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At least 1,603 records · Page 89Linked to original sources
PubMed2006

Disease mechanism and biomarkers of oral squamous cell carcinoma.

PURPOSE OF REVIEW: This review focuses on oral cancer disease mechanisms and discusses ongoing research to identify molecular signatures or biomarkers for oral cancer. Other areas covered include the analysis, validation, and predictive value of these markers. RECENT FINDINGS: During the past years, progress has been made in the oral cancer genetic markers field, which includes alterations of the p53 tumor suppressor protein, the inactivation of cyclin dependant kinase inhibitors (e.g. p16) and the overexpression of the epidermal growth factor receptor. Many of these markers are thought to have potential clinical interest, yet few of them are being used in a clinical setting for oral cancer management. The particular modifications that characterize each step of oral cancer progression can now be profiled by several high throughput discovery techniques. Genomic and proteomic studies of oral cancer tissues, plasma, and saliva of oral cancer patients, have allowed the identification of several promising cancer signatures. SUMMARY: Important progress has been made in the molecular understanding of oral cancer and its application for diagnosis, prognosis and treatment. The increased efforts in translational research will result in earlier diagnosis of oral cancer, better knowledge of prognostic factors, and the development of targeted treatment regimens based on patients' clinical and biological characteristics at presentation.

Biomarkers, Tumor↗
PubMed2004

Proteomic analysis of pulmonary edema fluid and plasma in patients with acute lung injury.

Proteomics is the large-scale analysis of protein profiles. This approach has not yet been reported in the study of acute lung injury (ALI). This study details protein profiles in plasma and pulmonary edema fluid (EF) from 16 ALI patients and plasma and bronchoalveolar lavage fluid (BALF) from 12 normal subjects. More than 300 distinct protein spots were evident in the EF and BALF of both normal subjects and ALI patients. Of these, 158 were identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. In the plasma and EF protein profile of ALI patients, there were multiple qualitative changes. For instance, in all normal subjects, but in only one of the ALI patients, seven distinct surfactant protein A isoforms were evident. Nearly all ALI patients also had protein spots that indicate truncation or other posttranslational modifications. Several of these novel changes could serve as new biomarkers of lung injury.

Adult↗
PubMed2003

Magnetic resonance image-guided proteomics of human glioblastoma multiforme.

PURPOSE: To investigate the correlation between gadolinium contrast-enhancement patterns on T1-weighted magnetic resonance (MR) images and spatial changes in protein expression profiles in human glioblastoma multiforme (GBM) and the use of imaging as a noninvasive technique to evaluate the heterogeneity of solid tumors prior to microarray analysis. MATERIALS AND METHODS: Four patients with MR images and confirmed diagnosis of GBM were enrolled in the study. Intraoperative stereotaxy was used in conjunction with MR images to identify contrast-enhanced (CE) and nonenhanced (NE) regions of the tumor during surgical resection. Total protein was extracted from resected tumor samples using standard techniques and subjected to proteomic analysis using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS). RESULTS: We found that protein profiles from CE and NE regions within a given tumor have qualitative and semiquantitative proteomic pattern differences, suggesting an altered gene expression profile that correlates with detectable tissue imaging parameters. We also found that CE regions within the same tumor exhibited distinct differences in protein expression profiles, despite similar histological features. In addition, there were marked similarities in the proteomic patterns among the NE regions across all patients, while the CE regions were distinct, suggesting that the CE regions have complex protein profiles unique to individuals. CONCLUSION: The results demonstrate that major differences in protein expression patterns within a tumor can be correlated to radiographic findings. Image-guided proteomics holds promise for characterizing tissue prior to microarray analysis designed to identify specific diagnostic markers and therapeutic targets within solid tumors.

Brain Neoplasms↗
PubMed2004

MITOPRED: a genome-scale method for prediction of nucleus-encoded mitochondrial proteins.

