Biomedical subjects

Brian B Haab

Publications and source records attributed to Brian B Haab.

At least 19 recordsLinked to original sources

PubMed2007

Antibody array profiling reveals serum TSP-1 as a marker to distinguish benign from malignant prostatic disease.

BACKGROUND: Blood protein markers that provide more accurate or earlier diagnosis of prostate cancer should have a positive impact on prostate cancer treatment and management. METHODS: Serum samples from control subjects and patients with benign or malignant prostatic disease were analyzed on antibody arrays targeting multiple candidate prostate cancer markers and detected with two-color, rolling-circle amplification (TC-RCA). The measurements of certain antibodies were validated using immunoblots, immunoprecipitation/mass spectrometry, and sandwich immunoassays. RESULTS: Several potential disease-associated protein alterations were uncovered. The most significant was thrombospondin-1, which was strongly elevated in patients with benign prostatic disease and repressed in patients with prostate cancer. Thrombospondin-1 levels did not correlate with prostate-specific antigen (PSA) levels and differentiated benign from malignant disease with 79% sensitivity and 81% specificity. CONCLUSIONS: The measurement of thrombospondin-1 could be used to assist the decision to obtain a biopsy in men with suspected prostate cancer, which could lead to a reduction in the number of unnecessary prostatic biopsies.

Adult↗

PubMed2006

A reagent resource to identify proteins and peptides of interest for the cancer community: a workshop report.

On the basis of discussions with representatives from all sectors of the cancer research community, the National Cancer Institute (NCI) recognizes the immense opportunities to apply proteomics technologies to further cancer research. Validated and well characterized affinity capture reagents (e.g. antibodies, aptamers, and affibodies) will play a key role in proteomics research platforms for the prevention, early detection, treatment, and monitoring of cancer. To discuss ways to develop new resources and optimize current opportunities in this area, the NCI convened the "Proteomic Technologies Reagents Resource Workshop" in Chicago, IL on December 12-13, 2005. The workshop brought together leading scientists in proteomics research to discuss model systems for evaluating and delivering resources for reagents to support MS and affinity capture platforms. Speakers discussed issues and identified action items related to an overall vision for and proposed models for a shared proteomics reagents resource, applications of affinity capture methods in cancer research, quality control and validation of affinity capture reagents, considerations for target selection, and construction of a reagents database. The meeting also featured presentations and discussion from leading private sector investigators on state-of-the-art technologies and capabilities to meet the user community's needs. This workshop was developed as a component of the NCI's Clinical Proteomics Technologies Initiative for Cancer, a coordinated initiative that includes the establishment of reagent resources for the scientific community. This workshop report explores various approaches to develop a framework that will most effectively fulfill the needs of the NCI and the cancer research community.

Biomedical Research↗

PubMed2006

Applications of antibody array platforms.

Antibody arrays are valuable for the parallel analysis of multiple proteins in small sample volumes. The earliest and most widely used application of antibody arrays has been to measure multiple protein abundances, using sandwich assays and label-based assays, for biomarker discovery and biological studies. Modifications to these assays have led to studies profiling specific protein post-translational modifications. Additional novel uses include profiling enzyme activities and protein cell-surface expression. Finally, array-based antibody platforms are being used to assist the development and characterization of antibodies. Continued progress in the technology will surely lead to extensions of these applications and the development of new ways of using the methods.

Animals↗

PubMed2006

Mass spectrometry-based study of the plasma proteome in a mouse intestinal tumor model.

