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PubMed2004

Endocrine therapy for early breast cancer.

Breast cancer is a significant cause of morbidity and mortality. Adjuvant tamoxifen therapy for estrogen receptor-positive early breast cancer has had a major impact on mortality in clinical trials, and the observation that breast cancer mortality started to decline shortly after widespread tamoxifen prescription was introduced in several countries inevitably leads us to conclude that this intervention is responsible. Aromatase inhibitor therapy will undoubtedly become part of everyday practice in the future, although the optimization of aromatase inhibitor therapy as part of the overall endocrine package needs further definition. However, to suppose that a unified optimal sequence and duration is applicable to all patients is probably a fallacy, and underlying the overall effects of different treatments are individual patients with individual but potentially classifiable tumors requiring different management strategies. Characterization and individualization of therapies based on gene and proteomic expression profiling is a massive research undertaking, but could guide us towards a fairly simple set of key gene or protein expression profiles to guide adjuvant hormonal, chemotherapeutic or new biologic agent strategies that will define optimal treatment packages for women with early breast cancer. Within the next 5 years, the clinical reservations regarding adjuvant aromatase inhibitors and financial obstacles to access the aromatase inhibitors are likely to be overcome and, unless we are able to identify a cohort of women who will gain no additional benefit or who have a better outcome with tamoxifen, most postmenopausal women will be treated with aromatase inhibitor monotherapy or a sequential combination utilizing an aromatase inhibitor.

Antineoplastic Agents, Hormonal↗
PubMed2002

Genomics in anti-infective drug discovery--getting to endgame.

Whole chromosome sequence of prokaryotes has provided the availability of multiple bacterial pathogen sequence data and it has become a widely used tool in the drug discovery process. However the sequence data in itself is merely a starting point for drug discovery of novel antibacterial targets and, eventually, drugs. In order to leverage this large amount of data it is necessary to match an understanding of the microbial physiology of pathogenic bacteria to disease processes and identifying the gene products for which intervention may reduce or eliminate the infectious state. However, to date, the application of genomics to anti-infective drug discovery has not, since 1995 with the first complete sequence of a pathogenic bacterium, led to identification of a novel antibacterial agent. Here we review the field of bacterial genomics and how it is enabling the drug discovery process. Many new molecular-based technologies (proteomics, transcriptional profiling, studies of gene expression in vivo) have originated or have expanded into wider use, and have been made possible by the availability of complete bacterial genome sequence information and subsequent bioinformatic analytic tools. Taken together, these technologies, overlaid within an established drug discovery program, now affords the opportunity for the identification, validation, and process design for high-throughput target mining at unprecedented volumes and timeframes.

Anti-Bacterial Agents↗
PubMed2005

Hepatocellular carcinoma: therapy and prevention.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. The major etiologies and risk factors for the development of HCC are well defined and some of the multiple steps involved in hepatocarcinogenesis have been elucidated in recent years. Despite these scientific advances and the implementation of measures for the early detection of HCC in patients at risk, patient survival has not improved during the last three decades. This is due to the advanced stage of the disease at the time of clinical presentation and limited therapeutic options. The therapeutic options fall into five main categories: surgical interventions including tumor resection and liver transplantation, percutaneous interventions including ethanol injection and radiofrequency thermal ablation, transarterial interventions including embolization and chemoembolization, radiation therapy and drugs as well as gene and immune therapies. These therapeutic strategies have been evaluated in part in randomized controlled clinical trials that are the basis for therapeutic recommendations. Though surgery, percutaneous and transarterial interventions are effective in patients with limited disease (1-3 lesions, <5 cm in diameter) and compensated underlying liver disease (cirrhosis Child A), at the time of diagnosis more than 80% patients present with multicentric HCC and advanced liver disease or comorbidities that restrict the therapeutic measures to best supportive care. In order to reduce the morbidity and mortality of HCC, early diagnosis and the development of novel systemic therapies for advanced disease, including drugs, gene and immune therapies as well as primary HCC prevention are of paramount importance. Furthermore, secondary HCC prevention after successful therapeutic interventions needs to be improved in order to make an impact on the survival of patients with HCC. New technologies, including gene expression profiling and proteomic analyses, should allow to further elucidate the molecular events underlying HCC development and to identify novel diagnostic markers as well as therapeutic and preventive targets.

