Biomedical subjects

Brian B Haab

Publications and source records attributed to Brian B Haab.

25 records · Page 2Linked to original sources

PubMed2004

Multiplexed protein analysis using spotted antibody microarrays.

This chapter describes methods for the production and use of antibody microarrays. The methods are divided into (a) antibody handling and microarray production, (b) sample preparation, and (c) microarray use. Two types of detection methods are described: direct labeling and a fluorescence-linked immunosorbent assay (FLISA). In the direct labeling method, all proteins in a complex mixture are labeled with either a fluorophore or a hapten that allows subsequent detection. In FLISA detection, a capture antibody on the microarray captures the unlabeled protein target, which is detected by a detection antibody and a fluorophore-labeled secondary antibody. Each method has particular optimal uses, which are discussed in the text.

Antibodies↗

PubMed2003

Methods and applications of antibody microarrays in cancer research.

Antibody microarrays have great potential for significant value in biological research. Cancer research in particular could benefit from the unique experimental capabilities of this technology. This article examines the current state of antibody microarray technological developments and assay formats, along with a review of the demonstrated applications to cancer research. Work is ongoing in the refinement of various aspects of the protocols and the development of robust methods for routine use. Antibody microarray experimental formats can be broadly categorized into two classes: (1) direct labeling experiments, and (2) dual antibody sandwich assays. In the direct labeling method, the covalent labeling of all proteins in a complex mixture provides a means for detecting bound proteins after incubation on an antibody microarray. If proteins are labeled with a tag, such as biotin, the signal from bound proteins can be amplified. In the sandwich assay, proteins captured on an antibody microarray are detected by a cocktail of detection antibodies, each antibody matched to one of the spotted antibodies. Each format has distinct advantages and disadvantages. Several applications of antibody arrays to cancer research have been reported, including the analysis of proteins in blood serum, resected frozen tumors, cell lines, and on membranes of blood cells. These demonstrations clearly show the utility of antibody microarrays for cancer research and signal the imminent expansion of this platform to many areas of biological research.

Animals↗

PubMed2003

Microarrays of tumor cell derived proteins uncover a distinct pattern of prostate cancer serum immunoreactivity.

The broad characterization of the immune responses elicited by tumors has valuable applications in diagnostics and basic research. We present here the use of microarrays of tumor-derived proteins to profile the antibody repertoire in the sera of prostate cancer patients and controls. Two-dimensional liquid chromatography was used to separate proteins from the prostate cancer cell line LNCaP into 1760 fractions. These fractions were spotted in microarrays on coated microscope slides, and the microarrays were incubated individually with serum samples from 25 men with prostate cancer and 25 male controls. The amount of immunoglobulin bound to each fraction by each serum sample was quantified. Statistical analysis revealed that 38 of the fractions had significantly higher levels of immunoglobulin binding in the prostate cancer samples compared to the controls. Two fractions showed higher binding in the control samples. The significantly higher immunoglobulin reactivity from the prostate cancer samples may reflect a strong immune response to the tumors in the prostate cancer patients. We used multivariate analysis to classify the samples as either prostate cancer or control. In a cross-validation study, recursive partitioning classified the samples with 84% accuracy. A decision tree with two levels of partitioning classified the samples with 98% accuracy. Additional studies will allow further characterization of tumor antigens in prostate cancer and their significance for diagnosis. These results suggest that microarrays of fractionated proteins could be a powerful tool for tumor antigen discovery and cancer diagnosis.

Antibodies, Neoplasm↗

PubMed2003

Antibody microarray profiling of human prostate cancer sera: antibody screening and identification of potential biomarkers.