Early detection of cancer can greatly improve prognosis. Identification of proteins or peptides in the circulation, at different stages of cancer, would greatly enhance treatment decisions. Mass spectrometry (MS) is emerging as a powerful tool to identify proteins from complex mixtures such as plasma that may help identify novel sets of markers that may be associated with the presence of tumors. To examine this feature we have used a genetically modified mouse model, Apc(Min), which develops intestinal tumors with 100% penetrance. Utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified total plasma proteome (TPP) and plasma glycoproteome (PGP) profiles in tumor-bearing mice. Principal component analysis (PCA) and agglomerative hierarchial clustering analysis revealed that these protein profiles can be used to distinguish between tumor-bearing Apc(Min) and wild-type control mice. Leave-one-out cross-validation analysis established that global TPP and global PGP profiles can be used to correctly predict tumor-bearing animals in 17/19 (89%) and 19/19 (100%) of cases, respectively. Furthermore, leave-one-out cross-validation analysis confirmed that the significant differentially expressed proteins from both the TPP and the PGP were able to correctly predict tumor-bearing animals in 19/19 (100%) of cases. A subset of these proteins was independently validated by antibody microarrays using detection by two color rolling circle amplification (TC-RCA). Analysis of the significant differentially expressed proteins indicated that some might derive from the stroma or the host response. These studies suggest that mass spectrometry-based approaches to examine the plasma proteome may prove to be a valuable method for determining the presence of intestinal tumors.

Animals↗

PubMed2006

RCA-enhanced protein detection arrays.

There are many instances in which it is desirable to generate profiles of the relative abundance of a multiplicity of protein species. Examples include studies in embryonic development, immunobiology, drug responses, cancer biology, biomarkers, and so on. Microarray formats provide a convenient, high-throughput vehicle for generating such profiles, and the repertoire of proteins that can be measured is growing continuously as larger panels of specific antibodies become available. Here we describe methods for the use of antibody microarrays, whereby the detection of specifically bound antigens is enhanced by rolling circle amplification (RCA). RCA-enhanced protein detection on antibody microarrays provides a means for rapid protein profiling at high sensitivity. The set of RCA reagents remains unchanged for different microarray formats and compositions, and signal readout is performed using standard fluorescent dyes and scanners. The method is sensitive enough for the most challenging applications, such as the detection of low-abundance components of human serum.

Animals↗

PubMed2006

Profiling bladder cancer using targeted antibody arrays.

Bladder cancer is a common malignancy requiring a high degree of surveillance because of the frequent recurrences and the poor clinical outcome of invasive disease. To date, serum biomarkers for bladder cancer lack optimal sensitivity and specificity to assist in diagnosis and disease categorization. Here, we designed antibody arrays for bladder cancer by selecting antibodies against targets differentially expressed in bladder tumors. Serum protein profiles measured by an antibody array containing 254 antibodies discriminated bladder cancer patients from controls (n = 95) with a correct classification rate of 93.7%. A second independent antibody array containing 144 antibodies revealed that protein profiles provide predictive information by stratifying patients with bladder tumors (n = 37) based on their overall survival (P = 0.0479). In addition, serum proteins, such as c-met, that were top ranked at identifying bladder cancer patients were associated with pathological stage, tumor grade, and survival when validated by immunohistochemistry of tissue microarrays containing bladder tumors (n = 173). This study provides experimental evidence for the use of several integrated technologies strengthening the process of biomarker discovery. Serum protein profiles obtained by antibody arrays represent comprehensive means for bladder cancer diagnosis and clinical outcome stratification, which could potentially assist in selection of cancer patients who would benefit from early, individualized therapeutic intervention.

Adult↗

PubMed2005

Antibody microarray profiling reveals individual and combined serum proteins associated with pancreatic cancer.

We used antibody microarrays to probe the associations of multiple serum proteins with pancreatic cancer and to explore the use of combined measurements for sample classification. Serum samples from pancreatic cancer patients (n = 61), patients with benign pancreatic disease (n = 31), and healthy control subjects (n = 50) were probed in replicate experiment sets by two-color, rolling circle amplification on microarrays containing 92 antibodies and control proteins. The antibodies that had reproducibly different binding levels between the patient classes revealed different types of alterations, reflecting inflammation (high C-reactive protein, alpha-1-antitrypsin, and serum amyloid A), immune response (high IgA), leakage of cell breakdown products (low plasma gelsolin), and possibly altered vitamin K usage or glucose regulation (high protein-induced vitamin K antagonist-II). The accuracy of the most significant antibody microarray measurements was confirmed through immunoblot and antigen dilution experiments. A logistic-regression algorithm distinguished the cancer samples from the healthy control samples with a 90% and 93% sensitivity and a 90% and 94% specificity in duplicate experiment sets. The cancer samples were distinguished from the benign disease samples with a 95% and 92% sensitivity and an 88% and 74% specificity in duplicate experiment sets. The classification accuracies were significantly improved over those achieved using individual antibodies. This study furthered the development of antibody microarrays for molecular profiling, provided insights into the nature of serum-protein alterations in pancreatic cancer patients, and showed the potential of combined measurements to improve sample classification accuracy.