MOTIVATION: Currently available methods for the prediction of subcellular location of mitochondrial proteins rely largely on the presence of mitochondrial targeting signals in the protein sequences. However, a large fraction of mitochondrial proteins lack such signals, making those tools ineffective for genome-scale prediction of mitochondria-targeted proteins. Here, we propose a method for genome-scale prediction of nucleus-encoded mitochondrial proteins. The new method, MITOPRED, is based on the Pfam domain occurrence patterns and the amino acid compositional differences between mitochondrial and non-mitochondrial proteins. RESULTS: MITOPRED could predict mitochondrial proteins with 100% specificity at a 44% sensitivity rate and with 67% specificity at 99% sensitivity. Additionally, it was sufficiently robust to predict mitochondrial proteins across different eukaryotic species with similar accuracy. Based on Matthews correlation coefficient measure, the prediction performance of MITOPRED is clearly superior (0.73) to those of the two popular methods TargetP (0.51) and PSORT (0.53). Using this method, we predicted the nucleus-encoded mitochondrial proteins from six complete genomes (three invertebrate, two vertebrate and one plant species) and estimated the total number in each genome. In human, our method estimated the existence of 1362 mitochondrial proteins corresponding to 4.8% of the total proteome. AVAILABILITY: MITOPRED program is freely accessible at http://mitopred.sdsc.edu. Source code is available on request from the authors. SUPPLEMENTARY INFORMATION: Training data sets are also available at http://mitopred.sdsc.edu

Algorithms↗
PubMed2001

[Proteomic analysis: why and how ?].

The proteome, first formalized in 1995, designs all the proteins expressed by the genome of a cell, tissu, or organ at a defined time. Proteomic analysis leads to a description of the regulation of gene expression by the study of proteins and of their post-translational modifications. Proteomic analysis is based on three technologies: 1) Two-dimensional electrophoresis allowing the separation of thousands of proteins from a single mixture; 2) mass spectrometry allowing the characterization of picoquantities of polypeptides and providing data on post-translational modifications; 3) Bioinformatic which is required for the quantification of protein level and for the constitution of databases of protein expression profiles. Complementing the methods of the genomics, the use of proteomic analysis is widely spreading in the fields of fundamental biology, biomedicine and pharmacology for the identification of new biological markers and therapeutic targets.

Animals↗
PubMed2004

Proteome-wide identification of cellular targets affected by bisindolylmaleimide-type protein kinase C inhibitors.

Bisindolylmaleimide compounds such as GF109203X are potent inhibitors of protein kinase C (PKC) activity. Although bisindolylmaleimides are not entirely selective for PKC and are known to inhibit a few other protein kinases, these reagents have been extensively used to study the functional roles of PKC family enzymes in cellular signal transduction for more than a decade. Here, we establish a proteomics approach to gain further insights into the cellular effects of this compound class. Functional immobilization of suitable bisindolylmaleimide analogues in combination with the specific purification of cellular binding proteins by affinity chromatography led to the identification of several known and previously unknown enzyme targets. Subsequent in vitro binding and activity assays confirmed the protein kinases Ste20-related kinase and cyclin-dependent kinase 2 (CDK2) and the non-protein kinases adenosine kinase and quinone reductase type 2 as novel targets of bisindolylmaleimide inhibitors. As observed specifically for CDK2, minor chemical variation of the ligand by immobilizing the closely related bisindolylmaleimides III, VIII, and X dramatically affected target binding. These observed changes in affinity correlated with both the measured IC(50) values for in vitro CDK2 inhibition and results from molecular docking into the CDK2 crystal structure. Moreover, the conditions for affinity purification could be adapted in a way that immobilized bisindolylmaleimide III selectively interacted with either PKC alpha or ribosomal S6 protein kinase 1 only after activation of these kinases. Thus, we have established an efficient technique for the rapid identification of cellular bisindolylmaleimide targets and further demonstrate the comparative selectivity profiling of closely related kinase inhibitors within a cellular proteome.

Animals↗
PubMed2006

Molecular basis of cell-biomaterial interaction: insights gained from transcriptomic and proteomic studies.

