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 37 records · Page 2Linked to original sources
PubMed2006

[Clinical proteomics in laboratory medicine].

During the past few years, the emphasis on genomics has shifted via transcriptomics to proteomics, the science of understanding how the whole set of proteins are expressed and function at the cellular level. Recent progress in clinical proteomics is mostly thanks to sophisticated new methodologies for proteome analyses. In search for novel biomarkers for cancers and other disorders, we have taken advantage of the surface-enhanced laser/desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS) and the MALDI-TOF/TOF. Since personal and verbal reporting of alcohol use is not necessarily accurate, objective markers to assess alcohol consumption are required. We used the ProteinChip SELDI technology to generate comparative protein profiles of the consecutive serum samples obtained during abstinence and found that a 5.9kD peptide detected and identified by this technology could be a novel marker of heavy alcohol consumption. Recent advances in two-dimensional electrophoresis (2-DE) such as fluorescent 2-D differential gel electrophoresis (2-D DIGE) has made it possible to detect and quantitate the critical changes involved in disease pathogenesis. We could identify novel proteins with altered expression in primary esophageal cancer using the powerful method of agarose 2-DE and agarose 2-D DIGE. A number of proteins with altered expression between cancer and adjacent non-cancer tissues were identified. Among them, a 195-kDa protein, periplakin, was significantly downregulated in esophageal cancer, which was confirmed by immunoblotting and immunohistochemistry. Clinical proteomics consists of the discovery proteomics and the measurement proteomics. Although we still stand at the discovery proteomics, undoubtedly, the clinical proteomics will be a major contributor in laboratory medicine in the near future.

Clinical Laboratory Techniques↗
PubMed2005

Alzheimer's disease cerebrospinal fluid biomarker discovery: a proteomics approach.

There is significant interest in the identification of effective biomarkers for Alzheimer's disease. Such biomarkers could aid in the clinical diagnosis of the disease and may be useful in assessing the efficacy of various treatment strategies. The search for biomarkers often includes the analysis of changes in cerebrospinal fluid protein expression that correlate with disease. These changes can be measured using a variety of technologies for protein expression profiling. Although there is great promise in the application of these methods to biomarker discovery based on some preliminary observations, there are significant issues in the capabilities of most of these technologies that have limited their effective application. The most recent literature involving proteomic discovery of new cerebrospinal fluid biomarkers for Alzheimer's disease is reviewed.

Alzheimer Disease↗
PubMedDate not supplied

Capillary electrophoresis-mass spectrometry as a powerful tool in clinical diagnosis and biomarker discovery.

Proteome analysis is now emerging as key technology for deciphering biological processes and the discovery of biomarkers for diseases from tissues and body fluids. The complexity and wide dynamic range of protein expression poses a formidable challenge to both peptide separation technologies and mass spectrometry (MS). Here we review the efforts that have been undertaken to date, focussing on capillary electrophoresis coupled to mass spectrometry (CE-MS). We discuss CE-MS from an application point of view evaluating its merits and vices in regard to biomarker discovery and clinical applications. As examples, we present the use of CE-MS for the determination of protein patterns in urine, serum, and other body fluids. Finally, the benefits and limitations of CE-MS for the analysis of proteins in clinical samples are discussed against the background of alternative technologies.

Animals↗
PubMed2005

Practical proteomic biomarker discovery: taking a step back to leap forward.

There is a pressing need for radically improved proteomic screening methods that allow for earlier diagnosis of disease, for systematic monitoring of physiological responses and for uncovering the fundamental mechanisms of drug action. Recent developments in proteomic technology offer tremendous, yet untapped, potential to yield novel biomarkers that are translatable to routine clinical use. Despite the significant conceptual promise of comparative proteomic profiling as a research platform for biomarker discovery, however, major hurdles remain for practical and clinical implementation. In particular, there is growing recognition that rigorous experimental design principles are urgently required to validate conclusively the unproven methodologies currently being touted. Debate and confusion persist about where the burden of proof lies: statistically, biologically or clinically? Moreover, there is no consensus about what constitutes a meaningful benchmark. An important question is how to achieve a scientifically rigorous, and therefore convincing, proof-of-concept that can be accepted by the field. Key analytical challenges related to these issues that must be addressed by the burgeoning biomarker community are discussed here.

Animals↗
PubMed2004

Structure-based functional discovery of proteins: structural proteomics.

The discovery of biochemical and cellular functions of unannotated gene products begins with a database search of proteins with structure/sequence homologues based on known genes. Very recently, a number of frontier groups in structural biology proposed a new paradigm to predict biological functions of an unknown protein on the basis of its three-dimensional structure on a genomic scale. Structural proteomics (genomics), a research area for structure-based functional discovery, aims to complete the protein-folding universe of all gene products in a cell. It would lead us to a complete understanding of a living organism from protein structure. Two major complementary experimental techniques, X-ray crystallography and NMR spectroscopy, combined with recently developed high throughput methods have played a central role in structural proteomics research; however, an integration of these methodologies together with comparative modeling and electron microscopy would speed up the goal for completing a full dictionary of protein folding space in the near future.

