISH

EPA Science Inventory

The research presented here is part of a three-phased small fish computational toxicology project using a combination of 1) whole organism endpoints, 2) genomic, proteomic, and metabolomic approaches, and 3) computational modeling to (a) identify new molecular biomarkers of expos...

Proteomic analysis of acetaminophen-induced hepatotoxicity and identification of heme oxygenase 1 as a potential plasma biomarker of liver injury.

PubMed

Gao, Yuan; Cao, Zhijun; Yang, Xi; Abdelmegeed, Mohamed A; Sun, Jinchun; Chen, Si; Beger, Richard D; Davis, Kelly; Salminen, William F; Song, Byoung-Joon; Mendrick, Donna L; Yu, Li-Rong

2017-01-01

Overdose of acetaminophen (APAP) is a major cause of acute liver failure. This study was aimed to identify pathways related to hepatotoxicity and potential biomarkers of liver injury. Rats were treated with low (100 mg/kg) and high (1250 mg/kg) doses of APAP, and liver tissues at 6 and 24 h post-treatment were analyzed using a proteomic approach of 16O/18O labeling and 2D-LC-MS/MS. Molecular pathways evolved progressively from scattered and less significant perturbations to more focused and significant alterations in a dose- and time-dependent manner upon APAP treatment. Imbalanced expression of hemeoxygenase 1 (HMOX1) and biliverdin reductase A (BLVRA) was associated with hepatotoxicity. Protein abundance changes of a total of 31 proteins were uniquely correlated to liver damage, among which a dramatic increase of HMOX1 levels in plasma was observed. Liver injury-associated significant elevation of plasma HMOX1 was further validated in mice treated with APAP. This study unveiled molecular changes associated with APAP-induced liver toxicity at the pathway levels and identified HMOX1 as a potential plasma biomarker of liver injury. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Multiple reaction monitoring (MRM) of plasma proteins in cardiovascular proteomics.

PubMed

Dardé, Verónica M; Barderas, Maria G; Vivanco, Fernando

2013-01-01

Different methodologies have been used through years to discover new potential biomarkers related with cardiovascular risk. The conventional proteomic strategy involves a discovery phase that requires the use of mass spectrometry (MS) and a validation phase, usually on an alternative platform such as immunoassays that can be further implemented in clinical practice. This approach is suitable for a single biomarker, but when large panels of biomarkers must be validated, the process becomes inefficient and costly. Therefore, it is essential to find an alternative methodology to perform the biomarker discovery, validation, and -quantification. The skills provided by quantitative MS turn it into an extremely attractive alternative to antibody-based technologies. Although it has been traditionally used for quantification of small molecules in clinical chemistry, MRM is now emerging as an alternative to traditional immunoassays for candidate protein biomarker validation.

A comprehensive proteomics study on platelet concentrates: Platelet proteome, storage time and Mirasol pathogen reduction technology.

PubMed

Salunkhe, Vishal; De Cuyper, Iris M; Papadopoulos, Petros; van der Meer, Pieter F; Daal, Brunette B; Villa-Fajardo, María; de Korte, Dirk; van den Berg, Timo K; Gutiérrez, Laura

2018-03-19

Platelet concentrates (PCs) represent a blood transfusion product with a major concern for safety as their storage temperature (20-24°C) allows bacterial growth, and their maximum storage time period (less than a week) precludes complete microbiological testing. Pathogen inactivation technologies (PITs) provide an additional layer of safety to the blood transfusion products from known and unknown pathogens such as bacteria, viruses, and parasites. In this context, PITs, such as Mirasol Pathogen Reduction Technology (PRT), have been developed and are implemented in many countries. However, several studies have shown in vitro that Mirasol PRT induces a certain level of platelet shape change, hyperactivation, basal degranulation, and increased oxidative damage during storage. It has been suggested that Mirasol PRT might accelerate what has been described as the platelet storage lesion (PSL), but supportive molecular signatures have not been obtained. We aimed at dissecting the influence of both variables, that is, Mirasol PRT and storage time, at the proteome level. We present comprehensive proteomics data analysis of Control PCs and PCs treated with Mirasol PRT at storage days 1, 2, 6, and 8. Our workflow was set to perform proteomics analysis using a gel-free and label-free quantification (LFQ) approach. Semi-quantification was based on LFQ signal intensities of identified proteins using MaxQuant/Perseus software platform. Data are available via ProteomeXchange with identifier PXD008119. We identified marginal differences between Mirasol PRT and Control PCs during storage. However, those significant changes at the proteome level were specifically related to the functional aspects previously described to affect platelets upon Mirasol PRT. In addition, the effect of Mirasol PRT on the platelet proteome appeared not to be exclusively due to an accelerated or enhanced PSL. In summary, semi-quantitative proteomics allows to discern between proteome changes due to

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

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

PubMed

Wu, Long; Peng, Chun-Wei; Hou, Jin-Xuan; Zhang, Yan-Hua; Chen, Chuang; Chen, Liang-Dong; Li, Yan

2010-02-24

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. 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. 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. Coronin-1C could be a candidate biomarker to predict HCC invasive behavior.

Innovative use of novel biomarkers to improve the safety of renally-eliminated and nephrotoxic medications.

PubMed

Barreto, Erin F; Rule, Andrew D; Voils, Stacy A; Kane-Gill, Sandra L

2018-06-08

Over the last decade, the discovery and research into the application of novel renal biomarkers to improve medication efficacy and safety has expanded considerably. Pharmacists are uniquely positioned to leverage this new technology for renal assessment to improve medication dosing and monitoring. Serum cystatin C is a relatively new, inexpensive, functional renal biomarker that responds more quickly to changing renal function than creatinine and is not meaningfully affected by age, sex, skeletal muscle mass, dietary intake, or deconditioning. Cystatin C has been proposed as an adjunct or alternative to creatinine for glomerular filtration rate (GFR) assessment and estimation of drug clearance. Tissue inhibitor of metalloproteinase-2●insulin-like growth factor-binding protein 7 ([TIMP-2]●[IGFBP7]) is a composite of two damage biomarkers released into the urine at a checkpoint in mitosis when renal cells undergo stress or sense a future risk of damage. Concentrations of [TIMP-2]●[IGFBP7] increase before a rise in serum creatinine is evident, thus providing insightful information for evaluation in the context of other patient data to predict the risk for impending kidney injury. The purpose for this article is to provide a brief overview of novel renal biomarkers that are being used as a mechanism to improve medication safety, including discussion of cystatin C, as part of drug-dosing algorithms and specifically for vancomycin dosing, and use of [TIMP-2]●[IGFBP7] for risk prediction in acute kidney injury and drug-induced kidney disease. Select cases of clinical experience with use of novel renal biomarkers are outlined, and lessons learned and future applications are described. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Cardiovascular Redox and Ox Stress Proteomics

PubMed Central

Kumar, Vikas; Calamaras, Timothy Dean; Haeussler, Dagmar; Colucci, Wilson Steven; Cohen, Richard Alan; McComb, Mark Errol; Pimentel, David

2012-01-01

Abstract Significance: Oxidative post-translational modifications (OPTMs) have been demonstrated as contributing to cardiovascular physiology and pathophysiology. These modifications have been identified using antibodies as well as advanced proteomic methods, and the functional importance of each is beginning to be understood using transgenic and gene deletion animal models. Given that OPTMs are involved in cardiovascular pathology, the use of these modifications as biomarkers and predictors of disease has significant therapeutic potential. Adequate understanding of the chemistry of the OPTMs is necessary to determine what may occur in vivo and which modifications would best serve as biomarkers. Recent Advances: By using mass spectrometry, advanced labeling techniques, and antibody identification, OPTMs have become accessible to a larger proportion of the scientific community. Advancements in instrumentation, database search algorithms, and processing speed have allowed MS to fully expand on the proteome of OPTMs. In addition, the role of enzymatically reversible OPTMs has been further clarified in preclinical models. Critical Issues: The identification of OPTMs suffers from limitations in analytic detection based on the methodology, instrumentation, sample complexity, and bioinformatics. Currently, each type of OPTM requires a specific strategy for identification, and generalized approaches result in an incomplete assessment. Future Directions: Novel types of highly sensitive MS instrumentation that allow for improved separation and detection of modified proteins and peptides have been crucial in the discovery of OPTMs and biomarkers. To further advance the identification of relevant OPTMs in advanced search algorithms, standardized methods for sample processing and depository of MS data will be required. Antioxid. Redox Signal. 17, 1528–1559. PMID:22607061

Top-down Proteomics in Health and Disease: Challenges and Opportunities

PubMed Central

Gregorich, Zachery R.; Ge, Ying

2014-01-01

Proteomics is essential for deciphering how molecules interact as a system and for understanding the functions of cellular systems in human disease; however, the unique characteristics of the human proteome, which include a high dynamic range of protein expression and extreme complexity due to a plethora of post-translational modifications (PTMs) and sequence variations, make such analyses challenging. An emerging “top-down” mass spectrometry (MS)-based proteomics approach, which provides a “bird’s eye” view of all proteoforms, has unique advantages for the assessment of PTMs and sequence variations. Recently, a number of studies have showcased the potential of top-down proteomics for unraveling of disease mechanisms and discovery of new biomarkers. Nevertheless, the top-down approach still faces significant challenges in terms of protein solubility, separation, and the detection of large intact proteins, as well as the under-developed data analysis tools. Consequently, new technological developments are urgently needed to advance the field of top-down proteomics. Herein, we intend to provide an overview of the recent applications of top-down proteomics in biomedical research. Moreover, we will outline the challenges and opportunities facing top-down proteomics strategies aimed at understanding and diagnosing human diseases. PMID:24723472

SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer.

PubMed

Petricoin, Emanuel F; Liotta, Lance A

2004-02-01

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

Biomarkers to guide clinical therapeutics in rheumatology?

PubMed

Robinson, William H; Mao, Rong

2016-03-01

The use of biomarkers in rheumatology can help identify disease risk, improve diagnosis and prognosis, target therapy, assess response to treatment, and further our understanding of the underlying pathogenesis of disease. Here, we discuss the recent advances in biomarkers for rheumatic disorders, existing impediments to progress in this field, and the potential of biomarkers to enable precision medicine and thereby transform rheumatology. Although significant challenges remain, progress continues to be made in biomarker discovery and development for rheumatic diseases. The use of next-generation technologies, including large-scale sequencing, proteomic technologies, metabolomic technologies, mass cytometry, and other single-cell analysis and multianalyte analysis technologies, has yielded a slew of new candidate biomarkers. Nevertheless, these biomarkers still require rigorous validation and have yet to make their way into clinical practice and therapeutic development. This review focuses on advances in the biomarker field in the last 12 months as well as the challenges that remain. Better biomarkers, ideally mechanistic ones, are needed to guide clinical decision making in rheumatology. Although the use of next-generation techniques for biomarker discovery is making headway, it is imperative that the roadblocks in our search for new biomarkers are overcome to enable identification of biomarkers with greater diagnostic and predictive utility. Identification of biomarkers with robust diagnostic and predictive utility would enable precision medicine in rheumatology.

Clinical potential of proteomics in the diagnosis of ovarian cancer.

PubMed

Ardekani, Ali M; Liotta, Lance A; Petricoin, Emanuel F

2002-07-01

The need for specific and sensitive markers of ovarian cancer is critical. Finding a sensitive and specific test for its detection has an important public health impact. Currently, there are no effective screening options available for patients with ovarian cancer. CA-125, the most widely used biomarker for ovarian cancer, does not have a high positive predictive value and it is only effective when used in combination with other diagnostic tests. However, pathologic changes taking place within the ovary may be reflected in biomarker patterns in the serum. Combination of mass spectra generated by new proteomic technologies, such as surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) and artificial-intelligence-based informatic algorithms, have been used to discover a small set of key protein values and discriminate normal from ovarian cancer patients. Serum proteomic pattern analysis might be applied ultimately in medical screening clinics, as a supplement to the diagnostic work-up and evaluation.

Responses of Mytilus galloprovincialis to bacterial challenges by metabolomics and proteomics.

PubMed

Ji, Chenglong; Wu, Huifeng; Wei, Lei; Zhao, Jianmin; Wang, Qing; Lu, Hongjian

2013-08-01

Pathogens can cause diseases and lead to massive mortalities of aquaculture animals and substantial economic loss. In this work, we studied the responses induced by Micrococcus luteus and Vibrio anguillarum in gill of mussel Mytilus galloprovincialis at protein and metabolite levels. Metabolic biomarkers (e.g., amino acids, betaine, ATP) suggested that both M. luteus and V. anguillarum induced disturbances in energy metabolism and osmotic regulation. The unique and some more remarkably altered metabolic biomarkers (threonine, alanine, aspartate, taurine, succinate) demonstrated that V. anguillarum could cause more severe disturbances in osmotic regulation and energy metabolism. Proteomic biomarkers (e.g., goose-type lysozyme 2, matrilin, ependymin-related protein, peptidyl-prolyl cis-trans isomerases) indicated that M. luteus caused immune stress, and disturbances in signaling pathways and protein synthesis. However, V. anguillarum mainly induced oxidative stress and disturbance in energy metabolism in mussel gills indicated by altered procollagen-proline dioxygenase, protein disulfide isomerase, nucleoside diphosphate kinases, electron transfer flavoprotein and glutathione S-transferase. This work confirmed that an integration of proteomics and metabolomics could provide an insightful view into the effects of pathogens to the marine mussel M. galloprovincialis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dried Blood Spot Proteomics: Surface Extraction of Endogenous Proteins Coupled with Automated Sample Preparation and Mass Spectrometry Analysis

NASA Astrophysics Data System (ADS)

Martin, Nicholas J.; Bunch, Josephine; Cooper, Helen J.

2013-08-01

Dried blood spots offer many advantages as a sample format including ease and safety of transport and handling. To date, the majority of mass spectrometry analyses of dried blood spots have focused on small molecules or hemoglobin. However, dried blood spots are a potentially rich source of protein biomarkers, an area that has been overlooked. To address this issue, we have applied an untargeted bottom-up proteomics approach to the analysis of dried blood spots. We present an automated and integrated method for extraction of endogenous proteins from the surface of dried blood spots and sample preparation via trypsin digestion by use of the Advion Biosciences Triversa Nanomate robotic platform. Liquid chromatography tandem mass spectrometry of the resulting digests enabled identification of 120 proteins from a single dried blood spot. The proteins identified cross a concentration range of four orders of magnitude. The method is evaluated and the results discussed in terms of the proteins identified and their potential use as biomarkers in screening programs.

Clinical proteomic analysis of scrub typhus infection.

PubMed

Park, Edmond Changkyun; Lee, Sang-Yeop; Yun, Sung Ho; Choi, Chi-Won; Lee, Hayoung; Song, Hyun Seok; Jun, Sangmi; Kim, Gun-Hwa; Lee, Chang-Seop; Kim, Seung Il

2018-01-01

Scrub typhus is an acute and febrile infectious disease caused by the Gram-negative α-proteobacterium Orientia tsutsugamushi from the family Rickettsiaceae that is widely distributed in Northern, Southern and Eastern Asia. In the present study, we analysed the serum proteome of scrub typhus patients to investigate specific clinical protein patterns in an attempt to explain pathophysiology and discover potential biomarkers of infection. Serum samples were collected from three patients (before and after treatment with antibiotics) and three healthy subjects. One-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry was performed to identify differentially abundant proteins using quantitative proteomic approaches. Bioinformatic analysis was then performed using Ingenuity Pathway Analysis. Proteomic analysis identified 236 serum proteins, of which 32 were differentially expressed in normal subjects, naive scrub typhus patients and patients treated with antibiotics. Comparative bioinformatic analysis of the identified proteins revealed up-regulation of proteins involved in immune responses, especially complement system, following infection with O. tsutsugamushi , and normal expression was largely rescued by antibiotic treatment. This is the first proteomic study of clinical serum samples from scrub typhus patients. Proteomic analysis identified changes in protein expression upon infection with O. tsutsugamushi and following antibiotic treatment. Our results provide valuable information for further investigation of scrub typhus therapy and diagnosis.

Urinary proteomics in renal pathophysiology: Impact of proteinuria.

PubMed

Sancho-Martínez, Sandra M; Prieto-García, Laura; Blanco-Gozalo, Víctor; Fontecha-Barriuso, Miguel; López-Novoa, José M; López-Hernández, Francisco J

2015-06-01

Urinary differential proteomics is used to study renal pathophysiological mechanisms, find novel markers of biological processes and renal diseases, and stratify patients according to proteomic profiles. The proteomic procedure determines the pathophysiological meaning and clinical relevance of results. Urine samples for differential proteomic studies are usually normalized by protein content, regardless of its pathophysiological characteristics. In the field of nephrology, this approach translates into the comparison of a different fraction of the total daily urine output between proteinuric and nonproteinuric samples. Accordingly, alterations in the level of specific proteins found by this method reflect the relative presence of individual proteins in the urine; but they do not necessarily show alterations in their daily excretion, which is a key parameter for the understanding of the pathophysiological meaning of urinary components. For renal pathophysiology studies and clinical biomarker identification or determination, an alternative proteomic concept providing complementary information is based on sample normalization by daily urine output, which directly informs on changes in the daily excretion of individual proteins. This is clinically important because daily excretion (rather than absolute or relative concentration) is the only self-normalized way to evaluate the real meaning of urinary parameters, which is also independent of urine concentration. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2007-01-01

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

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

PubMed Central

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

2007-01-01

Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools. PMID:17090601

Genomic atlas of the human plasma proteome.

PubMed

Sun, Benjamin B; Maranville, Joseph C; Peters, James E; Stacey, David; Staley, James R; Blackshaw, James; Burgess, Stephen; Jiang, Tao; Paige, Ellie; Surendran, Praveen; Oliver-Williams, Clare; Kamat, Mihir A; Prins, Bram P; Wilcox, Sheri K; Zimmerman, Erik S; Chi, An; Bansal, Narinder; Spain, Sarah L; Wood, Angela M; Morrell, Nicholas W; Bradley, John R; Janjic, Nebojsa; Roberts, David J; Ouwehand, Willem H; Todd, John A; Soranzo, Nicole; Suhre, Karsten; Paul, Dirk S; Fox, Caroline S; Plenge, Robert M; Danesh, John; Runz, Heiko; Butterworth, Adam S

2018-06-01

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.

