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PubMed2006

Performance characteristics of colorimetric protein microarrays compared to ELISA.

Miniaturization and multiplexing are two areas that need improvement in immunoassays. However, it is unclear how associated changes in size, substrate, binding capacity, protein concentration, and other parameters affect sensitivity and quantitative range. In the study here we compared a new protein microarray substrate and system (Zeta-Grip, Miragene Inc., Anaheim, CA) with enzyme-linked immunosorbent assay (ELISA) for the application of immunoassays. We found that the protein microarray system performed better than ELISA in both sensitivity and quantitative range for use in immunoassay.

Colorimetry↗

PubMed2003

CGH-Plotter: MATLAB toolbox for CGH-data analysis.

CGH-Plotter is a MATLAB toolbox with a graphical user interface for the analysis of comparative genomic hybridization (CGH) microarray data. CGH-Plotter provides a tool for rapid visualization of CGH-data according to the locations of the genes along the genome. In addition, the CGH-Plotter identifies regions of amplifications and deletions, using k-means clustering and dynamic programming. The application offers a convenient way to analyze CGH-data and can also be applied for the analysis of cDNA microarray expression data. CGH-Plotter toolbox is platform independent and requires MATLAB 6.1 or higher to operate.

Cluster Analysis↗

PubMed2005

stam--a Bioconductor compliant R package for structured analysis of microarray data.

BACKGROUND: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles. The definition of novel subclasses based on gene expression is a difficult problem not addressed systematically by currently available software tools. RESULTS: We present a computational tool for semi-supervised molecular disease entity detection. It automatically discovers molecular heterogeneities in phenotypically defined disease entities and suggests alternative molecular sub-entities of clinical phenotypes. This is done using both gene expression data and functional gene annotations. We provide stam, a Bioconductor compliant software package for the statistical programming environment R. We demonstrate that our tool detects gene expression patterns, which are characteristic for only a subset of patients from an established disease entity. We call such expression patterns molecular symptoms. Furthermore, stam finds novel sub-group stratifications of patients according to the absence or presence of molecular symptoms. CONCLUSION: Our software is easy to install and can be applied to a wide range of datasets. It provides the potential to reveal so far indistinguishable patient sub-groups of clinical relevance.

Calibration↗

PubMed2005

Understanding signal transduction through functional proteomics.

The study of signal transduction provides fundamental information regarding the regulation of all biologic processes that support the normal function of life. Functional proteomics, a rapidly emerging discipline that aims to understand the expression, function and regulation of the entire set of proteins in a given cell type, tissue or organism, offers unprecedented opportunity for signal transduction research in terms of understanding cellular behavior and regulation at the systems level. Indeed, swift progress in the area of proteomics has demonstrated the major impact of proteomic approaches on signal transduction and biomedical research. In this review, recent and innovative applications of functional proteomics in determining changes in protein contents, modifications, activities and interactions underpinning signaling transduction pathways are discussed.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2006

[Preliminary study of serum proteome biomarkers of hypopharyngeal squamous cell carcinoma].

OBJECTIVE: To screen the serum proteome biomarkers of hypopharyngeal squamous cell carcinoma (HSCC) and to establish a predictive model for early detection of HSCC. METHODS: Serum samples were collected from 48 HSCC patients before surgery and 52 age and sex-matched individuals without cancer used as controls. The samples were divided into 2 sets: training set (including 36 HSCC patients and 36 controls) and blind testing set (including 12 HSCC patients and 16 controls). With WCX2 and IMAC3 protein chips, surface-enhanced laser desorption/ionization (SELDI) was used to analyze the serum protein profiling. 72 samples of the training set were analyzed by a decision tree algorithm to be able to differentiate HSCC patients from controls. Double-blind test was used to determine the sensitivity and specificity of the classification model. RESULTS: Ranging from 2000 - 50000 (M/Z), 11 potential biomarkers on WCX2 and 19 biomarkers on IMAC3 protein chip could differentiate HSCC patients from the control set (P < 10(-5)). Among them 4 candidate protein peaks with the m/z values of 7796, 4216, 5927, and 5361 were selected to be used to establish a predictive model by Biomarker Pattern Software. The model separated effectively the HSCC samples from the control samples, achieving a sensitivity of 94.44%, and a specificity of 88.89%. An accuracy of 85.71% (24/28), sensitivity of 91.67% (11/12), specificity of 81.25% (13/16), positive predictive value of 78.57%% (11/14), and negative predictive value of 92.85% (13/14) were validated in the double-blind testing set. CONCLUSION: The SELDI-TOF-MS Protein Chip combined with artificial intelligence classification algorithm helps find serum proteome biomarkers and establish predictive model for early diagnosis of HSCC. This technique has potential for the development of a screening test for the detection of HSCC.

Adult↗

PubMed2003

Approaches to proteomic analysis of human tumors.

