Hematopathology: New Technologies
Moderators: Dr. John Wing Chan and Dr. Thomas Grogan
Section 5 -
Proteomics and Lymphoid Malignancies
Andrew L. Feldman
Proteins are the functional building blocks of the signaling mechanisms that relay information within
and between cells. This information includes signals that trigger division, apoptosis, and recruitment
of other cells that promote or inhibit cell survival. Proteins carry information along these signaling
pathways much like electricity in an electric circuit; the information varies according to the type and
amount of protein, the location (extracellular, cytoplasmic, nuclear), and post-translational
modifications. Thus, proteomic analysis of tissues or body fluids offers a real-time window on the flow
of cellular information in health and disease.
The analysis of protein expression using immunohistochemistry and flow cytometry has become a critical
component of the classification of lymphoid malignancies. Proteomics, like other "-omics" technologies,
differs from these types of protein analysis mostly in scale. Microarray technology has allowed
high-throughput analysis of large numbers of analytes in multiple clinical specimens. New bioinformatic
tools for analyzing and clustering these data have facilitated the detection of trends in large sample
groups that would not be evident in individual cases. Gene expression microarrays have been employed in
this manner to define new disease subtypes (e.g. the ABC and GCB subtypes of diffuse large B-cell
) and suggest new biologic factors in lymphoma (e.g. cyclin D1-negative mantle cell lymphoma
). Similar evaluation at the proteomic level might be expected to yield even more functionally
relevant information, since not all expressed genes are translated, and not all proteins are in an active
configuration . However, several technical limitations stand in the way of directly applying gene
expression profiling methodology to proteomics. First, developing specific protein ligands is more
difficult than generating complementary DNA sequences for binding; second, linear amplification of
proteins for analysis of small samples has not yet been achieved; third, protein concentrations vary in
abundance thousands of times more than RNA species, challenging the dynamic range of existing detection
strategies; finally, the number of protein species (around 300,000) far exceeds the number of known genes
The two major protein detection strategies for proteomic analysis are ligand-based approaches and mass
spectrometry-based approaches. Ligand-based approaches are discussed here. The most commonly used
protein ligands are antibodies, but other protein ligands can be used for specific applications,
including lectins, other proteins, and DNA. Development of antibodies against specific
post-translational modifications (phosphorylation, specific cleavage sites) has allowed assessment of the
activation status of specific proteins, information not available using genomic strategies. Using a
combination of such antibodies, the activation status of entire signaling pathways can be assayed. This
approach is promising for individualizing treatment of patients with molecular therapies that target
Immunohistochemistry and flow cytometry have begun to be used for proteomic-scale assessment of
lymphoid neoplasms. Tissue microarrays have become a high-throughput strategy for validating gene
expression array findings and investigating utility of new immunophenotyping panels, such as in diffuse
large B-cell lymphoma
and Hodgkin lymphoma . Quantitative analysis of protein expression in
tissue microarrays, including the ability to assay subcellular protein localization , may greatly
facilitate profiling cell signaling pathways in paraffin embedded tissue. Flow cytometry has the
advantage of being able to accurately assess multiple markers on individual cells. This is particularly
important in lymphoid neoplasms, where the neoplastic cells often are admixed with numerous
non-neoplastic cells that contribute significantly to overall protein levels in tissue lysates. The use
of unsupervised clustering algorithms ,
single-cell phosphoproteomics , and microfluidic
technologies for flow cytometry  are expected to advance proteomic applications of this field
As with gene expression analysis, the microarray format is conducive to proteomic profiling .
Though the format of protein microarrays varies, all have in common the detection of colocalized protein
and ligand on a solid phase. Forward-phase and reverse-phase protein microarrays have been described.
In forward-phase arrays, multiple ligands are immobilized on the solid phase and each array is probed
with one or more protein samples. For example, multiple antibodies can be spotted on the solid phase,
and the array can be probed with labeled protein samples. Ghobrial et al. used this approach to profile
protein expression in mantle cell lymphoma. Not all findings could be confirmed by downstream validation
techniques such as immunoblotting, indicating some potential limitations of this approach. Labeling
protein for array-based detection can be problematic. DNA generally is labeled by incorporating labeled
nucleotides during replication. Since a similar method is not available for protein amplification it is
the native protein that requires labeling. Incubating the sample with excess label can damage the
protein itself. Using insufficient label can lead to preferential labeling of large and/or high
abundance proteins, leaving low abundance proteins either unlabeled or inconsistently labeled.
Sandwich-type forward-phase microarrays avoid the protein labeling problem. This method also uses
immobilized antibody to capture proteins in the sample. These are detected by a second antibody, which
then is quantitated using standard detection systems as in an enzyme-linked immunosorbent assay (ELISA).
In practice, this latter step can lack specificity if too many proteins are analyzed simultaneously.
This approach, as well as related bead-based strategies, have been applied to quantitation of cytokines
 and in principle is broadly extendable for use with many other types of proteins. One of the
limitations of this approach is that the validation of antibody pairs for each protein of interest and
testing for multiplex cross-reactivity adds a level of complexity that makes it difficult to assay large
numbers of proteins.
Reverse-phase microarrays (RPMs) transcend some of the above limitations. In this technique, protein
lysates are spotted onto the solid phase, such as a nitrocellulose-coated glass slide. Each array
therefore contains numerous patient samples. Replicates of each sample typically are spotted in serial
dilution curves, improving accuracy tremendously. Depending on the type of arrayer used and diameter of
the spotting pin, very small volumes of lysate are used (e.g. 20 nL/spot). Thus this technique allows
proteomic analysis of very small samples, and has enabled analysis of samples obtained using laser
capture microdissection (LCM)
20,000 cells or less . Thus, there can be more
selectivity in the cell population to be analyzed than can be achieved with forward-phase arrays. Each
array is currently probed with a single antibody, though the potential for multiplexing exists .
Because hundreds of replicate arrays can be printed, the ability to measure numerous proteins is
enhanced. Unprobed arrays can be stored for years, allowing the analysis of additional proteins as new
antibodies or scientific information becomes available. Our group has used RPMs to analyze apoptotic
pathways in follicular lymphoma (FL) and follicular hyperplasia, using LCM to enrich for follicle center
cells. In two separate studies
increased activation of Akt was found in follicular lymphoma;
this increase did not correlate with Bcl-2 expression, suggesting that Akt signaling may represent a
second important antiapoptotic pathway in FL. In addition, elevated Bcl-2/Bax and Bcl-2/Bak ratios were
found to be associated with poor overall survival in FL patients . The prognostic significance of
the Bcl-2/Bax ratio present only when LCM was used and not when lysates of whole tissue sections were
analyzed (unpublished data). This finding emphasizes the importance of correlating molecular profiles
with histology and using tools to enrich for cells of interest when applicable.
The ability to analyze proteomic patterns and activation status of signaling pathways in tissue
samples will facilitate the real-time monitoring of patients before, during, and after receiving targeted
molecular therapies . The increasing availability of functionally specific targeted therapies (e.g.
tyrosine kinase inhibitors) will extend the importance of being able to assay multiple pathways to
determine the ideal drug(s) for an individual patient's tumor. During therapy confirmatory proteomic
analysis can be performed to make sure the targeted pathway has been successfully turned off. Reanalysis
at the time of recurrence may help guide further therapy, since the originally targeted proteins may no
longer be robustly expressed after treatment . Because of the importance of correlating molecular
profiles with histologic findings, hematopathologists need to become integrally involved in the design of
clinical trials aimed at validating this model of individualized molecular medicine.
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