Van Eyk, Dunn - Proteomic and Genomic Analysis of Cardiovascular Disease - 2003 (522919), страница 101
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This includes providing more focus in a given phase, simplifying clinical studies in order to shorten timelines,and providing a greater effort towards the discovery, and then utility, of biomarkers and surrogate endpoints as indicators of therapeutic benefit and clinical endpoints. Proteomic and genomic technologies applied to target identification can simultaneously identify genes and proteins that are co-regulated with drug targets.Both targets and co-regulated genes/proteins can be potential surrogate biomarkers for use in pre-clinical and clinical studies. This is an example of the growingintegration of the early and late stages of drug discovery and development.
Similarly, both of these technologies are being incorporated into clinical trial designsand are beginning to generate databases of individualized and population datathat should prove useful in understanding a disease state or the effects of specificdrug classes. One current problem with biomarkers is that it takes just as longand is just as expensive to discover the biomarker, as it is to do the clinical trials,thus potentially negating the utility of the biomarker in the first place. On theother hand, pharmacogenomics is now beginning to provide an objective measureof a drug’s biological efficacy, including its potential adverse effects.
However, itwill take a few more years and considerable clinical trial data to reveal the trueimpact of pharmacogenomics on general medical and healthcare practices, and ontarget discovery and lead compound design. Thus it seems apparent that of all thestages in the research and development (R & D) process, it is the clinical development phase that requires further evolution in its approaches to insure that attrition rates for new drug entities are reduced.Pharmaceutical research companies are thus at a crossroads in terms of howtheir drug discovery and development processes should be adjusted to account forthe current realities of clinical market needs, business forces, socio-economic determinants, and health- and managed-care policies.
Challenges to selecting themost pharmacologically accessible or “druggable” targets, with specific and optimal physicochemical, safety and bioavailability properties, are multi-faceted. Solving them will require the integration of technology platforms across the R & Dprocess in such a manner as to ensure predictive paradigms for drug action and21.2 Emerging Proteomic Technologies in R & Ddisease modification, whether at the pre-clinical or clinical stages. Proteomics, asan ever-evolving set of technologies, is certainly poised to play a significant role inmaking the drug discovery and development process more efficient and robust,and examples of its emerging utility in target identification and validation, drugsafety and biomarker discovery, are described below.21.2Emerging Proteomic Technologies in R & DThe enabling technologies that contributed to the success of the genome initiatives now provide new tools to examine complex biological systems and processes.To achieve the latter will require an automated, quantitative and global measurement of gene expression at the protein level [9, 12].Pharmaceutical companies have actively embraced the acquisition, developmentand application of proteomic technologies to drug discovery and the study of disease pathophysiologies.
The most widespread strategy for studying global proteinexpression in biological systems has of course employed two-dimensional polyacrylamide gel electrophoresis (2D-PAGE or 2-DE) followed by enzymatic degradation of isolated protein spots, analytical peptide mapping, and bioinformaticssearches for identity matching. Using this method, thousands of proteins can beresolved in a gel and their expression quantified [13, 14].
However, certain typesof proteins possessing important cellular functions are not easily analyzed usingthis strategy. These proteins include membrane, low copy number, highly basic,and very large (> 150 kDa) and small (< 10 kDa) proteins. To this end, the application of sample fractionation, narrow pH range immobiline strips, novel and/or serial solubilization approaches, and enhanced detection methods including fluorescence staining, has addressed partially the aforementioned deficiencies in 2-DEtechnology [15]. Fluoroscence 2D difference gel electrophoresis (2D-DIGE) is avariant of 2-DE that uses molecular weight- and pI-matched, spectrally resolvableCy dyes to label protein samples prior to 2-DE [16].
This approach allows multiplexing (multiple co-separation of samples on the same gel) that has been suggested to significantly increase the throughput, accuracy, ease and speed of comparison, while demonstrating an apparent 105 dynamic range in sensitivity. Nonetheless, both conventional 2-DE and 2D-DIGE have shortcomings that have necessitated the search for alternative approaches to assessing system proteomes on thelarge-scale required for drug research.New separation strategies have emerged that are amenable to mass spectrometric techniques as a way to meet the growing need for the higher-throughputand simultaneous monitoring of all types of proteins in a biological system.