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

PubMed

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

2014-08-01

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

Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase.

PubMed

Sanchez-Niño, Maria Dolores; Sanz, Ana B; Ramos, Adrian M; Fernandez-Fernandez, Beatriz; Ortiz, Alberto

2017-04-01

Exponential technologies double in power or processing speed every year, whereas their cost halves. Deception and disruption are two key stages in the development of exponential technologies. Deception occurs when, after initial introduction, technologies are dismissed as irrelevant, while they continue to progress, perhaps not as fast or with so many immediate practical applications as initially thought. Twenty years after the first publications, clinical proteomics is still not available in most hospitals and some clinicians have felt deception at unfulfilled promises. However, there are indications that clinical proteomics may be entering the disruptive phase, where, once refined, technologies disrupt established industries or procedures. In this regard, recent manuscripts in CKJ illustrate how proteomics is entering the clinical realm, with applications ranging from the identification of amyloid proteins in the pathology lab, to a new generation of urinary biomarkers for chronic kidney disease (CKD) assessment and outcome prediction. Indeed, one such panel of urinary peptidomics biomarkers, CKD273, recently received a Food and Drug Administration letter of support, the first ever in the CKD field. In addition, a must-read resource providing information on kidney disease-related proteomics and systems biology databases and how to access and use them in clinical decision-making was also recently published in CKJ .

Proteomic and metabolomic responses in hepatopancreas of Mytilus galloprovincialis challenged by Micrococcus luteus and Vibrio anguillarum.

PubMed

Wu, Huifeng; Ji, Chenglong; Wei, Lei; Zhao, Jianmin; Lu, Hongjian

2013-12-06

The outbreak of pathogens can induce diseases and lead to massive mortalities of aquaculture animals including fish, mollusk and shrimp. In this work, the responses induced by Micrococcus luteus and Vibrio anguillarum were investigated in hepatopancreas of mussel Mytilus galloprovincialis using proteomics and metabolomics. Metabolic biomarkers demonstrated that M. luteus and V. anguillarum injections could induce osmotic stress and disturbance in energy metabolism. And the uniquely and more markedly altered metabolic biomarkers (glutamine, succinate, aspartate, glucose, ATP, homarine and tyrosine) indicated that V. anguillarum could cause more severe disturbances in osmotic regulation and energy metabolism. The differentially altered proteins meant that M. luteus and V. anguillarum induced different effects in mussels. However, the common proteomic biomarkers, arginine kinase and small heat shock protein, demonstrated that these two bacteria induced similar effects including oxidative stress and disturbance in energy metabolism in M. galloprovincialis. In addition, some metabolic biomarkers, ATP and glutamine, were confirmed by related proteins including arginine kinase, ATP synthase, nucleoside diphosphate kinase and glutamine synthetase in bacteria-challenged mussels. This study demonstrated that proteomics and metabolomics could provide an insightful view into the effects of environmental pathogens to the marine mussel M. galloprovincialis. The outbreak of pathogens can lead to diseases and massive mortalities of aquaculture animals including fish, mollusk and shrimp. The mussel M. galloprovincialis distributes widely along the Bohai coast and is popularly consumed as delicious seafood by local residents. This bivalve has become one of the important species in marine aquaculture industry in China. Therefore a study on pathogen-induced effects is necessary. In the present study, an integrated metabolomic and proteomic approach was used to elucidate the

Proteomics analysis of dendritic cell activation by contact allergens reveals possible biomarkers regulated by Nrf2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mussotter, Franz, E-mail: franz.mussotter@bfr.bund

Allergic contact dermatitis is a widespread disease with high clinical relevance affecting approximately 20% of the general population. Typically, contact allergens are low molecular weight electrophilic compounds which can activate the Keap1/Nrf2 pathway. We performed a proteomics study to reveal possible biomarkers for dendritic cell (DC) activation by contact allergens and to further elucidate the role of Keap1/Nrf2 signaling in this process. We used bone marrow derived dendritic cells (BMDCs) of wild-type (nrf2{sup +/+}) and Nrf2 knockout (nrf2{sup −/−}) mice and studied their response against the model contact sensitizers 2,4-dinitrochlorobenzene (DNCB), cinnamaldehyde (CA) and nickel(II) sulfate by 2-dimensional polyacrylamide gelmore » electrophoresis (2D-PAGE) in combination with electrospray ionization tandem mass spectrometry (ESI-MS/MS). Sodium dodecyl sulfate (SDS, 100 μM) served as irritant control. While treatment with nickel(II) sulfate and SDS had only little effects, CA and DNCB led to significant changes in protein expression. We found 18 and 30 protein spots up-regulated in wild-type cells treated with 50 and 100 μM CA, respectively. For 5 and 10 μM DNCB, 32 and 37 spots were up-regulated, respectively. Almost all of these proteins were not differentially expressed in nrf2{sup −/−} BMDCs, indicating an Nrf2-dependent regulation. Among them proteins were detected which are involved in oxidative stress and heat shock responses, as well as in signal transduction or basic cellular pathways. The applied approach allowed us to differentiate between Nrf2-dependent and Nrf2-independent cellular biomarkers differentially regulated upon allergen-induced DC activation. The data presented might contribute to the further development of suitable in vitro testing methods for chemical-mediated sensitization. - Highlights: • Contact allergens induce proteins involved in DC maturation Nrf2-dependently. • Induction of these proteins points to a

Proteomic approach for identifying gonad differential proteins in the oyster (Crassostrea angulata) following food-chain contamination with HgCl2.

PubMed

Zhang, Qing-Hong; Huang, Lin; Zhang, Yong; Ke, Cai-Huan; Huang, He-Qing

2013-12-06

Hg discharged into the environmental waters can generally be bioaccumulated, transformed and transmited by living organisms, thus resulting in the formation of Hg-toxicity food chains. The pathway and toxicology of food chain contaminated with environmental Hg are rarely revealed by proteomics. Here, we showed that differential proteomics had the potential to understand reproduction toxicity mechanism in marine molluscs through the Hg-contaminated food chain. Hg bioaccumulation was found in every link of the HgCl2-Chlorella vulgaris-oyster-mice food chain. Morphological observations identified the lesions in both the oyster gonad and the mice ovary. Differential proteomics was used to study the mechanisms of Hg toxicity in the oyster gonad and to find some biomarkers of Hg contamination in food chain. Using 2-DE and MALDI-TOF/TOF MS, we identified 13 differential protein spots, of which six were up-regulated, six were down-regulated, while one was undecided. A portion of these differential proteins was further confirmed using real-time PCR and western blotting methods. Their major functions involved binding, protein translocation, catalysis, regulation of energy metabolism, reproductive functioning and structural molecular activity. Among these proteins, 14-3-3 protein, GTP binding protein, arginine kinase (AK) and 71kDa heat shock connate protein (HSCP 71) are considered to be suitable biomarkers of environmental Hg contamination. Furthermore, we established the gene correspondence, responding to Hg reproductive toxicity, between mouse and oyster, and then used real-time PCR to analyze mRNA differential expression of the corresponding genes in mice. The results indicated that the mechanism of Hg reproductive toxicity in mouse was similar to that in oyster. We suggest that the proteomics would be further developed in application research of food safety including toxicological mechanism. It is well known that mercury (Hg) is one of the best toxic metal elements in

Proteomic analysis of tissue samples in translational breast cancer research.

PubMed

Gromov, Pavel; Moreira, José M A; Gromova, Irina

2014-06-01

In the last decade, many proteomic technologies have been applied, with varying success, to the study of tissue samples of breast carcinoma for protein expression profiling in order to discover protein biomarkers/signatures suitable for: characterization and subtyping of tumors; early diagnosis, and both prognosis and prediction of outcome of chemotherapy. The purpose of this review is to critically appraise what has been achieved to date using proteomic technologies and to bring forward novel strategies - based on the analysis of clinically relevant samples - that promise to accelerate the translation of basic discoveries into the daily breast cancer clinical practice. In particular, we address major issues in experimental design by reviewing the strengths and weaknesses of current proteomic strategies in the context of the analysis of human breast tissue specimens.

Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

NASA Astrophysics Data System (ADS)

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

2017-01-01

The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

Proteomic identification of potential biomarkers for cervical squamous cell carcinoma and human papillomavirus infection.

PubMed

Qing, Song; Tulake, Wuniqiemu; Ru, Mingfang; Li, Xiaohong; Yuemaier, Reziwanguli; Lidifu, Dilare; Rouzibilali, Aierken; Hasimu, Axiangu; Yang, Yun; Rouziahong, Reziya; Upur, Halmurat; Abudula, Abulizi

2017-04-01

It is known that high-risk human papillomavirus infection is the main etiological factor in cervical carcinogenesis. However, human papillomavirus screening is not sufficient for early diagnosis. In this study, we aimed to identify potential biomarkers common to cervical carcinoma and human papillomavirus infection by proteomics for human papillomavirus-based early diagnosis and prognosis. To this end, we collected 76 cases of fresh cervical tissues and 116 cases of paraffin-embedded tissue slices, diagnosed as cervical squamous cell carcinoma, cervical intraepithelial neoplasia II-III, or normal cervix from ethnic Uighur and Han women. Human papillomavirus infection by eight oncogenic human papillomavirus types was detected in tissue DNA samples using a quantitative polymerase chain reaction. The protein profile of cervical specimens from human papillomavirus 16-positive squamous cell carcinoma and human papillomavirus-negative normal controls was analyzed by proteomics and bioinformatics. The expression of candidate proteins was further determined by quantitative reverse transcriptase-polymerase chain reaction and immunohistochemistry. We identified 67 proteins that were differentially expressed in human papillomavirus 16-positive squamous cell carcinoma compared to normal cervix. The quantitative reverse transcriptase-polymerase chain reaction analysis verified the upregulation of ASAH1, PCBP2, DDX5, MCM5, TAGLN2, hnRNPA1, ENO1, TYPH, CYC, and MCM4 in squamous cell carcinoma compared to normal cervix ( p < 0.05). In addition, the transcription of PCBP2, MCM5, hnRNPA1, TYPH, and CYC was also significantly increased in cervical intraepithelial neoplasia II-III compared to normal cervix. Immunohistochemistry staining further confirmed the overexpression of PCBP2, hnRNPA1, ASAH1, and DDX5 in squamous cell carcinoma and cervical intraepithelial neoplasia II-III compared to normal controls ( p < 0.05). Our data suggest that the expression of ASAH1, PCBP2, DDX5

A proteomic-based investigation of potential copper-responsive biomarkers: Proteins, conceptual networks, and metabolic pathways featuring Penicillium janthinellum from a heavy metal-polluted ecological niche.

PubMed

Feng, Xin; Xu, Jian; Liang, Yu; Chen, Guo-Li; Fan, Xian-Wei; Li, You-Zhi

2017-08-01

Filamentous fungi-copper (Cu) interactions are very important in the formation of natural ecosystems and the bioremediation of heavy metal pollution. However, important issues at the proteome level remain unclear. We compared six proteomes from Cu-resistant wild-type (WT) Penicillium janthinellum strain GXCR and a Cu-sensitive mutant (EC-6) under 0, 0.5, and 3 mmol/L Cu treatments using iTRAQ. A total of 495 known proteins were identified, and the following conclusions were drawn from the results: Cu tolerance depends on ATP generation and supply, which is relevant to glycolysis pathway activity; oxidative phosphorylation, the TCA cycle, gluconeogenesis, fatty acid synthesis, and metabolism are also affected by Cu; high Cu sensitivity is primarily due to an ATP energy deficit; among ATP generation pathways, Cu-sensitive and Cu-insensitive metabolic steps exist; gluconeogenesis pathway is crucial to the survival of fungi in Cu-containing and sugar-scarce environments; fungi change their proteomes via two routes (from ATP, ATP-dependent RNA helicases (ADRHs), and ribosome biogenesis to proteasomes and from ATP, ADRHs to spliceosomes and/or stress-adapted RNA degradosomes) to cope with changes in Cu concentrations; and unique routes exist through which fungi respond to high environmental Cu. Further, a general diagram of Cu-responsive paths and a model theory of high Cu are proposed at the proteome level. Our work not only provides the potential protein biomarkers that indicate Cu pollution and targets metabolic steps for engineering Cu-tolerant fungi during bioremediation but also presents clues for further insight into the heavy metal tolerance mechanisms of other eukaryotes. © 2017 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

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

PubMed

Soler, L; Oswald, I P

2018-04-30

Mycotoxins are natural food and feed contaminants that are toxic to human and animals. Proteomics is an adequate toolbox to investigate the mode of action and the effects of mycotoxins, as these toxicants often alter protein synthesis and degradation, as well as induce changes of important post-translational modifications. For instance, the contaminant deoxynivalenol induces a severe ribosomal stress that affects protein production, whereas the toxin Fumonisin B1 can alter the phosphorylation of a large number of proteins, and patulin is a potent proteotoxic molecule. The response to most mycotoxins is sex-dependent, males being generally more sensitive than females. In addition, for some toxins, the toxic effects observed were different for each sex. Nevertheless, the importance of accounting for a sex-dependent response is often overlooked in toxicology studies involving mycotoxins. Here we review the information that proteomics has provided in pre-clinical studies of mycotoxin exposure as well as the differential response of males and females to these molecules to highlight the need of including male and female individuals when evaluating the impact of mycotoxins in the cell proteome. The current trend in mycotoxicology is the combination of several -omics techniques in order to understand the mechanism of action and effects of these toxic natural food contaminants. One of the goals of these experiments is to determine "potential biomarkers" of mycotoxicoses. Nevertheless, the strategy followed in biomarker research must take into account as many possible factors as possible in order to find robust biomarkers for differential diagnosis. Among the factors that can have an influence in the response to mycotoxins, one of the most important is sex. Traditionally, males are preferentially used in research, as they are more sensitive to mycotoxins and their response is not dependent on hormonal levels, thus less variable. However the intrinsic and hormonal differences

PSA and beyond: alternative prostate cancer biomarkers

PubMed Central

2016-01-01

Background The use of biomarkers for prostate cancer screening, diagnosis and prognosis has the potential to improve the clinical management of the patients. Owing to inherent limitations of the biomarker prostate-specific antigen (PSA), intensive efforts are currently directed towards a search for alternative prostate cancer biomarkers, particularly those that can predict disease aggressiveness and drive better treatment decisions. Methods A literature search of Medline articles focused on recent and emerging advances in prostate cancer biomarkers was performed. The most promising biomarkers that have the potential to meet the unmet clinical needs in prostate cancer patient management and/or that are clinically implemented were selected. Conclusions With the advent of advanced genomic and proteomic technologies, we have in recent years seen an enormous spurt in prostate cancer biomarker research with several promising alternative biomarkers being discovered that show an improved sensitivity and specificity over PSA. The new generation of biomarkers can be tested via serum, urine, or tissue-based assays that have either received regulatory approval by the US Food and Drug Administration or are available as Clinical Laboratory Improvement Amendments-based laboratory developed tests. Additional emerging novel biomarkers for prostate cancer, including circulating tumor cells, microRNAs and exosomes, are still in their infancy. Together, these biomarkers provide actionable guidance for prostate cancer risk assessment, and are expected to lead to an era of personalized medicine. PMID:26790878

Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

PubMed

Nath, Anjali K; Krauthammer, Michael; Li, Puyao; Davidov, Eugene; Butler, Lucas C; Copel, Joshua; Katajamaa, Mikko; Oresic, Matej; Buhimschi, Irina; Buhimschi, Catalin; Snyder, Michael; Madri, Joseph A

2009-01-01

Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs). However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies. Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others) were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B) was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1) as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF) samples from women carrying normal fetuses and those with CHDs. The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs.

Proteomic-Based Detection of a Protein Cluster Dysregulated during Cardiovascular Development Identifies Biomarkers of Congenital Heart Defects

PubMed Central

Nath, Anjali K.; Krauthammer, Michael; Li, Puyao; Davidov, Eugene; Butler, Lucas C.; Copel, Joshua; Katajamaa, Mikko; Oresic, Matej; Buhimschi, Irina; Buhimschi, Catalin; Snyder, Michael; Madri, Joseph A.

2009-01-01

Background Cardiovascular development is vital for embryonic survival and growth. Early gestation embryo loss or malformation has been linked to yolk sac vasculopathy and congenital heart defects (CHDs). However, the molecular pathways that underlie these structural defects in humans remain largely unknown hindering the development of molecular-based diagnostic tools and novel therapies. Methodology/Principal Findings Murine embryos were exposed to high glucose, a condition known to induce cardiovascular defects in both animal models and humans. We further employed a mass spectrometry-based proteomics approach to identify proteins differentially expressed in embryos with defects from those with normal cardiovascular development. The proteins detected by mass spectrometry (WNT16, ST14, Pcsk1, Jumonji, Morca2a, TRPC5, and others) were validated by Western blotting and immunoflorescent staining of the yolk sac and heart. The proteins within the proteomic dataset clustered to adhesion/migration, differentiation, transport, and insulin signaling pathways. A functional role for several proteins (WNT16, ADAM15 and NOGO-A/B) was demonstrated in an ex vivo model of heart development. Additionally, a successful application of a cluster of protein biomarkers (WNT16, ST14 and Pcsk1) as a prenatal screen for CHDs was confirmed in a study of human amniotic fluid (AF) samples from women carrying normal fetuses and those with CHDs. Conclusions/Significance The novel finding that WNT16, ST14 and Pcsk1 protein levels increase in fetuses with CHDs suggests that these proteins may play a role in the etiology of human CHDs. The information gained through this bed-side to bench translational approach contributes to a more complete understanding of the protein pathways dysregulated during cardiovascular development and provides novel avenues for diagnostic and therapeutic interventions, beneficial to fetuses at risk for CHDs. PMID:19156209

Merging clinical chemistry biomarker data with a COPD database - building a clinical infrastructure for proteomic studies.

