PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “discovery proteomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7Linked to original sources
PubMed2006

Evaluation of multiprotein immunoaffinity subtraction for plasma proteomics and candidate biomarker discovery using mass spectrometry.

Strategies for removal of high abundance proteins have been increasingly utilized in proteomic studies of serum/plasma and other body fluids to enhance the detection of low abundance proteins and achieve broader proteome coverage; however, both the reproducibility and specificity of the high abundance protein depletion process still represent common concerns. Here we report a detailed evaluation of immunoaffinity subtraction performed applying the ProteomeLab IgY-12 system that is commonly used in human serum/plasma proteome characterization in combination with high resolution LC-MS/MS. Plasma samples were repeatedly processed using this approach, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. The removal of target proteins by the immunoaffinity subtraction system and the overall process was highly reproducible. Non-target proteins, including one spiked protein standard (rabbit glyceraldehyde-3-phosphate dehydrogenase), were also observed to bind to the column at different levels but also in a reproducible manner. The results suggest that multiprotein immunoaffinity subtraction systems can be readily integrated into quantitative strategies to enhance detection of low abundance proteins in biomarker discovery studies.

Biomarkers↗
PubMed2004

Proteomics for hepatocellular carcinoma marker discovery.

Refinements of serological markers and screening of patients at high risk for developing hepatocellular carcinoma (HCC) may lead to better HCC detection, earlier intervention, and successful treatment, improving long-term outcomes. Proteomics promises the discovery of biomarkers for early HCC detection and diagnosis. Proteomic-based profiling uniquely allows delineation of global changes in expression patterns resulting from transcriptional and posttranscriptional control, posttranslational modifications, and shifts in proteins between cellular compartments. Approaches to that effect include direct serum protein profiling and comparative analysis of protein expression in normal, precancerous, and early-stage tumor tissues. Identification of panels of tumor antigens that elicit a humoral response also may contribute to the discovery of new markers for HCC screening and diagnosis. Today, 2-dimensional polyacrylamide gel electrophoresis, multidimensional liquid chromatography, mass spectrometry, and protein microarrays are among the proteomic tools available for biomarker and drug target discovery. We review these technologies and their application to the study of HCC. Our objective is to provide a framework for appreciating the promise, while at the same time understanding the challenges behind translating proteomics discovery into novel diagnostic tests.

Biomarkers, Tumor↗
PubMed2004

Quality, not quantity: the role of natural products and chemical proteomics in modern drug discovery.

Chemical genetics and reverse chemical genetics parallel classical genetics but target genes at the protein level and have proven useful in recent years for screening combinatorial libraries for compounds of biological interest. However, the performance of combinatorial chemistry in filling pharmaceutical pipelines has been lower than anticipated and the tide may be turning back to Nature in the search for new drug candidates. Even though diversity oriented synthesis is now producing molecules that are natural product-like in terms of size and complexity, these molecules have not evolved to interact with biomolecules. Natural products, on the other hand, have evolved to interact with biomolecules, which is why so many can be found in pharmacopoeias. However, the cellular targets and modes of action of these fascinating compounds are seldom known, hindering the drug development process. This review focuses on the emergence of chemical proteomics and reverse chemical proteomics as tools for the discovery of cellular receptors for natural products, thereby generating protein/ligand pairs that will prove useful in identifying new drug targets and new biologically active small molecule scaffolds. Such a system-wide approach to identifying new drugable targets and their small molecule ligands will help unblock the pharmaceutical product pipelines by speeding the process of target and lead identification.

Animals↗
PubMed2002

Proteomics approaches towards antigen discovery and vaccine development.

Vaccines have proved to be powerful medical interventions, and recent advances in immunology and in microbial pathogen genomics now allow the rational design of molecularly defined vaccines. Classical proteomics and immunoproteomics approaches such as serological proteome analysis (SERPA) have already provided first vaccine candidate antigens. The same is true for approaches based on recombinant DNA technology, and in the future protein arrays may further accelerate this kind of research. Taken together, these technologies will allow identification of the full set of antigens (ie, the immunome) targeted by the immune system in a certain pathological situation. The comparison of multiple immunomes may allow the discovery of immunogenic structural features shared and conserved between different pathogens, which could form the basis of broadly protective vaccines. In this review, recent proteomics and other post-genomics approaches for the identification of antigens in infectious disease and cancer, as well as strategies for their characterization, are discussed.

Antigens↗
PubMed2004

Proteomic characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery.

