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At least 91 records · Page 5Linked to original sources
PubMed2004

Serum proteomic profiling can discriminate prostate cancer from benign prostates in men with total prostate specific antigen levels between 2.5 and 15.0 ng/ml.

PURPOSE: Artificial intelligence based pattern recognition algorithms have been developed and successfully used to analyze complex serum proteomic data streams generated by surface enhanced, laser desorption ionization time-of-flight mass spectroscopy. In the current study we used a high performance, hybrid quadrupole time-of-flight mass spectrometer to generate discriminatory serum proteomic profiles to determine if this technology could be used to determine the need for prostate biopsy in men with elevated prostate specific antigen (PSA). MATERIALS AND METHODS: Serum samples were collected from 154 men with serum PSA 2.5 to 15.0 ng/ml and/or abnormal digital rectal examination prior to transrectal ultrasound guided biopsy. Serum samples were applied to WCX2 (weak cation exchange protein chip) Protein Arrays (Ciphergen Biosystems, Fremont, California) by a Biomek 2000 robotic liquid handler (Beckman-Coulter, Chaska, Minnesota) and low molecular weight (less than 20 kDa) proteomic patterns were generated with an API QSTAR Pulsar i LC/MS/MS System (Applied Biosystems, Framingham, Massachusetts). High resolution mass spectra were analyzed with a pattern recognition bioinformatics tool, that is Proteome Quest beta version 1.0 (Correlogic Systems, Inc., Bethesda, Maryland), in an attempt to identify and discover key discriminating ion signatures. Serum samples from 63 men (2 or more negative prostate biopsies in 23, 1 negative biopsy in 10 and biopsy detected prostate cancer [CaP] in 30) were used to train the diagnostic algorithm. The remaining 91 samples, including 28 of prostate cancer and 63 of 1 or more negative biopsies, were analyzed in blinded fashion. RESULTS: The most discriminatory model was found using the WCX2 chip. Testing the remaining 91 men with this model yielded 100% sensitivity and 67% specificity. In other words, if the proteomic pattern had been used to determine the need for prostate biopsy in this cohort of men with PSA between 2.5 and 15.0 ng/ml, 67% (42 of 63) with negative biopsies would have avoided unnecessary biopsy, while no cancers would have been missed. CONCLUSIONS: Our data demonstrate that high resolution mass spectroscopy can generate serum proteomic patterns that discriminate men with elevated PSA due to benign processes from men with CaP even when PSA is within the diagnostic gray zone. We are currently expanding the testing set to determine the reliability of this new technology to decrease unnecessary prostate biopsies without compromising the detection of curable CaP.

Algorithms↗
PubMed2000

High-throughput profiling of the mitochondrial proteome using affinity fractionation and automation.

Recent studies have demonstrated the need for complementing cellular genomic information with specific information on expressed proteins, or proteomics, since the correlation between the two is poor. Typically, proteomic information is gathered by analyzing samples on two-dimensional gels with the subsequent identification of specific proteins of interest by using trypsin digestion and mass spectrometry in a process termed peptide mass fingerprinting. These procedures have, as a rule, been labor-intensive and manual, and therefore of low throughput. The development of automated proteomic technology for processing large numbers of samples simultaneously has made the concept of profiling entire proteomes feasible at last. In this study, we report the initiation of the (eventual) complete profile of the rat mitochondrial proteome by using high-throughput automated equipment in combination with a novel fractionation technique using minispin affinity columns. Using these technologies, approximately one hundred proteins could be identified in several days. In addition, separate profiles of calcium binding proteins, glycoproteins, and hydrophobic or membrane proteins could be generated. Because mitochondrial dysfunction has been implicated in numerous diseases, such as cancer, Alzheimer's disease and diabetes, it is probable that the identification of the majority of mitochondrial proteins will be a beneficial tool for developing drug and diagnostic targets for associated diseases.