Adenocarcinoma↗

PubMed2005

Distinctive serum protein profiles involving abundant proteins in lung cancer patients based upon antibody microarray analysis.

BACKGROUND: Cancer serum protein profiling by mass spectrometry has uncovered mass profiles that are potentially diagnostic for several common types of cancer. However, direct mass spectrometric profiling has a limited dynamic range and difficulties in providing the identification of the distinctive proteins. We hypothesized that distinctive profiles may result from the differential expression of relatively abundant serum proteins associated with the host response. METHODS: Eighty-four antibodies, targeting a wide range of serum proteins, were spotted onto nitrocellulose-coated microscope slides. The abundances of the corresponding proteins were measured in 80 serum samples, from 24 newly diagnosed subjects with lung cancer, 24 healthy controls, and 32 subjects with chronic obstructive pulmonary disease (COPD). Two-color rolling-circle amplification was used to measure protein abundance. RESULTS: Seven of the 84 antibodies gave a significant difference (p < 0.01) for the lung cancer patients as compared to healthy controls, as well as compared to COPD patients. Proteins that exhibited higher abundances in the lung cancer samples relative to the control samples included C-reactive protein (CRP; a 13.3 fold increase), serum amyloid A (SAA; a 2.0 fold increase), mucin 1 and alpha-1-antitrypsin (1.4 fold increases). The increased expression levels of CRP and SAA were validated by Western blot analysis. Leave-one-out cross-validation was used to construct Diagonal Linear Discriminant Analysis (DLDA) classifiers. At a cutoff where all 56 of the non-tumor samples were correctly classified, 15/24 lung tumor patient sera were correctly classified. CONCLUSION: Our results suggest that a distinctive serum protein profile involving abundant proteins may be observed in lung cancer patients relative to healthy subjects or patients with chronic disease and may have utility as part of strategies for detecting lung cancer.

Antibodies↗

PubMed2005

Optimized normalization for antibody microarrays and application to serum-protein profiling.

The measurements of coordinated patterns of protein abundance using antibody microarrays could be used to gain insight into disease biology and to probe the use of combinations of proteins for disease classification. The correct use and interpretation of antibody microarray data requires proper normalization of the data, which has not yet been systematically studied. Therefore we undertook a study to determine the optimal normalization of data from antibody microarray profiling of proteins in human serum specimens. Forty-three serum samples collected from patients with pancreatic cancer and from control subjects were probed in triplicate on microarrays containing 48 different antibodies, using a direct labeling, two-color comparative fluorescence detection format. Seven different normalization methods representing major classes of normalization for antibody microarray data were compared by their effects on reproducibility, accuracy, and trends in the data set. Normalization with ELISA-determined concentrations of IgM resulted in the most accurate, reproducible, and reliable data. The other normalization methods were deficient in at least one of the criteria. Multiparametric classification of the samples based on the combined measurement of seven of the proteins demonstrated the potential for increased classification accuracy compared with the use of individual measurements. This study establishes reliable normalization for antibody microarray data, criteria for assessing normalization performance, and the capability of antibody microarrays for serum-protein profiling and multiparametric sample classification.

Adenocarcinoma↗

PubMed2005

Methods of comparative proteomic profiling for disease diagnostics.

The recent development of numerous technologies for proteome analysis holds the promise of new and more precise methods for disease diagnosis. In this review, we provide an overview of some of these technologies including two-dimensional gel electrophoresis (2DE), historically the workhorse of proteomic analysis, as well as some newer approaches such as liquid phase separations combined with mass spectrometry, and protein microarrays. It is evident that each method has its own strengths and weaknesses and no single method will be optimal in all applications. However, the continuing development of innovative strategies for protein separation and analysis is providing a wealth of new tools for multi-dimensional protein profiling that will advance our capabilities in disease diagnostics and our understanding of disease pathology.

