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Results for “discovery proteomics”

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PubMed2001

Proteome analysis and its impact on the discovery of serological tumor markers.

BACKGROUND: Proteomics is a rapidly growing field of research that is becoming increasingly important as we enter the post-genome era. Remarkable improvements in the technologies of high-resolution two-dimensional polyacrylamide gel electrophoresis (2D PAGE) and mass spectrometry (MS) have marked the start of proteome analysis and its application to the study of human diseases. Besides studying the proteins involved in carcinogenesis, it is also applicable to the discovery of serological tumor markers for clinical uses, such as for hepatocellular carcinoma. CONCLUSIONS: The combination of 2D PAGE and MS is the most widely used technique for proteomics, although other more automated high-throughput techniques are being developed.

Biomarkers, Tumor↗

PubMed2006

A multiplexed proteomics approach to differentiate neurite outgrowth patterns.

We report here a method for proteomics pattern discovery by utilizing a self-organizing map approach to analyze data obtained from a novel multiplex iTRAQ proteomics method. Through the application of this technique, we were able to delineate the early molecular events preceding dorsal root ganglia neurite outgrowth induced by either nerve growth factor (NGF) or an immunophilin ligand, JNJ460. Following pattern analysis we discovered that each neurotrophic agent promoted mostly distinct increases in protein expression with few overlapping patterns. In the NGF-treated group, proteins possessing "biosynthesis function" (p < 0.002) and "ribosome localization" (p < 0.0003) were increased, while proteins promoting "organogenesis" (p < 0.004) and related "signal transduction" (p < 0.008) functions were notably increased in the JNJ460-treated group. This study suggests that the properties of neurite outgrowth triggered by NGF and JNJ460 can be distinguished at the proteome level. Multiplexed proteomics analysis, along with pattern discovery bioinformatics tools, has the capability to differentiate subtle neuroproteomics patterns.

Animals↗

PubMedDate not supplied

Proteomics as a tool for discovery: proteins implicated in Alzheimer's disease are highly expressed in normal pancreatic islets.

A proteomic analysis of islets was undertaken to determine the protein constituents of normal adult mouse islets. Unexpectedly, we identified several islet proteins that are associated with the pathogenesis of Alzheimer's disease. Some of these proteins had chaperone activity that is integral to proper protein folding. This group includes GRP78, valosin-containing protein, calreticulin, protein disulfide isomerase, DnaK, HSP70, HSP60, and TCP-1. Additionally, neuronal proteins key to coordinated neuronal guidance and survival were also identified in islets. This group includes proprotein convertase subtilisin, collapsin response mediator protein 2, ubiquinol-cytochrome c reductase core protein, L-3-hydroxyacyl-Coenzyme A dehydrogenase, glutamine synthetase, peroxiredoxin, and secretogogin. An important subset of the proteins identified here has not been reported previously in pancreatic islets. Abnormal activity of these proteins in brain may contribute to the pathogenesis of Alzheimer's disease, a neurodegenerative condition characterized by focal amyloid deposits with neurofibrillary tangles. The putative role of these proteins in Alzheimer's pathogenesis is intriguing given the possible clinical relationship and pathological similarity of Alzheimer's disease to type 2 diabetes. These findings have therefore led to the hypothesis that these proteins may also play a role in type 2 diabetes.

Alzheimer Disease↗

PubMed2024

Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium.

The 68th Benzon Foundation Symposium brought together leading experts to explore the integration of mass spectrometry-based proteomics and artificial intelligence to revolutionize personalized medicine. This report highlights key discussions on recent technological advances in mass spectrometry-based proteomics, including improvements in sensitivity, throughput, and data analysis. Particular emphasis was placed on plasma proteomics and its potential for biomarker discovery across various diseases. The symposium addressed critical challenges in translating proteomic discoveries to clinical practice, including standardization, regulatory considerations, and the need for robust "business cases" to motivate adoption. Promising applications were presented in areas such as cancer diagnostics, neurodegenerative diseases, and cardiovascular health. The integration of proteomics with other omics technologies and imaging methods was explored, showcasing the power of multimodal approaches in understanding complex biological systems. Artificial intelligence emerged as a crucial tool for the acquisition of large-scale proteomic datasets, extracting meaningful insights, and enhancing clinical decision-making. By fostering dialog between academic researchers, industry leaders in proteomics technology, and clinicians, the symposium illuminated potential pathways for proteomics to transform personalized medicine, advancing the cause of more precise diagnostics and targeted therapies.

