Want to hear what your colleagues have to say about the latest in
Clinical Proteomics? This study polled over 300 clinical scientists
to learn more about the tools and techniques used for protein
profiling and data management, problems and limitations with existing
technologies, and the reagents and instrumentation used on a daily
Advances in laboratory instrumentation and data management
technologies have led to the emergence of a new field called clinical
proteomics, which applies high-throughput protein analysis techniques
to identify protein expression patterns that are indicative of disease
states.**The Science Advisory Board wanted to examine this developing
field and profiled over 300 scientists currently conducting clinical
proteomics research in a comprehensive study. Rather than focusing on
genetic alterations that may lead to a particular disease, many
researchers believe that changes in protein expression patterns are
the most accurate way to identify diseases in their early stages and
to determine the most effective courses of treatment.**In fact, study
participants identified protein expression patterns associated with
diseases to be the most common objective of protein profiling
In contrast to existing diagnostic assays, which examine protein
biomarkers one at a time, clinical proteomics is based on creating
protein profiles that simultaneously detect hundreds or even thousands
of proteins in a single assay.**"I believe that the effectiveness of
clinical proteomics will hinge on two technological components: rapid,
multiplex protein detection assays and data analysis systems to
assimilate vast amounts of protein expression data from healthy and
diseased individuals into clinically relevant data sets," professes
Dr. Tamara Zemlo, Director of Scientific & Medical Communications for
The Science Advisory Board.**Although the description, clinical
precedes the word, proteomics, 67% of protein profiling assays are
performed in a basic research laboratory.
Until recently, two-dimensional polyacrylamide gel electrophoresis (2D
PAGE) was the dominant methodology for protein profiling.**While 2D
PAGE provides the capability to analyze hundreds of different proteins
in a single experiment, the technique has inherent limitations that
restrict its usefulness in a clinical setting.**Drawbacks to 2D PAGE
include limited throughput capabilities, requirements for large sample
volumes, gel-to-gel variability, and the inability to measure low
abundance proteins.**Although advanced techniques such as differential
in-gel electrophoresis (DIGE), which uses differentially labeled
protein populations to compare different samples on the same gel, are
extending the applicability of 2D PAGE, the future of clinical
proteomics appears to lie in two other technologies: mass spectrometry
and protein chips or protein arrays.**However despite this emphasis on
high throughput technologies, gel electrophoresis and immunoblotting
are the two most popular techniques for validating data from protein
Mass spectrometry analyzes proteins based on the mass-to-charge (m/z)
ratio of ionized peptides and proteins.**A typical mass spectrometer
consists of an ionization source, a mass analyzer, and a detector for
counting the number of analytes at each m/z ratio.**In addition, mass
spectrometers are often coupled with separation devices such as liquid
chromatography instrumentation.**Aside from providing rapid data about
the various proteins that are present in a biological sample, mass
spectrometry also offers information about posttranslational
modifications that may be associated with a particular disease state.*
Recent innovations in mass spectrometry include isotope-coded affinity
tagging (ICAT) to facilitate the analysis of complex protein mixtures
and imaging mass spectrometry, which provides spatial analysis of
protein patterns in tissue sections.**Although current mass
spectrometers are limited in their abilities to create reliable
protein profiles from unprocessed biological samples, it seems likely
that instruments with higher mass accuracy, increased dynamic range,
and better resolution will eventually appear, greatly extending the
usefulness of mass spectrometry in a clinical setting.