PubMed

Eriksson, Jonatan; Andersson, Simone; Appelqvist, Roger; Wieslander, Elisabet; Truedsson, Mikael; Bugge, May; Malm, Johan; Dahlbäck, Magnus; Andersson, Bo; Fehniger, Thomas E; Marko-Varga, György

2016-01-01

Data from biological samples and medical evaluations plays an essential part in clinical decision making. This data is equally important in clinical studies and it is critical to have an infrastructure that ensures that its quality is preserved throughout its entire lifetime. We are running a 5-year longitudinal clinical study, KOL-Örestad, with the objective to identify new COPD (Chronic Obstructive Pulmonary Disease) biomarkers in blood. In the study, clinical data and blood samples are collected from both private and public health-care institutions and stored at our research center in databases and biobanks, respectively. The blood is analyzed by Mass Spectrometry and the results from this analysis then linked to the clinical data. We built an infrastructure that allows us to efficiently collect and analyze the data. We chose to use REDCap as the EDC (Electronic Data Capture) tool for the study due to its short setup-time, ease of use, and flexibility. REDCap allows users to easily design data collection modules based on existing templates. In addition, it provides two functions that allow users to import batches of data; through a web API (Application Programming Interface) as well as by uploading CSV-files (Comma Separated Values). We created a software, DART (Data Rapid Translation), that translates our biomarker data into a format that fits REDCap's CSV-templates. In addition, DART is configurable to work with many other data formats as well. We use DART to import our clinical chemistry data to the REDCap database. We have shown that a powerful and internationally adopted EDC tool such as REDCap can be extended so that it can be used efficiently in proteomic studies. In our study, we accomplish this by using DART to translate our clinical chemistry data to a format that fits the templates of REDCap.

The proteomic landscape of triple-negative breast cancer.

PubMed

Lawrence, Robert T; Perez, Elizabeth M; Hernández, Daniel; Miller, Chris P; Haas, Kelsey M; Irie, Hanna Y; Lee, Su-In; Blau, C Anthony; Villén, Judit

2015-04-28

Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Current state of the art for enhancing urine biomarker discovery

PubMed Central

Harpole, Michael; Davis, Justin; Espina, Virginia

2016-01-01

Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual's metabolic and pathophysiologic state. High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins. Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals. PMID:27232439

Top-down Proteomics: Technology Advancements and Applications to Heart Diseases

PubMed Central

Cai, Wenxuan; Tucholski, Trisha M.; Gregorich, Zachery R.; Ge, Ying

2016-01-01

Introduction Diseases of the heart are a leading cause of morbidity and mortality for both men and women worldwide, and impose significant economic burdens on the healthcare systems. Despite substantial effort over the last several decades, the molecular mechanisms underlying diseases of the heart remain poorly understood. Areas covered Altered protein post-translational modifications (PTMs) and protein isoform switching are increasingly recognized as important disease mechanisms. Top-down high-resolution mass spectrometry (MS)-based proteomics has emerged as the most powerful method for the comprehensive analysis of PTMs and protein isoforms. Here, we will review recent technology developments in the field of top-down proteomics, as well as highlight recent studies utilizing top-down proteomics to decipher the cardiac proteome for the understanding of the molecular mechanisms underlying diseases of the heart. Expert commentary Top-down proteomics is a premier method for the global and comprehensive study of protein isoforms and their PTMs, enabling the identification of novel protein isoforms and PTMs, characterization of sequence variations, and quantification of disease-associated alterations. Despite significant challenges, continuous development of top-down proteomics technology will greatly aid the dissection of the molecular mechanisms underlying diseases of the hearts for the identification of novel biomarkers and therapeutic targets. PMID:27448560

Advances in Proteomics Data Analysis and Display Using an Accurate Mass and Time Tag Approach

PubMed Central

Zimmer, Jennifer S.D.; Monroe, Matthew E.; Qian, Wei-Jun; Smith, Richard D.

2007-01-01

Proteomics has recently demonstrated utility in understanding cellular processes on the molecular level as a component of systems biology approaches and for identifying potential biomarkers of various disease states. The large amount of data generated by utilizing high efficiency (e.g., chromatographic) separations coupled to high mass accuracy mass spectrometry for high-throughput proteomics analyses presents challenges related to data processing, analysis, and display. This review focuses on recent advances in nanoLC-FTICR-MS-based proteomics approaches and the accompanying data processing tools that have been developed to display and interpret the large volumes of data being produced. PMID:16429408

System Vaccinology for the Evaluation of Influenza Vaccine Safety by Multiplex Gene Detection of Novel Biomarkers in a Preclinical Study and Batch Release Test

PubMed Central

Mizukami, Takuo; Momose, Haruka; Kuramitsu, Madoka; Takizawa, Kazuya; Araki, Kumiko; Furuhata, Keiko; Ishii, Ken J.; Hamaguchi, Isao; Yamaguchi, Kazunari

2014-01-01

Vaccines are beneficial and universal tools to prevent infectious disease. Thus, safety of vaccines is strictly evaluated in the preclinical phase of trials and every vaccine batch must be tested by the National Control Laboratories according to the guidelines published by each country. Despite many vaccine production platforms and methods, animal testing for safety evaluation is unchanged thus far. We recently developed a systems biological approach to vaccine safety evaluation where identification of specific biomarkers in a rat pre-clinical study evaluated the safety of vaccines for pandemic H5N1 influenza including Irf7, Lgals9, Lgalsbp3, Cxcl11, Timp1, Tap2, Psmb9, Psme1, Tapbp, C2, Csf1, Mx2, Zbp1, Ifrd1, Trafd1, Cxcl9, β2m, Npc1, Ngfr and Ifi47. The current study evaluated whether these 20 biomarkers could evaluate the safety, batch-to-batch and manufacturer-to-manufacturer consistency of seasonal trivalent influenza vaccine using a multiplex gene detection system. When we evaluated the influenza HA vaccine (HAv) from four different manufactures, the biomarker analysis correlated to findings from conventional animal use tests, such as abnormal toxicity test. In addition, sensitivity of toxicity detection and differences in HAvs were higher and more accurate than with conventional methods. Despite a slight decrease in body weight caused by HAv from manufacturer B that was not statistically significant, our results suggest that HAv from manufacturer B is significantly different than the other HAvs tested with regard to Lgals3bp, Tapbp, Lgals9, Irf7 and C2 gene expression in rat lungs. Using the biomarkers confirmed in this study, we predicted batch-to-batch consistency and safety of influenza vaccines within 2 days compared with the conventional safety test, which takes longer. These biomarkers will facilitate the future development of new influenza vaccines and provide an opportunity to develop in vitro methods of evaluating batch-to-batch consistency and

Biomarkers--a pot of gold or a can of worms?: Meeting report from the 2nd World Congress on Biomarkers & Clinical Research, 2011, Baltimore, USA.

PubMed

Weber, Georg F; Warren, Jeremy; Shoma, Hitoshi; Chen, Tao; Halim, Abdel; Chakravarty, Geetika

2012-08-01

Biomarkers are biological agents used as indicators of biological states. In clinical applications, biomarkers reflect the presence, severity, or progression of disease states. They may also predict risk or responsiveness of a disease to a given treatment. There has been increasingly intense research interest in biomarkers, yet their translation into routine clinical use is lagging. To stimulate communication and cross-fertilization, the 2nd World Congress on Biomarkers & Clinical Research was held in Baltimore, MD, USA in 2011. The symposium covered a broad range of basic and applied biomarker research with the intent to facilitate bench-to-bedside developments. Sessions discussed DNA-based, proteomic, and blood-borne markers. The presentations covered biomarkers for cancer, other various diseases, and toxicological agents. Other topics included biomarker data assimilation, validation, standardization and quality control, as well as molecular imaging and informatics. New high-throughput assays, model systems and emerging technologies give reasons to hope for further rapid progress in the field.

Acute Phase Response and Metabolic Syndrome Biomarkers of Libby Asbestos Exposure

EPA Science Inventory

Identification of biomarkers assists in the disease diagnosis and environmental health risk assessment. Exposure to Libby amphibole (LA) has been associated with increased cardiovascular mortality. We hypothesized that rats exposed to LA would present a unique serum proteomic pro...

Proteomic analysis of urine in rats chronically exposed to fluoride.

PubMed

Kobayashi, Claudia Ayumi Nakai; Leite, Aline de Lima; da Silva, Thelma Lopes; dos Santos, Lucilene Delazari; Nogueira, Fábio César Sousa; Santos, Keity Souza; de Oliveira, Rodrigo Cardoso; Palma, Mario Sérgio; Domont, Gilberto Barbosa; Buzalaf, Marília Afonso Rabelo

2011-01-01

Urine is an ideal source of materials to search for potential disease-related biomarkers as it is produced by the affected tissues and can be easily obtained by noninvasive methods. 2-DE-based proteomic approach was used to better understand the molecular mechanisms of injury induced by fluoride (F(-)) and define potential biomarkers of dental fluorosis. Three groups of weanling male Wistar rats were treated with drinking water containing 0 (control), 5, or 50 ppm F(-) for 60 days (n = 15/group). During the experimental period, the animals were kept individually in metabolic cages, to analyze the water and food consumption, as well as fecal and urinary F(-) excretion. Urinary proteome profiles were examined using 2-DE and Colloidal Coomassie Brilliant Blue staining. A dose-response regarding F(-) intake and excretion was detected. Quantitative intensity analysis revealed 8, 11, and 8 significantly altered proteins between control vs. 5 ppm F(-), control vs. 50 ppm F(-) and 5 ppm F(-) vs. 50 ppm F(-) groups, respectively. Two proteins regulated by androgens (androgen-regulated 20-KDa protein and α-2μ-globulin) and one related to detoxification (aflatoxin-B1-aldehyde-reductase) were identified by MALDI-TOF-TOF MS/MS. Thus, proteomic analysis can help to better understand the mechanisms underlying F(-) toxicity, even in low doses. Copyright © 2010 Wiley Periodicals, Inc.

Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives.

PubMed

Zhou, Li; Wang, Kui; Li, Qifu; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

2016-01-01

Cancer is a common disease that is a leading cause of death worldwide. Currently, early detection and novel therapeutic strategies are urgently needed for more effective management of cancer. Importantly, protein profiling using clinical proteomic strategies, with spectacular sensitivity and precision, offer excellent promise for the identification of potential biomarkers that would direct the development of targeted therapeutic anticancer drugs for precision medicine. In particular, clinical sample sources, including tumor tissues and body fluids (blood, feces, urine and saliva), have been widely investigated using modern high-throughput mass spectrometry-based proteomic approaches combined with bioinformatic analysis, to pursue the possibilities of precision medicine for targeted cancer therapy. Discussed in this review are the current advantages and limitations of clinical proteomics, the available strategies of clinical proteomics for the management of precision medicine, as well as the challenges and future perspectives of clinical proteomics-driven precision medicine for targeted cancer therapy.

Multiplex Biomarker Approaches in Type 2 Diabetes Mellitus Research.

PubMed

Ozanne, Susan E; Rahmoune, Hassan; Guest, Paul C

2017-01-01

Type 2 diabetes mellitus is a multifactorial condition resulting in high fasting blood glucose levels. Although its diagnosis is straightforward, there is not one set of biomarkers or drug targets that can be used for classification or personalized treatment of individuals who suffer from this condition. Instead, the application of multiplex methods incorporating a systems biology approach is essential in order to increase our understanding of this disease. This chapter reviews the state of the art in biomarker studies of human type 2 diabetes from a proteomic and metabolomic perspective. Our main focus was on biomarkers for disease prediction as these could lead to early intervention strategies for the best possible patient outcomes.

Application of Large-Scale Aptamer-Based Proteomic Profiling to Planned Myocardial Infarctions.

PubMed

Jacob, Jaison; Ngo, Debby; Finkel, Nancy; Pitts, Rebecca; Gleim, Scott; Benson, Mark D; Keyes, Michelle J; Farrell, Laurie A; Morgan, Thomas; Jennings, Lori L; Gerszten, Robert E

2018-03-20

Emerging proteomic technologies using novel affinity-based reagents allow for efficient multiplexing with high-sample throughput. To identify early biomarkers of myocardial injury, we recently applied an aptamer-based proteomic profiling platform that measures 1129 proteins to samples from patients undergoing septal alcohol ablation for hypertrophic cardiomyopathy, a human model of planned myocardial injury. Here, we examined the scalability of this approach using a markedly expanded platform to study a far broader range of human proteins in the context of myocardial injury. We applied a highly multiplexed, expanded proteomic technique that uses single-stranded DNA aptamers to assay 4783 human proteins (4137 distinct human gene targets) to derivation and validation cohorts of planned myocardial injury, individuals with spontaneous myocardial infarction, and at-risk controls. We found 376 target proteins that significantly changed in the blood after planned myocardial injury in a derivation cohort (n=20; P <1.05E-05, 1-way repeated measures analysis of variance, Bonferroni threshold). Two hundred forty-seven of these proteins were validated in an independent planned myocardial injury cohort (n=15; P <1.33E-04, 1-way repeated measures analysis of variance); >90% were directionally consistent and reached nominal significance in the validation cohort. Among the validated proteins that were increased within 1 hour after planned myocardial injury, 29 were also elevated in patients with spontaneous myocardial infarction (n=63; P <6.17E-04). Many of the novel markers identified in our study are intracellular proteins not previously identified in the peripheral circulation or have functional roles relevant to myocardial injury. For example, the cardiac LIM protein, cysteine- and glycine-rich protein 3, is thought to mediate cardiac mechanotransduction and stress responses, whereas the mitochondrial ATP synthase F 0 subunit component is a vasoactive peptide on its release

Influence of Diet on the Proteome of Drosophila Melanogaster as Assessed by Two-Dimensional Gel Electrophoresis and Capillary Liquid Chromatography–Mass Spectrometry: The Hamburger Effect Revisited

PubMed Central

Culwell, Thomas F.; Thulin, Craig D.; Merrell, Karen J.; Graves, Steven W.

2008-01-01

Proteomic biomarker discovery has been called into question. Diamandis hypothesized that seemingly trivial factors, such as eating a hamburger, may cause sufficient proteomic change as to confound proteomic differences. This has been termed the hamburger effect. Little is known about the variability of complex proteomes in response to the environment. Two methods—two-dimensional gel electrophoresis (2DGE) and capillary liquid chromatography–electrospray ionization time-of-flight mass spectrometry (LCMS)—were used to study the hamburger effect in two cross-sections of the soluble fruit fly proteome. 2DGE measured abundant proteins, whereas LCMS measured small proteins and peptides. Proteomic differences between males and females were first evaluated to assess the discriminatory capability of the methods. Likewise, wild-type and white-eyed flies were analyzed as a further demonstration that genetically based proteomic differences could be observed above the background analytical variation. Then dietary interventions were imposed. Ethanol was added to the diet of some populations without significant proteomic effect. However, after a 24-h fast, proteomic differences were found using LCMS but not 2DGE. Even so, only three of ~1000 molecular species were altered significantly, suggesting that the influence of even an extreme diet change produced only modest proteomic variability, and that much of the fruit fly proteome remains relatively constant in response to diet. These experiments suggest that proteomics can be a viable approach to biomarker discovery. PMID:19137114

Report of the roundtable discussion organised by the Swiss Proteomics Society (SPS), Bern, 8th December 2004.

PubMed

Noukakis, Dimitrios; Gadola, Stephan; Stöcklin, Reto

2005-08-01

How close are we to using proteomics tools in the every day practice of physicians? What are the socio-economical issues our health care system may face with the advent of biomarkers for early diagnosis? How to get the specialists from the various disciplines integrated in proteomics to establish a common understanding of the clinical issues and develop the necessary standards (methods, biochemicals and IT)? These were the kind of questions a panel of specialists tried to answer during the roundtable discussion that took place in Bern during the Swiss Proteomics Society 2004 congress.

Discovery of potential protein biomarkers of lung adenocarcinoma in bronchoalveolar lavage fluid by SWATH MS data-independent acquisition and targeted data extraction.

PubMed

Ortea, I; Rodríguez-Ariza, A; Chicano-Gálvez, E; Arenas Vacas, M S; Jurado Gámez, B

2016-04-14

Lung cancer currently ranks as the neoplasia with the highest global mortality rate. Although some improvements have been introduced in recent years, new advances in diagnosis are required in order to increase survival rates. New mildly invasive endoscopy-based diagnostic techniques include the collection of bronchoalveolar lavage fluid (BALF), which is discarded after using a portion of the fluid for standard pathological procedures. BALF proteomic analysis can contribute to clinical practice with more sensitive biomarkers, and can complement cytohistological studies by aiding in the diagnosis, prognosis, and subtyping of lung cancer, as well as the monitoring of treatment response. The range of quantitative proteomics methodologies used for biomarker discovery is currently being broadened with the introduction of data-independent acquisition (DIA) analysis-related approaches that address the massive quantitation of the components of a proteome. Here we report for the first time a DIA-based quantitative proteomics study using BALF as the source for the discovery of potential lung cancer biomarkers. The results have been encouraging in terms of the number of identified and quantified proteins. A panel of candidate protein biomarkers for adenocarcinoma in BALF is reported; this points to the activation of the complement network as being strongly over-represented and suggests this pathway as a potential target for lung cancer research. In addition, the results reported for haptoglobin, complement C4-A, and glutathione S-transferase pi are consistent with previous studies, which indicates that these proteins deserve further consideration as potential lung cancer biomarkers in BALF. Our study demonstrates that the analysis of BALF proteins by liquid chromatography-tandem mass spectrometry (LC-MS/MS), combining a simple sample pre-treatment and SWATH DIA MS, is a useful method for the discovery of potential lung cancer biomarkers. Bronchoalveolar lavage fluid (BALF

Mining the human urine proteome for monitoring renal transplant injury

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sigdel, Tara K.; Gao, Yuqian; He, Jintang

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

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

PubMed

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

2016-04-29

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

MALDI-TOF mass spectrometry analysis of small molecular weight compounds (under 10 KDa) as biomarkers of rat hearts undergoing arecoline challenge.