Chromatography, Liquid↗

PubMed2005

Antibody arrays in cancer research.

Antibody arrays have valuable applications in cancer research. Many different antibody array technologies have been developed, each with particular advantages, disadvantages, and optimal applications. The methods have been demonstrated on various sample types, such as serum, plasma, and other bodily fluids; cell culture supernatants; tissue culture lysates; and resected tumor specimens. The applications to cancer research have included profiling proteins to identify candidate biomarkers, characterizing signaling pathways, and the measurement of changes in modification or expression level of cancer-related proteins. Further innovations in the methods and experimental strategies are broadening the scope of the applications and the type of information that can be gathered. These alternate formats and uses of antibody arrays include arrays to measure whole cells, arrays to measure enzyme activities, reverse phase arrays, and bead-based arrays. This article reviews the various types of antibody array methods and their applications to cancer research.

Animals↗

PubMed2005

HUPO Plasma Proteome Project specimen collection and handling: towards the standardization of parameters for plasma proteome samples.

There is a substantial list of pre-analytical variables that can alter the analysis of blood-derived samples. We have undertaken studies on some of these issues including choice of sample type, stability during storage, use of protease inhibitors, and clinical standardization. As there is a wide range of sample variables and a broad spectrum of analytical techniques in the HUPO PPP effort, it is not possible to define a single list of pre-analytical standards for samples or their processing. We present here a compendium of observations, drawing on actual results and sound clinical theories and practices. Based on our data, we find that (1) platelet-depleted plasma is preferable to serum for certain peptidomic studies; (2) samples should be aliquoted and stored preferably in liquid nitrogen; (3) the addition of protease inhibitors is recommended, but should be incorporated early and used judiciously, as some form non specific protein adducts and others interfere with peptide studies. Further, (4) the diligent tracking of pre-analytical variables and (5) the use of reference materials for quality control and quality assurance, are recommended. These findings help provide guidance on sample handling issues, with the overall suggestion being to be conscious of all possible pre-analytical variables as a prerequisite of any proteomic study.

Blood Platelets↗

PubMed2005

Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: systematic variation between sample types and calibration of mass spectrometry data.

Four different immunoassay and antibody microarray methods performed at four different sites were used to measure the levels of a broad range of proteins (N = 323 assays; 39, 88, 168, and 28 assays at the respective sites; 237 unique analytes) in the human serum and plasma reference specimens distributed by the Plasma Proteome Project (PPP) of the HUPO. The methods provided a means to (1) assess the level of systematic variation in protein abundances associated with blood preparation methods (serum, citrate-anticoagulated-plasma, EDTA-anticoagulated-plasma, or heparin-anticoagulated-plasma) and (2) evaluate the dependence on concentration of MS-based protein identifications from data sets using the HUPO specimens. Some proteins, particularly cytokines, had highly variable concentrations between the different sample preparations, suggesting specific effects of certain anticoagulants on the stability or availability of these proteins. The linkage of antibody-based measurements from 66 different analytes with the combined MS/MS data from 18 different laboratories showed that protein detection and the quality of MS data increased with analyte concentration. The conclusions from these initial analyses are that the optimal blood preparation method is variable between analytes and that the discovery of blood proteins by MS can be extended to concentrations below the ng/mL range under certain circumstances. Continued developments in antibody-based methods will further advance the scientific goals of the PPP.

Blood Proteins↗

PubMed2005

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Algorithms↗

PubMed2005

Multiplexed protein analysis using antibody microarrays and label-based detection.

This chapter describes methods for the production and use of antibody microarrays. The experimental methods are divided into three sections. The first gives information relating to the preparation and handling of antibodies and the production of microarrays. The second relates to the preparation of the samples, from either blood, tissue, or cell lysates. The third section describes methods for using the samples on antibody microarrays. Two related detection methods are described in which the proteins of a sample to be analyzed are labeled with a tag to allow detection after capture on antibody microarrays.

