Richard C. Zangar

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 µl). 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 ∼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.

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.

Application of Photonic Crystal Enhanced Fluorescence to Cancer Biomarker Microarrays

We report on the use of photonic crystal surfaces as a high-sensitivity platform for detection of a panel of cancer biomarkers in a protein microarray format. The photonic crystal surface is designed to provide an optical resonance at the excitation wavelength of cyanine-5 (Cy5), thus providing an increase in fluorescent intensity for Cy5-labeled analytes measured with a confocal microarray scanner, compared to a glass surface. The sandwich enzyme-linked immunosorbent assay (ELISA) is undertaken on a microarray platform to undertake a simultaneous, multiplex analysis of 24 antigens on a single chip. Our results show that the resonant excitation effect increases the signal-to-noise ratio by 3.8- to 6.6-fold, resulting in a decrease in detection limits of 6-89%, with the exact enhancement dependent upon the antibody-antigen interaction. Dose-response characterization of the photonic crystal antibody microarrays shows the capability to detect common cancer biomarkers in the <2 pg/mL concentration range within a mixed sample.

Multiple Mechanisms Are Responsible for Transactivation of the Epidermal Growth Factor Receptor in Mammary Epithelial Cells

The number of distinct signaling pathways that can transactivate the epidermal growth factor receptor (EGFR) in a single cell type is unclear. Using a single strain of human mammary epithelial cells, we found that a wide variety of agonists, such as lysophosphatidic acid (LPA), uridine triphosphate, growth hormone, vascular endothelial growth factor, insulin-like growth factor-1 (IGF-1), and tumor necrosis factor-α, require EGFR activity to induce ERK phosphorylation. In contrast, hepatocyte growth factor can stimulate ERK phosphorylation independent of the EGFR. EGFR transactivation also correlated with an increase in cell proliferation and could be inhibited with metalloprotease inhibitors. However, there were significant differences with respect to transactivation kinetics and sensitivity to different inhibitors. In particular, IGF-1 displayed relatively slow transactivation kinetics and was resistant to inhibition by the selective ADAM-17 inhibitor WAY-022 compared with LPA-induced transactivation. Studies using anti-ligand antibodies showed that IGF-1 transactivation required amphiregulin production, whereas LPA was dependent on multiple ligands. Direct measurement of ligand shedding confirmed that LPA treatment stimulated shedding of multiple EGFR ligands, but paradoxically, IGF-1 had little effect on the shedding rate of any ligand, including amphiregulin. Instead, IGF-1 appeared to work by enhancing EGFR activation of Ras in response to constitutively produced amphiregulin. This enhancement of EGFR signaling was independent of both receptor phosphorylation and PI-3-kinase activity, suggestive of a novel mechanism. Our studies demonstrate that within a single cell type, the EGFR autocrine system can couple multiple signaling pathways to ERK activation and that this modulation of EGFR autocrine signaling can be accomplished at multiple regulatory steps.

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.

Cytotoxicity of trichloroethylene and S-(1, 2-dichlorovinyl)-L-cysteine in primary cultures of rat renal proximal tubular and distal tubular cells.

Activities of several glutathione-dependent enzymes, expression of cytochrome P450 isoenzymes, and time- and concentration-dependent cytotoxicity of trichloroethylene (TRI) and S-(1, 2-dichlorovinyl)-L-cysteine (DCVC) were evaluated in primary cultures of proximal tubular (PT) and distal tubular (DT) cells from rat kidney. These cells exhibited cytokeratin staining and maintained activities of all glutathione-dependent enzymes measured. Of the cytochrome P450 isoenzymes studied, only CYP4A expression was detected. CYP4A mRNA and protein expression were higher in primary cultures of DT cells than in PT cells and were increased in DT cells by ciprofibrate treatment. Incubation of cells for 6 h with concentrations of TRI as high as 10 mM resulted in minimal cytotoxicity, as determined by release of lactate dehydrogenase (LDH). In contrast, marked cytotoxicity resulted from incubation of PT or DT cells with DCVC. Addition to cultures of TRI (2-10 mM) for 24 or 72 h resulted in modest, but significant time- and concentration-dependent increases in LDH release. Treatment of cells with DCVC (0.1-1 mM) for 24 h caused significant increases in LDH release and alterations in cellular protein and DNA content. Finally, exposure of primary cultures to TRI or DCVC for 72 h followed by 3 h of recovery caused a slight increase in the expression of vimentin, consistent with cellular regeneration. These studies demonstrate the utility of the primary renal cell cultures for the study of CYP4A expression and mechanisms of TRI-induced cellular injury.

Evaluating concentration estimation errors in ELISA microarray experiments.

BackgroundEnzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a proteins 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.ResultsWe 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.ConclusionsThis 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.

Surface chemistries for antibody microarrays.

Enzyme-linked immunosorbent assay (ELISA) microarrays promise to be a powerful tool for the detection of disease biomarkers. The original technology for printing ELISA microarray chips and capturing antibodies on slides was derived from the DNA microarray field. However, due to the need to maintain antibody structure and function when immobilized, surface chemistries used for DNA microarrays are not always appropriate for ELISA microarrays. In order to identify better surface chemistries for antibody capture, a number of commercial companies and academic research groups have developed new slide types that could improve antibody function in microarray applications. In this review we compare and contrast the commercially available slide chemistries, as well as highlight some promising recent advances in the field.

Protein modifications as potential biomarkers in breast cancer.

A variety of post-translational protein modifications (PTMs) are known to be altered as a result of cancer development. Thus, these PTMs are potentially useful biomarkers for breast cancer. Mass spectrometry, antibody microarrays and immunohistochemistry techniques have shown promise for identifying changes in PTMs. In this review, we summarize the current literature on PTMs identified in the plasma and tumor tissue of breast-cancer patients or in breast cell lines. We also discuss some of the analytical techniques currently being used to evaluate PTMs.

ProMAT: protein microarray analysis tool

SUMMARY ProMAT is a software tool for statistically analyzing data from enzyme-linked immunosorbent assay microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code. AVAILABILITY ProMAT is available at http://www.pnl.gov/statistics/ProMAT. ProMAT requires Java version 1.5.0 and R version 1.9.1 (or more recent versions). ProMAT requires either Windows XP or Mac OS 10.4 or newer versions.