Animals↗
PubMed2005

Proteomics in nutrition research: principles, technologies and applications.

The global profiling of the whole protein complement of the genome expressed in a particular cell or organ, or in plasma or serum, makes it possible to identify biomarkers that respond to alterations in diet or to treatment, and that may have predictive value for the modelling of biological processes. Proteomics has not yet been applied on a large scale in nutritional studies, yet it has advantages over transcriptome profiling techniques in that it directly assesses the entities that carry out the biological functions. The present review summarizes the different approaches in proteomics research, with special emphasis on the current technical 'workhorses': two-dimensional (2D)-PAGE with immobilized pH gradients and protein identification by MS. Using a work-flow approach, we provide information and advice on sample handling and preparation, protein solubilization and pre-fractionation, protein separation by 2D-PAGE, detection and quantification via computer-assisted analysis of gels, and protein identification and characterization techniques by means of MS. Examples from nutritional studies employing proteomics are provided to demonstrate not only the advantages but also the limitations of current proteome analysis platforms.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2001

Profiling the specific reactivity of the proteome with non-directed activity-based probes.

BACKGROUND: The field of proteomics aims to characterize dynamics in protein function on a global level. However, several classes of proteins, in particular low abundance proteins, remain difficult to characterize using standard proteomics technologies. Recently, chemical strategies have emerged that profile classes of proteins based on activity rather than quantity, thereby greatly facilitating the analysis of low abundance constituents of the proteome. RESULTS: In order to expand the classes of proteins susceptible to analysis by activity-based methods, we have synthesized a library of biotinylated sulfonate esters and applied its members to complex proteomes under conditions that distinguish patterns of specific protein reactivity. Individual sulfonates exhibited unique profiles of proteome reactivity that in extreme cases appeared nearly orthogonal to one another. A robustly labeled protein was identified as a class I aldehyde dehydrogenase and shown to be irreversibly inhibited by members of the sulfonate library. CONCLUSIONS: Through screening the proteome with a non-directed library of chemical probes, diverse patterns of protein reactivity were uncovered. These probes labeled protein targets based on properties other than abundance, circumventing one of the major challenges facing contemporary proteomics research. Considering further that the probes were found to inhibit a target enzyme's catalytic activity, the methods described herein should facilitate the identification of compounds possessing both selective proteome reactivities and novel bioactivities.

Aldehyde Dehydrogenase↗
PubMedDate not supplied

Clinical cancer proteomics: promises and pitfalls.

Proteome analysis promises to be valuable for the identification of tissue and serum biomarkers associated with human malignancies. In addition, proteome technologies offer the opportunity to analyze protein expression profiles and to analyze the activity of signaling pathways. Many published proteomic studies of human tumor tissue are associated with weaknesses in tumor representativity, sample contamination by nontumor cells and serum proteins. Studies often include a moderate number of tumors which may not be representative of clinical materials. It is therefore very important that biomarkers identified by proteomics are validated in representative tumor materials by other techniques, such as immunohistochemistry. Proteome technologies can be used to identify disease markers in human serum. Tumor derived proteins are present at nanomolar to picomolar concentrations in cancer patient sera, 10(6)-10(9)-fold lower than albumin, and will give rise to correspondingly smaller spots/peaks in protein separations. This leads to the need to prefractionate serum samples before analysis. Despite various pitfalls, proteomic analysis is a promising approach to the identification of biomarkers, and for generation of protein expression profiles that can be analyzed by artificial learning methods for improved diagnosis of human malignancy. Recent advances in the field of proteomic analysis of human tumors are summarized in the present review.

Biomarkers, Tumor↗
PubMed2002

Operomics: integrated genomic and proteomic profiling of cells and tissues.