Antibodies↗

PubMed2004

Oltipraz, 3H-1,2-dithiole-3-thione, and sulforaphane induce overlapping and protective antioxidant responses in murine microglial cells.

Oltipraz (OPZ) is a known inducer of glutathione S-transferases and a mechanism-based inhibitor of cytochrome P450 1A2. Given the detoxification characteristics of this compound, the transcriptional effects of OPZ, along with the related naturally occurring compounds 3H-1,2-dithiole-3-thione (D3T) and sulforaphane (SF), were examined by gene expression profiling in murine BV-2 microglial cells, a neuronal macrophage cell type that mediates inflammatory responses in the brain. We show that the three compounds generate largely overlapping transcriptional changes in genes that are associated with detoxification and antioxidant responses. In addition, induction of an antioxidant/detoxification response in the microglial cells by OPZ, D3T, or SF was also able to protect cells from H2O2 -induced toxicity and to attenuate the production of reactive oxygen species in response to lipopolysaccharide treatment of cells. These results show that OPZ, D3T, and SF activate overlapping changes in gene expression and that they can regulate detoxification/antioxidant responses in multiple cells types, including cell types known to have a role in the production of oxidative stress.

Animals↗

PubMed2004

Molecular profiling of human hepatocellular carcinoma defines mutually exclusive interferon regulation and insulin-like growth factor II overexpression.

Molecular subtyping of human hepatocellular carcinoma (HCC) with potential mechanistic and therapeutic impact has not been achieved thus far. We have analyzed the mRNA expression patterns of 43 different human HCC samples and 3 HCC cell lines in comparison with normal adult liver using high-density cDNA microarrays. Two main groups of HCC, designated group A (65%) and group B (35%), were distinguished based on clustering of the most highly varying genes. Group A HCCs were characterized by induction of a number of interferon (IFN)-regulated genes, whereas group B was characterized mainly by down-regulation of several apoptosis-relevant and IFN-regulated genes. The number of apoptotic tumor cells and tumor-infiltrating lymphocytes was significantly higher in tumors of group A as compared with those of group B. Based on the expression pattern, group B was further subdivided into two subgroups, designated subgroup B1 (6 of 43 tumors, 14%) and subgroup B2 (9 of 43 tumors, 21%). A prominent characteristic of subgroup B1 was high overexpression of insulin-like growth factor (IGF)-II. All tested HCC cell lines expressed equally high concentrations of IGF-II transcripts and co-segregated with group B1 in clustering. IGF-II overexpression and induction of IFN-related genes were mutually exclusive, even when analysis was extended to other cancer expression profile studies. Moreover, IFN-gamma treatment substantially reduced IGF-II expression in HCC cells. In conclusion, cDNA microarray analyses provided subtyping of HCCs that is related to intratumor inflammation and tumor cell apoptosis. This profiling may be of mechanistic and therapeutic impact because IGF-II overexpression has been linked to reduced apoptosis and increased proliferation and may be accessible to therapeutic intervention.

Carcinoma, Hepatocellular↗

PubMed2004

Two-color, rolling-circle amplification on antibody microarrays for sensitive, multiplexed serum-protein measurements.

The ability to conveniently and rapidly profile a diverse set of proteins has valuable applications. In a step toward further enabling such a capability, we developed the use of rolling-circle amplification (RCA) to measure the relative levels of proteins from two serum samples, labeled with biotin and digoxigenin, respectively, that have been captured on antibody microarrays. Two-color RCA produced fluorescence up to 30-fold higher than direct-labeling and indirect-detection methods using antibody microarrays prepared on both polyacrylamide-based hydrogels and nitrocellulose. Replicate RCA measurements of multiple proteins from sets of 24 serum samples were highly reproducible and accurate. In addition, RCA enabled reproducible measurements of distinct expression profiles from lower-abundance proteins that were not measurable using the other detection methods. Two-color RCA on antibody microarrays should allow the convenient acquisition of expression profiles from a great diversity of proteins for a variety of applications.

Antibodies↗