Proteomics↗

PubMed2002

Proteomic approaches to tumor marker discovery.

CONTEXT: Current tumor markers for ovarian cancer still lack adequate sensitivity and specificity to be applicable in large populations. High-throughput proteomic profiling and bioinformatics tools allow for the rapid screening of a large number of potential biomarkers in serum, plasma, or other body fluids. OBJECTIVE: To determine whether protein profiles of plasma can be used to identify potential biomarkers that improve the detection of ovarian cancer. DESIGN: We analyzed plasma samples that had been collected between 1998 and 2001 from patients with sporadic ovarian serous neoplasms before tumor resection at various International Federation of Gynecology and Obstetrics stages (stage I [n = 11], stage II [n = 3], and stage III [n = 29]) and from women without known neoplastic disease (n = 38) using proteomic profiling and bioinformatics. We compared results between the patients with and without cancer and evaluated their discriminatory performance against that of the cancer antigen 125 (CA125) tumor marker. RESULTS: We selected 7 biomarkers based on their collective contribution to the separation of the 2 patient groups. Among them, we further purified and subsequently identified 3 biomarkers. Individually, the biomarkers did not perform better than CA125. However, a combination of 4 of the biomarkers significantly improved performance (P < or =.001). The new biomarkers were complementary to CA125. At a fixed specificity of 94%, an index combining 2 of the biomarkers and CA125 achieves a sensitivity of 94% (95% confidence interval, 85%-100.0%) in contrast to a sensitivity of 81% (95% confidence interval, 68%-95%) for CA125 alone. CONCLUSIONS: The combined use of bioinformatics tools and proteomic profiling provides an effective approach to screen for potential tumor markers. Comparison of plasma profiles from patients with and without known ovarian cancer uncovered a panel of potential biomarkers for detection of ovarian cancer with discriminatory power complementary to that of CA125. Additional studies are required to further validate these biomarkers.

Adult↗

PubMed2006

Proteome-based plasma biomarkers for Alzheimer's disease.

Alzheimer's disease is a common and devastating disease for which there is no readily available biomarker to aid diagnosis or to monitor disease progression. Biomarkers have been sought in CSF but no previous study has used two-dimensional gel electrophoresis coupled with mass spectrometry to seek biomarkers in peripheral tissue. We performed a case-control study of plasma using this proteomics approach to identify proteins that differ in the disease state relative to aged controls. For discovery-phase proteomics analysis, 50 people with Alzheimer's dementia were recruited through secondary services and 50 normal elderly controls through primary care. For validation purposes a total of 511 subjects with Alzheimer's disease and other neurodegenerative diseases and normal elderly controls were examined. Image analysis of the protein distribution of the gels alone identifies disease cases with 56% sensitivity and 80% specificity. Mass spectrometric analysis of the changes observed in two-dimensional electrophoresis identified a number of proteins previously implicated in the disease pathology, including complement factor H (CFH) precursor and alpha-2-macroglobulin (alpha-2M). Using semi-quantitative immunoblotting, the elevation of CFH and alpha-2M was shown to be specific for Alzheimer's disease and to correlate with disease severity although alternative assays would be necessary to improve sensitivity and specificity. These findings suggest that blood may be a rich source for biomarkers of Alzheimer's disease and that CFH, together with other proteins such as alpha-2M may be a specific markers of this illness.

Aged↗

PubMedDate not supplied

Bacterial proteomics and its role in antibacterial drug discovery.