Animals↗
PubMed2005

Serum, salivary and tissue proteomics for discovery of biomarkers for head and neck cancers.

Initial clinically oriented applications of emerging proteomic technologies that aim to identify biomarkers for head and neck squamous cell carcinoma diagnostics have yielded promising results. The development of new proteomic diagnostics remains critical for the early detection of head and neck squamous cell carcinoma at more treatable stages. Prognostic markers for disease recurrence and treatment sensitivities are also required. In this overview of current biomarker identification strategies for head and neck squamous cell carcinoma, different combinations of mass spectrometry platforms, laser capture microscopy and 2D gel electrophoresis procedures are summarized as applied to readily available clinical specimens (tissue, blood and saliva). Issues related to assay reproducibility, management of large data sets and future improvements in clinical proteomics are also addressed.

Algorithms↗
PubMed2003

Application of proteomics for discovery of protein biomarkers.

Biomarkers of drug efficacy and toxicity are becoming a key need in the drug development process. Mass spectral-based proteomic technologies are ideally suited for the discovery of protein biomarkers in the absence of any prior knowledge of quantitative changes in protein levels. The success of any biomarker discovery effort will depend upon the quality of samples analysed, the ability to generate quantitative information on relative protein levels and the ability to readily interpret the data generated. This review will focus on the strengths and weaknesses of technologies currently utilised to address these issues.

Animals↗
PubMed2004

Research issues and strategies for genomic and proteomic biomarker discovery and validation: a statistical perspective.

The development and validation of clinically useful biomarkers from high-dimensional genomic and proteomic information pose great research challenges. Present bottlenecks include: that few of the biomarkers showing promise in initial discovery were found to warrant subsequent validation; and biomarker validation is expensive and time consuming. Biomarker evaluation should proceed in an orderly fashion to enhance rigor and efficiency. A molecular profiling approach, although promising, has a high chance of yielding biased results and overfitted models. Specimens from cohorts or intervention trials are essential to eliminate biases. The high cost for biomarker validation motivates some novel study design features, including sequential filtering and DNA pooling. For data analysis, logistic regression (in particular, boosting logistic regression) has features of robustness against model misspecification, and has resistance to model overfitting. Model assessment and cross-validation are critical components of data analysis. Having an independent test set is a vital feature of study design.

Biomarkers, Tumor↗
PubMedDate not supplied

Biomedical applications of protein chips.

The development of microchips involving proteins has accelerated within the past few years. Although DNA chip technologies formed the precedent, many different strategies and technologies have been used because proteins are inherently a more complex type of molecule. This review covers the various biomedical applications of protein chips in diagnostics, drug screening and testing, disease monitoring, drug discovery (proteomics), and medical research. The proteomics and drug discovery section is further subdivided to cover drug discovery tools (on-chip separations, expression profiling, and antibody arrays), molecular interactions and signaling pathways, the identification of protein function, and the identification of novel therapeutic compounds. Although largely focused on protein chips, this review includes chips involving cells and tissues as a logical extension of the type of data that can be generated from these microchips.

Animals↗
PubMed2006

Biomarker discovery by proteomics: challenges not only for the analytical chemist.

This forum article outlines some of the major challenges in present day biomarker discovery research. Notably the dilemma of reaching sufficient concentration sensitivity versus the required analysis time per sample is highlighted using a model calculation. A number of possible developments and recent research findings are considered to show possible ways out of this dilemma. Finally, the challenge of processing large, megavariate datasets prior to statistical analysis is presented.

Animals↗
PubMedDate not supplied

Place of pattern in proteomic biomarker discovery.

The role of pattern in biomarker discovery and clinical diagnosis is examined in its historical context. The use of MS-derived pattern is treated as a logical extension of prior applications of non-MS-derived pattern. Criticisms pertaining to specific technology platforms and analytic methodologies are considered separately from the larger issues of pattern utility and deployment in biomarker discovery. We present a hybrid strategy that marries the desirable attributes of high-information content MS pattern with the capability to obtain identity, and explore the key steps in establishing a data analysis pipeline for pattern-based biomarker discovery.

Biomarkers↗
PubMed2003

Evaluation of ethanol-fixed, paraffin-embedded tissues for proteomic applications.