The completion of the Human Genome Project and the successful use of high-throughput array formats for mRNA measurements has spurred a revival of interest in the field of proteomics. Clinical cancer specimens will be a critical component of proteomic studies of cancer, both for discovering new insights into TSG function, and for validation of discoveries that are made in the laboratory. Global protein analysis methods hold great potential for facilitating the discovery of novel tumor suppressor genes, as well as providing a better understanding of the biochemical role of these proteins.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2002

Design of buffer exchange surfaces and sensor chips for biosensor chip mass spectrometry.

The feasibility of buffer exchange in biosensor chip mass spectrometry, along with the construction of base sensor chips and use of alternative chip chemistries, is demonstrated in this work. Beta-2-microglobulin (beta2m) was used as an analyte and captured in the first flow cell (FC1) on the sensor chip surface by an immobilized anti-beta2m antibody. Low pH buffer was then used to elute the captured analyte from the flow cell and route it to a second flow cell (FC2) downstream that served as a cation exchanger that retains the analyte. Following additional washes in FC1, the analyte present in FC2 was either eluted with a higher pH buffer (to demonstrate the possibility of elution into a downstream trypsin flow cell), or it was subjected to matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry analysis to verify its presence in FC2. In a separate experiment, a gold-sputtered glass slide (base chip) was activated through a formation of 11-mercaptoundecanoic acid self-assembled monolayer and via reaction with 1,1"-carbonyldiimidazole. The activated chip was placed manually into the biosensor and two surfaces (flow cells) were derivatized with antibodies to beta2m and cystatin C (cysC). To evaluate the chip performance, diluted human urine aliquot was injected over the flow cells. Following the surface plasmon resonance analysis, the chip was MALDI-TOF MS analyzed, yielding signals from beta2m and cysC from their respective flow cells. Artifacts arising from the surface chemistries were not observed in the analysis.

Buffers↗

PubMed2005

Proteomic approaches in colon cancer: promising tools for new cancer markers and drug target discovery.

Novel technologies are needed from which to identify new and more efficient biomarkers and improved molecular targets for the expedient and accurate diagnosis and treatment of colorectal cancer. Many advances have been made in direct and virtual imaging for detection of polyps and malignant-type lesions. These require tissue verification before definitive intervention. Inclusion of a simple serum test, more accurate than CEA, especially for early cancer detection, would make virtual imaging much more successful. Proteomics, the study of the proteins and protein pathways involved in disease, is a new dimension in preclinical and clinical development. Mass spectrometric analysis of serum proteins has been shown to be a fast and simple approach yielding a large datastream of information to mine for biomarker patterns. Preliminary studies in a variety of cancers has shown this to be a promising direction. Protein arrays of tumor lysates allows assessment of expression and activation of proteins that may be specific colorectal cancer targets or targets that are shown to be universally important in cancer, such as those proteins involved in angiogenesis. Small quantities of tumor are needed for this technique and allow direct analysis of the biochemical events ongoing in the tumor and/or the stroma. This provides insight into the biology of the disease and can be used to identify targets for therapeutic intervention as well as to monitor the ability to successfully attack those targets. Together, these 2 technologies have been shown to advance the field and may be important new steps in diagnosis, prognosis, and treatment of colorectal cancer.

Biomarkers, Tumor↗

PubMed2006

Use of protein chip mass spectrometry to monitor biotinylation reactions.

Surface-enhanced laser desorption/ionization time-of-flight analysis was used to monitor both the kinetics and heterogeneity of product formation during the biotinylation of a number of model proteins and peptide targets. The selected molecules were the IgG-binding protein, protein A, human serum albumin, and a synthetic peptide corresponding to the N terminus of a streptococcal M1 protein. The extent of biotinylation was determined by kinetic analysis of the shift in molecular mass from the native material. Each residue modified by reaction with N-hydroxysuccinimide biotin resulted in an addition of approximately 341 amu to the native protein or polypeptide. The novelty of the method was in the ability to determine the molecular mass shift, without first separating the targeted molecule from the biotinylating reagent. The analysis was rapid, simple, and provided information on the average number of biotin molecules added and the homogeneity of the resulting product.

Antigens, Bacterial↗

PubMed2005

Identification of biomarkers for breast cancer in nipple aspiration and ductal lavage fluid.