One of the most promising applications for mass spectrometry, from a
clinical proteomics perspective, involves detecting proteins that are
captured on protein chips, as exemplified by Ciphergen's ProteinChip
system.**Using a variety of hydrophobic, ionic, or metal affinity
chromatographic matrices and different reaction conditions,
ProteinChips can effectively segregate proteins in biological samples
based on the proteins' physical properties.**Protein identification is
accomplished through surface enhanced laser desorption ionization
(SELDI) coupled with a time-of-flight (TOF) mass analyzer.**The
potential usefulness of this system is evidenced by reported findings
from the Clinical Proteomics Program that was established as a joint
venture between the National Cancer Institute and the Food and Drug
Administration (FDA).**Although the program is only two years old,
researchers already have achieved impressive success in the prognosis
and diagnosis of ovarian cancer using protein chips and SELDI-TOF
Another type of protein chip that is commonly used for protein
profiling is the protein array.**Of the arrays of arrays used in
protein profiling experiments, 49% come from a commercial
supplier.Similar in concept to the DNA microarray, most protein arrays
consist of a matrix of capture agents that are attached to the surface
of glass slide.**Although serum is the most frequently used source of
samples used in protein profiling according to study particpants,
capture agents can be peptides, nucleic acid aptamers, antibodies, or
other types of proteins.**Researchers often use the same
instrumentation for producing and analyzing protein arrays as they do
for DNA microarrays.**However, there are significant differences
between nucleic acids and proteins, particularly in protein stability
and conformation requirements, which add an extra degree of challenge
to protein array studies.
"As a scientist with prior experience in developing diagnostic test
kits for the clinic, the major problem to overcome in applying
proteomics technologies in the clinic will be the speed and ease of
using the application. Most widely performed tests can be performed
within two to four hours with minimal manipulations. In addition, the
test results are frequently presented from the physician to the
patient with just as much ease within 48 hours of sample processing.
It seems that current proteomics technologies, 2-D gel
electrophoresis, lab-on-a-chip or "protein chip arrays" are more
complicated to perform, or will be more difficult to explain. These
issues are on top of the "minor" challenges for developing new tests.
For example, the FDA regulations required for new tests to supplant
existing gold standard diagnostic tests must show efficiencies in
sensitivity and specificity."
-Staff Scientist, North America
One of the most common types of protein array is the antibody array,
which consists of small amounts of many different antibodies or
antibody fragments spotted in a microarray format.**While it is easy
to obtain large amounts of individual antibodies, there are few
suppliers that can provide high quality, small quantities of the
thousands of different antibodies that are needed to produce a single
antibody array.**Given this limitation, study participants believe
that detecting proteins in low concentrations is the primary
shortcoming of arrays used for protein profiling.**Furthermore, there
are many proteins for which antibodies are not currently available.*
Most experts believe that traditional methods of antibody production
(i.e., animals and hybridoma cells) are not suitable for meeting the
needs of antibody arrayers.** Instead, bacterially produced
antibodies, such as those generated using phage display libraries,
seem to be the most promising approach for creating the diversity of
antibodies that are required for protein profiling.
Aside from the chip- and slide-based arrays described above, there are
several other types of protein arrays that are being used for protein
profiling.**For example, bead arrays consist of capture agents that
are attached to labeled microspheres, rather than to a planar surface.
*In this type of system, captured analyte molecules are detected by
flow cytometry.**Other protein array formats include microfluidic
lab-on-a-chip assays and systems that utilize innovative detection
methodologies, such as surface plasmon resonance.
Slightly more than one-third of the diagnostic and testing assays
developed by members of The Science Advisory Board using protein
profiling information are dedicated to cancer.**Other potential
applications of this technique include Autoimmune disorders,
infectious diseases, cardiovascular disease, and Alzheimer's are just
a few of the other areas that are likely to benefit from advances in
proteomic analysis.**In addition, researchers are using protein
profiling for drug discovery as well as for monitoring the efficacy
and side effects of therapeutic drug treatments.**
"Understanding the interaction among the different proteins [will be a
major challenge to applying proteomic technologies to clinical care].
No matter the methods that are in use today. What you see is a static
picture of something that has already happened. You do not know how
the procedure affected the system and you cannot distinguish the
disease-relevant reactions from the normal ones."
