Biomedical subjects

Richard C Zangar

Publications and source records attributed to Richard C Zangar.

13 recordsLinked to original sources

PubMed2006

ELISA microarray technology as a high-throughput system for cancer biomarker validation.

A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue. An additional challenge with cancer screening is that most cancers are rare in the general population, meaning that assay specificity must be very high. Otherwise, the number of false positives will be much greater than the number of true positives. Due to these challenges associated with biomarker validation, it is necessary to analyze thousands of samples in order to obtain a clear idea of the utility of a screening assay. Enzyme-linked immunosorbent assay (ELISA) microarray technology can simultaneously quantify levels of multiple proteins and, thus, has the potential to accelerate validation of protein biomarkers for clinical use. This review will discuss current ELISA microarray technology and potential advances that could help to achieve the reproducibility and throughput that are required to evaluate cancer biomarkers.

Biomarkers, Tumor↗

PubMed2005

Evaluating concentration estimation errors in ELISA microarray experiments.

BACKGROUND: Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization, and statistical diagnostics when evaluating ELISA microarray concentration estimation errors. RESULTS: We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error. We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration. CONCLUSIONS: This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses. Applying propagation of error to a variety of ELISA microarray concentration estimation models is straightforward. Displaying the results in the three-panel layout succinctly summarizes both the standard and sample data while providing an informative critique of applicability of the fitted model, the uncertainty in concentration estimates, and the quality of both the experiment and the ELISA microarray process.

Algorithms↗

PubMed2005

A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy.

Characterization of the human blood plasma proteome is critical to the discovery of routinely useful clinical biomarkers. We used an accurate mass and time (AMT) tag strategy with high-resolution mass accuracy cLC-FT-ICR MS to perform a global proteomic analysis of pilot study samples as part of the HUPO Plasma Proteome Project. HUPO reference serum and citrated plasma samples from African Americans, Asian Americans, and Caucasian Americans were analyzed, in addition to a Pacific Northwest National Laboratory reference serum and plasma. The AMT tag strategy allowed us to leverage two previously published "shotgun" proteomics experiments to perform global analyses on these samples in triplicate in less than 4 days total analysis time. A total of 722 (22% with multiple peptide identifications) International Protein Index redundant proteins, or 377 protein families by ProteinProphet, were identified over the six individual HUPO serum and plasma samples. The samples yielded a similar number of identified redundant proteins in the plasma samples (average 446 +/- 23) as found in the serum samples (average 440 +/- 20). These proteins were identified by an average of 956 +/- 35 unique peptides in plasma and 930 +/- 11 unique peptides in serum. In addition to this high-throughput analysis, the AMT tag approach was used with a Z-score normalization to compare relative protein abundances. This analysis highlighted both known differences in serum and citrated plasma such as fibrinogens, and reproducible differences in peptide abundances from proteins such as soluble activin receptor-like kinase 7b and glycoprotein m6b. The AMT tag strategy not only improved our sample throughput but also provided a basis for estimated quantitation.

Blood Proteins↗

PubMed2005

Studying cellular processes and detecting disease with protein microarrays.

Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications, and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.

Cell Physiological Phenomena↗

PubMed2004

Mechanisms that regulate production of reactive oxygen species by cytochrome P450.

Mammalian cytochromes P450 (P450) are a family of heme-thiolate enzymes involved in the oxidative metabolism of a variety of endogenous and exogenous lipophilic compounds. Poor coupling of the P450 catalytic cycle results in continuous production of reactive oxygen species (ROS), which affects signaling pathways and other cellular functions. P450 generation of ROS is tightly controlled by regulation of gene transcription as well as by modulation of interactions between protein constituents of the monooxygenase that affects its activity, coupling, and stability. Malfunction of these mechanisms may result in a burst of ROS production, which can cause lipid peroxidation and oxidative stress. In turn, oxidative stress downregulates P450 levels by a variety of feedback mechanisms. This review provides an overview of recent advances in our understanding of these feedback mechanisms that serve to limit P450 production of ROS. Some of the more likely physiological and cellular effects of P450 generation of ROS are also discussed.

Animals↗

PubMed2004

Interactions of phospholipase D and cytochrome P450 protein stability.

