By Kelly Rae Chi
Pulling Out Proteins
Troubleshooting discovery and validation of protein biomarkers for cancer.
Researchers have long pinned hopes on biological indicators—or
molecular biomarkers—to serve as tools to help clinicians identify
populations at risk, classify tumor types, or monitor disease progression in cancer,
which is diagnosed in an estimated 11 million people worldwide each year. Genes have
held the spotlight for many years as potential biomarkers of cancer, but
increasingly, researchers are turning to individual proteins or groups of proteins
and their modifications with the belief that these molecules hold secrets to cancer
pathophysiology.
Because protein modifications can be extremely diverse (leading to a large
number of isoforms) and proteins cannot be amplified like DNA can, they don't always
offer a clear molecular distinction between a cancer patient and healthy control.
"There are several difficulties in the study of proteins that are not inherent in
the study of nucleic acids," writes William Cho, a scientific officer in clinical
oncology at Queen Elizabeth Hospital in Hong Kong, in an email. For example,
"genetic information is static while the protein complement of a cell is dynamic."
Proteins have secondary and tertiary structures that must often be maintained during
their analysis. Many potential biomarkers are masked by overabundant proteins, such
as amylase in saliva.
"People are doing a lot of technology development to discover biomarkers," says Akhilesh Pandey, an associate professor at John Hopkins University in Baltimore, Maryland. "What has still not come across is that once you do discovery you are actually not even close to being done."
For researchers lucky enough to find biomarker candidates, the story doesn't
end there: the best candidates must be chosen and validated in more patient sets, a
process that involves years of work. "People are doing a lot of technology
development to discover biomarkers," says Akhilesh Pandey, an associate professor at
Johns Hopkins University in Baltimore, Maryland. "What has still not come across is
that once you do discovery you are actually not even close to being done."
The Scientist talked with researchers about some of these
problems and how they went about solving them. Here's what we found:
Eliminating Amylase
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Saliva bubbles in a petri dish
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Courtesy of Arnie Rosner
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User:
David Wong, Professor, University of
California, Los Angeles School of Dentistry
Project:
Searching human saliva for protein
biomarkers of oral squamous cell carcinoma
and other cancers
Problem:
Salivary amylase is overabundant
. "Most of the time what is being
seen reduces the opportunity to identify
lower-level proteomic information, such as
cytokines and other low-molecular-weight
proteins," says Wong. The group tried five
different antibody-based technologies, to
no avail. They needed a way to eliminate
amylase and unmask potential biomarkers.
Solution:
After two years, Wong's group
finally found a way that seems to deplete
amylase in a study published last year by
a group of Israeli scientists (Electrophoresis,
29:1-8, 2008). The technique involves
filtering whole saliva in an added step. The
setup is a 1-mL plastic syringe filled with
1 gram of potato starch. A small 0.45-μm
filter is placed at the tip. Saliva is added to
the top and pressed through the syringe
using the plunger. "It really works quite
well," Wong says.
Cost:
$10/assay once it's set up
Considerations:
When the Israeli group
removed amylase, they used a 2-D gel to
reveal 15 previously undetected proteins
close to 60 kDa. In Wong's lab, a postdoc
is still working on the technique. "The data
shows that, at least on a 1-D gel, we can
see that amylase band disappearing," he
says. Amylase has been shown to bind
starches, but does the new method pull out
other things as well? "The immediate question
we're asking right now is, 'In addition
to amylase, are other proteins remaining
behind or are they being depleted?'"
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Lit Probe
User:
Akhilesh Pandey, associate professor,
Johns Hopkins University
Project:
Validating potential biomarkers for
early detection in pancreatic and breast cancer
Problem:
There are so many potential candidate
biomarkers needing validation that it's
difficult for researchers to know which ones
to pick to invest time and money. The choice
often involves a rushed "cherry picking" of the
candidates they are most familiar with. Pandey
recently served on a nonprofit panel looking to
fund validation work for 60 different potential
biomarkers, but it proved challenging to pick
which biomarker candidates should get priority.
Solution:
In collaboration with several other
scientists, Pandey pored over ~50,000 published
articles on pancreatic cancer. They
started with a broad list of any data on mRNA
and proteins in pancreatic cancer. They divided
this set into type of pancreatic cancer and the
cell type where overexpression was observed.
Then, they asked, "Where are these molecules?"
They carried out a broader literature
search to pinpoint the tissues in which each
molecule had been localized. Finally, they
asked whether these molecules had also been
implicated in chronic pancreatitis, a potential
confounding factor. Pandey is planning
to publish this work and make a web-based
portal available with added, wiki-like features
so that the cancer researchers can add in both
published and unpublished results.
Cost:
7000 person-hours
Considerations:
Researchers considering
validation studies can employ this strategy
on a smaller scale for themselves instead
of rushing into experiments. "This is vital
because validation experiments are time
consuming, cost money and yet are not
'glamorous.' It is important to get it right by
working on a candidate biomarker with a
higher likelihood of success," he says.
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Niche Finder
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2D gel of C.glutamicum proteins
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© Research Center Jülich
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User:
James Mobley, director of the urologic
and clinical proteomics facility, University
of Alabama at Birmingham
Project:
Developing lipid and protein biomarkers
for pancreatic cancer using serum,
plasma, and urine
Problem:
Mobley works with beginning
biomarker researchers who are often caught
in a Catch-22: In order to get funding for
in-depth prospective trials, they need to
spend money generating pilot data. When
researchers came to him hoping to identify protein biomarkers for pancreatic cancer,
they were faced with a mountain of choices,
including which fluids and tissues to analyze
and which platform (low-, medium-, or highthroughput)
to choose.