Carcinoma, Hepatocellular↗
PubMed2005

Prognosis of follicular lymphomas.

Although numerous treatment approaches are proposed for patients with follicular lymphoma, criteria to help in choosing a treatment for a given patient and for comparing trial results are lacking. Several retrospective studies have analyzed prognostic factors, but their conclusions rely on limited numbers of patients treated during long periods, and their results are discordant. The Follicular Lymphoma International Prognostic Index was designed from the data recorded over 8 years of nearly 5000 patients registered worldwide. Five factors are used (age, Ann Arbor stage, number of nodal sites, serum lactate dehydrogenase level, and hemoglobin level) to build a 3-category index. This index, together with new biologic markers such as gene profiling and proteomics, could help provide an optimal treatment option for patients with follicular lymphoma.

Humans↗
PubMed2003

Apoptosis in the myelodysplastic syndromes.

Myelodysplastic syndromes (MDS) are neoplastic dyscrasias characterized by peripheral cytopenia, despite a normocellular or hypercellular bone marrow. In the past decade, it has become apparent that this ineffective hemopoiesis is largely caused by excessive apoptosis of myeloid precursors. There is no evidence for gain-of-function mutations within the apoptotic machinery in MDS. It appears that the apoptosis is a reactive phenomenon fueled by cytokines. The provoking stimulus for the proapoptotic intramedullary milieu in MDS is unknown. The evolution of MDS from early relatively chronic to aggressive and frankly leukemic phenotype is accompanied by a suppression of apoptosis. This metamorphosis correlates with changes in intracellular levels of Bcl-2-family proteins, but the genetic basis for this shift has not been elucidated clearly. Expression profiling and proteomic technologies may offer the best means to unravel this process.

Apoptosis↗
PubMed2006

Swine and circovirus.

In the 1990s Post-weaning, multi-systemic wasting syndrome (PMWS) emerged in N. America and Europe as a major disease problem with significant welfare and economic consequences for pig producers. The disease, characterised by wasting, respiratory, enteric and lymphoid system problems in pigs of 4-16 weeks of age, has since spread so that today it has a global distribution. PCV-2 is consistently associated with PMWS, is more abundant in association with PMWS and is considered by many to be the causative agent of the syndrome. However, several lines of evidence indicate that PCV-2 is necessary but not sufficient to cause the full range of clinical signs associated with PMWS, suggesting the involvement of an as yet unidentified factor or factors. The process of identifying unknown agents and their respective roles in the pathogenesis of complex syndromes now has an ever broadening spectrum of analytical techniques available. Immune phenotyping, cytokine responses, micro-array profiling, and proteomics are just some of the techniques available. This paper describes the philosophy and the application of these and classical techniques in an integrated, holistic manner to the problem of PMWS and circoviruses, by examination of samples collected from a prospective, clinical case-control study, and discusses some of the preliminary findings in relation to the efforts to understand the aetiopathogenesis of PMWS.

Animals↗
PubMed2002

Autoantibody profiling for the study and treatment of autoimmune disease.

Proteomics technologies enable profiling of autoantibody responses using biological fluids derived from patients with autoimmune disease. They provide a powerful tool to characterize autoreactive B-cell responses in diseases including rheumatoid arthritis, multiple sclerosis, autoimmune diabetes, and systemic lupus erythematosus. Autoantibody profiling may serve purposes including classification of individual patients and subsets of patients based on their 'autoantibody fingerprint', examination of epitope spreading and antibody isotype usage, discovery and characterization of candidate autoantigens, and tailoring antigen-specific therapy. In the coming decades, proteomics technologies will broaden our understanding of the underlying mechanisms of and will further our ability to diagnose, prognosticate and treat autoimmune disease.