We developed a practical strategy for serum protein profiling using antibody microarrays and applied the method to the identification of potential biomarkers in prostate cancer serum. Protein abundances from 33 prostate cancer and 20 control serum samples were compared to abundances from a common reference pool using a two-color fluorescence assay. Robotically spotted microarrays containing 184 unique antibodies were prepared on two different substrates: polyacrylamide based hydrogels on glass and poly-1-lysine coated glass with a photoreactive cross-linking layer. The hydrogel substrate yielded an average six-fold higher signal-to-noise ratio than the other substrate, and detection of protein binding was possible from a greater number of antibodies using the hydrogels. A statistical filter based on the correlation of data from "reverse-labeled" experiment sets accurately predicted the agreement between the microarray measurements and enzyme-linked immunosorbent assay measurements, showing that this parameter can serve to screen for antibodies that are functional on microarrays. Having defined a set of reliable microarray measurements, we identified five proteins (von Willebrand Factor, immunoglobulinM, Alpha1-antichymotrypsin, Villin and immunoglobulinG) that had significantly different levels between the prostate cancer samples and the controls. These developments enable the immediate use of high-density antibody and protein microarrays in biomarker discovery studies.

Antibodies, Neoplasm↗

PubMed2002

Autoantigen microarrays for multiplex characterization of autoantibody responses.

We constructed miniaturized autoantigen arrays to perform large-scale multiplex characterization of autoantibody responses directed against structurally diverse autoantigens, using submicroliter quantities of clinical samples. Autoantigen microarrays were produced by attaching hundreds of proteins, peptides and other biomolecules to the surface of derivatized glass slides using a robotic arrayer. Arrays were incubated with patient serum, and spectrally resolvable fluorescent labels were used to detect autoantibody binding to specific autoantigens on the array. We describe and characterize arrays containing the major autoantigens in eight distinct human autoimmune diseases, including systemic lupus erythematosus and rheumatoid arthritis. This represents the first report of application of such technology to multiple human disease sera, and will enable validated detection of antibodies recognizing autoantigens including proteins, peptides, enzyme complexes, ribonucleoprotein complexes, DNA and post-translationally modified antigens. Autoantigen microarrays represent a powerful tool to study the specificity and pathogenesis of autoantibody responses, and to identify and define relevant autoantigens in human autoimmune diseases.

Animals↗

PubMed2002

CIT: identification of differentially expressed clusters of genes from microarray data.

Cluster Identification Tool (CIT) is a microarray analysis program that identifies differentially expressed genes. Following division of experimental samples based on a parameter of interest, CIT uses a statistical discrimination metric and permutation analysis to identify clusters of genes or individual genes that best differentiate between the experimental groups. CIT integrates with the freely available CLUSTER and TREEVIEW programs to form a more complete microarray analysis package.

Algorithms↗

PubMedDate not supplied

Development of natural protein microarrays for diagnosing cancer based on an antibody response to tumor antigens.

The detection of autoantibodies to tumor antigens has potential utility for the early diagnosis of cancers. In previous studies, we have identified tumor antigens based on Western blot analysis of tumor cell lysates that were incubated with subject sera to identify proteins that elicit specific reactivity in sera from patients with the corresponding tumor type. More recently, we have explored the use of microarrays spotted with tumor proteins as an alternative to Western blots. Microarrays provide a high throughput, high sensitivity alternative to the use of Western blots for tumor antigen profiling. In this study, we have assessed the reproducibility of natural protein microarrays and their ability to distinguish between lung cancer sera and controls. Protein lysates from the A549 human lung adenocarcinoma cell line were separated into 1840 fractions that were spotted in duplicate, along with various controls, on nitrocellulose coated slides. Sera from 18 newly diagnosed patients with lung cancer and from 15 healthy controls were each hybridized to an individual microarray. The reactivity of arrayed proteins with Ig was determined by incubation with biotinylated goat-anti-human-Ig followed by phycoerythrin-conjugated streptavidin. The intensity measures of duplicate spots (within-slide) and duplicate slides (between-slides) were highly reproducible, exhibiting correlation values >0.9. A total of 63 of the 1840 arrayed fractions demonstrated increased reactivity in cancer patients relative to controls as measured by a rank-based statistic (p < 0.008). Microarrays of tumor-derived proteins provide the means for uncovering a repertoire of tumor antigens that have induced an antibody response in patients with specific cancers.

Adenocarcinoma↗