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

High-Density Reverse-Phase Protein Arrays

Designing Solutions for Biomarker Research at the Protein Level
  • Dror I. Baruch, Ph.D.

The quest to cure cancer requires an ever-expanding tool kit to identify and validate biomarkers for better detection, diagnosis, prognosis, and treatment of cancer. 

The vast number of discoveries being made with new technologies have required the development and implementation of comprehensive quantitative methods to link these discoveries with biospecimens from various cancers. Array technologies including DNA microarrays, qPCR arrays, antibody arrays, recombinant protein arrays, tissue arrays, and reverse phase protein arrays (RPPA) are among the methods being used for this task.

Many of the platforms in use are complementary to each other, but only a few are able to interrogate hundreds or thousands of biospecimens with sufficient sensitivity and deliver relevant quantitative results at an affordable price. Solutions available from OriGene Technologies use qPCR methods at the RNA level and high-density tissue lysate RPPA at the protein level.

Cancer RPPAs are protein lysates from cancer and normal tissues arrayed at high-density on a nitrocellulose-coated glass slide, which allows simultaneous interrogation of hundreds of samples using high-quality antibodies (Figure 1A). A major use of these arrays is identification and validation of potential biomarkers. This is accomplished by measuring quantitative differences in the expression profiles and post-translational modifications of proteins from cancer and normal tissues (Figures 1B and 2).

Developing RPPAs

High-density RPPAs require a large number of high-quality human biospecimens, which must be banked at reputable institutes, contain a high percentage of tumor, include comprehensive clinical data, and be verified by a certified pathologist. Such samples are often expensive and hard to find.

OriGene’s cancer biorepository of 12,000 donors allows its researchers to use a large number of samples across 11 cancers for comprehensive cancer RPPAs.

Another challenge is extracting and standardizing a large number of samples from various tissues and different tumor content. The most straightforward solution is using a single standard operating procedure for all samples, regardless of tumor content.

Some researchers use laser-capture microdissection to enrich the sample for only cancer cells. Although this method is more accurate, it is often unnecessary and results in limited and expensive material. Mild nondenaturizing detergents (NP40 and Deoxy-cholate) with complete protease and phosphatase inhibitor cocktails are preferred in the extraction process in order to preserve the structure and phosphorylation state of the proteins.

Quantifying the different lysates remains a problem. The most commonly used method is protein concentration, in which all samples are diluted to a single concentration (usually 1 mg/mL), followed by 4–5 serial dilutions, which provides a single standardized curve. This curve is printed in triplicate for more accurate quantification.

This procedure is sufficient to accurately detect quantitative changes among samples (Figures 1B and 2). OriGene has found an 84% match between IHC data in the patient pathology report and the expression level measured by the array for ERBB2 among breast samples. These were further confirmed by Western blot analysis.

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.