Clinical cancer proteomics aims at the identification of markers for early detection and predictive purposes, as well as to provide novel targets for drug discovery and therapeutic intervention. Proteomics-based analysis of traditional sources of biomarkers, such as serum, plasma, or tissue lyzates, has resulted in a wealth of information and the finding of several potential tumor biomarkers. However, many of these markers have shown limited usefulness in a clinical setting, underscoring the need for new clinically relevant sources. Here we present a novel and highly promising source of biomarkers, the tumor interstitial fluid (TIF) that perfuses the breast tumor microenvironment. We collected TIFs from small pieces of freshly dissected invasive breast carcinomas and analyzed them by two-dimensional polyacrylamide gel electrophoresis in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Western immunoblotting, as well as by cytokine-specific antibody arrays. This approach provided for the first time a snapshot of the protein components of the TIF, which we show consists of more than one thousand proteins--either secreted, shed by membrane vesicles, or externalized due to cell death--produced by the complex network of cell types that make up the tumor microenvironment. So far, we have identified 267 primary translation products including, but not limited to, proteins involved in cell proliferation, invasion, angiogenesis, metastasis, inflammation, protein synthesis, energy metabolism, oxidative stress, the actin cytoskeleton assembly, protein folding, and transport. As expected, the TIF contained several classical serum proteins. Considering that the protein composition of the TIF reflects the physiological and pathological state of the tissue, it should provide a new and potentially rich resource for diagnostic biomarker discovery and for identifying more selective targets for therapeutic intervention.

Adult↗
PubMed2004

A proteomic approach for the discovery of protease substrates.

Standardized, comprehensive platforms for the discovery of protease substrates have been extremely difficult to create. Screens for protease specificity are now frequently based on the cleavage patterns of peptide substrates, which contain small recognition motifs that are required for the cleavage of the scissile bond within an active site. However, these studies do not identify in vivo substrates, nor can they lead to the definition of the macromolecular features that account for the biological specificity of proteases. To use properly folded proteins in a proteomic screen for protease substrates, we used 2D difference gel electrophoresis and tandem MS to identify substrates of an apoptosis-inducing protease, granzyme B. We confirmed the cleavage of procaspase-3, one of the key substrates of this enzyme, and identified several substrates that were previously unknown, as well as the cleavage site for one of these substrates. We were also able to observe the kinetics of substrate cleavage and cleavage product accumulation by using the 2D difference gel electrophoresis methodology. "Protease proteomics" may therefore represent an important tool for the discovery of the native substrates of a variety of proteases.

Amino Acid Sequence↗
PubMed2004

MHC-bound antigens and proteomics for novel target discovery.

The MHC molecules present normal as well as disease-related and pathogen-derived peptides to T cells as a way of alerting the immune system of the health status of a cell. Proteomic technologies involving immunoaffinity purification are now extensively used to separate MHC complexes from their peptide cargo, and then the peptides are sequenced by tandem mass spectrometry. The identified peptides are tested as vaccine candidates for viral diseases, immunostimulants for treating cancer, and immune-tolerance-inducing agents for autoimmune disorders. One of the challenges in devising novel HLA-peptide-based immunotherapies is to decipher whether a therapeutic window exists between the induction of tumor immunity and the onset of autoimmunity, which can have dangerous sequelae. This review will cover these topics with an overview of the vast possibilities emerging in the field of proteomic analyses of MHC-bound antigens as novel targets for immunotherapy.

Animals↗
PubMedDate not supplied

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

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

Biomarkers, Tumor↗
PubMed2003

High-throughput proteomics and protein biomarker discovery in an experimental model of inflammatory hyperalgesia: effects of nimesulide.

OBJECTIVE: The goal of this study was to derive a systematic approach for the identification of protein species profiles that selectively identify subgroups of similar but distinct pain models and correlate with the therapeutic efficacy (or lack thereof) of drug intervention. METHODS: Using high-throughput surface-enhanced laser desorption ionization (SELDI) mass spectrometry proteomic technology based on ProteinChip arrays, we conducted a comparative analysis of the profile of protein expression in cerebral spinal fluid (CSF) from rats exposed to either injection of complete Freund's adjuvant (CFA) [a model of inflammatory pain] or chronic constriction injury (CCI) [a model of neuropathic pain]. The CFA model was then further studied for the effects of treatment with the NSAID, nimesulide (a preferential cyclo-oxygenase [COX]-2 inhibitor). RESULTS: Among other observations, we found that the content of two metal (copper) binding protein species (2.9 and 3.2kDa) and three anionic protein species (4.0, 6.9 and 8.2kDa) were increased in the CSF of rats with inflammatory pain in a time-dependent fashion, at 7 and 14 days after CFA injection. These changes were highly selective for the CFA model, as no detectable increase in these protein biomarkers was found in the CCI neuropathic pain model. Further, we found that most of the changes in the biomarker protein species induced by the inflammatory pain were prevented by treatment with nimesulide and correlated with the antihyperalgesic effect of this drug. CONCLUSION: This study demonstrates that CSF biomarker profiles, as detected by SELDI technology, can consistently and reproducibly differentiate inflammatory from neuropathic pain, and reflect the analgesic action produced by the preferential COX-2 inhibitor, nimesulide. The characterisation and identification of these biomarkers will provide invaluable insight into the pathophysiology of pain mechanisms, in addition to further understanding of the value of nimesulide in the treatment of inflammatory pain.

