PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “clinical 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 19 recordsLinked to original sources
PubMed2005

Homo sapiens proteomics: clinical perspectives.

The complete human genome sequencing project opened the route to a new holistic scientific movement, characterised by the investigation of the functional elements of our genetic heredity mainly in respect to multifactorial diseases such as cancer, diabetes, dementias, etc. The clinical proteomics tries to highlight the relationships between the main molecular physiological effectors, proteins, with defined physiopathological conditions. The development of a new generation of mass spectrometers is deeply changing the technologies employed in these investigations, enabling direct quantitative analysis of clinical samples such as, blood, urine, saliva and biopsy samples. In this manuscript we introduce and discuss the main phases of these investigations and their possible follow up in diagnostic and functional studies.

Chromatography, High Pressure Liquid↗
PubMed2004

National Heart, Lung, And Blood Institute Clinical Proteomics Working Group report.

The National Heart, Lung, and Blood Institute (NHLBI) Clinical Proteomics Working Group was charged with identifying opportunities and challenges in clinical proteomics and using these as a basis for recommendations aimed at directly improving patient care. The group included representatives of clinical and translational research, proteomic technologies, laboratory medicine, bioinformatics, and 2 of the NHLBI Proteomics Centers, which form part of a program focused on innovative technology development. This report represents the results from a one-and-a-half-day meeting on May 8 and 9, 2003. For the purposes of this report, clinical proteomics is defined as the systematic, comprehensive, large-scale identification of protein patterns ("fingerprints") of disease and the application of this knowledge to improve patient care and public health through better assessment of disease susceptibility, prevention of disease, selection of therapy for the individual, and monitoring of treatment response.

Biological Specimen Banks↗
PubMed2002

Clinical proteomics for cancer biomarker discovery and therapeutic targeting.

As we emerge into the post-genome era, proteomics finds itself as the driving force field as we translate the nucleic acid information archive into understanding how the cell actually works and how disease processes operate. Even so, the traditionally held view of proteomics as simply cataloging and developing lists of the cellular protein repertoire of a cell are now changing, especially in the sub-discipline of clinical proteomics. The most relevant information archive to clinical applications and drug development involves the elucidation of the information flow of the cell; the "software" of protein pathway networks and circuitry. The deranged circuitry of the cell as the drug target itself as well as the effect of the drug on not just the target, but also the entire network, is what we now are striving towards. Clinical proteomics, as a new and most exciting sub-discipline of proteomics, involves the bench-to-bedside clinical application of proteomic tools. Unlike the genome, there are potentially thousands of proteomes: each cell type has its own unique proteome. Moreover, each cell type can alter its proteome depending on the unique tissue microenvironment in which it resides, giving rise to multiple permutations of a single proteome. Since there is no polymerase chain reaction equivalent to proteomics- identifying and discovering the "wiring diagram" of a human diseased cell in a biopsy specimen remains a daunting challenge. New micro-proteomic technologies are being and still need to be developed to drill down into the proteomes of clinically relevant material. Cancer, as a model disease, provides a fertile environment to study the application of proteomics at the bedside. The promise of clinical proteomics and the new technologies that are developed is that we will detect cancer earlier through discovery of biomarkers, we will discover the next generation of targets and imaging biomarkers, and we can then apply this knowledge to patient-tailored therapy.

Algorithms↗
PubMed2003

The application of clinical proteomics to cancer and other diseases.

The term "clinical proteomics" refers to the application of available proteomics technologies to current areas of clinical investigation. The ability to simultaneously and comprehensively examine changes in large numbers of proteins in the context of disease or other changes in physiological conditions holds great promise as a tool to unlock the solutions to difficult clinical research questions. Proteomics is a rapidly growing field that combines high throughput analytical methodologies such as two-dimensional gel electrophoresis and SELDI mass spectrometry methods with complex bioinformatics to study systems biology--the system of interest is defined by the investigator. Even with all its potential, however, studies must be carefully designed in order to differentiate true clinical differences in protein expression from differences originating from variation in sample collection, variation in experimental condition, and normal biological variability. Proteomic analyses are already widely in use for clinical studies ranging from cancer to other diseases such as cardiovascular disease, organ transplant, and pharmacodynamic studies.

Biomarkers↗
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↗
PubMedDate not supplied

Clinical proteomics: revolutionizing disease detection and patient tailoring therapy.