Gene-expression profiling technologies in general, and proteomic technologies in particular have proven extremely useful to study the physiological response of bacterial cells to various environmental stress conditions. Complex protein toolkits coordinated by sophisticated regulatory networks have evolved to accommodate bacterial survival under ever-present stress conditions such as varying temperatures, nutrient availability, or antibiotics produced by other microorganisms that compete for habitat. In the last decades, application of man-made antibacterial agents resulted in additional bacterial exposure to antibiotic stress. Whereas the targeted use of antibiotics has remarkably reduced human suffering from infectious diseases, the ever-increasing emergence of bacteria that are resistant to antibiotics has led to an urgent need for novel antibiotic strategies. The intent of this review is to present an overview of the major achievements of proteomic approaches to study adaptation networks that are crucial for bacterial survival with a special emphasis on the stress induced by antibiotic treatment. A further focus will be the review of the, so far few, published efforts to exploit the knowledge derived from bacterial proteomic studies directly for the antibacterial drug-discovery process.

Anti-Bacterial Agents↗

PubMed2026

Targeted Modulation of Abundant Proteins Enhances Proteomic Profiling of Ovarian Cancer Ascites: A Pilot Technical Workflow Comparison.

Ascites from ovarian cancer patients are increasingly recognized as a valuable biofluid for cancer research, as its protein composition reflects the disease state and may reveal biomarkers of treatment sensitivity and response. However, the detection of low-abundance proteins is hindered by the presence of highly abundant proteins such as albumin. In this study, we evaluated five protein preparation methods for their effectiveness in depleting high-abundance or enriching low-abundance proteins in ovarian cancer ascites. The Norgen (Nor), Minutes (Min), and Perchloric acid (PerCA) methods were based on abundant protein depletion, while the Urine (Uri) and Nanomics (Nano) kits focused on low-abundance protein enrichment. Processed samples were analyzed using label-free quantitative bottom-up proteomics by LC-MS/MS, followed by a bioinformatics assessment. Compared with undepleted ascites (UnD), Min, Nor, Nano, and PerCA increased protein identifications, whereas Uri produced profiles similar to those of UnD. Notably, PerCA and Nano enabled the identification of distinct protein subsets associated with cancer-related pathways, including immune responses and autophagy. PerCA enriched transmembrane and secreted immunomodulatory glycoproteins, whereas Nano enrichment primarily captured secreted, nuclear, and cytoplasmic soluble proteins. Overall, our results show that both high-abundance protein depletion and low-abundance enrichment improve ascites proteome coverage, each offering distinct advantages in identifying biologically relevant low-abundance proteins.

Female↗

PubMed2004

The impact of transcriptome and proteome analyses on antibiotic drug discovery.

Recent scientific publications demonstrate the increasing interest in measurement of genome-wide gene expression on transcript and protein level in response to treatment with antibacterial agents. Nevertheless, the number of large bacterial transcriptome and proteome datasets available so far is limited, although a high number and diversity of antibiotic-triggered expression profiles aid to optimally exploit these technologies. The first published examples substantiate the need to establish these so-called reference compendia of bacterial expression profiles, to discover the molecular mechanism-of-action of uncharacterized bioactive substances. In addition, such compendia open up ways for novel cell-based drug screening approaches.

Anti-Bacterial Agents↗

PubMed2000

Subproteomics based upon protein cellular location and relative solubilities in conjunction with composite two-dimensional electrophoresis gels.

Progress in the field of proteomics is dependent upon an ability to visualise close to an entire protein complement via a given array technology. These efforts have previously centred upon two-dimensional gel electrophoresis in association with immobilised pH gradients in the first dimension. However, limitations in this technology, including the inability to separate hydrophobic, basic, and low copy number proteins have hindered the analysis of complete proteomes. The challenge is now to overcome these limitations through access to new technology and improvements in existing methodologies. Proteomics can no longer be equated with a single two-dimensional electrophoresis gel. Greater information can be obtained using targeted biological approaches based upon sample prefractionation into specific cellular compartments to determine protein location, while novel immobilised pH gradients spanning single pH units can be used to display poorly abundant proteins due to their increased resolving power and loading capacity. In this study, we show the effectiveness of a combined use of two differential subproteomes (as defined by relative solubilities, cellular location and narrow-range immobilised pH gradients) to increase the resolution of proteins contained on two-dimensional gels. We also present new results confirming that this method is capable of displaying up to a further 45% of a given microbial proteome. Subproteomics, utilising up to 40 two-dimensional gels per sample will become a powerful tool for near-to-total proteome analysis in the postgenome era. Furthermore, this new approach can direct biological focus towards molecules of specific interest within complex cells and thus simplify efforts in discovery-based proteome research.