We previously reported that ethanol fixation and paraffin embedding of tissues produce excellent histomorphology and good preservation of macromolecules. Here, we present a detailed evaluation of ethanol-fixed tissues for proteomic initiatives. When proteins were extracted from ethanol-fixed, paraffin-embedded prostate tissue, resolved by two-dimensional gel electrophoresis (2-DE), and stained by standard methods, several hundred protein molecules could be detected and successfully analyzed by mass spectrometry. Protein profiles obtained from ethanol-fixed tissues were highly similar to those observed from frozen tissues, in contrast to the poor protein recovery from formalin-fixed material. The protein content of specific cells that were microdissected from ethanol-fixed tissue sections using laser capture microdissection could also be successfully analyzed by 2-DE. We observed that eosin staining of tissue sections had a detrimental effect on protein separation, whereas hematoxylin staining had minimal consequence. In order to illustrate the applicability of ethanol-fixed tissues for proteomic discovery studies, we compared the protein profiles of patient-matched, normal prostatic epithelial cells and invasive adenocarcinoma cells obtained from ethanol-fixed, paraffin-embedded tissues. A number of differentially expressed proteins was discovered and identified by mass spectrometry. Immunohistochemical analyses performed on ethanol-fixed tissue sections were in agreement with the proteomic discovery findings. In light of these results, we conclude that ethanol-fixed tissues can be successfully utilized for proteomic analyses.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2006

Comprehensive phenotyping in multiple sclerosis: discovery based proteomics and the current understanding of putative biomarkers.

Currently, there is no single test for multiple sclerosis (MS). Diagnosis is confirmed through clinical evaluation, abnormalities revealed by magnetic resonance imaging (MRI), and analysis of cerebrospinal fluid (CSF) chemistry. The early and accurate diagnosis of the disease, monitoring of progression, and gauging of therapeutic intervention are important but elusive elements of patient care. Moreover, a deeper understanding of the disease pathology is needed, including discovery of accurate biomarkers for MS. Herein we review putative biomarkers of MS relating to neurodegeneration and contributions to neuropathology, with particular focus on autoimmunity. In addition, novel assessments of biomarkers not driven by hypotheses are discussed, featuring our application of advanced proteomics and metabolomics for comprehensive phenotyping of CSF and blood. This strategy allows comparison of component expression levels in CSF and serum between MS and control groups. Examination of these preliminary data suggests that several CSF proteins in MS are differentially expressed, and thus, represent putative biomarkers deserving of further evaluation.

Autoantibodies↗
PubMed2005

Proteomic biomarker discovery in cerebrospinal fluid for neurodegenerative diseases.

The clinical diagnosis of major neurodegenerative disorders, e.g. Alzheimer's disease, Parkinson's disease, and dementia with Lewy body, remains unsatisfactory based on current clinical criteria and limited laboratory investigations. The possibility of identifying multiple novel biomarkers for neurodegenerative diseases, those related to disease pathogeneses in particular, has been greatly enhanced with recent advances in genomics, proteomics, and metabolomics. In this chapter, we will be reviewing a few issues related to proteomic identification of proteins in human cerebrospinal fluid (CSF) as well as unique protein markers that could be used for clinical diagnosis of various neurodegenerative diseases or monitoring their progression. Great attention has been directed to practical considerations and limitations of several major aspects of proteomic analysis of human CSF.

Apolipoproteins B↗
PubMed2026

Proteomics-driven discovery of intervention windows and risk subtypes in osteoporosis: A prospective cohort study.

Given the limited feasibility of population-wide bone mineral density screening and the infrequency of long-term monitoring in healthy individuals, identifying the window for early intervention and the populations to be prioritized for screening is critical. This study aimed to identify intervention windows for osteoporosis and to determine potential high-risk subtypes within the healthy population. Based on proteomic data from 41,408 healthy adults, we conducted the DE-SWAN method to identify change peaks in plasma protein during the pre-diagnostic osteoporosis phase, and employed finite Gaussian mixture model-based clustering to delineate high-risk subtypes of osteoporosis. We identified 122 protein biomarkers significantly associated with osteoporosis risk throughout the follow-up period. Importantly, we identified two critical peaks occurring approximately 10 and 6 years before diagnosis, with the former enriched in immune-related pathways and the latter prominently involving responses to retinoic acid and glucocorticoids. Furthermore, one high-risk subtype for osteoporosis was identified in both males and females, termed the Frailty and Obesity Subtype. This subtype is characterized by a high degree of frailty and obesity, accompanied by a significantly elevated risk of both osteoporosis and fractures. Finally, we developed a predictive model comprising 10 proteins for identifying high-risk subtypes of osteoporosis, which demonstrated better performance than the traditional risk factor model (AUC: 0.743 vs. 0.680). Our findings demonstrate that proteomic profiling can reveal early molecular changes and identify high-risk subtypes years before clinical onset, providing a foundation for screening and precision prevention of osteoporosis.

Proteomics↗