The evolving discipline of Clinical Proteomics is more than simply describing and enumerating the systematic changes in the protein constituency of a cell, or just generating lists of proteins that increase or decrease in expression as a cause or consequence of disease. Clinical applications of proteomics involve the use of proteomic technologies at the bedside with the ultimate goal to characterize the information flow through the intra- and extracellular molecular protein networks that interconnect organ and circulatory systems together. These networks are both new targets for therapeutics themselves as well as underpin the dynamic changes that give rise to cascades of new diagnostic biomarkers. The analysis of human cancer can be used as a model for how clinical proteomics is having an impact at the bedside for early detection, rational therapeutic targeting, and patient-tailored therapy.

Animals↗
PubMed2026

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗
PubMed2006

Direct-tissue SELDI-TOF mass spectrometry analysis: a new application for clinical proteomics.

BACKGROUND: New molecular profiling technologies can aid in analysis of small pathologic samples obtained by minimally invasive biopsy and may enable the discovery of key biomarkers synergistic with anatomopathologic analysis related to prognosis, therapeutic response, and innovative target validation. Thus proteomic analysis at the histologic level in healthy and pathologic settings is a major issue in the field of clinical proteomics. METHODS: We used surface-enhanced laser desorption ionization-time-of-flight mass spectrometry (SELDI-TOF MS) technology with surface chromatographic subproteome enrichment and preservation of the spatial distribution of proteomic patterns to detect discrete modifications of protein expression. We performed in situ proteomic profiling of mouse tissue and samples of human cancer tissue, including brain and lung cancer. RESULTS: This approach permitted the discrimination of glioblastomas from oligodendrogliomas and led to the identification of 3 potential markers. CONCLUSION: Direct tissue proteomic analysis is an original application of SELDI-TOF MS technology that can expand the use of clinical proteomics as a complement to the anatomopathological diagnosis.

Animals↗
PubMed2006

Effects of preanalytical variables on peptide and protein measurements in human serum and plasma: implications for clinical proteomics.

There is a wealth of knowledge in the field of in vitro diagnostics with regard to preanalytical variables and their impact on the determination of peptide and protein analytes in human serum and plasma. This information is applicable to clinical proteomics investigations, which utilize the same sample types. Studies have demonstrated that the majority of variations and errors in in vitro diagnostics seem to occur in the preanalytical phase prior to specimen analysis. Preanalytical processes include study design, compliance of the subjects investigated, compliance of the technical staff in adherence to protocols, choice of specimens utilized and sample collection and processing. These variables can have a dramatic impact on the determination of analytes and can affect result outcomes, reproducibility and the validity of investigations. By drawing analogies to in vitro diagnostics practices, specific variables that are likely to impact the results of proteomics studies can be identified. Recognition of such variables is the first step towards their understanding and, eventually, controlling their impact. In this article, we will review preanalytical variables, provide examples for their effects on the determination of distinct peptides and proteins and discuss potential implications for clinical proteomics investigations.

Anticoagulants↗
PubMed2004

HUPO initiatives relevant to clinical proteomics.

The past few years have seen a tremendous interest in the potential of proteomics to address unmet needs in biomedicine. Such unmet needs include more effective strategies for early disease detection and monitoring and more effective therapies, in addition to developing a better understanding of disease pathogenesis. Proteomics is particularly suited for investigating biological fluids to identify disease-related alterations and to develop molecular signatures for disease processes. However, much of the effort undertaken in clinical proteomics to date represents either demonstrations of principles or relatively small-scale studies when compared with genomics effort and accomplishments or more pertinently when contrasted with the tremendous untapped potential of clinical proteomics. Clearly, we are in the early stages. What seems to be urgently needed is an organized effort to build a solid foundation for proteomics that includes developing a much needed infrastructure with adequate resources. The Human Proteome Organization (HUPO) is fostering an organized international effort in proteomics that includes initiatives around organ systems and biological fluids that have disease relevance as well as development of proteomics resources.

Humans↗
PubMed2006

Current status and prospects of clinical proteomics studies on detection of colorectal cancer: hopes and fears.

