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Apr 1, 2010 (Vol. 30, No. 7)

High-Density Reverse-Phase Protein Arrays

Designing Solutions for Biomarker Research at the Protein Level

  • Utility and Data Analysis

    Significant effort has been made to identify high-quality antibodies and develop sensitive detection methods. The sensitivity and specificity of the primary antibody is a determining factor in the success of the assay. Antibodies need to be highly reactive with cell lysate and give a predominant single band by Western blot.

    A good way to start is by choosing antibodies with proven track records or those made against native proteins. Often, several antibodies need to be tested before finding one with the desired properties. RPPA require minute amounts of lysate (1–2 ng), making it possible to conduct thousands of assays with the same material. Detection often requires the use of tyramide signal amplification systems such as the one depicted in Figure 1A. To assist with this complicated task, OriGene has developed a small inexpensive RPPAs for validation of reagents and procedures.

    A curve-fitting solution is the most accurate way to analyze RPPAs (Figure 1B). Changes between cancer and normal tissue can be quantified by dividing the readout from each sample with the median expression of normal samples from the same tissue (Figure 2).

    When represented in a simple heat map format, the clustering of aberrant expression (both high and low) in particular cancers become apparent. The analysis shows that ERBB2 is overexpressed not only in breast and ovarian cancer but also in a number of other cancers. In addition, it is downregulated in some kidney and liver cancers (Figure 2). Such findings have clinical implications for extending the use of current tests and drugs to additional cancers. More detailed analysis can be made using the clinical data provided with each sample. For example, the higher expression of Phospho c-Myc in ovarian cancer samples is mainly restricted to stage 2C and 3 and appears in 83% of these samples (10/12).

    Using a variety of high-quality antibodies, it is possible to create an expression profile for each cancer and discover associations within clinical data.

    High-density RPPAs provide quantitative profiling of protein expression and post-translational modifications of cancer and normal cells and tissues. With this method, proteins are extracted from many biospecimens and arrayed using a standardized protein dilution curve. This large-scale method can identify cancer-associated alterations at the protein level. This makes high-density RPPAs a powerful and important tool for cancer research.

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