Antibody Formation↗
PubMed2003

Exploitation of molecular profiling techniques for GM food safety assessment.

Several strategies have been developed to identify unintended alterations in the composition of genetically modified (GM) food crops that may occur as a result of the genetic modification process. These include comparative chemical analysis of single compounds in GM food crops and their conventional non-GM counterparts, and profiling methods such as DNA/RNA microarray technologies, proteomics and metabolite profiling. The potential of profiling methods is obvious, but further exploration of specificity, sensitivity and validation is needed. Moreover, the successful application of profiling techniques to the safety evaluation of GM foods will require linked databases to be built that contain information on variations in profiles associated with differences in developmental stages and environmental conditions.

Consumer Product Safety↗
PubMed2001

Solution and chip arrays in protein profiling.

The industrialization of proteomics demands reproducible, robust and high-throughput profiling technologies that current two-dimensional gel electrophoresis cannot achieve. New technologies in protein arrays, either on chips or with self-encoded elements in solution, hold much promise for interrogating the diverse and immense proteome.

Biosensing Techniques↗
PubMed2005

Bioinformatics approaches in clinical proteomics.

Protein expression profiling is increasingly being used to discover, validate and characterize biomarkers that can potentially be used for diagnostic purposes and to aid in pharmaceutical development. Correct analysis of data obtained from these experiments requires an understanding of the underlying analytic procedures used to obtain the data, statistical principles underlying high-dimensional data and clinical statistical tools used to determine the utility of the interpreted data. This review summarizes each of these steps, with the goal of providing the nonstatistician proteomics researcher with a working understanding of the various approaches that may be used by statisticians. Emphasis is placed on the process of mining high-dimensional data to identify a specific set of biomarkers that may be used in a diagnostic or other assay setting.

Computational Biology↗
PubMed2006

Putting proteomics on target: activity-based profiling of ubiquitin and ubiquitin-like processing enzymes.

Modification of proteins with ubiquitin (Ub) and Ub-like modifiers (Ubls) plays a fundamental role in cell biology. As a consequence, proteomics-based efforts were developed to characterize proteins that are modified by Ub or Ubls. A more focused functional proteomics strategy relies on active-site probes based on the Ub/Ubl scaffold, which specifically targets Ub/Ubl-processing enzymes. Activity-based profiling with such tools led to the identification of novel gene products with Ub/Ubl-processing activity and uncovered novel control mechanisms regulating their activity. This review discusses recent advances in chemistry-based functional proteomics applications, and how this information can provide a framework for drug development against Ub/Ubl-processing enzymes.

Animals↗
PubMed2005

High-resolution functional proteomics by active-site peptide profiling.

Characterization and functional annotation of the large number of proteins predicted from genome sequencing projects poses a major scientific challenge. Whereas several proteomics techniques have been developed to quantify the abundance of proteins, these methods provide little information regarding protein function. Here, we present a gel-free platform that permits ultrasensitive, quantitative, and high-resolution analyses of protein activities in proteomes, including highly problematic samples such as undiluted plasma. We demonstrate the value of this platform for the discovery of both disease-related enzyme activities and specific inhibitors that target these proteins.

Animals↗
PubMed2006

High-throughput gene expression profiling--a work-in-progress with great potential for proteomics.

Since the invention of Northern blot profiling more than 30 years ago, scientists have progressed from being able to analyze only a few genes at a time to whole-genome and global differential gene expression profiling. This progress has been made possible by the development of several high-throughput technologies. Such technologies have gained increasing popularity in recent years because of significant discoveries made in the field of proteomics, and have already led to huge advances in the medical field. This article reviews the high-throughput technologies that have been undergoing development during the last two years for the selection of specific cell subtypes in a tissue, for the discovery and identification of all of the genes expressed in a system without pre-selection (open systems), and for the validation of selected genes (closed systems).