With the growing interest in clinical interventions that involve medical devices, the role for new biomaterials in modern medicine is currently expanding at a phenomenal rate. Failure of most implant materials stems from an inability to predict and control biological phenomena, such as protein adsorption and cell interaction, resulting in an inappropriate host response to the materials. Contemporary advances in biological investigation are starting to shift focus in the biomaterials field, in particular with the advent of high-throughput methodologies for gene and protein expression profiling. Here, we examine the role that emerging transcriptomic and proteomic technologies could play in relation to biomaterial development and usage. Moreover, a number of studies are highlighted which have utilized such approaches in order to try to create a deeper understanding of cell-biomaterial interactions and, hence, improve our ability to predict and control the biocompatibility of new materials.

Biocompatible Materials↗
PubMed2003

From genomics to proteomics.

Proteomics is the study of the function of all expressed proteins. Tremendous progress has been made in the past few years in generating large-scale data sets for protein-protein interactions, organelle composition, protein activity patterns and protein profiles in cancer patients. But further technological improvements, organization of international proteomics projects and open access to results are needed for proteomics to fulfil its potential.

Animals↗
PubMed2004

Identification of sigma factor sigma B-controlled genes and their impact on acid stress, high hydrostatic pressure, and freeze survival in Listeria monocytogenes EGD-e.

The gene encoding the alternative sigma factor sigma(B) in Listeria monocytogenes is induced upon exposure of cells to several stresses. In this study, we investigated the impact of a sigB null mutation on the survival of L. monocytogenes EGD-e at low pH, during high-hydrostatic-pressure treatment, and during freezing. The survival of Delta sigB mutant exponential-phase cells at pH 2.5 was 10,000-fold lower than the survival of EGD-e wild-type cells. Moreover, the Delta sigB mutant failed to show an acid tolerance response. Upon preexposure for 1 h to pH 4.5, the survival at pH 2.5 was 100,000-fold lower for the Delta sigB mutant than for the wild type. The glutamate decarboxylase (GAD) acid resistance system is important in survival and adaptation of L. monocytogenes in acidic conditions. The sigma(B) dependence of the gad genes (gadA, gadB, gadC, gadD, and gadE) was analyzed in silico. Putative sigma(B)-dependent promoter sites were found upstream of the gadCB operon (encoding a glutamate/gamma-aminobutyrate antiporter and a glutamate decarboxylase, respectively) and the lmo2434 gene (gadD, encoding a putative glutamate decarboxylase). Reverse transcriptase PCR revealed that expression of the gadCB operon and expression of gadD are indeed sigma(B) dependent. In addition, a proteomics approach was used to analyze the protein expression profiles upon acid exposure. Although the GAD proteins were not recovered, nine proteins accumulated in the wild type but not in the Delta sigB strain. These proteins included Pfk, GalE, ClpP, and Lmo1580. Exposure to pH 4.5, in order to preload cells with active sigma(B) and consequently with sigma (B)-dependent general stress proteins, also provided considerable protection against high-hydrostatic-pressure treatment and freezing. The combined data argue that the expression of sigma(B)-dependent genes provides L. monocytogenes with nonspecific multiple-stress resistance that may be relevant for survival in the natural environment as well as during food processing.

Bacterial Proteins↗
PubMed2006

Integrating synapse proteomics with transcriptional regulation.

The mammalian postsynaptic proteome (PSP) comprises a highly interconnected set of approximately 1,000 proteins. The PSP is organized into macromolecular complexes that have a modular architecture defined by protein interactions and function. Signals initiated by neurotransmitter receptors are integrated by these complexes and their constituent enzymes to orchestrate multiple downstream cellular changes, including transcriptional regulation of genes at the nucleus. Genome wide transcriptome studies are beginning to map the sets of genes regulated by the synapse proteome. Conversely, understanding the transcriptional regulation of genes encoding the synapse proteome will shed light on synapse formation. Mutations that disrupt synapse signalling complexes result in cognitive impairments in mice and humans, and recent evidence indicates that these mutation change gene expression profiles. We discuss the need for global approaches combining genetics, transcriptomics and proteomics in order to understand cognitive function and disruption in diseases.

Animals↗
PubMed2001

Bacterial cell cycle: seeing the big picture with microarrays.

Global assays of gene expression and protein stability during the Caulobacter crescentus cell cycle reveal that a surprisingly large fraction of the genome and proteome is affected as cells grow and divide. These studies are an important step toward understanding how the cell cycle is controlled in prokaryotes.