In the post-genome era, technologies are becoming available that allow the profiling of tissues and cell populations at multiple levels including genomic (DNA and RNA), proteomic (proteins and peptides) and post-proteomic (eg metabolomic). Operomics refers to the molecular analysis of tissues and cells at the three levels that are connected through the coding process - namely, DNA, RNA and protein. The premise is that no one level or type of analysis fully captures gene expression and that functional changes at the proteome level cannot be simply predicted from analyses at the DNA or RNA levels. An important determinant that weakens a direct link between RNA and protein levels is translational control that differentially regulates mRNA translation. In this paper, the approaches for genomic and proteomic profiling and the contribution of translational control are reviewed.

DNA Methylation↗
PubMed2005

Treatment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. The major etiologies and risk factors for HCC development 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 early HCC detection in patients at risk, patient survival has not improved during the last three decades. This is due in part to the advanced stage of the disease at the time of clinical presentation, in part due to the limited therapeutic options. These fall into four main categories: (1) surgical interventions, including tumour resection and liver transplantation, (2) percutaneous interventions, including ethanol injection and radiofrequency thermal ablation, (3) transarterial interventions, including embolisation and chemoembolisation and (4) drugs as well as gene and immune therapies. These therapeutic strategies have been evaluated in part in randomised controlled clinical trials that are the basis for therapeutic recommendations. While surgery and percutaneous as well as 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 morbidity and mortality from HCC, therefore, 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. Further, 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 further elucidate the molecular events underlying HCC development and identify novel diagnostic markers as well as therapeutic and preventive targets.

Carcinoma, Hepatocellular↗
PubMed1999

Proteomics in drug discovery.

The promise of genomics has dramatically altered the way drug discovery is now viewed. Overshadowed by the exuberance for genomics are the observations that most disease processes and treatments are manifest at the protein level and that there may not be a good correlation between gene expression and protein expression. An alternative and complementary approach to genomics is protein expression profiling - proteomics. The authors describe the technology, its advantages and some applications.

Journal Article↗
PubMed2005

Pathogenesis of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. The major aetiologies 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. However, no clear picture of how and in what sequence these factors interact at the molecular level has emerged yet. Malignant transformation of hepatocytes may occur as a consequence of various aetiologies, such as chronic viral hepatitis, alcohol, and metabolic disorders, in the context of increased cellular turnover induced by chronic liver injury, regeneration and cirrhosis. Activation of cellular oncogenes, inactivation of tumour suppressor genes, genomic instability, including DNA mismatch repair defects and impaired chromosomal segregation, overexpression of growth and angiogenic factors, and telomerase activation may contribute to the development of HCC. Overall, HCCs are genetically very heterogeneous tumours. New technologies, including gene expression profiling and proteomic analyses, should allow us to further elucidate the molecular events underlying HCC development and identify novel diagnostic markers as well as therapeutic targets.

Carcinoma, Hepatocellular↗
PubMed2000

Harnessing the power of the genome in the search for new antibiotics.

Over the past 40 years, the search for new antibiotics has been largely restricted to well-known compound classes active against a standard set of drug targets. Although many effective compounds have been discovered, insufficient chemical variability has been generated to prevent a serious escalation in clinical resistance. Recent advances in genomics have provided an opportunity to expand the range of potential drug targets and have facilitated a fundamental shift from direct antimicrobial screening programs toward rational target-based strategies. The application of genome-based technologies such as expression profiling and proteomics will lead to further changes in the drug discovery paradigm by combining the strengths and advantages of both screening strategies in a single program.

Anti-Bacterial Agents↗
PubMed2006

Radiation-guided gene therapy of cancer.