PubMed

Chen, Tung-Sheng; Chang, Mu-Hsin; Kuo, Wei-Wen; Lin, Yueh-Min; Yeh, Yu-Lan; Day, Cecilia Hsuan; Lin, Chien-Chung; Tsai, Fuu-Jen; Tsai, Chang-Hai; Huang, Chih-Yang

2013-04-01

Statistical and clinical reports indicate that betel nut chewing is strongly associated with progression of oral cancer because some ingredients in betel nuts are potential cancer promoters, especially arecoline. Early diagnosis for cancer biomarkers is the best strategy for prevention of cancer progression. Several methods are suggested for investigating cancer biomarkers. Among these methods, gel-based proteomics approach is the most powerful and recommended tool for investigating biomarkers due to its high-throughput. However, this proteomics approach is not suitable for screening biomarkers with molecular weight under 10 KDa because of the characteristics of gel electrophoresis. This study investigated biomarkers with molecular weight under 10 KDa in rats with arecoline challenge. The centrifuging vials with membrane (10 KDa molecular weight cut-off) played a crucial role in this study. After centrifuging, the filtrate (containing compounds with molecular weight under 10 KDa) was collected and spotted on a sample plate for MALDI-TOF mass spectrometry analysis. Compared to control, three extra peaks (m/z values were 1553.1611, 1668.2097 and 1740.1832, respectively) were found in sera and two extra peaks were found in heart tissue samples (408.9719 and 524.9961, respectively). These small compounds should play important roles and may be potential biomarker candidates in rats with arecoline. This study successfully reports a mass-based method for investigating biomarker candidates with small molecular weight in different types of sample (including serum and tissue). In addition, this reported method is more time-efficient (1 working day) than gel-based proteomics approach (5~7 working days).

The Multinational Arabidopsis Steering Subcommittee for Proteomics Assembles the Largest Proteome Database Resource for Plant Systems Biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weckwerth, Wolfram; Baginsky, Sacha; Van Wijk, Klass

2009-12-01

online resources, and raw data have been deposited in PRIDE and PRIDE BioMart. Included in this database is an Arabidopsis proteome map that provides evidence for the expression of {approx}50% of all predicted gene models, including several alternative gene models that are not represented in The Arabidopsis Information Resource (TAIR) protein database. A set of organ-specific biomarkers is provided, as well as organ-specific proteotypic peptides for 4105 proteins that can be used to facilitate targeted quantitative proteomic surveys. In the future, the AtProteome database will be linked to additional existing resources developed by MASCP members, such as PPDB, ProMEX, and SUBA. The most comprehensive study on the Arabidopsis chloroplast proteome, which includes information on chloroplast sorting signals, posttranslational modifications (PTMs), and protein abundances (analyzed by high-accuracy MS [Orbitrap]), was recently published by the van Wijk lab.2 These and previous data are available via the plant proteome database (PPDB; http://ppdb.tc.cornell.edu) for A. thaliana and maize. PPDB provides genome-wide experimental and functional characterization of the A. thaliana and maize proteomes, including PTMs and subcellular localization information, with an emphasis on leaf and plastid proteins. Maize and Arabidopsis proteome entries are directly linked via internal BLAST alignments within PPDB. Direct links for each protein to TAIR, SUBA, ProMEX, and other resources are also provided.« less

Plasma protein absolute quantification by nano-LC Q-TOF UDMSE for clinical biomarker verification

PubMed Central

ILIES, MARIA; IUGA, CRISTINA ADELA; LOGHIN, FELICIA; DHOPLE, VISHNU MUKUND; HAMMER, ELKE

2017-01-01

Background and aims Proteome-based biomarker studies are targeting proteins that could serve as diagnostic, prognosis, and prediction molecules. In the clinical routine, immunoassays are currently used for the absolute quantification of such biomarkers, with the major limitation that only one molecule can be targeted per assay. The aim of our study was to test a mass spectrometry based absolute quantification method for the verification of plasma protein sets which might serve as reliable biomarker panels for the clinical practice. Methods Six EDTA plasma samples were analyzed after tryptic digestion using a high throughput data independent acquisition nano-LC Q-TOF UDMSE proteomics approach. Synthetic Escherichia coli standard peptides were spiked in each sample for the absolute quantification. Data analysis was performed using ProgenesisQI v2.0 software (Waters Corporation). Results Our method ensured absolute quantification of 242 non redundant plasma proteins in a single run analysis. The dynamic range covered was 105. 86% were represented by classical plasma proteins. The overall median coefficient of variation was 0.36, while a set of 63 proteins was found to be highly stable. Absolute protein concentrations strongly correlated with values reviewed in the literature. Conclusions Nano-LC Q-TOF UDMSE proteomic analysis can be used for a simple and rapid determination of absolute amounts of plasma proteins. A large number of plasma proteins could be analyzed, while a wide dynamic range was covered with low coefficient of variation at protein level. The method proved to be a reliable tool for the quantification of protein panel for biomarker verification in the clinical practice. PMID:29151793

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

PubMed Central

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

2017-01-01

Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible ‘biomarkers’, which are predictors of one’s biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying ‘endophenotypes’ in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity. PMID:28698311

Proteomics Analysis of Bladder Cancer Exosomes*

PubMed Central

Welton, Joanne L.; Khanna, Sanjay; Giles, Peter J.; Brennan, Paul; Brewis, Ian A.; Staffurth, John; Mason, Malcolm D.; Clayton, Aled

2010-01-01

Exosomes are nanometer-sized vesicles, secreted by various cell types, present in biological fluids that are particularly rich in membrane proteins. Ex vivo analysis of exosomes may provide biomarker discovery platforms and form non-invasive tools for disease diagnosis and monitoring. These vesicles have never before been studied in the context of bladder cancer, a major malignancy of the urological tract. We present the first proteomics analysis of bladder cancer cell exosomes. Using ultracentrifugation on a sucrose cushion, exosomes were highly purified from cultured HT1376 bladder cancer cells and verified as low in contaminants by Western blotting and flow cytometry of exosome-coated beads. Solubilization in a buffer containing SDS and DTT was essential for achieving proteomics analysis using an LC-MALDI-TOF/TOF MS approach. We report 353 high quality identifications with 72 proteins not previously identified by other human exosome proteomics studies. Overrepresentation analysis to compare this data set with previous exosome proteomics studies (using the ExoCarta database) revealed that the proteome was consistent with that of various exosomes with particular overlap with exosomes of carcinoma origin. Interrogating the Gene Ontology database highlighted a strong association of this proteome with carcinoma of bladder and other sites. The data also highlighted how homology among human leukocyte antigen haplotypes may confound MASCOT designation of major histocompatability complex Class I nomenclature, requiring data from PCR-based human leukocyte antigen haplotyping to clarify anomalous identifications. Validation of 18 MS protein identifications (including basigin, galectin-3, trophoblast glycoprotein (5T4), and others) was performed by a combination of Western blotting, flotation on linear sucrose gradients, and flow cytometry, confirming their exosomal expression. Some were confirmed positive on urinary exosomes from a bladder cancer patient. In summary, the

A New Mass Spectrometry-compatible Degradable Surfactant for Tissue Proteomics

PubMed Central

Chang, Ying-Hua; Gregorich, Zachery R.; Chen, Albert J.; Hwang, Leekyoung; Guner, Huseyin; Yu, Deyang; Zhang, Jianyi; Ge, Ying

2015-01-01

Tissue proteomics is increasingly recognized for its role in biomarker discovery and disease mechanism investigation. However, protein solubility remains a significant challenge in mass spectrometry (MS)-based tissue proteomics. Conventional surfactants such as sodium dodecyl sulfate (SDS), the preferred surfactant for protein solubilization, are not compatible with MS. Herein, we have screened a library of surfactant-like compounds and discovered an MS-compatible degradable surfactant (MaSDeS) for tissue proteomics that solubilizes all categories of proteins with performance comparable to SDS. The use of MaSDeS in the tissue extraction significantly improves the total number of protein identifications from commonly used tissues, including tissue from the heart, liver, and lung. Notably, MaSDeS significantly enriches membrane proteins, which are often under-represented in proteomics studies. The acid degradable nature of MaSDeS makes it amenable for high-throughput mass spectrometry-based proteomics. In addition, the thermostability of MaSDeS allows for its use in experiments requiring high temperature to facilitate protein extraction and solubilization. Furthermore, we have shown that MaSDeS outperforms the other MS-compatible surfactants in terms of overall protein solubility and the total number of identified proteins in tissue proteomics. Thus, the use of MaSDeS will greatly advance tissue proteomics and realize its potential in basic biomedical and clinical research. MaSDeS could be utilized in a variety of proteomics studies as well as general biochemical and biological experiments that employ surfactants for protein solubilization. PMID:25589168

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

PubMed

Martyanov, Viktor; Whitfield, Michael L

2016-01-01

The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

Risk Factors and Biomarkers of Age-Related Macular Degeneration

PubMed Central

Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

2016-01-01

A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

The current status of biomarkers for predicting toxicity

PubMed Central

Campion, Sarah; Aubrecht, Jiri; Boekelheide, Kim; Brewster, David W; Vaidya, Vishal S; Anderson, Linnea; Burt, Deborah; Dere, Edward; Hwang, Kathleen; Pacheco, Sara; Saikumar, Janani; Schomaker, Shelli; Sigman, Mark; Goodsaid, Federico

2013-01-01

Introduction There are significant rates of attrition in drug development. A number of compounds fail to progress past preclinical development due to limited tools that accurately monitor toxicity in preclinical studies and in the clinic. Research has focused on improving tools for the detection of organ-specific toxicity through the identification and characterization of biomarkers of toxicity. Areas covered This article reviews what we know about emerging biomarkers in toxicology, with a focus on the 2012 Northeast Society of Toxicology meeting titled ‘Translational Biomarkers in Toxicology.’ The areas covered in this meeting are summarized and include biomarkers of testicular injury and dysfunction, emerging biomarkers of kidney injury and translation of emerging biomarkers from preclinical species to human populations. The authors also provide a discussion about the biomarker qualification process and possible improvements to this process. Expert opinion There is currently a gap between the scientific work in the development and qualification of novel biomarkers for nonclinical drug safety assessment and how these biomarkers are actually used in drug safety assessment. A clear and efficient path to regulatory acceptance is needed so that breakthroughs in the biomarker toolkit for nonclinical drug safety assessment can be utilized to aid in the drug development process. PMID:23961847

Proteomic Profiling of Mitochondrial Enzymes during Skeletal Muscle Aging.

PubMed

Staunton, Lisa; O'Connell, Kathleen; Ohlendieck, Kay

2011-03-07

Mitochondria are of central importance for energy generation in skeletal muscles. Expression changes or functional alterations in mitochondrial enzymes play a key role during myogenesis, fibre maturation, and various neuromuscular pathologies, as well as natural fibre aging. Mass spectrometry-based proteomics suggests itself as a convenient large-scale and high-throughput approach to catalogue the mitochondrial protein complement and determine global changes during health and disease. This paper gives a brief overview of the relatively new field of mitochondrial proteomics and discusses the findings from recent proteomic surveys of mitochondrial elements in aged skeletal muscles. Changes in the abundance, biochemical activity, subcellular localization, and/or posttranslational modifications in key mitochondrial enzymes might be useful as novel biomarkers of aging. In the long term, this may advance diagnostic procedures, improve the monitoring of disease progression, help in the testing of side effects due to new drug regimes, and enhance our molecular understanding of age-related muscle degeneration.

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

PubMed

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

2017-11-01

Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. We used samples from five patients with transudative pleural effusions for internal standard, five patients with tuberculous pleurisy, and the same numbers of patients having malignant effusions were enrolled in the study. We analyzed the proteins in pleural fluid from patients using a technique that combined two-dimensional liquid-phase electrophoresis and matrix assisted laser desorption/ionization-time of flight-mass spectrometry. We identified a total of 10 proteins with statistical significance. Among 10 proteins, trasthyretin, haptoglobin, metastasis-associated protein 1, t-complex protein 1, and fibroblast growth factor-binding protein 1 were related with malignant pleural effusions and human ceruloplasmin, lysozyme precursor, gelsolin, clusterin C complement lysis inhibitor, and peroxirexdoxin 3 were expressed several times or more in tuberculous pleural effusions. Highly expressed proteins in malignant pleural effusion were associated with carcinogenesis and cell growth, and proteins associated with tuberculous pleural effusion played a role in the response to inflammation and fibrosis. These findings will aid in the development of novel diagnostic tools for tuberculous pleurisy and malignant pleural effusion of lung cancer. © Copyright: Yonsei University College of Medicine 2017

Evaluation of the salivary proteome as a surrogate tissue for systems biology approaches to understanding appetite.

PubMed

Harden, Charlotte J; Perez-Carrion, Kristine; Babakordi, Zara; Plummer, Sue F; Hepburn, Natalie; Barker, Margo E; Wright, Phillip C; Evans, Caroline A; Corfe, Bernard M

2012-06-06

Current measurement of appetite depends upon tools that are either subjective (visual analogue scales), or invasive (blood). Saliva is increasingly recognised as a valuable resource for biomarker analysis. Proteomics workflows may provide alternative means for the assessment of appetitive response. The study aimed to assess the potential value of the salivary proteome to detect novel biomarkers of appetite using an iTRAQ-based workflow. Diurnal variation of salivary protein concentrations was assessed. A randomised, controlled, crossover study examined the effects on the salivary proteome of isocaloric doses of various long chain fatty acid (LCFA) oil emulsions compared to no treatment (NT). Fasted males provided saliva samples before and following NT or dosing with LCFA emulsions. The oil component of the DHA emulsion contained predominantly docosahexaenoic acid and the oil component of OA contained predominantly oleic acid. Several proteins were present in significantly (p<0.05) different quantities in saliva samples taken following treatments compared to fasting samples. DHA caused alterations in thioredoxin and serpin B4 relative to OA and NT. A further study evaluated energy intake (EI) in response to LCFA in conjunction with subjective appetite scoring. DHA was associated with significantly lower EI relative to NT and OA (p=0.039). The collective data suggest investigation of salivary proteome may be of value in appetitive response. This article is part of a Special Issue entitled: Proteomics: The clinical link. Copyright © 2011 Elsevier B.V. All rights reserved.

Recent advances in biomarkers and therapeutic interventions for hepatic drug safety - false dawn or new horizon?

PubMed

Clarke, Joanna I; Dear, James W; Antoine, Daniel J

2016-05-01

Drug-induced liver injury (DILI) represents a serious medical challenge and a potentially fatal adverse event. Currently, DILI is a diagnosis of exclusion, and whilst the electronic evaluation of serious drug-induced hepatotoxicity (eDISH) have revolutionised the early assessment of DILI, this model is dependent upon clinical chemistry parameters that lack sensitivity and specificity. DILI management usually consists of initial withdrawal of the suspected drug and, in the case of acetaminophen, administration of specific therapy. We summarise recent advances and knowledge gaps in the development and qualification of novel DILI biomarkers and therapeutic interventions. Promising biomarkers have been identified that provide increased hepatic specificity (miR-122), mechanistic insight (Keratin-18), and prognostic information (HMGB1, KIM-1, CSF-1). Pharmacogenomics holds potential to preselect susceptible populations and tailor drug therapy. Biomarkers can uncover new mechanisms of drug-induced pathophysiology which, for HMGB1 and CSF-1, have led to promising mechanism-based therapeutic interventions. However, these biomarkers have not been formally qualified and are not in routine clinical use. With the development of inventive clinical trials and by maximising DILI data registries, these novel biomarkers could add substantial value to the current armoury, change the management of DILI in the near future and improve patient safety.

Acute Phase Response, Inflammation and Metabolic Syndrome Biomarkers of Libby Asbestos Exposure

EPA Science Inventory

Background: Identification of biomarkers assists in the diagnosis of disease and the assessment of health risks from environmental exposures. Objective: We hypothesized that rats exposed to Libby amphibole (LA) would present with a unique serum proteomic profile which could help ...

Comparative Proteomics of Tumor and Paired Normal Breast Tissue Highlights Potential Biomarkers in Breast Cancer.

PubMed

Da Costa, Gustavo Góes; Gomig, Talita Helen Bombardelli; Kaviski, Rodrigo; Santos Sousa, Karla; Kukolj, Caroline; De Lima, Rubens Silveira; De Andrade Urban, Cicero; Cavalli, Iglenir J; Ribeiro, Enilze M S F

2015-01-01

Breast cancer is the most common type of cancer among women worldwide, and about 57,000 new cases are expected for the Brazilian population in 2015. Elucidation of protein expression and modification is essential for the biological understanding, early diagnosis and therapeutics of breast cancer. The main objectives of the study are comparison between the proteome of tumor and paired non-tumor breast cancer tissues, describing all identified proteins, highlighting the ones most differentially expressed and comparing the data with existing literature. The five paired samples from patients with invasive ductal carcinoma were analyzed by 2-DE and MS. We collected 161 identified spots corresponding to 110 distinct proteins. Forty-three differentially-expressed spots were common to at least two samples, and the ten proteins with the highest-fold changes were CASPE, ENOG, TPM1, CAPG, VIME, TPM3, TRFE, PDIA6, WDR61 and PDIA3. Metabolic enzymes and proteins with binding functions were the most representative functional classes of proteins with increased and decreased expression in tumor tissue respectively. Taking the fold change as a parameter, we point to future targets to be studied by functional methods in a search for biomarkers for initiation and progress of breast cancer. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nielson, Carrie M.; Wiedrick, Jack; Shen, Jian

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

Recent advances in stable isotope labeling based techniques for proteome relative quantification.

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2014-10-24

The large scale relative quantification of all proteins expressed in biological samples under different states is of great importance for discovering proteins with important biological functions, as well as screening disease related biomarkers and drug targets. Therefore, the accurate quantification of proteins at proteome level has become one of the key issues in protein science. Herein, the recent advances in stable isotope labeling based techniques for proteome relative quantification were reviewed, from the aspects of metabolic labeling, chemical labeling and enzyme-catalyzed labeling. Furthermore, the future research direction in this field was prospected. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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

2013-05-01

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

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

USDA-ARS?s Scientific Manuscript database

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...

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

PubMed

Kim, Eun Young; Lee, Min Young; Kim, Se Hyun; Ha, Kyooseob; Kim, Kwang Pyo; Ahn, Yong Min

2017-06-02

Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and control groups by incorporating data from serum proteomic analysis and heart rate variability (HRV) analysis for the identification of novel peripheral biomarkers. The study subjects consisted of 25 drug-free female MDD patients and 25 age- and sex-matched healthy controls. First, quantitative serum proteome profiles were analyzed by liquid chromatography-tandem mass spectrometry using pooled serum samples from 10 patients and 10 controls. Next, candidate proteins were quantified with multiple reaction monitoring (MRM) in 50 subjects. We also analyzed 22 linear and nonlinear HRV parameters in 50 subjects. Finally, we identified a combined biomarker panel consisting of proteins and HRV indexes using a support vector machine with recursive feature elimination. A separation between MDD and control groups was achieved using five parameters (apolipoprotein B, group-specific component, ceruloplasmin, RMSSD, and SampEn) at 80.1% classification accuracy. A combination of HRV and proteomic data achieved better classification accuracy. A high classification accuracy can be achieved by combining multimodal information from heart rate dynamics and serum proteomics in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD. Further studies using larger, independent cohorts are needed to verify the role of these candidate biomarkers for MDD diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Biomarkers for wound healing and their evaluation.