Solution:
They strategized to get one step
above what others have published on blood
and urine samples. Most previous studies
used small, pooled sample sets combined
with low-throughput platforms, such as 2-D
gels, used to pinpoint and identify proteins.
In this case, "there didn't seem to be a
whole lot of promise there," Mobley says.
For the few high-throughput approaches
there were some protein differences
between diseased and healthy states, but
none of them investigated urine samples.
"So we thought, if we do the study using [a
high-throughput technology] in matched
plasma, serum, and urine samples, there's
probably a good chance that we'll see some
differences and hopefully be able to differentiate
pancreatitis versus cancer."
Cost:
$7/sample for basic high-throughput
profiling
Considerations:
When funding is at a
minimum, investigate lower-cost technologies
that have yielded results, and know precisely
what experimental pieces may have
been missing. In the end, "in many cases, you
are left with partially reinventing the wheel,
but when that is the case, then at least make
a better wheel," he says.
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Searching Low
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Immunohistochemical staining for multiple biomarker targets in nasopharyngeal carcinoma tissue
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Courtesy of William Cho
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User:
William Cho, scientific officer in clinical
oncology at Queen Elizabeth Hospital,
Hong Kong
Project:
Comparing serum proteins of lung
cancer patients who smoked and never
smoked to those of healthy controls
Problem:
Using protein fractionation
methods, even after increasing the numbers of
fractions to get better resolution, the researchers
were missing low-abundance proteins
present in the serum and plasma. In addition,
this method is "quite tedious, less reproducible
when you use the manual method, and more
costly," Cho says. They wanted a method to
help dig into less-abundant serum proteins.
Solution:
In late 2005, Cho's lab tried a
technology designed to enhance the lowabundance
proteins (Equalizer Beads, a
product now called "ProteoMiner beads"
sold by Bio-Rad). The technology works by
having beads bound to a library of millions
of different hexapeptides (ligands). Each
bead-peptide combination binds to a different
protein in your serum sample. The
number of different bead-peptides available
for binding is relatively equal, so a large
percentage of the highly abundant proteins
don't find ligands and are washed away. The
process thus equalizes the amounts of highand
low-abundance proteins in your sample.
The assay can take about a week to set
up, Cho says. They found a small panel of
low-abundance proteins less than 1 nanogram
per mL, and are working on identifying
these using mass spectrometry.
Cost:
$100/sample using the ProteoMiner
Introductory Kit (or $72/sample using the
full kit)
Considerations:
Because the proteins are
"equalized," you can capture them but you
can't quantify them. Cho says you may still
be able to quantify later on, using the original
crude serum and a proteomics platform.
Cho's isn't the only system out there for this;
other companies such as Beckman Coulter
and Sigma Aldrich sell antibody-based kits
to deplete high-abundance proteins.
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Membrane Proteins
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Endothelial cells in cell culture.
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Courtesy of Christoph Roesli
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User:
Christoph Roesli, postdoc, Institute of
Pharmaceutical Sciences, Zurich, Switzerland
Project:
Identification of membrane protein
biomarkers to develop antibody-based
therapies for cancer
Problem:
Membrane proteins are often
difficult to identify using proteomics tools
because they are present in low abundance
and less soluble in water than intracellular
proteins. What's more, they often come with
chemical modifications, such as glycosylation
attachments and bonds formed between
cysteine amino acids on the proteins. Such
modifications can hinder proteomics studies
by making proteins difficult to digest with
enzymes and difficult to analyze.
Solution:
About five years ago, Roesli's
colleague developed a way to capture proteins
of interest by flushing the whole blood
system of living mice with biotin, which
modifies proteins on endothelial cells and
in close proximity to blood vessels. After
collecting and processing tissue of interest,
they capture the proteins using a streptavidin
sepharose column.
Last year, Roesli wanted to further
improve the biotinylation reaction by adding
two steps to break cysteine bonds and to
remove N-linked glycan chains, respectively.
After several rounds of optimization,
the combination of tris-(2-carboxyethyl)
phosphine and N-ethylmaleimide for cysteine
bond breakage and PNGase F for the
removal of N-linked glycans worked best.
Cost:
less than $100/sample for the whole
process
Considerations:
Commercial kits are
available for the biotinylation reactions, but,
Roesli says, "almost all people I talked with
say they have problems with the systems." If
you're new to the method, don't always trust
the kits. Expect to spend at least a month or
two optimizing conditions in your own lab.
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Main techniques for cancer biomarker discovery and validation
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Description |
Pros |
Cons |
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Two-dimensional gel electrophoresis
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An established method for identifying proteins by separating them based on charge across a defined pH gradient in one direction, and then by mass in the other direction. |
1) Ability to simultaneously monitor thousands of proteins
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1) Lack of throughput potential and reproducibility
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| 2) Compatible with various staining methods for protein identification |
2) Difficulties in resolving highly basic, high-molecular-weight, or low-abundance proteins |
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Matrix-assisted desorption/ionization time of flight (MALDI-Tof) mass spectrometry
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A method that ionizes proteins while keeping them intact, this can be used to identify proteins by mass, and in some variations, by sequence. |
1) Same-day data acquisition
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1) Usually compatible with a narrow range of protein masses
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| 2) Highly automated, good for large numbers of samples |
2) Peak intensity varies inexplicably between different proteins and experiments, but a two- to four-sample replicate may improve reproducibility |
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Enzyme-linked immunosorbent assay (ELISA)
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The traditional method of validating candidate biomarkers, this is an antibody-based method that captures and helps in quantification of specific proteins. |
1) Commonly used for low-abundance proteins;
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1) Dependent on antibody availability or quality
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| 2) Can detect proteins in the picomolar to nanomolar range |
2) Too expensive to implement on a large scale |
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