Animals↗
PubMed2006

Peptidomics: bridging the gap between proteome and metabolome.

Studies of naturally occurring peptides and protein profiling by 'classical' proteomics are linked by common analytical objectives and methodologies. The first international workshop "Peptidomics: methods and applications" held on 6-7th September 2005 at Royal Holloway University of London confirmed that the science of peptidomics is a rapidly developing activity of high interest to both academia and industry. This meeting featured talks by over 20 leading international scientists detailing methods and typical applications, including newly-developed capabilities for protein and peptide analyses. It provided a definition of the scope of the subject in terms of current and future technologies together with applications ranging from studies of defined biological extracts to complete ecosystems. The proceedings of this meeting, speakers' contact details and other relevant information can be accessed at: www.rhul.ac.uk/biosci/meetings.

Animals↗
PubMed2001

Profiling serine hydrolase activities in complex proteomes.

Serine hydrolases represent one of the largest and most diverse families of enzymes in higher eukaryotes, comprising numerous proteases, lipases, esterases, and amidases. The activities of many serine hydrolases are tightly regulated by posttranslational mechanisms, limiting the suitability of standard genomics and proteomics methods for the functional characterization of these enzymes. To facilitate the global analysis of serine hydrolase activities in complex proteomes, a biotinylated fluorophosphonate (FP-biotin) was recently synthesized and shown to serve as an activity-based probe for several members of this enzyme family. However, the extent to which FP-biotin reacts with the complete repertoire of active serine hydrolases present in a given proteome remains largely unexplored. Herein, we describe the synthesis and utility of a variant of FP-biotin in which the agent's hydrophobic alkyl chain linker was replaced by a more hydrophilic poly(ethylene glycol) moiety (FP-peg-biotin). When incubated with both soluble and membrane proteomes for extended reaction times, FP-biotin and FP-peg-biotin generated similar "maximal coverage" serine hydrolase activity profiles. However, kinetic analyses revealed that several serine hydrolases reacted at different rates with each FP agent. These rate differences were exploited in studies that used the biotinylated FPs to examine the target selectivity of reversible serine hydrolase inhibitors directly in complex proteomes. Finally, a general method for the avidin-based affinity isolation of FP-biotinylated proteins was developed, permitting the rapid and simultaneous identification of multiple serine peptidases, lipases, and esterases. Collectively, these studies demonstrate that chemical probes such as the biotinylated FPs can greatly accelerate both the functional characterization and molecular identification of active enzymes in complex proteomes.

Animals↗
PubMed2026

Subphenogroups of acute heart failure with preserved ejection fraction: comprehensive proteomics and pathway analysis.

BACKGROUND: Heterogeneity of heart failure with preserved ejection fraction (HFpEF) results in significant challenges for treatment development. Identifying and characterising distinct HFpEF phenogroups may aid in tailoring therapeutic strategies for these patients. The objective of this study was to assess proteomic patterns of HFpEF phenogroups identified through a machine-learning-based clustering model, with the aim of uncovering specific biological pathways associated with each phenogroup. METHODS: This study represents a post-hoc analysis of the ongoing Prospective mUlticenteR obServational stUdy of patIenTs with Heart Failure with preserved Ejection Fraction (PURSUIT-HFpEF) study, which is a multicentre prospective observational study of hospitalised patients with acute decompensated HFpEF. Of the overall cohort (N=1238), this study analysed 198 patients with HFpEF with available proteomics data. These patients were classified into four phenogroups using the machine-learning-based clustering model. The SomaScan assay V.4.1 was used to measure levels of >7000 plasma proteins, and subsequent pathway analysis was conducted to determine the biological differences among the phenogroups. RESULTS: We identified four distinct phenogroups: Phenogroup 1 ('rhythm trouble'), Phenogroup 2 ('ventricular-arterial uncoupling'), Phenogroup 3 ('low output and systemic congestion') and Phenogroup 4 ('systemic failure'). The proteomics revealed distinct protein expression profiles among the phenogroups, with ribonuclease 4, tax1-binding protein 1, regenerating islet-derived protein 3-gamma and alpha-1-antichymotrypsin being the most significant markers to specific identified phenogroups. Pathway analysis suggested differences in immune response, autonomic activation, cellular homeostasis and tissue repair mechanisms across the phenogroups. CONCLUSIONS: Using a comprehensive plasma proteomics approach, our study identified distinct proteomic profiles of HFpEF phenogroups, which in turn suggest specific underlying biological processes. These profiles suggest the involvement of inflammatory activation, tissue injury and regenerative responses, immune modulation and systemic stress signalling as key components of HFpEF pathophysiology. TRIAL REGISTRATION NUMBER: UMIN-CTR ID: UMIN000021831.