PubMed

Patel, S; Maheshwari, A; Chandra, A

2016-01-01

A biological marker (biomarker) is a substance used as an indicator of biological state. Advances in genomics, proteomics and molecular pathology have generated many candidate biomarkers with potential clinical value. Research has identified several cellular events and mediators associated with wound healing that can serve as biomarkers. Macrophages, neutrophils, fibroblasts and platelets release cytokines molecules including TNF-α, interleukins (ILs) and growth factors, of which platelet-derived growth factor (PDGF) holds the greatest importance. As a result, various white cells and connective tissue cells release both matrix metalloproteinases (MMPs) and the tissue inhibitors of metalloproteinases (TIMPs). Studies have demonstrated that IL-1, IL-6, and MMPs, levels above normal, and an abnormally high MMP/TIMP ratio are often present in non-healing wounds. Clinical examination of wounds for these mediators could predict which wounds will heal and which will not, suggesting use of these chemicals as biomarkers of wound healing. There is also evidence that the application of growth factors like PDGF will alleviate the recuperating process of chronic, non-healing wounds. Finding a specific biomarker for wound healing status would be a breakthrough in this field and helping treat impaired wound healing.

Biology and Biomarkers for Wound Healing.

PubMed

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

2016-09-01

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

Proteomic Profiling of the Pituitary Gland in Studies of Psychiatric Disorders.

PubMed

Krishnamurthy, Divya; Rahmoune, Hassan; Guest, Paul C

2017-01-01

Psychiatric disorders have been associated with perturbations of the hypothalamic-pituitary-adrenal axis. Therefore, proteomic studies of the pituitary gland have the potential to provide new insights into the underlying pathways affected in these conditions as well as identify new biomarkers or targets for use in developing improved medications. This chapter describes a protocol for preparation of pituitary protein extracts followed by characterization of the pituitary proteome by label-free liquid chromatography-tandem mass spectrometry in expression mode (LC-MS E ). The main focus was on establishing a method for identifying the major pituitary hormones and accessory proteins as many of these have already been implicated in psychiatric diseases.

Statistical issues in the design and planning of proteomic profiling experiments.

PubMed

Cairns, David A

2015-01-01

The statistical design of a clinical proteomics experiment is a critical part of well-undertaken investigation. Standard concepts from experimental design such as randomization, replication and blocking should be applied in all experiments, and this is possible when the experimental conditions are well understood by the investigator. The large number of proteins simultaneously considered in proteomic discovery experiments means that determining the number of required replicates to perform a powerful experiment is more complicated than in simple experiments. However, by using information about the nature of an experiment and making simple assumptions this is achievable for a variety of experiments useful for biomarker discovery and initial validation.

Linkage of exposure and effects using genomics, proteomics and metabolomics in small fish models (presentation)

EPA Science Inventory

This research project combines the use of whole organism endpoints, genomic, proteomic and metabolomic approaches, and computational modeling in a systems biology approach to 1) identify molecular indicators of exposure and biomarkers of effect to EDCs representing several modes/...

Effects of exercise on the urinary proteome.

PubMed

Kohler, Maxie; Schänzer, Wilhelm; Thevis, Mario

2015-01-01

Exercise-induced proteinuria has been observed and studied for more than a century. It was found that different sport disciplines alter the urinary proteome in different ways. Moderate-intensity exercise results in increased glomerular filtration, meaning that medium-sized proteins are excreted in higher amounts, while high-intensity exercise of short duration also increases the excretion of low molecular weight proteins as a result of tubular dysfunction. Exhaustive exercise may lead to the excretion of hemoglobin or myoglobin, which changes the urinary proteome considerably. Studies comparing protein maps of different sport types compared to a control group showed that quality and quantity of urinary proteins are interindividually different. In addition, urine samples collected before and after exercise exhibit substantially different protein patterns even from the same person. Therefore, further studies investigating the urinary proteome are desirable. As the variation of protein content and composition in urine are generally much higher than in other matrices, respective studies need to be well controlled and homogenous groups of volunteers should be chosen. In addition to the sport-related physiological and biochemical interest, exercise-induced protein changes also need to be considered for biomarker measurements from urine samples for kidney or other diseases.

Blood Biomarkers for Assessing the Exposure and Response of Mammals to Chemical and Biological Agents

DTIC Science & Technology

2012-03-15

of animals from three inbred mouse strains exposed to the toxins acetaminophen and carbon tetrachloride for transcriptomes, proteins and miRNA...biomarkers.; 3) establishing MRM mass spectrometry assays for at least 25 liver-specific blood proteins based on the acetaminophen, CCL4, and other model...tetrachloride for protein biomarkers using proteomics technologies, including MRM; 5) Analyzing time course experiments of rat tissues and blood exposed to

Biomarkers in inflammatory bowel disease: current practices and recent advances.

PubMed

Iskandar, Heba N; Ciorba, Matthew A

2012-04-01

Crohn's disease and ulcerative colitis represent the two main forms of the idiopathic chronic inflammatory bowel diseases (IBD). Currently available blood and stool based biomarkers provide reproducible, quantitative tools that can complement clinical assessment to aid clinicians in IBD diagnosis and management. C-reactive protein and fecal based leukocyte markers can help the clinician distinguish IBD from noninflammatory diarrhea and assess disease activity. The ability to differentiate between forms of IBD and predict risk for disease complications is specific to serologic tests including antibodies against Saccharomyces cerevisiae and perinuclear antineutrophil cytoplasmic proteins. Advances in genomic, proteomic, and metabolomic array based technologies are facilitating the development of new biomarkers for IBD. The discovery of novel biomarkers, which can correlate with mucosal healing or predict long-term disease course has the potential to significantly improve patient care. This article reviews the uses and limitations of currently available biomarkers and highlights recent advances in IBD biomarker discovery. Copyright © 2012 Mosby, Inc. All rights reserved.

Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis

PubMed Central

Craig-Schapiro, Rebecca; Kuhn, Max; Xiong, Chengjie; Pickering, Eve H.; Liu, Jingxia; Misko, Thomas P.; Perrin, Richard J.; Bales, Kelly R.; Soares, Holly; Fagan, Anne M.; Holtzman, David M.

2011-01-01

Background Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10–15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181). Methods and Findings Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age. Conclusions/Significance Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best

Human Brain Proteome Project - 12th HUPO BPP Workshop. 26 September 2009, Toronto, Canada.

PubMed

Gröttrup, Bernd; Eisenacher, Martin; Stephan, Christian; Marcus, Katrin; Lee, Bonghee; Meyer, Helmut E; Park, Young Mok

2010-06-01

The HUPO Brain Proteome Project (HUPO BPP) held its 12th workshop in Toronto on 26 September 2009 prior to the HUPO VIII World Congress. The principal aim of this project is to obtain a better understanding of neurodiseases and ageing, with the ultimate objective of discovering prognostic and diagnostic biomarkers, in addition to the development of novel diagnostic techniques and new medications. The attendees came together to discuss progress in the human clinical neuroproteomics and to define the needs and guidelines required for more advanced proteomic approaches.

Protein mass spectra data analysis for clinical biomarker discovery: a global review.

PubMed

Roy, Pascal; Truntzer, Caroline; Maucort-Boulch, Delphine; Jouve, Thomas; Molinari, Nicolas

2011-03-01

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarkers.

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

PubMed Central

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

2010-01-01

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

Inter-individual variation in expression: a missing link in biomarker biology?

PubMed

Little, Peter F R; Williams, Rohan B H; Wilkins, Marc R

2009-01-01

The past decade has seen an explosion of variation data demonstrating that diversity of both protein-coding sequences and of regulatory elements of protein-coding genes is common and of functional importance. In this article, we argue that genetic diversity can no longer be ignored in studies of human biology, even research projects without explicit genetic experimental design, and that this knowledge can, and must, inform research. By way of illustration, we focus on the potential role of genetic data in case-control studies to identify and validate cancer protein biomarkers. We argue that a consideration of genetics, in conjunction with proteomic biomarker discovery projects, should improve the proportion of biomarkers that can accurately classify patients.

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

PubMed Central

Kuo, Kung-Kai; Kuo, Chao-Jen; Chiu, Chiang-Yen; Liang, Shih-Shin; Huang, Chun-Hao; Chi, Shu-Wen; Tsai, Kun-Bow; Chen, Chiao-Yun; Hsi, Edward; Cheng, Kuang-Hung; Chiou, Shyh-Horng

2016-01-01

Objectives The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling. Methods Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion. Results Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining. Conclusions The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC. PMID:26262590

Creating a human brain proteome atlas--13th HUPO BPP Workshop March 30-31, 2010, Ochang, Korea.

PubMed

Gröttrup, Bernd; Stephan, Christian; Marcus, Katrin; Grinberg, Lea T; Wiltfang, Jens; Lee, Sang K; Kim, Young H; Meyer, Helmut E; Park, Young M

2011-07-01

The HUPO Brain Proteome Project (HUPO BPP) held its 13th workshop in Ochang from March 30th to 31st, 2010 prior to the Korean HUPO 10th Annual International Proteomics Conference. The principal aim of this project is to obtain a better understanding of neurodiseases and aging with the ultimate objective of discovering prognostic and diagnostic biomarkers, in addition to the development of novel diagnostic techniques and new medications. The attendees came together to discuss progress in the clinical neuroproteomics of human and to define the needs and guidelines required for more advanced proteomics approaches. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection.

PubMed

Yasui, Yutaka; Pepe, Margaret; Thompson, Mary Lou; Adam, Bao-Ling; Wright, George L; Qu, Yinsheng; Potter, John D; Winget, Marcy; Thornquist, Mark; Feng, Ziding

2003-07-01

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of 'signature' protein profiles specific to each pathologic state (e.g. normal vs. cancer) or differential profiles between experimental conditions (e.g. treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data-analytic strategy for discovering protein biomarkers based on such high-dimensional mass spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data-analytic strategy takes properties of the SELDI mass spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After this pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary

Differential Proteomic Analysis of Noncardia Gastric Cancer from Individuals of Northern Brazil

PubMed Central

Leal, Mariana Ferreira; Chung, Janete; Calcagno, Danielle Queiroz; Assumpção, Paulo Pimentel; Demachki, Samia; da Silva, Ismael Dale Cotrim Guerreiro; Chammas, Roger; Burbano, Rommel Rodríguez; de Arruda Cardoso Smith, Marília

2012-01-01

Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in larger clinical study

Characterization of the canine urinary proteome.

PubMed

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

2014-06-01

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

Facile preparation of salivary extracellular vesicles for cancer proteomics

NASA Astrophysics Data System (ADS)

Sun, Yan; Xia, Zhijun; Shang, Zhi; Sun, Kaibo; Niu, Xiaomin; Qian, Liqiang; Fan, Liu-Yin; Cao, Cheng-Xi; Xiao, Hua

2016-04-01

Extracellular vesicles (EVs) are membrane surrounded structures released by cells, which have been increasingly recognized as mediators of intercellular communication. Recent reports indicate that EVs participate in important biological processes and could serve as potential source for cancer biomarkers. As an attractive EVs source with merit of non-invasiveness, human saliva is a unique medium for clinical diagnostics. Thus, we proposed a facile approach to prepare salivary extracellular vesicles (SEVs). Affinity chromatography column combined with filter system (ACCF) was developed to efficiently remove the high abundant proteins and viscous interferences of saliva. Protein profiling in the SEVs obtained by this strategy was compared with conventional centrifugation method, which demonstrated that about 70% more SEVs proteins could be revealed. To explore its utility for cancer proteomics, we analyzed the proteome of SEVs in lung cancer patients and normal controls. Shotgun proteomic analysis illustrated that 113 and 95 proteins have been identified in cancer group and control group, respectively. Among those 63 proteins that have been consistently discovered only in cancer group, 12 proteins are lung cancer related. Our results demonstrated that SEVs prepared through the developed strategy are valuable samples for proteomics and could serve as a promising liquid biopsy for cancer.

Application of Proteomics in Acute Graft-Versus-Host Disease Management: An Integrative Review and Nursing Implications.

PubMed

Kalariya, Nilesh; Brassil, Kelly

2015-12-01

After allogeneic hematopoietic stem cell transplantation, one of the major barriers to clinical management of acute graft-versus-host disease (aGVHD) is a lack of reliable and validated noninvasive tests for diagnosis and prognosis. Proteomic studies have indicated a strong correlation between the level of certain body fluid proteins and clinical outcomes after aGVHD. Specific proteins have been identified that could be robust biomarkers for overall prognosis or for differential diagnosis of target organs in aGVHD. The authors aimed to evaluate the literature related to proteomic biomarkers that are indicated in the occurrence, severity, and management of aGVHD. PubMed and CINAHL® databases were searched for articles published from January 2004 to June 2014. Eight articles matching the inclusion criteria were identified, and the findings of these articles were summarized and their clinical implications noted. Proteomics appears to be a promising tool to assist oncology nurses and nurse practitioners with patient education, develop personalized plans of care to reduce morbidity, initiate communication regarding end-of-life decisions, and improve overall nursing management of the population of patients with aGVHD.

Potential biomarkers in psychiatry: focus on the cholesterol system

PubMed Central

Woods, Alisa G; Sokolowska, Izabela; Taurines, Regina; Gerlach, Manfred; Dudley, Edward; Thome, Johannes; Darie, Costel C

2012-01-01

Abstract Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders. PMID:22304330

Novel droplet platforms for the detection of disease biomarkers.

PubMed

Zec, Helena; Shin, Dong Jin; Wang, Tza-Huei

2014-09-01

Personalized medicine - healthcare based on individual genetic variation - has the potential to transform the way healthcare is delivered to patients. The promise of personalized medicine has been predicated on the predictive and diagnostic power of genomic and proteomic biomarkers. Biomarker screening may help improve health outcomes, for example, by identifying individuals' susceptibility to diseases and predicting how patients will respond to drugs. Microfluidic droplet technology offers an exciting opportunity to revolutionize the accessibility of personalized medicine. A framework for the role of droplet microfluidics in biomarker detection can be based on two main themes. Emulsion-based microdroplet platforms can provide new ways to measure and detect biomolecules. In addition, microdroplet platforms facilitate high-throughput screening of biomarkers. Meanwhile, surface-based droplet platforms provide an opportunity to develop miniaturized diagnostic systems. These platforms may function as portable benchtop environments that dramatically shorten the transition of a benchtop assay into a point-of-care format.

Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio)

PubMed Central

Yilmaz, Ozlem; Patinote, Amélie; Nguyen, Thao Vi; Com, Emmanuelle; Lavigne, Regis; Pineau, Charles; Sullivan, Craig V.; Bobe, Julien

2017-01-01

Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chromatography and tandem mass spectrometry. Obtained spectra were searched against a zebrafish proteome database and detected proteins were annotated, categorized and quantified based on normalized spectral counts. Manually curated and automated enrichment analyses revealed poor quality eggs to be deficient of proteins involved in protein synthesis and energy and lipid metabolism, and of some vitellogenin products and lectins, and to have a surfeit of proteins involved in endo-lysosomal activities, autophagy, and apoptosis, and of some oncogene products, lectins and egg envelope proteins. Results of pathway and network analyses suggest that this aberrant proteomic profile results from failure of oocytes giving rise to poor quality eggs to properly transit through final maturation, and implicated Wnt signaling in the etiology of this defect. Quantitative comparisons of abundant proteins in good versus poor quality eggs revealed 17 candidate egg quality markers. Thus, the zebrafish egg proteome is clearly linked to embryo developmental potential, a phenomenon that begs further investigation to elucidate the root causes of poor egg quality, presently a serious and intractable problem in livestock and human reproductive medicine. PMID:29145436

Scrambled eggs: Proteomic portraits and novel biomarkers of egg quality in zebrafish (Danio rerio).

PubMed

Yilmaz, Ozlem; Patinote, Amélie; Nguyen, Thao Vi; Com, Emmanuelle; Lavigne, Regis; Pineau, Charles; Sullivan, Craig V; Bobe, Julien

2017-01-01

Egg quality is a complex biological trait and a major determinant of reproductive fitness in all animals. This study delivered the first proteomic portraits of egg quality in zebrafish, a leading biomedical model for early development. Egg batches of good and poor quality, evidenced by embryo survival for 24 h, were sampled immediately after spawning and used to create pooled or replicated sample sets whose protein extracts were subjected to different levels of fractionation before liquid chromatography and tandem mass spectrometry. Obtained spectra were searched against a zebrafish proteome database and detected proteins were annotated, categorized and quantified based on normalized spectral counts. Manually curated and automated enrichment analyses revealed poor quality eggs to be deficient of proteins involved in protein synthesis and energy and lipid metabolism, and of some vitellogenin products and lectins, and to have a surfeit of proteins involved in endo-lysosomal activities, autophagy, and apoptosis, and of some oncogene products, lectins and egg envelope proteins. Results of pathway and network analyses suggest that this aberrant proteomic profile results from failure of oocytes giving rise to poor quality eggs to properly transit through final maturation, and implicated Wnt signaling in the etiology of this defect. Quantitative comparisons of abundant proteins in good versus poor quality eggs revealed 17 candidate egg quality markers. Thus, the zebrafish egg proteome is clearly linked to embryo developmental potential, a phenomenon that begs further investigation to elucidate the root causes of poor egg quality, presently a serious and intractable problem in livestock and human reproductive medicine.

Targeted proteomic assays for quantitation of proteins identified by proteogenomic analysis of ovarian cancer

DOE PAGES

Song, Ehwang; Gao, Yuqian; Wu, Chaochao; ...