Previous studies have suggested a relationship between cytochrome P450 (P450) 3A (CYP3A) conformation and the phospholipid composition of the associated membrane. In this study, we utilized a novel microsomal incubation system that mimics many of the characteristics of CYP3A degradation pathway that have been observed in vivo and in cultured cells to study the effects of phospholipid composition on protein stability. We found that addition of phosphatidylcholine-specific phospholipase D (PLD) stabilized CYP3A in this system, but that phosphatidylinositol-specific phospholipase C (PLC) was without effect. Addition of phosphatidic acid also stabilized CYP3A protein in the microsomes. The use of 1,10-phenanthroline (phenanthroline), an inhibitor of PLD activity, decreased CYP3A stability in incubated microsomes. Similarly, 6-h treatment of primary cultures of rat hepatocytes with phenanthroline resulted in nearly complete loss of CYP3A protein. Treatment of rats with nicardipine or dimethylsulfoxide (DMSO), which have been shown to affect CYP3A stability, altered the phospholipid composition of hepatic microsomes. It did not appear, though, that the changes in phospholipid composition that resulted from these in vivo treatments accounted for the change in CYP3A stability observed in hepatic microsomes from these animals.

Analysis of Variance↗

PubMed2004

Induced autocrine signaling through the epidermal growth factor receptor contributes to the response of mammary epithelial cells to tumor necrosis factor alpha.

In contrast to the well known cytotoxic effects of tumor necrosis factor (TNF) alpha in many mammary cancer cells, we have found that TNF stimulates the proliferation and motility of human mammary epithelial cells (HMECs). Since the response of HMECs to TNF is similar to effects mediated by epidermal growth factor receptor (EGFR) activation, we explored the potential role of cross-talk through the EGFR signaling pathways in mediating cellular responses to TNF. Using a microarray enzyme-linked immunoassay, we found that exposure to TNF stimulated the dose-dependent shedding of the EGFR ligand transforming growth factor alpha (TGFalpha). Both proliferation and motility of HMECs induced by TNF was prevented either by inhibiting membrane protein shedding with a metalloprotease inhibitor, by blocking epidermal growth factor receptor (EGFR) kinase activity, or by limiting ligand-receptor interactions with an antagonistic anti-EGFR antibody. EGFR activity was also necessary for TNF-induced release of matrix metalloprotease-9, thought to be an essential regulator of mammary cell migration. The cellular response to TNF was associated with a biphasic temporal pattern of extracellular signal-regulated kinase (ERK) phosphorylation, which was EGFR-dependent and modulated by inhibition of metalloprotease-mediated shedding. Significantly, the late phase of ERK phosphorylation, detectable within 4 h after exposure, was blocked by the metalloprotease inhibitor batimastat, indicating that autocrine signaling through ligand shedding was responsible for this secondary wave of ERK activity. Our results indicate a novel and important role for metalloprotease activation and EGFR transmodulation in mediating the cellular response to TNF.

Autocrine Communication↗

PubMed2004

A rational approach for discovering and validating cancer markers in very small samples using mass spectrometry and ELISA microarrays.

Identifying useful markers of cancer can be problematic due to limited amounts of sample. Some samples such as nipple aspirate fluid (NAF) or early-stage tumors are inherently small. Other samples such as serum are collected in larger volumes but archives of these samples are very valuable and only small amounts of each sample may be available for a single study. Also, given the diverse nature of cancer and the inherent variability in individual protein levels, it seems likely that the best approach to screen for cancer will be to determine the profile of a battery of proteins. As a result, a major challenge in identifying protein markers of disease is the ability to screen many proteins using very small amounts of sample. In this review, we outline some technological advances in proteomics that greatly advance this capability. Specifically, we propose a strategy for identifying markers of breast cancer in NAF that utilizes mass spectrometry (MS) to simultaneously screen hundreds or thousands of proteins in each sample. The best potential markers identified by the MS analysis can then be extensively characterized using an ELISA microarray assay. Because the microarray analysis is quantitative and large numbers of samples can be efficiently analyzed, this approach offers the ability to rapidly assess a battery of selected proteins in a manner that is directly relevant to traditional clinical assays.

Bacterial Proteins↗

PubMed2004

A protein microarray ELISA for screening biological fluids.

Protein microarrays permit the simultaneous measurement of many proteins in a small sample volume and therefore provide an attractive approach for the quantitative measurement of proteins in biological fluids, including serum. This chapter describes a microarray enzyme-linked immunosorbent assay (ELISA). Capture antibodies are immobilized onto a glass surface; the covalently attached antibodies bind a specific antigen from a sample overlaying the array. A second, biotinylated antibody that recognizes the same antigen as the first antibody, but at a different epitope, is then used for detection. Detection is based on an enzymatic signal-enhancement method known as tyramide signal amplification (TSA). By coupling a microarray-ELISA format with the signal amplification of tyramide deposition, the assay sensitivity is as low as sub-pg/mL.