Bacterial Proteins↗
PubMedDate not supplied

Molecular genetic tumor markers in non-small cell lung cancer.

Not only serum tumor markers, such as carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC) and carbohydrate antigen (CA) 125, but also serum growth factors have been examined to evaluate tumor stages and to predict the recurrence and metastasis in patients with non-small cell lung cancer (NSCLC) (1-5). In recent years, the analysis of the genome and proteome has advanced remarkably. An array of molecular genetic tumor markers (MGTMs) have been identified based on the biological characterization of tumors, such as tumor development, growth, invasion and metastasis. Molecular genetic tumor marker research has also entered a new era, since comprehensive gene profile analysis using cDNA microarrays and comprehensive protein expression analysis using proteomics technology have been developed. On the other hand, the frequency of lung cancer patients with which various tumor markers are associated is increasing in Japan (6-8). This paper reviews MGTMs characteristic of lung cancer and clarifies the clinical usefulness and applications of MGTM for cancer treatment.

Biomarkers, Tumor↗
PubMed2006

Quantitative proteomic analysis of post-translational modifications of human histones.

Histone proteins are subject to a range of post-transcriptional modifications in living cells. The combinatorial nature of these modifications constitutes the "histone code" that dictates chromatin structure and function during development, growth, differentiation, and homeostasis of cells. Deciphering of the histone code is hampered by the lack of analytical methods for monitoring the combinatorial complexity of reversible multisite modifications of histones, including acetylation and methylation. To address this problem, we used LC-MSMS technology and Virtual Expert Mass Spectrometrist software for qualitative and quantitative proteomic analysis of histones extracted from human small cell lung cancer cells. A total of 32 acetylations, methylations, and ubiquitinations were located in the human histones H2A, H2B, H3, and H4, including seven novel modifications. An LC-MSMS-based method was applied in a quantitative proteomic study of the dose-response effect of the histone deacetylase inhibitor (HDACi) PXD101 on histone acetylation in human cell cultures. Triplicate LC-MSMS runs at six different HDACi concentrations demonstrated that PXD101 affects acetylation of histones H2A, H2B, H3, and H4 in a site-specific and dose-dependent manner. This unbiased analysis revealed that a relative increase in acetylated peptide from the histone variants H2A, H2B, and H4 was accompanied by a relative decrease of dimethylated Lys(57) from histone H2B. The dose-response results obtained by quantitative proteomics of histones from HDACi-treated cells were consistent with Western blot analysis of histone acetylation, cytotoxicity, and dose-dependent expression profiles of p21 and cyclin A2. This demonstrates that mass spectrometry-based quantitative proteomic analysis of post-translational modifications is a viable approach for functional analysis of candidate drugs, such as HDAC inhibitors.

Acetylation↗
PubMed2006

Comparative two-dimensional gel electrophoresis maps for promastigotes of Leishmania amazonensis and Leishmania major.

The outcome of Leishmania infections is determined by both the parasite species and the host genetic makeup. While much has been learned regarding immune responses to this parasite, our knowledge on parasite-derived factors is limited. The recent completion of the L. major and L. infantum genome sequence projects and concurrent advancement in proteomics technology would greatly accelerate the search for novel Leishmania proteins. Using a proteomics-based approach to study species-specific Leishmania proteins, we developed high-resolution, broad pH (3-10) two-dimensional gel electrophoresis (2-DE) separations to determine protein-expression profiles between highly infectious forms of the parasitic species L. amazonensis (New World) and L. major (Old World). Approximately 1,650 and 1,530 distinct protein spots were detected in the L. amazonensis and L. major gels, respectively. While a vast majority of the spots had similar distribution and intensity, a few were computationally defined as preferentially expressed in L. amazonensis in comparison to L. major, or vice versa. These data attest to the feasibility of establishing a 2-DE-based protein array for inter-species profiling of Leishmania proteins and provide the framework for future design of proteome studies of Leishmania.

Animals↗
PubMed2004

Carcinoma and stromal enzyme activity profiles associated with breast tumor growth in vivo.