Cells↗

PubMed2005

Proteomic analysis of renal diseases: unraveling the pathophysiology and biomarker discovery.

Current biomedical applications of proteomics have been conducted with four main objectives: to better understand the normal biology and physiology of cells, microorganisms, tissues and organs; to explore the pathogenic mechanisms and better understand the pathophysiology of medical diseases; to identify novel biomarkers for early disease detection, prediction and prognosis; and to define new therapeutic targets, drugs and vaccines. This review focuses predominantly on proteomic applications to unravel the pathophysiology and to define novel biomarkers for various renal diseases (i.e., glomerular diseases, tubulointerstitial diseases, renal vascular disorders and renal cancers). In addition, proteomic evaluations of renal transplantation and renal replacement therapy (for acute renal failure and end-stage renal disease) are summarized. Personal opinion, future perspectives and information resources for the field of renal and urinary proteomics are provided.

Biomarkers↗

PubMed2002

Proteomic profiling of mechanistically distinct enzyme classes using a common chemotype.

Proteomics research requires methods to characterize the expression and function of proteins in complex mixtures. Toward this end, chemical probes that incorporate known affinity labeling agents have facilitated the activity-based profiling of certain enzyme families. To accelerate the discovery of proteomics probes for enzyme classes lacking cognate affinity labels, we describe here a combinatorial strategy. Members of a probe library bearing a sulfonate ester chemotype were screened against complex proteomes for activity-dependent protein reactivity, resulting in the labeling of at least six mechanistically distinct enzyme classes. Surprisingly, none of these enzymes represented targets of previously described proteomics probes. The sulfonate library was used to identify an omega-class glutathione S-transferase whose activity was upregulated in invasive human breast cancer lines. These results indicate that activity-based probes compatible with whole-proteome analysis can be developed for numerous enzyme classes and applied to identify enzymes associated with discrete pathological states.

Affinity Labels↗

PubMedDate not supplied

Molecular determinants of differential sensitivity to docetaxel and paclitaxel in human pediatric cancer models.

BACKGROUND: The differential sensitivity of some tumors to paclitaxel and docetaxel raises questions regarding the specific mechanisms responsible for the discrepant sensitivity to these taxanes. MATERIALS AND METHODS: Docetaxel and paclitaxel were evaluated and compared at maximum tolerated doses (MTD) and 0.5 MTDs against the human pediatric tumor xenograft models SK-N-MC and IMR32 (neuroblastoma), RH1 and RH30 (rhabdomyosarcoma) and KHOS/NP (osteosarcoma), with 8-10 animals per group. The drug effects on the expression of the beta-tubulin isotypes, Bcl-2, Bax, Bcl-XL and proteomic profiles were evaluated by immunobloting and SELDI mass spectrometry in tumor xenografts dosed at 0.5 MTDs. RESULTS: At MTDs, docetaxel was superior in neuroblastoma and osteosarcoma, while paclitaxel was more active in the rhabdomyosarcoma models. Docetaxel showed remarkable efficacy in KHOS/NP even at 0.5 MTD. The drugs had significantly different, yet highly heterogeneous effects on the tumor levels of betaI-tubulin (RH30), betaIII-tubulin (IMR32, KHOS/NP, RH]), Bax (IMR32, SK-N-MC) and Bcl-XL (KHOS/NP). In contrast, six protein species identified by proteomic profiling were consistently and differentially regulated by docetaxel and paclitaxel in all KHOS/NP xenografts. CONCLUSION: Anticancer activity showed no apparent correlation with drug effects on beta-tubulin isotypes and apoptotic markers. The mass spectrometry approach has potential for the discovery of proteomic biomarkers for drug sensitivity.

Animals↗

PubMed2002

Complexities in ETS-domain transcription factor function and regulation: lessons from the TCF (ternary complex factor) subfamily. The Colworth Medal Lecture.