Gene therapy has been proposed as a means to combat cancer. However, systemic toxicity observed in preclinical trials suggested the importance of selectively targeted delivery and inducible gene expression in tumor tissues. Discovery of radiation-inducible promoter sequences provides one way to minimize inadvertent toxicity from gene therapy in normal tissues. Radiation is administered to selectively induce cytotoxic gene expression in the targeted tumor tissues. With promising results from phase II clinical trials using TNF-expressing adenovirus, it is possible to have radiation-guided gene therapy regimes once the tumor-targeted delivery has been achieved. Tumor endothelium is an attractive biological target for gene therapy, because it has the advantage of stability, accessibility, and bioavailability for therapeutic agents. Technological development of DNA microarray, proteomic profiling, and phage-displayed libraries accelerates the identification of tumor-specific endothelial biomarkers and discovery of its relevant affinity reagents for targeted delivery. The application of radiation-guided gene delivery, its amplification, as well as expression of gene therapy presents great opportunities to be employed as an alternative cancer treatment.

Animals↗
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

Large scale protein profiling by combination of protein fractionation and multidimensional protein identification technology (MudPIT).

In the past decade, shotgun proteomic analysis has been utilized extensively to answer complex biological questions. New challenges arise in large scale proteomic profiling when dealing with complex biological mixtures such as the mammalian cell lysate. In this study, we explored the approach of protein separation prior to the shotgun multidimensional protein identification technology (MudPIT) analysis. We fractionated the mammalian cancer cell lysate using the PF 2D ProteomeLab system and analyzed the distribution of molecular weight, isoelectric point, and cellular localization of the eluted proteins. As a result, we were able to reduce sample complexity by protein fractionation and increase the possibility of detecting proteins with lower abundance in the complex protein mixture.

Biomarkers, Tumor↗
PubMed2003

Capillary isoelectric focusing-based multidimensional concentration/separation platform for proteome analysis.

An integrated proteome concentration/separation approach involving on-line combination of capillary isoelectric focusing (CIEF) with capillary reversed-phase liquid chromatography (CRPLC) is developed for providing significant analyte concentration and extremely high resolving power toward protein and peptide mixtures. Upon completion of analyte focusing, the self-sharpening effect greatly restricts analyte diffusion and contributes to analyte stacking in narrowly focused bands with a concentration factor of approximately 240. In addition to analyte focusing, CIEF as the first separation dimension resolves proteins/peptides on the basis of their differences in pI and offers greater resolving power than that achieved in strong cation exchange chromatography. The grouping of two highly resolving and completely orthogonal separation techniques of CIEF and CRPLC, together with analyte focusing and concentration, significantly enhances the dynamic range and sensitivity of conventional mass spectrometry toward the identification of low-abundance proteins. The CIEF-based multidimensional separation/concentration platform enables the identification of a greater number of yeast soluble proteins than methods presented in the literature, yet requires a protein loading of only 9.6 microg. This protein loading is 2-3 orders of magnitude lower than those employed by the reported non-gel-based proteome techniques. The distribution of a codon adaptation index value for identified yeast proteins approximates to that predicted for the entire yeast proteome and supports the capability of CIEF-based proteome separation technology for achieving comprehensive proteome analysis. By reducing the inner diameter of chromatography columns from 180 microm to 100 microm, the required protein loading is further decreased from 9.6 microg to 960 ng, illustrating the potential usage of this proteome technology for the analysis of protein profiles within small cell populations or limited tissue samples.

Chromatography, Liquid↗
PubMed2006

Genetics and molecular profiling of multiple myeloma: novel tools for clinical management?

The understanding of molecular events involved in multiple myeloma (MM) development as well as of mechanisms underlying sensitivity/resistance to anticancer drugs has been dramatically increased by the wide-spread use of modern technologies for genetic analysis, global gene expression and proteomic profiling. Such analytical approaches, which are presently supported by reliable bioinformatic tools, have depicted a new scenario for the development of molecular-based anti-MM agents and for predicting clinical outcome. IgH translocations or a hyperdiploid state are emerging as early genetic signatures of MM which lead to deregulated expression of cyclin D. At present however, the major challenge remains the definition of the potential role of cytogenetic techniques and molecular profiling technologies in individual patient management. Here we will describe the prospective potential and current achievements of such technologies which might produce major advancements in the treatment of this still incurable disease.