Cancer research depends on the use of human cell lines for both the in vitro (culture) and in vivo (xenograft) analysis of tumor progression and treatment. However, the extent to which cultured preparations of human cancer lines display similar properties in vivo, where important host factors may influence tumor biology, remains unclear. Here, we address this question by conducting a functional proteomic analysis of the human breast cancer line MDA-MB-231 grown in culture and as orthotopic xenograft tumors in the mammary fad pad of immunodeficient mice. Using a suite of activity-based chemical probes, we identified carcinoma (human) enzyme activities that were expressed selectively in culture or in xenograft tumors. Likewise, distinct groups of stromal (mouse) enzyme activities were found that either infiltrated or were excluded from xenograft tumors, indicating a contribution by specific host components to breast cancer development. MDA-MB-231 cells isolated from tumors exhibited profound differences in their enzyme activity profiles compared with the parent cell line, including the dramatic posttranscriptional up-regulation of the serine proteases urokinase plasminogen activator and tissue plasminogen activator and down-regulation of the glycolytic enzyme phosphofructokinase. These altered enzyme activity profiles correlated with significantly greater tumor growth rates and metastases for xenograft-derived MDA-MB-231 cells upon reintroduction into mice. Collectively, these data indicate that the in vivo environment of the mouse mammary fat pad cultivates the growth of human breast cancer cells with elevated tumorigenic properties and highlight the value of activity-based protein profiling for identifying proteomic signatures that depict such changes in cancer cell biology.

Amino Acid Sequence↗
PubMed2004

Prediction of protein subcellular locations using fuzzy k-NN method.

MOTIVATION: Protein localization data are a valuable information resource helpful in elucidating protein functions. It is highly desirable to predict a protein's subcellular locations automatically from its sequence. RESULTS: In this paper, fuzzy k-nearest neighbors (k-NN) algorithm has been introduced to predict proteins' subcellular locations from their dipeptide composition. The prediction is performed with a new data set derived from version 41.0 SWISS-PROT databank, the overall predictive accuracy about 80% has been achieved in a jackknife test. The result demonstrates the applicability of this relative simple method and possible improvement of prediction accuracy for the protein subcellular locations. We also applied this method to annotate six entirely sequenced proteomes, namely Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Oryza sativa, Arabidopsis thaliana and a subset of all human proteins. AVAILABILITY: Supplementary information and subcellular location annotations for eukaryotes are available at http://166.111.30.65/hying/fuzzy_loc.htm

Algorithms↗
PubMed2005

Proteome analysis of serovars Typhimurium and Pullorum of Salmonella enterica subspecies I.

BACKGROUND: Salmonella enterica subspecies I includes several closely related serovars which differ in host ranges and ability to cause disease. The basis for the diversity in host range and pathogenic potential of the serovars is not well understood, and it is not known how host-restricted variants appeared and what factors were lost or acquired during adaptations to a specific environment. Differences apparent from the genomic data do not necessarily correspond to functional proteins and more importantly differential regulation of otherwise identical gene content may play a role in the diverse phenotypes of the serovars of Salmonella. RESULTS: In this study a comparative analysis of the cytosolic proteins of serovars Typhimurium and Pullorum was performed using two-dimensional gel electrophoresis and the proteins of interest were identified using mass spectrometry. An annotated reference map was created for serovar Typhimurium containing 233 entries, which included many metabolic enzymes, ribosomal proteins, chaperones and many other proteins characteristic for the growing cell. The comparative analysis of the two serovars revealed a high degree of variation amongst isolates obtained from different sources and, in some cases, the variation was greater between isolates of the same serovar than between isolates with different sero-specificity. However, several serovar-specific proteins, including intermediates in sulphate utilisation and cysteine synthesis, were also found despite the fact that the genes encoding those proteins are present in the genomes of both serovars. CONCLUSION: Current microbial proteomics are generally based on the use of a single reference or type strain of a species. This study has shown the importance of incorporating a large number of strains of a species, as the diversity of the proteome in the microbial population appears to be significantly greater than expected. The characterisation of a diverse selection of strains revealed parts of the proteome of S. enterica that alter their expression while others remain stable and allowed for the identification of serovar-specific factors that have so far remained undetected by other methods.

Bacterial Proteins↗