2017-07-19

Here, mass spectrometry (MS) based targeted proteomic methods such as selected reaction monitoring (SRM) are becoming the method of choice for preclinical verification of candidate protein biomarkers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute has investigated the standardization and analytical validation of the SRM assays and demonstrated robust analytical performance on different instruments across different laboratories. An Assay Portal has also been established by CPTAC to provide the research community a resource consisting of large set of targeted MS-based assays, and a depository to share assays publicly, providing that assays meet the guidelines proposed bymore » CPTAC. Herein, we report 98 SRM assays covering 70 candidate protein biomarkers previously reported as associated with ovarian cancer that have been thoroughly characterized according to the CPTAC Assay Characterization Guidance Document. The experiments, methods and results for characterizing these SRM assays for their MS response, repeatability, selectivity, stability, and reproducible detection of endogenous analytes are described in detail.« less

Proteomic Characterization of Host Response to Yersinia pestis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chromy, B; Perkins, J; Heidbrink, J

Host-pathogen interactions result in protein expression changes within both the host and the pathogen. Here, results from proteomic characterization of host response following exposure to Yersinia pestis, the causative agent of plague, and to two near neighbors, Y. pseudotuberculosis and Y. enterocolitica, are reported. Human monocyte-like cells were chosen as a model for macrophage immune response to pathogen exposure. Two-dimensional electrophoresis followed by mass spectrometry was used to identify host proteins with differential expression following exposure to these three closely related Yersinia species. This comparative proteomic characterization of host response clearly shows that host protein expression patterns are distinct formore » the different pathogen exposures, and contributes to further understanding of Y. pestis virulence and host defense mechanisms. This work also lays the foundation for future studies aimed at defining biomarkers for presymptomatic detection of plague.« less

Biology and Biomarkers for Wound Healing

PubMed Central

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

2016-01-01

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

PROTEOMICS in aquaculture: applications and trends.

PubMed

Rodrigues, Pedro M; Silva, Tomé S; Dias, Jorge; Jessen, Flemming

2012-07-19

Over the last forty years global aquaculture presented a growth rate of 6.9% per annum with an amazing production of 52.5 million tonnes in 2008, and a contribution of 43% of aquatic animal food for human consumption. In order to meet the world's health requirements of fish protein, a continuous growth in production is still expected for decades to come. Aquaculture is, though, a very competitive market, and a global awareness regarding the use of scientific knowledge and emerging technologies to obtain a better farmed organism through a sustainable production has enhanced the importance of proteomics in seafood biology research. Proteomics, as a powerful comparative tool, has therefore been increasingly used over the last decade to address different questions in aquaculture, regarding welfare, nutrition, health, quality, and safety. In this paper we will give an overview of these biological questions and the role of proteomics in their investigation, outlining the advantages, disadvantages and future challenges. A brief description of the proteomics technical approaches will be presented. Special focus will be on the latest trends related to the aquaculture production of fish with defined nutritional, health or quality properties for functional foods and the integration of proteomics techniques in addressing this challenging issue. Copyright © 2012 Elsevier B.V. All rights reserved.

Advances in targeted proteomics and applications to biomedical research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Tujin; Song, Ehwang; Nie, Song

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics, 12, 1074–1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications inmore » human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed.« less

Biomarkers for the early diagnosis of hepatocellular carcinoma

PubMed Central

Tsuchiya, Nobuhiro; Sawada, Yu; Endo, Itaru; Saito, Keigo; Uemura, Yasushi; Nakatsura, Tetsuya

2015-01-01

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Although the prognosis of patients with HCC is generally poor, the 5-year survival rate is > 70% if patients are diagnosed at an early stage. However, early diagnosis of HCC is complicated by the coexistence of inflammation and cirrhosis. Thus, novel biomarkers for the early diagnosis of HCC are required. Currently, the diagnosis of HCC without pathological correlation is achieved by analyzing serum α-fetoprotein levels combined with imaging techniques. Advances in genomics and proteomics platforms and biomarker assay techniques over the last decade have resulted in the identification of numerous novel biomarkers and have improved the diagnosis of HCC. The most promising biomarkers, such as glypican-3, osteopontin, Golgi protein-73 and nucleic acids including microRNAs, are most likely to become clinically validated in the near future. These biomarkers are not only useful for early diagnosis of HCC, but also provide insight into the mechanisms driving oncogenesis. In addition, such molecular insight creates the basis for the development of potentially more effective treatment strategies. In this article, we provide an overview of the biomarkers that are currently used for the early diagnosis of HCC. PMID:26457017

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

PubMed Central

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

The use of biomarkers in occupational health research, practice, and policy.

PubMed

Schulte, P A; Hauser, J E

2012-08-13

Biomarkers are potentially useful tools for occupational health and safety research, practice, and policy. However, the full realization of this potential has not been achieved. In this paper, the progress made in these three usage areas is reviewed to identify what efforts can be taken to realize the full promise of biomarkers. Biomarker uses are described by a diverse taxonomy that builds on the categories of exposure, effect and susceptibility, and the continuum between exposure and disease prognosis. The most significant uses of biomarkers in occupational health have been in biological monitoring of workers. Other important uses have been in enhancing research and assessing mechanisms of action of occupational toxicants at low exposures. Seven critical areas will influence the extent to which the potential of biomarkers in occupational health and safety is realized. These include: (1) adequate investment in validation; (2) obtaining international agreement on exposure guidelines; (3) exploring the utility of biomarkers in regulation; (4) applying biomarkers to critical occupational safety and health questions; (5) developing the exposome; (6) utilizing biomarkers to address emerging occupational health issues; and (7) continuing to address the ethical and social justice issues related to biomarkers. Overall, if biomarkers are to make a major contribution to occupational health and safety then a more holistic approach to bringing them from the laboratory to practice will be needed. Published by Elsevier Ireland Ltd.

A rapid method for preparation of the cerebrospinal fluid proteome.

PubMed

Larssen, Eivind; Brede, Cato; Hjelle, Anne Bjørnstad; Øysaed, Kjell Birger; Tjensvoll, Anne Bolette; Omdal, Roald; Ruoff, Peter

2015-01-01

The cerebrospinal fluid (CSF) proteome is of great interest for investigation of diseases and conditions involving the CNS. However, the presence of high-abundance proteins (HAPs) can interfere with the detection of low-abundance proteins, potentially hindering the discovery of new biomarkers. Therefore, an assessment of the CSF subproteome composition requires depletion strategies. Existing methods are time consuming, often involving multistep protocols. Here, we present a rapid, accurate, and reproducible method for preparing the CSF proteome, which allows the identification of a high number of proteins. This method involves acetonitrile (ACN) precipitation for depleting HAPs, followed by immediate trypsination. As an example, we demonstrate that this method allows discrimination between multiple sclerosis patients and healthy subjects. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Application of SILAC Mouse in Human Body Fluid Proteomics Analysis Reveals Protein Patterns Associated with IgA Nephropathy.

PubMed

Zhao, Shilin; Li, Rongxia; Cai, Xiaofan; Chen, Wanjia; Li, Qingrun; Xing, Tao; Zhu, Wenjie; Chen, Y Eugene; Zeng, Rong; Deng, Yueyi

2013-01-01

Body fluid proteome is the most informative proteome from a medical viewpoint. But the lack of accurate quantitation method for complicated body fluid limited its application in disease research and biomarker discovery. To address this problem, we introduced a novel strategy, in which SILAC-labeled mouse serum was used as internal standard for human serum and urine proteome analysis. The SILAC-labeled mouse serum was mixed with human serum and urine, and multidimensional separation coupled with tandem mass spectrometry (IEF-LC-MS/MS) analysis was performed. The shared peptides between two species were quantified by their SILAC pairs, and the human-only peptides were quantified by mouse peptides with coelution. The comparison for the results from two replicate experiments indicated the high repeatability of our strategy. Then the urine from Immunoglobulin A nephropathy patients treated and untreated was compared by this quantitation strategy. Fifty-three peptides were found to be significantly changed between two groups, including both known diagnostic markers for IgAN and novel candidates, such as Complement C3, Albumin, VDBP, ApoA,1 and IGFBP7. In conclusion, we have developed a practical and accurate quantitation strategy for comparison of complicated human body fluid proteome. The results from such strategy could provide potential disease-related biomarkers for evaluation of treatment.

Microwave & Magnetic (M2) Proteomics Reveals CNS-Specific Protein Expression Waves that Precede Clinical Symptoms of Experimental Autoimmune Encephalomyelitis

NASA Astrophysics Data System (ADS)

Raphael, Itay; Mahesula, Swetha; Purkar, Anjali; Black, David; Catala, Alexis; Gelfond, Jonathon A. L.; Forsthuber, Thomas G.; Haskins, William E.

2014-09-01

Central nervous system-specific proteins (CSPs), transported across the damaged blood-brain-barrier (BBB) to cerebrospinal fluid (CSF) and blood (serum), might be promising diagnostic, prognostic and predictive protein biomarkers of disease in individual multiple sclerosis (MS) patients because they are not expected to be present at appreciable levels in the circulation of healthy subjects. We hypothesized that microwave & magnetic (M2) proteomics of CSPs in brain tissue might be an effective means to prioritize putative CSP biomarkers for future immunoassays in serum. To test this hypothesis, we used M2 proteomics to longitudinally assess CSP expression in brain tissue from mice during experimental autoimmune encephalomyelitis (EAE), a mouse model of MS. Confirmation of central nervous system (CNS)-infiltrating inflammatory cell response and CSP expression in serum was achieved with cytokine ELISPOT and ELISA immunoassays, respectively, for selected CSPs. M2 proteomics (and ELISA) revealed characteristic CSP expression waves, including synapsin-1 and α-II-spectrin, which peaked at day 7 in brain tissue (and serum) and preceded clinical EAE symptoms that began at day 10 and peaked at day 20. Moreover, M2 proteomics supports the concept that relatively few CNS-infiltrating inflammatory cells can have a disproportionally large impact on CSP expression prior to clinical manifestation of EAE.

Omics-based biomarkers: current status and potential use in the clinic.

PubMed

Quezada, Héctor; Guzmán-Ortiz, Ana Laura; Díaz-Sánchez, Hugo; Valle-Rios, Ricardo; Aguirre-Hernández, Jesús

In recent years, the use of high-throughput omics technologies has led to the rapid discovery of many candidate biomarkers. However, few of them have made the transition to the clinic. In this review, the promise of omics technologies to contribute to the process of biomarker development is described. An overview of the current state in this area is presented with examples of genomics, proteomics, transcriptomics, metabolomics and microbiomics biomarkers in the field of oncology, along with some proposed strategies to accelerate their validation and translation to improve the care of patients with neoplasms. The inherent complexity underlying neoplasms combined with the requirement of developing well-designed biomarker discovery processes based on omics technologies present a challenge for the effective development of biomarkers that may be useful in guiding therapies, addressing disease risks, and predicting clinical outcomes. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Proteomic Analysis of Serum from Patients with Major Depressive Disorder to Compare Their Depressive and Remission Statuses

PubMed Central

Lee, Jiyeong; Joo, Eun-Jeong; Lim, Hee-Joung; Park, Jong-Moon; Lee, Kyu Young; Park, Arum; Seok, AeEun

2015-01-01

Objective Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. Methods Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. Results The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. Conclusion This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation. PMID:25866527

To label or not to label: applications of quantitative proteomics in neuroscience research.

PubMed

Filiou, Michaela D; Martins-de-Souza, Daniel; Guest, Paul C; Bahn, Sabine; Turck, Christoph W

2012-02-01

Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Growth and Proteome Response of Temperate and Polar Diatoms Thalassiosira pseudonana and Chaetoceros sp. to variations in Cobalt and Zinc: Identification of the High-Affinity Zinc Transporter and Potential for Use as a Biomarker

NASA Astrophysics Data System (ADS)

Kellogg, M. M.; Moran, D. M.; McIlvin, M. R.; Allen, A. E.; Saito, M. A.

2016-02-01

Marine diatoms such as the temperate Thalassiosira pseudonana (Tp) and the polar Chaetoceros sp (Ch) are known to be important contributors to marine primary productivity and the global carbon cycle. The nutritional use of zinc (Zn) in diatoms and the ability to substitute cobalt (Co) for Zn has been previously demonstrated to be of importance in their growth and biochemistry. We conducted physiological experiments with Zn and Co on these diatoms and analyzed their proteomic response. Growth studies involving Tp confirmed previous studies' findings showing Zn/Co substitution, while studies on Ch showed a toxic response to high Zn abundances. Proteome responses of Tp to Zn limitation identified a putative and previously unidentified transporter that was undetectable at high Zn concentration and became highly abundant at two lower Zn concentrations. The distribution of this protein in nature and its potential use as a Zn stress biomarker in diatoms will be discussed.

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

PubMed

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

2017-02-10

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

Monitoring Peptidase Activities in Complex Proteomes by MALDI-TOF Mass Spectrometry

PubMed Central

Villanueva, Josep; Nazarian, Arpi; Lawlor, Kevin; Tempst, Paul

2009-01-01

Measuring enzymatic activities in biological fluids is a form of activity-based proteomics and may be utilized as a means of developing disease biomarkers. Activity-based assays allow amplification of output signals, thus potentially visualizing low-abundant enzymes on a virtually transparent whole-proteome background. The protocol presented here describes a semi-quantitative in vitro assay of proteolytic activities in complex proteomes by monitoring breakdown of designer peptide-substrates using robotic extraction and a MALDI-TOF mass spectrometric read-out. Relative quantitation of the peptide metabolites is done by comparison with spiked internal standards, followed by statistical analysis of the resulting mini-peptidome. Partial automation provides reproducibility and throughput essential for comparing large sample sets. The approach may be employed for diagnostic or predictive purposes and enables profiling of 96 samples in 30 hours. It could be tailored to many diagnostic and pharmaco-dynamic purposes, as a read-out of catalytic and metabolic activities in body fluids or tissues. PMID:19617888

Methodology and Applications of Disease Biomarker Identification in Human Serum

PubMed Central

Sahab, Ziad J.; Semaan, Suzan M.; Sang, Qing-Xiang Amy

2007-01-01

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood. PMID:19662190

Salivary Biomarkers in Cancer Detection

PubMed Central

Wang, Xiaoqian; Kaczor-Urbanowicz, Karolina Elżbieta; Wong, David T.W.

2017-01-01

Cancer is the second most common cause of death in the United States. Its symptoms are often not specific and absent, until the tumors have already metastasized. Therefore, there is an urgent demand for developing rapid, highly accurate and non-invasive tools for cancer screening, early detection, diagnostics, staging and prognostics. Saliva as a multi-constituent oral fluid, comprises secretions from the major and minor salivary glands, extensively supplied by blood. Molecules such as DNAs, RNAs, proteins, metabolites, and microbiota, present in blood, could be also found in saliva. Recently, salivary diagnostics has drawn significant attention for the detection of specific biomarkers, since the sample collection and processing are simple, cost-effective, precise and do not cause patient discomfort. Here, we review recent salivary candidate biomarkers for systemic cancers by dividing them according to their origin into: genomic, transcriptomic, proteomic, metabolomic and microbial types. PMID:27943101

Standardized protocols for quality control of MRM-based plasma proteomic workflows.

PubMed

Percy, Andrew J; Chambers, Andrew G; Smith, Derek S; Borchers, Christoph H

2013-01-04

Mass spectrometry (MS)-based proteomics is rapidly emerging as a viable technology for the identification and quantitation of biological samples, such as human plasma--the most complex yet commonly employed biofluid in clinical analyses. The transition from a qualitative to quantitative science is required if proteomics is going to successfully make the transition to a clinically useful technique. MS, however, has been criticized for a lack of reproducibility and interlaboratory transferability. Currently, the MS and plasma proteomics communities lack standardized protocols and reagents to ensure that high-quality quantitative data can be accurately and precisely reproduced by laboratories across the world using different MS technologies. Toward addressing this issue, we have developed standard protocols for multiple reaction monitoring (MRM)-based assays with customized isotopically labeled internal standards for quality control of the sample preparation workflow and the MS platform in quantitative plasma proteomic analyses. The development of reference standards and their application to a single MS platform is discussed herein, along with the results from intralaboratory tests. The tests highlighted the importance of the reference standards in assessing the efficiency and reproducibility of the entire bottom-up proteomic workflow and revealed errors related to the sample preparation and performance quality and deficits of the MS and LC systems. Such evaluations are necessary if MRM-based quantitative plasma proteomics is to be used in verifying and validating putative disease biomarkers across different research laboratories and eventually in clinical laboratories.

Next-Generation Proteomics and Its Application to Clinical Breast Cancer Research.

PubMed

Mardamshina, Mariya; Geiger, Tamar

2017-10-01

Proteomics technology aims to map the protein landscapes of biological samples, and it can be applied to a variety of samples, including cells, tissues, and body fluids. Because the proteins are the main functional molecules in the cells, their levels reflect much more accurately the cellular phenotype and the regulatory processes within them than gene levels, mutations, and even mRNA levels. With the advancement in the technology, it is possible now to obtain comprehensive views of the biological systems and to study large patient cohorts in a streamlined manner. In this review we discuss the technological advancements in mass spectrometry-based proteomics, which allow analysis of breast cancer tissue samples, leading to the first large-scale breast cancer proteomics studies. Furthermore, we discuss the technological developments in blood-based biomarker discovery, which provide the basis for future development of assays for routine clinical use. Although these are only the first steps in implementation of proteomics into the clinic, extensive collaborative work between these worlds will undoubtedly lead to major discoveries and advances in clinical practice. Copyright © 2017 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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.

Proteomic and N-glycoproteomic quantification reveal aberrant changes in the human saliva of oral ulcer patients.

PubMed

Zhang, Ying; Wang, Xi; Cui, Dan; Zhu, Jun

2016-12-01

Human whole saliva is a vital body fluid for studying the physiology and pathology of the oral cavity. As a powerful technique for biomarker discovery, MS-based proteomic strategies have been introduced for saliva analysis and identified hundreds of proteins and N-glycosylation sites. However, there is still a lack of quantitative analysis, which is necessary for biomarker screening and biological research. In this study, we establish an integrated workflow by the combination of stable isotope dimethyl labeling, HILIC enrichment, and high resolution MS for both quantification of the global proteome and N-glycoproteome of human saliva from oral ulcer patients. With the help of advanced bioinformatics, we comprehensively studied oral ulcers at both protein and glycoprotein scales. Bioinformatics analyses revealed that starch digestion and protein degradation activities are inhibited while the immune response is promoted in oral ulcer saliva. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomarkers for equine joint injury and osteoarthritis.

