StudiesClinical Proteomics 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 research. 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 profiling experiments. 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 detection systems. 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.” -decipher07, 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.” -juanc16, 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 samples. “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 different results.” -TS, 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. ### Would you like to find out what your colleagues believe will be the major challenge in successfully applying proteomic technologies to clinical care? Please click here to read their opinions. [ View Current & Future Studies ] [ View Past Studies ] |
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