Chromosome Aberrations↗
PubMed2004

Profile identification of disease-associated humoral antigens using AMIDA, a novel proteomics-based technology.

We describe AMIDA (autoantibody-mediated identification of antigens), a novel target identification technology based on the immunoprecipitation of disease-specific antigens by autologous serum antibodies followed by two-dimensional electrophoretic separation, and their identification via mass spectrometry. Twenty-seven potential carcinoma antigens were identified including proteins of hitherto unknown function. Validation of one of the identified antigens, cytokeratin 8, revealed its de novo expression in hyperplastic tissue, gradual overexpression with increasing malignancy, and ectopic localization on the cell surface. Furthermore, a strong prevalence of CK8-specific antibodies occurred in the serum of cancer patients already at early disease stages. In situ hybridization for one marker of unknown function, KIAA1273/TOB3, demonstrated its strong overexpression in head and neck carcinomas, thus making it a likely tumor antigen candidate. Eventually, AMIDA could foster significant improvements for the diagnosis and therapy of human diseases eliciting a humoral immune response, and allows for the rapid identification of new target molecules.

Allergy and Immunology↗
PubMed2002

Informatic tools for proteome profiling.

In recent years, the practice of proteomics research has experienced a dramatic shift within the pharmaceutical and biotechnology industry with the widespread implementation of novel applications. The areas of interest extend all the way from discovery of novel drug, vaccine, and diagnostic targets, characterization of protein-based products, toxicology, and identification of surrogate markers of activity in clinical research, to the ability to provide information on the mechanisms of drug action. The power of two-dimensional gel electrophoresis as well as advances in mass spectrometric techniques combined with sequence database correlation have enabled speed and accuracy in identification of proteins in complex mixtures. This article surveys currently available software and informatic tools related to these methods for proteome profiling. The broad acceptance of these technologies, however, has not been accompanied by significant advances in the informatics and software tools necessary to support the analysis and management of the massive amounts of data generated in the process. In this context, this article also discusses the importance of relational databases for protein identification data management.

Biotechnology↗
PubMed2006

Cytokeratin-20 and seminal vesicle secretory protein VI as possible marker proteins in urinary bladder preneoplastic lesions induced by N-butyl-N-(4-hydroxybutyl) nitrosamine.

BACKGROUND: A simple and non-invasive methods for the diagnosis of transitional cell carcinoma of the bladder are needed for the prevention of invasive tumor. A proteomic technology has recently been developed to facilitate protein profiling of biological mixtures. We tried to detect the marker proteins by proteomic approach during the initiation stages on N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN)-induced bladder carcinogenesis in rats. METHODS: Ten rats in group A were given 0.05% BBN in drinking water for 12 weeks. Other 10 rats in group B with 10 rats were designated as a control group and were not given BBN. Whole urinary bladders of all rats were excised at 12 weeks from the beginning of the experiment. Conventional proteomics was performed with high resolution 2-dimension gel electrophoresis followed by computational image analysis and protein identification using mass spectrometry. RESULTS: A comparison of urinary bladder hyperplasia tissue with control tissue showed that five proteins; actin gamma2 propeptide, cytokeratin-20 (CK-20), proapolipoprotein, alpha2 actin (alpha-cardiac actin) and heat shock 27 kDa protein-1 were over-expressed in hyperplastic tissues. Three proteins; transcription factor myocardin, seminal vesicle secretory protein VI (SVS-VI) precursor and hypothetical protein RMT-7 were under-expressed in hyperplastic tissues. CONCLUSION: In our animal mode, BBN-induced urinary bladder mucosal hyperplasia resulted in an increase in the expression of five proteins and a decrease in the expression of three proteins. Of these, CK-20 and SVS-VI seem to be of particular interest. However other method such as Western blotting seems to be needed for confirmation of these proteins and more information on human bladder tissue is needed for clinical application.

Animals↗