Humans↗
PubMed2005

Influences of blood sample processing on low-molecular-weight proteome identified by surface-enhanced laser desorption/ionization mass spectrometry.

BACKGROUND: Profiling approaches in proteomics, such as surface-enhanced laser desorption/ionization (SELDI) mass spectrometry, are used in disease marker discovery. The aim of this study was to investigate the potential influence of selected preanalytical factors on the results obtained. METHODS: Plasma samples anticoagulated with EDTA, citrate, or heparin, and serum samples from healthy volunteers were profiled by SELDI on CM10, immobilized metal affinity capture (IMAC) array with copper, and H50 chip surfaces. Using linear mixed-effects models, we examined the influence of elapsed time between venipuncture and sample separation (immediate to 24 h) and the type of serum tube used (Greiner Vacuette activator, gel serum separator, or plain tubes). We analyzed purified platelets, as well as platelet-poor and platelet-rich plasma samples treated with calcium and/or thrombin to determine the platelet contribution, directly or via the clotting process, to the profiles generated. We then used cluster analysis to identify samples with similar peak profiles. RESULTS: Different plasma types and sera could be distinguished on the basis of cluster analyses of their spectral profiles. Elapsed time between venipuncture and separation of plasma and serum from blood samples altered the profiles obtained, particularly for serum samples and particularly on IMAC chips. The type of serum collection tube also affected the profiles because of differences in clotting time. In vitro manipulation of platelets revealed that specific peaks in IMAC profiles of serum appeared to be derived directly from platelets. Several other peaks, including some of those exhibiting time-dependent changes, arose during the clotting process. CONCLUSION: Preanalytical variables, such as sample handling, can markedly influence results.

Adult↗
PubMedDate not supplied

Chemistry-based functional proteomics: mechanism-based activity-profiling tools for ubiquitin and ubiquitin-like specific proteases.

Determining the biological function of newly discovered gene products requires the development of novel functional approaches. To facilitate this task, recent developments in proteomics include small molecular probes that target proteolytic enzyme families including serine, threonine, and cysteine proteases. For the families of ubiquitin (Ub) and ubiquitin-like (UBL)-specific proteases, such tools were lacking until recently. Here, we review the advances made in the development of protein-based active site-directed probes that target proteases specific for ubiquitin and ubiquitin-like proteins. Such probes were applied successfully to discover and characterize novel Ub/UBL-specific proteases. Ub/UBL processing and deconjugation are performed by a diverse set of proteases belonging to several different enzyme families, including members of the ovarian tumor domain (OTU) protease family. A further definition of this family of enzymes will benefit from a directed chemical proteomics approach. Some of the Ub/UBL-specific proteases react with multiple Ub/UBLs and members of the same protease family can recognize multiple Ub/UBLs, underscoring the need for tools that appropriately address enzyme specificity.

B-Lymphocytes↗