Protein Microarray Technology

The physical and biological activity of any organisms is mainly depended on the genetic information which stored in DNA. A process at which a gene gives rise to a phenotype is called as gene expression. Analysis of gene expression can be used to interpret the changes that occur at biological level of a stressed cell or tissue. Hybridization technology helps to study the gene expression of multiple cell at a same time. Among them microarray technology is a high- throughput technology to study the gene expression at transcription level (DNA) or translation level (Protein). Analysis the protein only can predict the accurate changes that happens in a tissue, when they are infected by a disease causing organisms. Protein microarray mainly used to identify the interactions and activities of proteins with other molecules, and to determine their function for a system at normal state and stressed state. The scope of this chapter is to outline a detail description on the fabrication, types, data analysis, and application of protein microarray technology towards gene expression profiling.

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Protein microarray technology

Trends in Biotechnology ◽

10.1016/s0167-7799(01)01910-2 ◽

2002 ◽

Vol 20 (4) ◽

pp. 160-166 ◽

Cited By ~ 362

Author(s):

Markus F Templin ◽

Dieter Stoll ◽

Monika Schrenk ◽

Petra C Traub ◽

Christian F Vöhringer ◽

...

Keyword(s):

Protein Microarray ◽

Microarray Technology

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Abstract 869: Evaluate breast cancer diagnostic antibody specificity by using high density protein microarray technology

10.1158/1538-7445.am2014-869 ◽

2014 ◽

Author(s):

Donghui Ma ◽

Jian Chen ◽

Wei Fu ◽

Julie McDowell ◽

Kehu Yuan

Keyword(s):

Breast Cancer ◽

Protein Microarray ◽

High Density ◽

Antibody Specificity ◽

Microarray Technology ◽

Cancer Diagnostic

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Experimental Design & Analysis of Protein Array Data: Applying Methods from cDNA Arrays.

Blood ◽

10.1182/blood.v104.11.4280.4280 ◽

2004 ◽

Vol 104 (11) ◽

pp. 4280-4280

Author(s):

Jeanette E. Eckel ◽

Antje Hoering ◽

Irene Ghobrial

Keyword(s):

Gene Expression ◽

Experimental Design ◽

Differential Expression ◽

Protein Microarray ◽

Random Noise ◽

Reference Sample ◽

Fold Change ◽

Protein Array ◽

Microarray Technology ◽

Cdna Arrays

Abstract It appears that a number of recent manuscripts using protein microarray technology are using equivalent analysis procedures that the gene-expression microarray community implemented in their infancy. That is, utilizing a classic reference design such that the ratio of the sample of interest to a reference sample is the response of interest and assessing fold change to determine differential expression. For example, recent publications have concluded that proteins with a fold change less than 0.7 or greater than 1.3 demonstrate significant down- or up-regulated differential expression, respectively. However, fold change is an unreliable measure of differential expression and statistical models that distinguish true signal from random noise should be utilized instead of fold changes. Over the last half decade a tremendous amount of research has been devoted to gene-expression microarrays to vastly improve on the areas of experimental design, normalization and statistical analyses to assess differential expression and classification and these methods are directly applicable to protein microarray technology. Thus, the objective is to review the statistical methodology that has been developed for two-color cDNA arrays that is directly applicable to protein arrays. Examples are provided from a mantle-cell lymphoma protein-array experiment.

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Protein multiplex sandwich immunoassay: A reliable and objective method for complete molecular characterization of breast cancer from core needle biopsies

Journal of Clinical Oncology ◽

10.1200/jco.2006.24.18_suppl.20025 ◽

2006 ◽

Vol 24 (18_suppl) ◽

pp. 20025-20025 ◽

Cited By ~ 1

Author(s):

G. Sauer ◽

N. Schneiderhahn-Marra ◽

M. Bãuerle ◽

C. Kurzeder ◽

K. Koretz ◽

...

Keyword(s):

Breast Cancer ◽

Protein Microarray ◽

Sandwich Immunoassay ◽

Therapeutic Options ◽

Clinical Samples ◽

General Interest ◽

Data Sets ◽

Microarray Technology ◽

Core Needle ◽

Marker Proteins

20025 Background: Within the last years, protein microarrays have been developed to quantify a large number of parameters present in a given sample simultaneously. Such miniaturised and parallelised sandwich immunoassays are of general interest for all proteomic and diagnostic approaches in which several parameters have to be determined from small samples. We describe the development of a bead-based flow cytometry that represents a convenient approach for rapid multiplex detection of functional target molecules from breast cancer biopsies. Methods: Briefly, sonographically guided core needle biopsies (CNB) were performed from 120 breast cancer masses from different patients. All biopsies were carried out with an automated core biopsy device fitted with 14-gauge (22 mm excursion) needles. Tumor samples were frozen on at −70 Celsius and pulverized. Proteins were extracted, allowing the simultaneous quantification of more than hundred proteins by a bead-based multiplex sandwich immunoassay. Results: The total amount of extracted protein from tumor tissues (mean weight of 20 mg) ranged from 300 to 1000 μg. We demonstrate appropriate sensitivity, reproducibility, and robustness for this protein microarray technology to characterize clinical samples and generate reliable data sets. A set of multiplexed sandwich immunoassays based on Luminex beads were developed that identify marker proteins indicative of prognosis or response to therapeutic options. Up to almost hundred parameters were identified and quantified simultaneously of which estrogen, progesterone and HER2 status in the multiplex assay was highly significant correlated to results obtained by immunohistochemistry (IHC) (p < 0.01). Conclusions: Our results demonstrate that this new bead-based protein microarray technology rapidly and reliably characterizes tissue samples to generate data sets of molecular marker. Therefore, this technology may once replace traditional IHC in determining marker proteins indicative of prognosis or response to therapeutic options. No significant financial relationships to disclose.

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