Amides↗

PubMed2003

Hydroperoxy-10,12-octadecadienoic acid stimulates cytochrome P450 3A protein aggregation by a mechanism that is inhibited by substrate.

We recently demonstrated that microsomes from nicardipine-treated rats will form cytochrome P450 3A (CYP3A) aggregates when incubated at 37 degrees C. CYP3A substrates inhibited the protein aggregation and subsequent degradation, suggesting that this process is important in substrate-mediated stabilization of CYP3A. In this paper, we demonstrate that oxidative stress is a key factor in the formation of CYP3A aggregates in incubated microsomes and in a reconstituted system with purified enzymes. Our data further suggest that the effects of oxidative stress are mediated by lipid hydroperoxides, which are efficiently metabolized by CYP3A. In the presence of substrate, the CYP3A-mediated lipid hydroperoxide metabolism is inhibited along with the associated protein aggregation. Therefore, these studies provide a mechanistic model of why CYP3A has a relatively short half-life and how substrates stabilize CYP3A.

Animals↗

PubMed2003

Suppression of cytochrome P450 3A protein levels by proteasome inhibitors.

We have previously reported that CYP3A cross-links with polyubiquitinated proteins in microsomes from nicardipine-treated rats in a process that is distinct from classical polyubiquitination. To further examine the role of the proteasome in CYP3A degradation, we investigated the effects of proteasome inhibitors lactacystin, MG132, proteasome inhibitor 1, and hemin in primary cultures of rat and human hepatocytes. With the exception of hemin, these agents increased the total pool of ubiquitinated proteins in microsomes isolated from rat hepatocytes, indicating that lactacystin, MG132, and proteasome inhibitor 1 effectively inhibited the proteasome in these cells. All four agents caused a reduction in the amount of the major approximately 55-kDa CYP3A band, opposite to what would be expected if the ubiquitin-proteasome pathway degraded CYP3A. Only hemin treatment caused an increase in high molecular mass (HMM) CYP3A bands. Because hemin treatment did not alter levels of ubiquitin in CYP3A immunoprecipitates, the HMM CYP3A bands formed in response to hemin treatment clearly were not due to proteasome inhibition. Rather, because hemin treatment also caused an increase in HMM CYP3A in the detergent-insoluble fraction of the 10,000g pellet, the HMM CYP3A seems to represent a large protein complex that is unlikely to primarily represent ubiquitination.

Animals↗

PubMed2003

Proteomic characterization of nipple aspirate fluid: identification of potential biomarkers of breast cancer.

Mammary ductal cells are the origin for 70-80% of breast cancers. Nipple aspirate fluid (NAF) contains proteins directly secreted by the ductal and lobular epithelium in non-lactating women. Proteomic approaches offer a largely unbiased way to evaluate NAF as a source of biomarkers and are sufficiently sensitive for analysis of small NAF volumes (10-50 microl). In this study, we initially evaluated a new process for obtaining NAF and discovered that this process resulted in a volume of NAF that was suitable for analysis in approximately 90% of subjects. Proteomic characterization of NAF identified 64 proteins. Although this list primarily includes abundant and moderately abundant NAF proteins, very few of these proteins have previously been reported in NAF. At least 15 of the NAF proteins identified have previously been reported to be altered in serum or tumor tissue from women with breast cancer, including cathepsin D and osteopontin. In summary, this study provides the first characterization of the NAF proteome and identifies several candidate proteins for future studies on breast cancer markers in NAF.

Adult↗

PubMedDate not supplied

Elevated HGF levels in sera from breast cancer patients detected using a protein microarray ELISA.

We developed an ELISA in high-density microarray format to detect hepatocyte growth factor (HGF) in human serum. The microassay can detect HGF at sub-pg/mL concentrations in sample volumes of 100 microL or less. The microassay is also quantitative and was used to detect elevated HGF levels in sera from recurrent breast cancer patients. The microarray format provides the potential for high-throughput quantitation of multiple biomarkers in parallel, as demonstrated with a multiplex analysis of five biomarker proteins.

Biomarkers, Tumor↗