PURPOSE: To establish a comprehensive proteomic approach for biomarker discovery and validation in breast fluid. EXPERIMENTAL DESIGN: A total of 95 specimens from three institutions were used including 10 nipple aspiration fluid (5 stage I/II cancerous breasts and 5 age-matched healthy controls), 42 ductal lavage fluid from 14 patients with unilateral stage I/II cancer (25 from 9 cancerous breasts and 17 from 7 contralateral breasts), and 42 ductal lavage fluid from 14 high-risk women (multiple ducts repeated lavage). Differentially expressed protein/peptides were discovered by proteomic analysis of training sample, using ProteinChip arrays and surface-enhanced laser desorption ionization (SELDI) time-of-flight mass spectrometry, and validated on independently collected testing samples. After protein identification, ELISA was done to confirm the SELDI findings. RESULTS: We were able to obtain reproducible protein profiles using minimal amount of protein (1 mug) by applying an optimized chip protocol and SELDI. We were able to select cancer-associated biomarkers despite large individual variability by applying both unsupervised and supervised cluster analysis. Furthermore, we were able to train and test candidate biomarkers on independently collected samples and identified one component of a multimarker panel as human neutrophil peptides 1 to 3. CONCLUSIONS: Breast fluid is a rich source of breast cancer biomarkers. In combination with high-throughput novel proteomic profiling technology and multicenter study design, markers that are highly specific to breast cancer can be discovered and validated. Our observations also suggest that persistent elevation of human neutrophil peptide in high-risk women may imply early onset of cancer not yet detectable by current detection method. Proof of this hypothesis requires follow-up on a larger study population.

Adenocarcinoma↗

PubMed2003

Electrochemiluminescent biosensors array for the concomitant detection of choline, glucose, glutamate, lactate, lysine and urate.

A multifunctional bio-sensing chip was designed based on the electrochemiluminescent (ECL) detection of enzymatically produced hydrogen peroxide. Six different oxidases specific for choline, glucose, glutamate, lactate, lysine and urate were non-covalently immobilised on imidodiacetic acid chelating beads (glucose oxidase only) or on diethylaminoethyl (DEAE) anion exchanger beads, and spotted on the surface of a glassy carbon foil (25 mm(2) square), entrapped in PVA-SbQ photopolymer. The chip measurement was achieved by applying during 3 min a +850 mV potential between the glassy carbon electrode and a platinum pseudo-reference, while capturing a numeric image of the multifunctional bio-sensing chip with a CCD camera. The use of luminol supporting beads (DEAE-Sepharose) included in the sensing layer was shown to enable the achievement of spatially well defined signals, and to solve the hydrogen peroxide parasite signal which appeared between contiguous spots using luminol free in solution. The detection limits of the different biosensor were found to be 1 microM for glutamate, lysine and uric acid, 20 microM for glucose and 2 microM for choline and lactate. The detection ranges were 1-25 microM (uric acid), 1 microM-0.5 mM (glutamate and lysine), 20 microM-2 mM (glucose) and 2 microM-0.2 mM (choline and lactate). The ECL chip was used for the detection of glucose, lactate and uric acid in human serum matrix. Good correlations between measured and expected values were found without the need of internal calibration of the sample, demonstrating the potentiality of the ECL multifunctional bio-sensing chip.

Biosensing Techniques↗

PubMed2005

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.

OBJECTIVE: To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. METHODS: A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps. RESULTS: The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8. CONCLUSION: SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Adult↗

PubMed2004

Kinome profiling for studying lipopolysaccharide signal transduction in human peripheral blood mononuclear cells.

The DNA array technique allows comprehensive analysis of the genome and transcriptome, but the high throughput array-based assessment of intracellular signal transduction remains troublesome. The goal of this study was to test a new peptide array technology for studying the activity of all kinases of whole cell lysates, the kinome. Cell lysates from human peripheral blood mononuclear cells before and after stimulation with lipopolysaccharide were used for in vitro phosphorylation with [gamma-33P]ATP arrays consisting of 192 peptides (substrates for kinases) spotted on glass. The usefulness of peptide arrays for studying signal transduction was demonstrated by the generation of the first comprehensive description of the temporal kinetics of phosphorylation events induced by lipopolysaccharide stimulation. Furthermore analysis of the signals obtained suggested activation of p21Ras by lipopolysaccharide, and this was confirmed by direct measurement of p21Ras GTP levels in lipopolysaccharide-stimulated human peripheral blood mononuclear cells, which represents the first direct demonstration of p21Ras activation by stimulation of a Toll receptor family member. Further confidence in the usefulness of peptide array technology for studying signal transduction came from Western blot analysis of lipopolysaccharide-stimulated cells, which corroborated the signals obtained using peptide arrays as well as from the demonstration that kinase inhibitors effected peptide array phosphorylation patterns consistent with the expected action of these inhibitors. We conclude that this first metabolic array is a useful method to determine the enzymatic activities of a large group of kinases, offering high throughput analysis of cellular metabolism and signal transduction.

Amino Acid Sequence↗

PubMed2003

Protein arrays for autoantibody profiling and fine-specificity mapping.