PubMed

McIlwraith, C Wayne; Kawcak, Christopher E; Frisbie, David D; Little, Christopher B; Clegg, Peter D; Peffers, Mandy J; Karsdal, Morten A; Ekman, Stina; Laverty, Sheila; Slayden, Richard A; Sandell, Linda J; Lohmander, L S; Kraus, Virginia B

2018-03-01

We report the results of a symposium aimed at identifying validated biomarkers that can be used to complement clinical observations for diagnosis and prognosis of joint injury leading to equine osteoarthritis (OA). Biomarkers might also predict pre-fracture change that could lead to catastrophic bone failure in equine athletes. The workshop was attended by leading scientists in the fields of equine and human musculoskeletal biomarkers to enable cross-disciplinary exchange and improve knowledge in both. Detailed proceedings with strategic planning was written, added to, edited and referenced to develop this manuscript. The most recent information from work in equine and human osteoarthritic biomarkers was accumulated, including the use of personalized healthcare to stratify OA phenotypes, transcriptome analysis of anterior cruciate ligament (ACL) and meniscal injuries in the human knee. The spectrum of "wet" biomarker assays that are antibody based that have achieved usefulness in both humans and horses, imaging biomarkers and the role they can play in equine and human OA was discussed. Prediction of musculoskeletal injury in the horse remains a challenge, and the potential usefulness of spectroscopy, metabolomics, proteomics, and development of biobanks to classify biomarkers in different stages of equine and human OA were reviewed. The participants concluded that new information and studies in equine musculoskeletal biomarkers have potential translational value for humans and vice versa. OA is equally important in humans and horses, and the welfare issues associated with catastrophic musculoskeletal injury in horses add further emphasis to the need for good validated biomarkers in the horse. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:823-831, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma.

PubMed

O'Grady, John P; Meyer, Kevin W; Poe, Derrick N

2017-01-01

The improving efficacy of many biological therapeutics and identification of low-level biomarkers are driving the analytical proteomics community to deal with extremely high levels of sample complexity relative to their analytes. Many protein quantitation and biomarker validation procedures utilize an immunoaffinity enrichment step to purify the sample and maximize the sensitivity of the corresponding liquid chromatography tandem mass spectrometry measurements. In order to generate surrogate peptides with better mass spectrometric properties, protein enrichment is followed by a proteolytic cleavage step. This is often a time-consuming multistep process. Presented here is a workflow which enables rapid protein enrichment and proteolytic cleavage to be performed in a single, easy-to-use reactor. Using this strategy Klotho, a low-abundance biomarker found in plasma, can be accurately quantitated using a protocol that takes under 5 h from start to finish.

Comparative Testis Tissue Proteomics Using 2-Dye Versus 3-Dye DIGE Analysis.

PubMed

Holland, Ashling

2018-01-01

Comparative tissue proteomics aims to analyze alterations of the proteome in response to a stimulus. Two-dimensional difference gel electrophoresis (2D-DIGE) is a modified and advanced form of 2D gel electrophoresis. DIGE is a powerful biochemical method that compares two or three protein samples on the same analytical gel, and can be used to establish differentially expressed protein levels between healthy normal and diseased pathological tissue sample groups. Minimal DIGE labeling can be used via a 2-dye system with Cy3 and Cy5 or a 3-dye system with Cy2, Cy3, and Cy5 to fluorescently label samples with CyDye flours pre-electrophoresis. DIGE circumvents gel-to-gel variability by multiplexing samples to a single gel and through the use of a pooled internal standard for normalization. This form of quantitative high-resolution proteomics facilitates the comparative analysis and evaluation of tissue protein compositions. Comparing tissue groups under different conditions is crucially important for advancing the biomedical field by characterization of cellular processes, understanding pathophysiological development and tissue biomarker discovery. This chapter discusses 2D-DIGE as a comparative tissue proteomic technique and describes in detail the experimental steps required for comparative proteomic analysis employing both options of 2-dye and 3-dye DIGE minimal labeling.

Phosphoproteomic biomarkers predicting histologic nonalcoholic steatohepatitis and fibrosis.

PubMed

Younossi, Zobair M; Baranova, Ancha; Stepanova, Maria; Page, Sandra; Calvert, Valerie S; Afendy, Arian; Goodman, Zachary; Chandhoke, Vikas; Liotta, Lance; Petricoin, Emanuel

2010-06-04

The progression of nonalcoholic fatty liver disease (NAFLD) has been linked to deregulated exchange of the endocrine signaling between adipose and liver tissue. Proteomic assays for the phosphorylation events that characterize the activated or deactivated state of the kinase-driven signaling cascades in visceral adipose tissue (VAT) could shed light on the pathogenesis of nonalcoholic steatohepatitis (NASH) and related fibrosis. Reverse-phase protein microarrays (RPMA) were used to develop biomarkers for NASH and fibrosis using VAT collected from 167 NAFLD patients (training cohort, N = 117; testing cohort, N = 50). Three types of models were developed for NASH and advanced fibrosis: clinical models, proteomics models, and combination models. NASH was predicted by a model that included measurements of two components of the insulin signaling pathway: AKT kinase and insulin receptor substrate 1 (IRS1). The models for fibrosis were less reliable when predictions were based on phosphoproteomic, clinical, or the combination data. The best performing model relied on levels of the phosphorylation of GSK3 as well as on two subunits of cyclic AMP regulated protein kinase A (PKA). Phosphoproteomics technology could potentially be used to provide pathogenic information about NASH and NASH-related fibrosis. This information can lead to a clinically relevant diagnostic/prognostic biomarker for NASH.

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

PubMed

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

2017-03-01

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

Molecular biomarkers to guide precision medicine in localized prostate cancer.

PubMed

Smits, Minke; Mehra, Niven; Sedelaar, Michiel; Gerritsen, Winald; Schalken, Jack A

2017-08-01

Major advances through tumor profiling technologies, that include next-generation sequencing, epigenetic, proteomic and transcriptomic methods, have been made in primary prostate cancer, providing novel biomarkers that may guide precision medicine in the near future. Areas covered: The authors provided an overview of novel molecular biomarkers in tissue, blood and urine that may be used as clinical tools to assess prognosis, improve selection criteria for active surveillance programs, and detect disease relapse early in localized prostate cancer. Expert commentary: Active surveillance (AS) in localized prostate cancer is an accepted strategy in patients with very low-risk prostate cancer. Many more patients may benefit from watchful waiting, and include patients of higher clinical stage and grade, however selection criteria have to be optimized and early recognition of transformation from localized to lethal disease has to be improved by addition of molecular biomarkers. The role of non-invasive biomarkers is challenging the need for repeat biopsies, commonly performed at 1 and 4 years in men under AS programs.

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. Copyright © 2013 Elsevier Inc. All rights reserved.

Proteomic Profiling of Serial Prediagnostic Serum Samples for Early Detection of Colon Cancer in the U.S. Military.

PubMed

Shao, Stephanie; Neely, Benjamin A; Kao, Tzu-Cheg; Eckhaus, Janet; Bourgeois, Jolie; Brooks, Jasmin; Jones, Elizabeth E; Drake, Richard R; Zhu, Kangmin

2017-05-01

Background: Serum proteomic biomarkers offer a promising approach for early detection of cancer. In this study, we aimed to identify proteomic profiles that could distinguish colon cancer cases from controls using serial prediagnostic serum samples. Methods: This was a nested case-control study of active duty military members. Cases consisted of 264 patients diagnosed with colon cancer between 2001 and 2009. Controls were matched to cases on age, gender, race, serum sample count, and collection date. We identified peaks that discriminated cases from controls using random forest data analysis with a 2/3 training and 1/3 validation dataset. We then included epidemiologic data to see whether further improvement of model performance was obtainable. Proteins that corresponded to discriminatory peaks were identified. Results: Peaks with m/z values of 3,119.32, 2,886.67, 2,939.23, and 5,078.81 were found to discriminate cases from controls with a sensitivity of 69% and a specificity of 67% in the year before diagnosis. When smoking status was included, sensitivity increased to 76% while histories of other cancer and tonsillectomy raised specificity to 76%. Peaks at 2,886.67 and 3,119.32 m/z were identified as histone acetyltransferases while 2,939.24 m/z was a transporting ATPase subunit. Conclusions: Proteomic profiles in the year before cancer diagnosis have the potential to discriminate colon cancer patients from controls, and the addition of epidemiologic information may increase the sensitivity and specificity of discrimination. Impact: Our findings indicate the potential value of using serum prediagnostic proteomic biomarkers in combination with epidemiologic data for early detection of colon cancer. Cancer Epidemiol Biomarkers Prev; 26(5); 711-8. ©2016 AACR . ©2016 American Association for Cancer Research.

Profiling the Aspergillus fumigatus Proteome in Response to Caspofungin ▿ †

PubMed Central

Cagas, Steven E.; Jain, Mohit Raja; Li, Hong; Perlin, David S.

2011-01-01

The proteomic response of Aspergillus fumigatus to caspofungin was evaluated by gel-free isobaric tagging for relative and absolute quantitation (iTRAQ) as a means to determine potential biomarkers of drug action. A cell fractionation approach yielding 4 subcellular compartment fractions was used to enhance the resolution of proteins for proteomic analysis. Using iTRAQ, a total of 471 unique proteins were identified in soluble and cell wall/plasma membrane fractions at 24 and 48 h of growth in rich media in a wild-type drug-susceptible strain. A total of 122 proteins showed at least a 2-fold change in relative abundance following exposure to caspofungin (CSF) at just below the minimum effective concentration (0.12 μg/ml). The largest changes were seen in the mitochondrial hypoxia response domain protein (AFUA_1G12250), the level of which decreased >16-fold in the secreted fraction, and ChiA1, the level of which decreased 12.1-fold in the cell wall/plasma membrane fraction. The level of the major allergen and cytotoxin AspF1 was also shown to decrease by 12.1-fold upon the addition of drug. A subsequent iTRAQ analysis of an echinocandin-resistant strain (fks1-S678P) was used to validate proteins specific to drug action. A total of 103 proteins in the 2 fractions tested by iTRAQ were differentially expressed in the wild-type susceptible strain but not significantly changed in the resistant strain. Of these potential biomarkers, 11 had levels that changed at least 12-fold. Microarray analysis of the susceptible strain was performed to evaluate the correlation between proteomics and genomics, with a total of 117 genes found to be changing at least 2-fold. Of these, a total of 22 proteins with significant changes identified by iTRAQ also showed significant gene expression level changes by microarray. Overall, these data have the potential to identify biomarkers that assess the relative efficacy of echinocandin drug therapy. PMID:20974863

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This

The search for biomarkers of hepatocellular carcinoma and the impact on patient outcome.

PubMed

Black, Alyson P; Mehta, Anand S

2018-05-14

Hepatocellular carcinoma (HCC) is the 5th most common cancer, but the 3rd leading cause of cancer death globally with approximately 700,000 fatalities annually. The severity of this cancer arises from its difficulty to detect and treat. The major etiologies of HCC are liver fibrosis or cirrhosis from chronic viral infections, as well as metabolic conditions. Since most cases arise from prior pathologies, biomarker surveillance in high-risk individuals is an essential approach for early detection and improved patient outcome. While many molecular biomarkers have been associated with HCC, there are few that have made clinical impact for this disease. Here we review some major approaches used for HCC biomarker discovery-proteomics and glycomics-and describe new methodologies being tested for biomarker development. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative proteomic profiling of the serum differentiates pancreatic cancer from chronic pancreatitis.

PubMed

Saraswat, Mayank; Joenväärä, Sakari; Seppänen, Hanna; Mustonen, Harri; Haglund, Caj; Renkonen, Risto

2017-07-01

Finland ranks sixth among the countries having highest incidence rate of pancreatic cancer with mortality roughly equaling incidence. The average age of diagnosis for pancreatic cancer is 69 years in Nordic males, whereas the average age of diagnosis of chronic pancreatitis is 40-50 years, however, many cases overlap in age. By radiology, the evaluation of a pancreatic mass, that is, the differential diagnosis between chronic pancreatitis and pancreatic cancer is often difficult. Preoperative needle biopsies are difficult to obtain and are demanding to interpret. New blood based biomarkers are needed. The accuracy of the only established biomarker for pancreatic cancer, CA 19-9 is rather poor in differentiating between benign and malignant mass of the pancreas. In this study, we have performed mass spectrometry analysis (High Definition MS E ) of serum samples from patients with chronic pancreatitis (13) and pancreatic cancer (22). We have quantified 291 proteins and performed detailed statistical analysis such as principal component analysis, orthogonal partial least square discriminant analysis and receiver operating curve analysis. The proteomic signature of chronic pancreatitis versus pancreatic cancer samples was able to separate the two groups by multiple statistical techniques. Some of the enriched pathways in the proteomic dataset were LXR/RXR activation, complement and coagulation systems and inflammatory response. We propose that multiple high-confidence biomarker candidates in our pilot study including Inter-alpha-trypsin inhibitor heavy chain H2 (Area under the curve, AUC: 0.947), protein AMBP (AUC: 0.951) and prothrombin (AUC: 0.917), which should be further evaluated in larger patient series as potential new biomarkers for differential diagnosis. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Identification of candidate biomarkers of the exposure to PCBs in contaminated cattle: A gene expression- and proteomic-based approach.

PubMed

Girolami, F; Badino, P; Spalenza, V; Manzini, L; Renzone, G; Salzano, A M; Dal Piaz, F; Scaloni, A; Rychen, G; Nebbia, C

2018-05-28

Dioxins and polychlorinated biphenyls (PCBs) are widespread and persistent contaminants. Through a combined gene expression/proteomic-based approach, candidate biomarkers of the exposure to such environmental pollutants in cattle subjected to a real eco-contamination event were identified. Animals were removed from the polluted area and fed a standard ration for 6 months. The decontamination was monitored by evaluating dioxin and PCB levels in pericaudal fat two weeks after the removal from the contaminated area (day 0) and then bimonthly for six months (days 59, 125 and 188). Gene expression measurements demonstrated that CYP1B1 expression was significantly higher in blood lymphocytes collected in contaminated animals (day 0), and decreased over time during decontamination. mRNA levels of interleukin 2 showed an opposite quantitative trend. MALDI-TOF-MS polypeptide profiling of serum samples ascertained a progressive decrease (from day 0 to 188) of serum levels of fibrinogen β-chain and serpin A3-7-like fragments, apolipoprotein (APO) C-II and serum amyloid A-4 protein, along with an augmented representation of transthyretin isoforms, as well as APOC-III and APOA-II proteins during decontamination. When differentially represented species were combined with serum antioxidant, acute phase and proinflammatory protein levels already ascertained in the same animals (Cigliano et al., 2016), bioinformatics unveiled an interaction network linking together almost all components. This suggests the occurrence of a complex PCB-responsive mechanism associated with animal contamination/decontamination, including a cohort of protein/polypeptide species involved in blood redox homeostasis, inflammation and lipid transport. All together, these results suggest the use in combination of such biomarkers for identifying PCB-contaminated animals, and for monitoring the restoring of their healthy condition following a decontamination process. Copyright © 2018 Elsevier B.V. All

Advances in targeted proteomics and applications to biomedical research

PubMed Central

Shi, Tujin; Song, Ehwang; Nie, Song; Rodland, Karin D.; Liu, Tao; Qian, Wei-Jun; Smith, Richard D.

2016-01-01

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) with targeted data extraction on fast scanning high-resolution accurate-mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale quantification of hundreds of target proteins are discussed. PMID:27302376

Subfractionation, characterization and in-depth proteomic analysis of glomerular membrane vesicles in human urine

PubMed Central

Hogan, Marie C.; Johnson, Kenneth L.; Zenka, Roman M.; Charlesworth, M. Cristine; Madden, Benjamin J.; Mahoney, Doug W.; Oberg, Ann L.; Huang, Bing Q.; Nesbitt, Lisa L.; Bakeberg, Jason L.; Bergen, H. Robert; Ward, Christopher J.

2014-01-01

Urinary exosome-like vesicles (ELVs) are a heterogenous mixture (diameter 40–200nm) containing vesicles shed from all segments of the nephron including glomerular podocytes. Contamination with Tamm Horsfall protein (THP) oligomers has hampered their isolation and proteomic analysis. Here we improved ELV isolation protocols employing density centrifugation to remove THP and albumin, and isolated a glomerular membranous vesicle (GMV) enriched subfraction from 7 individuals identifying 1830 proteins and in 3 patients with glomerular disease identifying 5657 unique proteins. The GMV fraction was composed of podocin/podocalyxin positive irregularly shaped membranous vesicles and podocin/podocalyxin negative classical exosomes. Ingenuity pathway analysis identified integrin, actin cytoskeleton and RhoGDI signaling in the top three canonical represented signaling pathways and 19 other proteins associated with inherited glomerular diseases. The GMVs are of podocyte origin and the density gradient technique allowed isolation in a reproducible manner. We show many nephrotic syndrome proteins, proteases and complement proteins involved in glomerular disease are in GMVs and some were shed in the disease state (nephrin, TRPC6 and INF2 and PLA2R). We calculated sample sizes required to identify new glomerular disease biomarkers, expand the ELV proteome and provide a reference proteome in a database that may prove useful in the search for biomarkers of glomerular disease. PMID:24196483

The unique peptidome: Taxon-specific tryptic peptides as biomarkers for targeted metaproteomics.

PubMed

Mesuere, Bart; Van der Jeugt, Felix; Devreese, Bart; Vandamme, Peter; Dawyndt, Peter

2016-09-01

The Unique Peptide Finder (http://unipept.ugent.be/peptidefinder) is an interactive web application to quickly hunt for tryptic peptides that are unique to a particular species, genus, or any other taxon. Biodiversity within the target taxon is represented by a set of proteomes selected from a monthly updated list of complete and nonredundant UniProt proteomes, supplemented with proprietary proteomes loaded into persistent local browser storage. The software computes and visualizes pan and core peptidomes as unions and intersections of tryptic peptides occurring in the selected proteomes. In addition, it also computes and displays unique peptidomes as the set of all tryptic peptides that occur in all selected proteomes but not in any UniProt record not assigned to the target taxon. As a result, the unique peptides can serve as robust biomarkers for the target taxon, for example, in targeted metaproteomics studies. Computations are extremely fast since they are underpinned by the Unipept database, the lowest common ancestor algorithm implemented in Unipept and modern web technologies that facilitate in-browser data storage and parallel processing. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A proteomic signature of ovarian cancer tumor fluid identified by highthroughput and verified by targeted proteomics.