-Principal Investigator, Central/South America
However, before protein profiling is adopted as a routine clinical
methodology, reproducibility standards for proteomic patterns must be
established based on empirical data from many different patient
"The major challenge will be the reproducibility of results if only
small/limited samples are available. If three or more replicates are
needed time is also a limiting factor. One major problem might also be
inter-laboratory differences in sample processing resulting in
-Post Doctoral Fellow, Europe
The participants profiled believe that increased assay sensitivity is
the improvement most needed before protein profiling assays can be
used for disease diagnosis/prognosis in a clinical setting. Toward
this end, powerful bioinformatics tools are currently being used to
assimilate output from mass spectrometry and protein array studies
into retrospective or prospective data sets.**Those data sets, in
turn, serve as input for artificial intelligence systems, which
"learn" to recognize proteomic patterns associated with particular
disease states or physiological parameters.**"As levels of reference
data increase and as the accuracy and reproducibility of protein
detection technologies improve, I think that the field of clinical
proteomics will radically alter our current approaches to disease
diagnosis and treatment," predicts Zemlo.
Visit [Only registered users see links. ] to read
the results of this and other important studies.
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allied health professionals who convene electronically to express
their opinions about the tools and technologies transforming science
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I’d like to provide an update the “promise” of Ciphergen’s ProteinChip system mentioned in your repost of the Science Advisory Board article.
Vermillion, then known as Ciphergen, has since had its OVA1 test approved as the first proteomics-based in vitro diagnostic multivariate index assay (IVDMIA) for breast cancer. (bit.ly/seldi-vermillion)
OVA1 includes four novel protein biomarkers that were discovered and validated using the SELDI platform, a high-throughput biomarker discovery and protein-profiling tool. The SELDI platform enabled Vermillion to complete a 600-sample validation study in less than six months. Other technologies take the same time to screen 10–15 samples.
For more information about how Vermillion used SELDI, now sold by Bio-Rad, read a case study: bit.ly/seldi.
Protein Detection Business Unit
SELDI sucks when it comes to mass spectrometry. Has bad resolution, and biomarker studies show it has lousy reproducibility.
MALDI has much better resolution, sensitivity; and you can manipulate your biological fluids to clean them up and give better results.
Of course LC-MS-MS is the best in class for protein identification.
For more info check out the links in this old thread:
[Only registered users see links. ]
Here's an updated link to the "SELDI Controversy article"
----> [Only registered users see links. ]
And an excerpt (this is only ~50% of article)
SELDI allows researchers to capture proteins of interest on a chip and then analyse them by MS in a similar way to MALDI (matrix assisted laser desorption/ionisation) MS.
In MALDI, a biological sample is mixed with a matrix and deposited on a surface before allowing to dry, whereas in SELDI the sample is spotted on a surface that is modified to bind certain proteins while the rest of the sample is washed away.
This leads to simpler mass spectra with fewer background peaks to confuse the identification of low abundance species.
The 'controversy' surrounding the use of the technology originated with work published in the journal The Lancet that described the use of SELDI TOF (time-of-flight) MS techniques to detect the early stages of ovarian cancer.
In the article, Petricoin and Liotta described the use of the technology combined with a cluster analysis algorithm to determine identify the presence of early stage ovarian cancer. The findings were remarkable and the authors claimed a 94 per cent positive predictive value.
However, research published in the journal Bioinformatics that re-examined the earlier work by Petricoin and Liotta suggested that there were inconsistencies in the experimental procedure.
Indeed the authors wrote: "these concerns suggest that much of the structure uncovered in these experiments could be due to artefacts of sample processing, not the underlying biology of cancer."
According to Dr Nelson Cooke, marketing manager for Protein Detection at Bio-Rad: "the controversy has been whether or not you can really use the pattern based method that Petricoin published to distinguish between diseased and non-diseased states and thatissue has generated a negative image for the entire SELDI platform."
This is perhaps surprising as the issue with the techniques used has never been with the specific MS approach but rather with the sample preparation and data analysis steps.
Nevertheless, the controversy led to Ciphergen selling the instrument part of its business to Bio-Rad with the company announcing a name change to Vermillion as it refocuses on developing diagnostic tests using the technology.
Notice the mention of simpler mass spectra--the peaks are way too simple for accurate protein profiling or ID, they are usually too wide for ID, and cross-validation on a more sensitive machine shows multiple peaks where SELDI would show 1-wide prominent peak.
I'm not saying that the scientists didn't find valid biomarkers, just that the SELDI is a piece of crap, and a lousy investment.