Analysis of Variance↗
PubMed2005

Prerequisites for peptidomic analysis of blood samples: II. Analysis of human plasma after oral glucose challenge -- a proof of concept.

Mass spectrometric plasma analysis for biomarker discovery has become an exploratory focus in proteomic research: the challenges of analyzing plasma samples by mass spectrometry have become apparent not only since the human proteome organization (HUPO) has put much emphasis on the human plasma proteome. This work demonstrates fundamental proteomic research to reveal sensitivity and quantification capabilities of our Peptidomics technologies by detecting distinct changes in plasma peptide composition in samples after challenging healthy volunteers with orally administered glucose. Differential Peptide Display (DPD) is a technique for peptidomics studies to compare peptides from distinct biological samples. Mass spectrometry (MS) is used as a qualitative and quantitative analysis tool without previous trypsin digestion or labeling of the samples. Circulating peptides (< 15 kDa) were extracted from 1.3 mL plasma samples and the extracts separated by liquid chromatography into 96 fractions. Each fraction was subjected to MALDI MS, and mass spectra of all fractions were combined resulting in a 2D-display of > 2,000 peptides from each sample. Endogenous peptides that responded to oral glucose challenge were detected by DPD of pre-and post-challenge plasma samples from 16 healthy volunteers and subsequently identified by nESI-qTOF MS. Two of the 15 MS peaks that were significantly modulated by glucose challenge were subsequently identified as insulin and C-peptide. These results were validated by using immunoassays for insulin and C-peptide. This paper serves as a proof of principle for proteomic biomarker discovery down to the pM concentration range by using small amounts of human plasma.

Adult↗
PubMed2001

A proteomic approach for the discovery of early detection markers of hepatocellular carcinoma.

Individuals chronically infected with hepatitis B or C virus (HBV, HCV) are at high risk for the development of hepatocellular carcinoma (HCC), with disease progression occurring relentlessly over many years. The diagnosis of HCC usually occurs at late stages in the disease when there are few effective treatment options and the prognosis for patients with HCC is very poor. The long latency period, together with clearly identified at risk populations, provide opportunities for earlier detection that will allow more timely and effective treatment of this devastating cancer. We are using a proteomic approach to test the hypothesis that changes in the amount of certain serum polypeptides, or changes in their post-translational modifications, can be used to predict the onset of HCC. Advances in the standardization of two dimensional gel electrophoresis (2DE) coupled with computerized image analysis now permit the reproducible resolution of thousands of polypeptides per run. Serum polypeptides from individuals at different stages in the disease continuum are being resolved by 2DE to identify those that change with disease progression. Polypeptides found by this method can be further characterized by mass spectrometry. In addition, the potential for changes in the glycan structure of certain polypeptides to serve as a marker for disease progression can be explored. The proteomic approach is expected to liberate us from the need to "cherry pick" or guess the best biomarkers and let the data tell us which are the best indicators of disease. Information may also be gleaned about the pathobiology of the disease process.

Biomarkers↗
PubMed2005

Blood-brain barrier genomics, proteomics, and new transporter discovery.

The blood-brain barrier (BBB) is an impermeable cellular interface that physically separates the blood from the interstices of the brain. The endothelial cells lining the brain blood vessels form the principle barrier, and their unique phenotype is a consequence of dynamic interactions with several perivascular cell types present in the brain parenchyma. In addition, BBB dysfunction has been observed in the large majority of neurological diseases, but the causes of aberrant vascular behavior are generally unknown. Because of its barrier phenotype, drug delivery to the brain has also proven to be a very difficult task. Global genomics and proteomics analyses are currently being used to examine BBB function in healthy and diseased brain to better characterize this dynamic interface. It is becoming increasingly evident that these approaches have the potential to clarify the unique attributes of a healthy BBB, to identify therapeutic targets in diseased brain, and to identify novel conduits for noninvasive delivery of drugs against these targets. This review will discuss the application of genomics and proteomics to blood-brain barrier research and will offer views on the prospects of such approaches.