PubMed

Poersch, Aline; Grassi, Mariana Lopes; Carvalho, Vinícius Pereira de; Lanfredi, Guilherme Pauperio; Palma, Camila de Souza; Greene, Lewis Joel; de Sousa, Christiani Bisinoto; Carrara, Hélio Humberto Angotti; Candido Dos Reis, Francisco José; Faça, Vitor Marcel

2016-08-11

Tumor fluid samples have emerged as a rich source for the identification of ovarian cancer in the context of proteomics studies. To uncover differences among benign and malignant ovarian samples, we performed a quantitative proteomic study consisting of albumin immunodepletion, isotope labeling with acrylamide and in-depth proteomic profiling by LC-MS/MS in a pool of 10 samples of each histological type. 1135 proteins were identified, corresponding to 505 gene products. 223 proteins presented associated quantification and the comparative analysis of histological types revealed 75 differentially abundant proteins. Based on this, we developed a panel for targeted proteomic analysis using the multiple reaction monitoring (MRM) method for validation of 51 proteins in individual samples of high-grade serous ovarian tumor fluids (malignant) and benign serous cystadenoma tumor fluids. This analysis showed concordant results in terms of average amounts of proteins, and APOE, SERPINF2, SERPING1, ADAM17, CD44 and OVGP1 were statistically significant between benign and malignant group. The results observed in the MRM for APOE were confirmed by western blotting, where APOE was more abundant in malignant samples. This molecular signature can contribute to improve tumor stratification and shall be investigated in combination with current biomarkers in larger cohorts to improve ovarian cancer diagnosis. Despite advances in cancer research, ovarian cancer has a high mortality and remains a major challenge due to a number of particularities of the disease, especially late diagnosis caused by vague clinical symptoms, the cellular and molecular heterogeneity of tumors, and the lack of effective treatment. Thus, efforts are directed to better understand this neoplasia, its origin, development and, particularly the identification and validation of biomarkers for early detection of the disease in asymptomatic stage. In the present work, we confirmed by MRM method in individual ovarian

Surviving the infarct: A profile of cardiac myosin binding protein-C pathogenicity, diagnostic utility, and proteomics in the ischemic myocardium.

PubMed

Lynch, Thomas L; Sadayappan, Sakthivel

2014-08-01

Cardiac myosin binding protein-C (cMyBP-C) is a regulatory protein of the contractile apparatus within the cardiac sarcomere. Ischemic injury to the heart during myocardial infarction (MI) results in the cleavage of cMyBP-C in a phosphorylation-dependent manner and release of an N-terminal fragment (C0C1f) into the circulation. C0C1f has been shown to be pathogenic within cardiac tissue, leading to the development of heart failure. Based on its high levels and early release into the circulation post-MI, C0C1f may serve as a novel biomarker for diagnosing MI more effectively than current clinically used biomarkers. Over time, circulating C0C1f could trigger an autoimmune response leading to myocarditis and progressive cardiac dysfunction. Given the importance of cMyBP-C phosphorylation state in the context of proteolytic cleavage and release into the circulation post-MI, understanding the posttranslational modifications (PTMs) of cMyBP-C would help in further elucidating the role of this protein in health and disease. Accordingly, recent studies have implemented the latest proteomics approaches to define the PTMs of cMyBP-C. The use of such proteomics assays may provide accurate quantitation of the levels of cMyBP-C in the circulation following MI, which could, in turn, demonstrate the efficacy of using plasma cMyBP-C as a cardiac-specific early biomarker of MI. In this review, we define the pathogenic and potential immunogenic effects of C0C1f on cardiac function in the post-MI heart. We also discuss the most advanced proteomics approaches now used to determine cMyBP-C PTMs with the aim of validating C0C1f as an early biomarker of MI. © The Authors PROTEOMICS - Clinical Applications Published by Wiley-VCH Verlag GmbH & Co. KGaA.

A High-Resolution Proteomic Landscaping of Primary Human Dental Stem Cells: Identification of SHED- and PDLSC-Specific Biomarkers.

PubMed

Taraslia, Vasiliki; Lymperi, Stefania; Pantazopoulou, Vasiliki; Anagnostopoulos, Athanasios K; Papassideri, Issidora S; Basdra, Efthimia K; Bei, Marianna; Kontakiotis, Evangelos G; Tsangaris, George Th; Stravopodis, Dimitrios J; Anastasiadou, Ema

2018-01-05

Dental stem cells (DSCs) have emerged as a promising tool for basic research and clinical practice. A variety of adult stem cell (ASC) populations can be isolated from different areas within the dental tissue, which, due to their cellular and molecular characteristics, could give rise to different outcomes when used in potential applications. In this study, we performed a high-throughput molecular comparison of two primary human adult dental stem cell (hADSC) sub-populations: Stem Cells from Human Exfoliated Deciduous Teeth (SHEDs) and Periodontal Ligament Stem Cells (PDLSCs). A detailed proteomic mapping of SHEDs and PDLSCs, via employment of nano-LC tandem-mass spectrometry (MS/MS) revealed 2032 identified proteins in SHEDs and 3235 in PDLSCs. In total, 1516 proteins were expressed in both populations, while 517 were unique for SHEDs and 1721 were exclusively expressed in PDLSCs. Further analysis of the recorded proteins suggested that SHEDs predominantly expressed molecules that are involved in organizing the cytoskeletal network, cellular migration and adhesion, whereas PDLSCs are highly energy-producing cells, vastly expressing proteins that are implicated in various aspects of cell metabolism and proliferation. Applying the Rho-GDI signaling pathway as a paradigm, we propose potential biomarkers for SHEDs and for PDLSCs, reflecting their unique features, properties and engaged molecular pathways.

A High-Resolution Proteomic Landscaping of Primary Human Dental Stem Cells: Identification of SHED- and PDLSC-Specific Biomarkers

PubMed Central

Taraslia, Vasiliki; Lymperi, Stefania; Pantazopoulou, Vasiliki; Anagnostopoulos, Athanasios K.; Basdra, Efthimia K.; Bei, Marianna; Kontakiotis, Evangelos G.; Tsangaris, George Th.; Stravopodis, Dimitrios J.; Anastasiadou, Ema

2018-01-01

Dental stem cells (DSCs) have emerged as a promising tool for basic research and clinical practice. A variety of adult stem cell (ASC) populations can be isolated from different areas within the dental tissue, which, due to their cellular and molecular characteristics, could give rise to different outcomes when used in potential applications. In this study, we performed a high-throughput molecular comparison of two primary human adult dental stem cell (hADSC) sub-populations: Stem Cells from Human Exfoliated Deciduous Teeth (SHEDs) and Periodontal Ligament Stem Cells (PDLSCs). A detailed proteomic mapping of SHEDs and PDLSCs, via employment of nano-LC tandem-mass spectrometry (MS/MS) revealed 2032 identified proteins in SHEDs and 3235 in PDLSCs. In total, 1516 proteins were expressed in both populations, while 517 were unique for SHEDs and 1721 were exclusively expressed in PDLSCs. Further analysis of the recorded proteins suggested that SHEDs predominantly expressed molecules that are involved in organizing the cytoskeletal network, cellular migration and adhesion, whereas PDLSCs are highly energy-producing cells, vastly expressing proteins that are implicated in various aspects of cell metabolism and proliferation. Applying the Rho-GDI signaling pathway as a paradigm, we propose potential biomarkers for SHEDs and for PDLSCs, reflecting their unique features, properties and engaged molecular pathways. PMID:29304003

Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

PubMed Central

Chauhan, Ranjit; Lahiri, Nivedita

2016-01-01

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

Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications.

PubMed

Sohail, Waleed; Majeed, Fatimah; Afroz, Amber

2018-06-11

The prevalence of Diabetes Mellitus Type 2 (DM 2) is increasing every passing year due to some global changes in lifestyles of people. The exact underlying mechanisms of the progression of this disease are not yet known. However recent advances in the combined omics more particularly in proteomics and genomics have opened a gateway towards the understanding of predetermined genetic factors, progression, complications and treatment of this disease. Here we shall review the recent advances in proteomics that have led to an early and better diagnostic approaches in controlling DM 2 more importantly the comparison of structural and functional protein biomarkers that are modified in the diseased state. By applying these advanced and promising proteomic strategies with bioinformatics applications and bio-statistical tools the prevalence of DM 2 and its associated disorders i-e nephropathy and retinopathy are expected to be controlled. Copyright © 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Application of “omics” to Prion Biomarker Discovery

PubMed Central

Huzarewich, Rhiannon L. C. H.; Siemens, Christine G.; Booth, Stephanie A.

2010-01-01

The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrPSc, a pathological isoform of the host protein PrPC, which is an essential component of the infectious prion. Immunochemical detection of PrPSc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrPSc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases. PMID:20224650

Contributions of immunoaffinity chromatography to deep proteome profiling of human biofluids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Chaochao; Duan, Jicheng; Liu, Tao

2016-05-01

Human biofluids, especially blood plasma or serum, hold great potential as the sources of potential biomarkers for various diseases; however, the enormous dynamic range of protein concentrations in biofluids represents a significant analytical challenge to detect promising low-abundance protein biomarkers. Over the last decade, various immunoaffinity chromatographic methods have been developed and routinely applied for separating low-abundance proteins from the high and moderate-abundance proteins, thus enabling more effective detection of low-abundance proteins. Herein, we review the advances of immunoaffinity separation methods and their contributions to the proteomics applications of different human biofluids. The limitations and future perspective of immunoaffinity separationmore » methods are also discussed.« less

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

PubMed

Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

2016-09-01

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

Osteoarthritis Year in Review 2016: biomarkers (biochemical markers).

PubMed

Mobasheri, A; Bay-Jensen, A-C; van Spil, W E; Larkin, J; Levesque, M C

2017-02-01

The aim of this "Year in Review" article is to summarize and discuss the implications of biochemical marker related articles published between the Osteoarthritis Research Society International (OARSI) 2015 Congress in Seattle and the OARSI 2016 Congress in Amsterdam. The PubMed/MEDLINE bibliographic database was searched using the combined keywords: 'biomarker' and 'osteoarthritis'. The PubMed/MEDLINE literature search was conducted using the Advanced Search Builder function (http://www.ncbi.nlm.nih.gov/pubmed/advanced). Over two hundred new biomarker-related papers were published during the literature search period. Some papers identified new biomarkers whereas others explored the biological properties and clinical utility of existing markers. There were specific references to several adipocytokines including leptin and adiponectin. ADAM Metallopeptidase with Thrombospondin Type 1 motif 4 (ADAMTS-4) and aggrecan ARGS neo-epitope fragment (ARGS) in synovial fluid (SF) and plasma chemokine (CeC motif) ligand 3 (CCL3) were reported as potential new knee biomarkers. New and refined proteomic technologies and novel assays including a fluoro-microbead guiding chip (FMGC) for measuring C-telopeptide of type II collagen (CTX-II) in serum and urine and a novel magnetic nanoparticle-based technology (termed magnetic capture) for collecting and concentrating CTX-II, were described this past year. There has been steady progress in osteoarthritis (OA) biomarker research in 2016. Several novel biomarkers were identified and new technologies have been developed for measuring existing biomarkers. However, there has been no "quantum leap" this past year and identification of novel early OA biomarkers remains challenging. During the past year, OARSI published a set of recommendations for the use of soluble biomarkers in clinical trials, which is a major step forward in the clinical use of OA biomarkers and bodes well for future OA biomarker development. Copyright © 2016 The

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

PubMed

Fowler, Bruce A; 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

Systematic Evaluation of the Use of Human Plasma and Serum for Mass-Spectrometry-Based Shotgun Proteomics.

PubMed

Lan, Jiayi; Núñez Galindo, Antonio; Doecke, James; Fowler, Christopher; Martins, Ralph N; Rainey-Smith, Stephanie R; Cominetti, Ornella; Dayon, Loïc

2018-04-06

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP 2 ). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP 2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

Individual Biomarkers Using Molecular Personalized Medicine Approaches.

PubMed

Zenner, Hans P

2017-01-01

Molecular personalized medicine tries to generate individual predictive biomarkers to assist doctors in their decision making. These are thought to improve the efficacy and lower the toxicity of a treatment. The molecular basis of the desired high-precision prediction is modern "omex" technologies providing high-throughput bioanalytical methods. These include genomics and epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, imaging, and functional analyses. In most cases, producing big data also requires a complex biomathematical analysis. Using molecular personalized medicine, the conventional physician's check of biomarker results may no longer be sufficient. By contrast, the physician may need to cooperate with the biomathematician to achieve the desired prediction on the basis of the analysis of individual big data typically produced by omex technologies. Identification of individual biomarkers using molecular personalized medicine approaches is thought to allow a decision-making for the precise use of a targeted therapy, selecting the successful therapeutic tool from a panel of preexisting drugs or medical products. This should avoid the treatment of nonresponders and responders that produces intolerable unwanted effects. © 2017 S. Karger AG, Basel.

Proteomics of drug resistance in Candida glabrata biofilms.

PubMed

Seneviratne, C Jayampath; Wang, Yu; Jin, Lijian; Abiko, Y; Samaranayake, Lakshman P

2010-04-01

Candida glabrata is a fungal pathogen that causes a variety of mucosal and systemic infections among compromised patient populations with higher mortality rates. Previous studies have shown that biofilm mode of the growth of the fungus is highly resistant to antifungal agents compared with the free-floating or planktonic mode of growth. Therefore, in the present study, we used 2-D DIGE to evaluate the differential proteomic profiles of C. glabrata under planktonic and biofilm modes of growth. Candida glabrata biofilms were developed on polystyrene surfaces and age-matched planktonic cultures were obtained in parallel. Initially, biofilm architecture, viability, and antifungal susceptibility were evaluated. Differentially expressed proteins more than 1.5-fold in DIGE analysis were subjected to MS/MS. The transcriptomic regulation of these biomarkers was evaluated by quantitative real-time PCR. Candida glabrata biofilms were highly resistant to the antifungals and biocides compared with the planktonic mode of growth. Candida glabrata biofilm proteome when compared with its planktonic proteome showed upregulation of stress response proteins, while glycolysis enzymes were downregulated. Similar trend could be observed at transcriptomic level. In conclusion, C. glabrata biofilms possess higher amount of stress response proteins, which may potentially contribute to the higher antifungal resistance seen in C. glabrata biofilms.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.

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

Proteomic Analysis of the Human Olfactory Bulb.

PubMed

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

2017-08-01

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

PROTEOMICS OF THE AMNIOTIC FLUID IN ASSESSMENT OF THE PLACENTA – RELEVANCE FOR PRETERM BIRTH

PubMed Central

Buhimschi, Irina A.; Buhimschi, Catalin S.

2008-01-01

Proteomics is the study of expressed proteins and has emerged as a complement to genomic research. The major advantage of proteomics over DNA-RNA based technologies is that it more closely relates to phenotype and not the source code. Proteomics thus holds the promise of providing direct insight into the true mechanisms of human disease. Historically, examination of the placenta was the first modality to subclassify pathogenetical entities responsible for preterm birth. Because placenta is a key pathophysiological participant in several major obstetrical syndromes (preterm birth, preeclampsia, intrauterine growth restriction) identification of relevant biomarkers of placental function can profoundly impact on the prediction of fetal outcome and treatment efficacy. Proteomics is a young science and studies that associate proteomic patterns with long-term outcome require follow-up of children up to school age. In the interim, placental pathological footprints of cellular injury can be useful as intermediate outcomes. Furthermore, knowledge of the identity of the dys-regulated proteins may provide the necessary insight into novel pathophysiological pathways and unravel possible targets for therapeutic intervention that could not have been envisioned through hypothesis-driven approaches. PMID:18191197

Circulating Extracellular Vesicles with Specific Proteome and Liver MicroRNAs Are Potential Biomarkers for Liver Injury in Experimental Fatty Liver Disease

PubMed Central

Povero, Davide; Eguchi, Akiko; Li, Hongying; Johnson, Casey D.; Papouchado, Bettina G.; Wree, Alexander; Messer, Karen; Feldstein, Ariel E.

2014-01-01

Background & Aim Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in both adult and children. Currently there are no reliable methods to determine disease severity, monitor disease progression, or efficacy of therapy, other than an invasive liver biopsy. Design Choline Deficient L-Amino Acid (CDAA) and high fat diets were used as physiologically relevant mouse models of NAFLD. Circulating extracellular vesicles were isolated, fully characterized by proteomics and molecular analyses and compared to control groups. Liver-related microRNAs were isolated from purified extracellular vesicles and liver specimens. Results We observed statistically significant differences in the level of extracellular vesicles (EVs) in liver and blood between two control groups and NAFLD animals. Time-course studies showed that EV levels increase early during disease development and reflect changes in liver histolopathology. EV levels correlated with hepatocyte cell death (r2 = 0.64, p<0.05), fibrosis (r2 = 0.66, p<0.05) and pathological angiogenesis (r2 = 0.71, p<0.05). Extensive characterization of blood EVs identified both microparticles (MPs) and exosomes (EXO) present in blood of NAFLD animals. Proteomic analysis of blood EVs detected various differentially expressed proteins in NAFLD versus control animals. Moreover, unsupervised hierarchical clustering identified a signature that allowed for discrimination between NAFLD and controls. Finally, the liver appears to be an important source of circulating EVs in NAFLD animals as evidenced by the enrichment in blood with miR-122 and 192 - two microRNAs previously described in chronic liver diseases, coupled with a corresponding decrease in expression of these microRNAs in the liver. Conclusions These findings suggest a potential for using specific circulating EVs as sensitive and specific biomarkers for the noninvasive diagnosis and monitoring of NAFLD. PMID:25470250

Integrated Proteomic Profiling of Cell Line Conditioned Media and Pancreatic Juice for the Identification of Pancreatic Cancer Biomarkers