Colorectal adenocarcinoma (CRC) is the third most common type of cancer and the fourth most frequent cause of death due to cancer worldwide. Given the natural history of CRC, early diagnosis appears to be the most appropriate tool to reduce disease-related mortality. A field of recent interest is clinical proteomics, which was reported to lead to high sensitivity and specificities for early detection of several solid tumors. This emerging field uses mass spectrometry-based protein profiles/patterns of easy accessible body fluids to distinguish cancer from non-cancer patients. These discrepancies may be a result of: (1) proteins being abnormally produced or shed and added to the serum proteome, (2) proteins clipped or modified as a consequence of the disease process, or (3) proteins subtracted from the proteome owing to disease-related proteolytic degradation pathways. Therefore, protein pattern diagnostics would provide easy and reliable tools for detection of cancer. This paper focuses on the current status of clinical proteomics research in oncology and in colorectal cancer especially, and will reflect on pitfalls and fears in this relatively new area of clinical medicine, which are reproducibility issues and pre-analytical factors, statistical issues, and identification and nature of discriminating proteins/peptides.

Adenocarcinoma↗
PubMedDate not supplied

[Clinical proteomics: towards early detection of cancers].

A key challenge in clinical proteomic of cancer is the identification of biomarkers that would allow early detection, diagnosis and monitor progression of the disease to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and surfaced-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry is one of the most interesting new approaches for cancer diagnostic using proteomic profiling. This review aims to summarize the results of studies that have used this new technology method for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems and still requires some efforts to be standardised and validated.

Biomarkers, Tumor↗
PubMed2002

ProteinChip clinical proteomics: computational challenges and solutions.

ProteinChip technology, a suite of analytical tools that includes retentate chromatography, on-chip protein characterization, and multivariate analysis, allows researchers to examine patterns ofprotein expression and modification. Based on the surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) approach, ProteinChip technology has been pioneered by researchers at Ciphergen Biosystems (Fremont, CA, USA), as well as by users of Ciphergen's commercial embodiment of this technology the ProteinChip Biomarker System. This report will begin with a background of the technology and describe its applications in clinical proteomics and will then conclude with a discussion of tools and strategies to mine the large amounts of data generated during the course of a typical clinical proteomics study.

Biomarkers↗
PubMed2003

Mass spectrometry-based clinical proteomics.

In recent years, mass spectrometry (MS) has been recognized as a 'Gold Standard' tool for the identification and analysis of individual proteins in expression proteomics studies. Moreover, MS has proven useful for the analysis of nucleic acids for single nucleotide polymorphism (SNP) genotyping purposes. With the increased usage of MS as a standard tool for life science applications and the advancement of MS instrumentation, sample preparation and bioinformatics, MS technology has entered novel screening and discovery application areas that are beyond the traditional protein identification and characterization applications. The areas of clinical diagnostics and predictive medicine are just two prime examples of these fields. Predictive markers or biomarkers for early diagnosis of diseases are of growing importance for the human healthcare community. The goal of using MS in clinical proteomics is to generate protein profiles (mass to charge [m/z] ratio versus signal intensity) from readily available body fluids like serum, saliva and urine to detect changes in protein levels that reflect changes in the disease states. Whereas the results originating from individual protein markers may be intriguing, data resulting from the analysis of complex, multiple biomarker patterns may be unequivocal. These biomarker patterns are hidden in complex mass spectra and are not always obvious to the human eye. Sophisticated bioinformatics algorithms have to be applied to determine these unique biomarker patterns. Here, we review the latest developments concerning the use of MS for the discovery of biomarker patterns and for the identification of individual biomarkers in the field of clinical proteomics applications.

Biomarkers↗
PubMed2006

Clinical proteomics and mass spectrometry profiling for cancer detection.

A key challenge in the clinical proteomics of cancer is the identification of biomarkers that would enable early detection, diagnosis and monitoring of disease progression to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer a unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and mass spectrometry is one of the most interesting new approaches for cancer diagnostics using proteomic profiling. This review presents two technologies in this field, surface-enhanced laser desorption/ionization time-of-flight and Clinprot, and aims to summarize the results of studies obtained with the first of them for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems, and still requires some efforts to be standardized and validated.

Biomarkers, Tumor↗
PubMed2002

Clinical proteomics: translating benchside promise into bedside reality.

The ultimate goal of proteomics is to characterize the information flow through protein networks. This information can be a cause, or a consequence, of disease processes. Clinical proteomics is an exciting new subdiscipline of proteomics that involves the application of proteomic technologies at the bedside, and cancer, in particular, is a model disease for studying such applications. Here, we describe proteomic technologies that are being developed to detect cancer earlier, to discover the next generation of targets and imaging biomarkers, and finally to tailor the therapy to the patient.

Female↗
PubMed2005

Modeling of protein signaling networks in clinical proteomics.

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomic endpoints in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states. One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor microenvironment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination, clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.

Humans↗