Protein arrays provide a powerful approach to study autoimmune disease. Autoimmune responses activate B cells to produce autoantibodies that recognize self-molecules termed autoantigens, many of which are proteins or protein complexes. Protein arrays enable profiling of the specificity of autoantibody responses against panels of peptides and proteins representing known autoantigens as well as candidate autoantigens. In addition to identifying autoantigens and mapping immunodominant epitopes, proteomic analysis of autoantibody responses will further enable diagnosis, prognosis, and tailoring of antigen-specific tolerizing therapy.

Animals↗

PubMed2004

Protein profiling and identification of modulators regulated by the E7 oncogene in the C33A cell line by proteomics and genomics.

Human papillomaviruses (HPVs) have been recognized as the primary cause of cervical cancer. HPV 16 E7 binds to tumor suppressor retinoblastoma protein, and interferes with its function, causing release of the transcription factor E2F, which influences expression of cell cycle-related genes. This study was performed to identify the genes and proteins modulated by the HPV E7 oncogene. An HPV-negative cervical cancer cell line (C33A) was prepared to establish a stable cell line expressing E7. In order to analyze the target molecules modulated by E7 expression, we used two approaches: matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) and DNA microarrays. Forty-seven spots were identified in C33A/E7 by two-dimensional electrophoresis and MALDI/TOF MS. Protein disulfide isomerase A3, integrase interactor 1 protein, growth inhibitory protein, glutathione S-transferase P, and vav proto-oncogene were down-regulated, whereas heat shock 60 kDa protein 1, Ku70 binding protein, alpha enolase, 26S proteasome subunit were up-regulated. A genomic approach using a microarray kit showed that IL-12R beta 1, cytochrome c, and tumor necrosis factor receptor II were induced by the E7 oncogene. These results suggest that E7 can evade immune surveillance by suppressing or inducing these cell signaling factors, cell cycle regulators, and chaperones.

Cell Cycle Proteins↗

PubMed2005

Albumin depletion of human plasma also removes low abundance proteins including the cytokines.

The use of proteomics for efficient, accurate, and complete analysis of clinical samples poses a variety of technical challenges. The presence of higher abundance proteins in the plasma, such as albumin, may mask the detection of lower abundance proteins such as the cytokines. Methods have been proposed to deplete the sample of these higher abundance proteins to facilitate detection of those with lower abundance. In this study, a commercially available albumin depletion kit was used to determine if removal of albumin would measurably reduce detection of lower abundance cytokine proteins in human plasma. The Montage Albumin Deplete Kit (Millipore) was used to deplete albumin from LPS-stimulated whole blood from 15 normal human donors. Albumin depletion was measured using the BCG reagent and SDS-PAGE, and cytokine recovery was determined by a microassay immunoassay that measures both pro- and anti-inflammatory cytokines. Average albumin depletion from the samples was 72%. However, several cytokines were also significantly reduced when the albumin was removed from the plasma. Additionally, there was a variable reduction in cytokine recovery from a known mixture of cytokines in a minimal amount of plasma that were loaded onto the columns. These data demonstrate that there may be a non-specific loss of cytokines following albumin depletion, which may confound subsequent proteomic analysis.

Cytokines↗

PubMed2005

Parallel detection and quantification using nine immunoassays in a protein microarray for drug from serum samples.

A protein microarray system for detection and quantification of nine prohibited drugs in serum is described. Chemically modified slides were chosen as the microarray substrates because of their suitable for drug-BSA printing. The developed protein microarray was able to preserve the biological function of the haptens, when immobilized on the microarray surface and demonstrated binding with their corresponding antibodies. The microarray could also be used for quantitative analysis when mouse IgG was chosen as an internal control for data processing. There was no qualitative difference between the results obtained using the protein microarray and ELISA. The protein microarray technology should be applicable to performing, simultaneously, large scale screening tests for many different analytes in serum.

Blood Chemical Analysis↗

PubMed2005

The TOR and EGO protein complexes orchestrate microautophagy in yeast.

The rapamycin-sensitive TOR signaling pathway in Saccharomyces cerevisiae positively controls cell growth in response to nutrient availability. Accordingly, TOR depletion or rapamycin treatment causes regulated entry of cells into a quiescent growth phase. Although this process has been elucidated in considerable detail, the transition from quiescence back to proliferation is poorly understood. Here, we describe the identification of a conserved member of the RagA subfamily of Ras-related GTPases, Gtr2, which acts in a vacuolar membrane-associated protein complex together with Ego1 and Ego3 to ensure proper exit from rapamycin-induced growth arrest. We demonstrate that the EGO complex, in conjunction with TOR, positively regulates microautophagy, thus counterbalancing the massive rapamycin-induced, macroautophagy-mediated membrane influx toward the vacuolar membrane. Moreover, large-scale genetic analyses of the EGO complex confirm the existence of a growth control mechanism originating at the vacuolar membrane and pinpoint the amino acid glutamine as a key metabolite in TOR signaling.

Antifungal Agents↗