Animals↗
PubMed2002

Proteomics: New Developments in Target Discovery.

The Society for Medicines Research in collaboration with the Biological and Medicinal Chemistry sector of the Royal Society for Chemistry held a meeting on September 19, 2002, in London, United Kingdom to discuss proteomics in drug discovery. The meeting gave the most up-to-date overview of current progress in this new field, the challenges in silico, in vitro and in vivo, together with consideration of the increasing contribution of bioanalysis, bioinformatics and pharmacogenomics. Speakers from Celera Genomics, Oxford GlycoSciences and GlaxoSmithKline, among other companies and institutions, were present. (c) 2002 Prous Science. All rights reserved.

Journal Article↗
PubMed2005

Target identification and validation in drug discovery: the role of proteomics.

Proteomics, the study of cellular protein expression, is an evolving technology platform that has the potential to identify novel proteins involved in key biological processes in the cell that may serve as potential drug targets. While proteomics has considerable theoretical promise, individual cells/tissues have the potential to generate many millions of proteins while the current analytical technologies that involve the use of time-consuming two dimensional gel electrophoresis (2DIGE) and various mass spectrometry (MS) techniques are unable to handle complex biological samples without multiple high-resolution purification steps to reduce their complexity. This can significantly limit the speed of data generation and replication and requires the use of bioinformatic algorithms to reconstitute the parent proteome, a process that does not always result in a reproducible outcome. In addition, membrane bound proteins, e.g., receptors and ion channels, that are the targets of many existing drugs, are not amenable to study due, in part, to limitations in current proteomic techniques and also to these being present in low abundance and thus disproportionally represented in proteome profiles. Subproteomes with reduced complexity have been used to generate data related to specific, hypothesis-driven questions regarding target identification, protein-interaction networks and signaling pathways. However progress to date, with the exception of diagnostic proteomics in the field of cancer, has been exceedingly slow with an inability to put such studies in the context of a larger proteome, limiting the value of the information. Additionally the pathway for target validation (which can be more accurately described at the preclinical level as target confidence building) remains unclear. It is important that the ability to measure and interrogate proteomes matches expectations, avoiding a repetition of the disappointment and subsequent skepticism that accompanied what proved to be unrealistic expectations for the rapid contribution of data based on the genome maps, to biomedical research.

Computational Biology↗
PubMedDate not supplied

Biomarker discovery in urine by proteomics.

A hypothesis was formed that it would be possible to isolate an adequate amount of protein from a patient, having normal renal function, to identify biological markers of a particular disease state using a variety of proteomics techniques. To support this hypothesis, three samples of urine were collected from a volunteer: first when healthy, later when experiencing acute inflammation due to a pilonidal abcess, and again later still after successful recovery from the condition. The urine from these samples was processed by solid-phase extraction to concentrate and desalt the endogenous proteins and peptides. The proteins and peptides from these urine samples were analyzed in three different experiments: (1) traditional two-dimensional gel electrophoresis followed by proteolysis and mass spectrometric identification of various protein spots, (2) whole mixture proteolysis followed by one-dimensional packed capillary liquid chromatography and tandem mass spectrometry, (3) whole mixture proteolysis followed by two-dimensional capillary liquid chromatography and tandem mass spectrometry. In all three cases, a set of proteins was identified representing putative biomarkers. Each of these proteins was then found to have been previously linked in the scientific literature to inflammation. One acute phase reactant in particular, orosomucoid, was readily observed in all three experiments to dramatically increase in abundance, thereby supporting the hypothesis.

Animals↗
PubMed2004

In vitro biomarker discovery for atherosclerosis by proteomics.

The purpose of this study was to identify in vitro and then prioritize a tractable set of protein biomarker candidates of atherosclerosis that may eventually be developed to measure the extent, progression, regression, and stability of atherosclerotic lesions. A study was conducted using an in vitro"foam cell" model based on the stimulation of differentiated THP1 cells with oxidized low-density lipoprotein (oxidized LDL) as compared with low-density lipoprotein (LDL). Analysis of the proteins contained in the cell supernatant using proteome scanning technology identified 59 proteins as being increased, 57 with no statistically measurable difference, and 17 decreasing in abundance following treatment with oxidized LDL, as compared with LDL. From the up-regulated list, proteins were prioritized based on their analytical confidence as well as their relevance to atherosclerosis pathways. Within the group of increased abundance, seven families of proteins were of particular interest: fatty acid-binding proteins, chitinase-like enzymes, cyclophilins, cathepsins, proteoglycans, urokinase-type plasminogen activator receptor, and a macrophage scavenger receptor.

Amino Acid Sequence↗