The ETS-domain transcription factor family can be divided into a series of subfamilies. Elk-1 represents the founding member of the ternary complex factor (TCF) subfamily. By focusing on the TCF subfamily, we can demonstrate the complexities that exist in the function and regulation of ETS-domain transcription factors. This article focuses on Elk-1 in detail and summarizes the functions of other TCFs. The key themes covered include the domain structure of the TCFs, the mechanisms of complex formation with serum response factor, regulation of TCFs by mitogen-activated protein kinase cascades, and transcriptional regulatory properties of the TCFs. Finally, the emerging role of the TCFs in vivo is discussed. A picture is developing indicating that, while these proteins exhibit significant sequence and functional conservation, key differences in their structure and regulation are being identified which may relate to unique functions of these proteins in vivo.

Amino Acid Sequence↗

PubMed2026

Enrichment Performance Assessment of Extracellular Vesicles Using Different Functionalized Magnetic Materials and Application in Urinary Proteomics of Prostate Cancer.

Extracellular vesicles (EVs) are lipid bilayer nanovesicles that mediate intercellular communication and hold significant potential for clinical applications. Although material-based isolation strategies offer promising alternatives to conventional methods, their relative performances have not been systematically evaluated. In this study, we conducted a comparative assessment of magnetic nanomaterials with distinct surface functionalities, including metal oxides (TiO2), metal-organic frameworks (UiO-66), biopolymeric materials (chitosan), and lipid probes (DSPE-PEG, DOPE-PEG, and CLS-PEG). A comprehensive evaluation across multiple dimensions including capture capacity, capture rate, sample volume, and product purity reveals that the bifunctional magnetic nanomaterial Fe3O4@UiO-66@DSPE material exhibits superior EV capture performance. This material enables the efficient and stable enrichment of high-purity EVs by synergizing Zr4+-phosphate coordination with lipid bilayer anchoring, and preserves EV biological integrity and activity. Meanwhile, this method could be highly compatible with proteomics, and over 1000 proteins are identified by proteomic analysis of urinary EVs, while 34 proteins are upregulated and 25 proteins are downregulated in prostate cancer patients relative to healthy donors. Notably, the differentially expressed proteins, such as AGT, ITIH4, and PGLYRP2, are associated with disease progression. Overall, this work highlights the superior performance of the Fe3O4@UiO-66@DSPE material for efficient and selective EV isolation. It provides a powerful tool for clinical liquid biopsy and proteomic biomarker discovery, enabling early diagnosis, prognostic evaluation, and precision therapy.

Humans↗

PubMed2004

Candidate-based proteomics in the search for biomarkers of cardiovascular disease.

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.

Animals↗

PubMed2006

Cancer proteomics and its application to discovery of therapy response markers in human cancer.

The administration of chemotherapy either alone or in combination with radiotherapy is an important factor in reducing the mortality and morbidity of cancer patients. Resistance to both chemotherapy and radiotherapy represents a major obstacle to a successful outcome. The identification of novel biomarkers that can be used to predict treatment response would allow therapy to be tailored on an individual patient basis. Although the mechanisms are unclear, it is accepted that development of therapy resistance is a multifactorial phenomenon involving alterations in several cellular pathways. Proteome analysis methods are powerful tools for identifying factors associated with resistance to anticancer therapy because they facilitate the simultaneous analysis of whole proteomes. The current review describes the plethora of existing proteomic approaches and details the studies that have identified biomarkers that may be useful in the prediction of clinical response to anticancer therapy.

Biomarkers, Tumor↗

PubMed2006

Enhanced detectability in proteome studies.

The discovery of candidate biomarkers from biological materials coupled with the development of detection methods holds both incredible clinical potential as well as significant challenges. However, the proteomic techniques still provide the low dynamic range of protein detection at lower abundances. This review describes the current development of potential methods to enhance the detection and quantification in proteome studies. It also includes the bioinformatics tools that are helpfully used for data mining of protein ontology. Therefore, we believe that this review provided many proteomic approaches, which would be very potent and useful for proteome studies and for further diagnostic and therapeutic applications.

Biomarkers↗