For amore detailed understanding of these technologies, many of which are analyticalbased, the reader is directed to other chapters within this book or to recent comprehensive reviews [17, 18]. However, all the techniques mentioned below mustbe viewed as emerging only, and their true utility has yet to be fully evaluated.There is a dire need for advances in sample fractionation, both at the protein and36536621 Proteomics in Pharmaceutical R & Dpeptide level, and significant improvements in the informatics and software toolsnecessary to support the analysis and management of the massive amounts ofdata generated in the process. Thus, until such time as these analytical technologies are fully developed and validated, any proteomics initiative would be bestserved by still relying on complementary 2-DE methodology.An exciting and recent alternative to the traditional 2-DE approach for a comparative and quantitative global protein assessment is the isotope-coded affinitytag (ICAT) method combined with direct MS/MS analysis (as developed by RuediAebersold and his group at the Institute for Systems Biology) [17, 19, 20].
Thistechnology involves the cysteine-specific, covalent labeling of proteins with isotopically normal or heavy ICAT reagents, proteolysis of the combined, labeled proteinmixture, followed by the isolation and MS analysis of the labeled peptides [19].This approach offers the potential for high sensitivity, coverage and throughput,and the ability to be quantitative in its ability to assess differential expression. TheICAT technology has now been applied to the proteomic studies of yeast [19], human myeloid leukemia or HL-60 cells [21], and normal and metastatic humanprostate epithelial cells [20]. A number of improvements have been made to thetechnology since its initial implementation including optimized labeling conditions [22], enhanced software able to differentiate peptides based on their abundance [20], and the application of ESI-TOF MS [20] and MALDI Q-TOF [23] toaugment identification and quantification. Most recently, Aebersold’s group hasdescribed a new strategy based on the 2-DE separation of proteins labeled withICAT reagents, and their identification and quantification by MALDI-TOF [24].This ICAT variant seems particularly useful for the study of differentially processed or post-translationally modified proteins.
Another variation of the ICATapproach involves a phosphoprotein ICAT approach or PhIAT to quantify measurements of differences in phosphorylation state of proteins [25, 26]. The Aebersold group has also devised an ICAT variant using a solid-phase (i.e., beads) isotope tagging or SPAT approach that involves labeling post-proteolysis [27].
A sideby-side comparison with the ICAT method revealed that the SPAT approach issimpler (i.e., a single step for labeling and isolation of peptides), more efficient(i.e., almost exclusive recovery of cysteinyl peptides) and efficient (i.e., unaffectedby proteolytic enzymes, denaturants and detergents that would require their removal). Lastly, the commercialization of ICAT reagents by Applied Biosystems hasenabled the establishment of this technology in numerous labs, particularly thatof pharmaceutical and biotech (e.g., Celera and Oxford Glycosciences) companies,and the beginning of its wider application to quantitative proteome projects.The extension of ICAT beyond the choice of cysteine as a labeling site to otherfeatures has formed the basis for the global internal standard technology or GISTdeveloped by Regnier et al.
[28]. The GIST technology involves tryptic digestion ofsamples prior to their differential isotopic labeling of the resulting peptides, mixing of the samples, fractionation of the peptide mixture by RP-LC, and isotope ratio analysis by MALDI-MS and ESI-MS. This technology has the potential advantage of uniformity in the labeling of all peptides, accuracy in quantifying differential protein expression, and flexibility in MS analysis. All this should lend itself21.2 Emerging Proteomic Technologies in R & Dparticularly well to the assessment of post-translational modifications of proteinsfollowing regulated changes in cell function.Stults and colleagues at Genentech have developed an analytical procedure, referred to as the mass western experiment, which is based on ICAT methodology,but does not require electrophoresis or other initial purification steps prior toanalysis by LC-MS [29].
The underlying concept of this technology is that the specificity of the CID fragmentation pattern of a peptide is analogous to using an antibody for the identification of a protein as in Western blotting. This approach differs from true Western blots in that protein size cannot be obtained.
The masswestern experiment apparently maximizes sensitivity and reduces the possibilitythat some peptides go otherwise undetected as demonstrated by the application ofthis approach to the quantitative identification of the cell surface proteins prostatestem cell antigen and ErbB2 in prostate and breast tumor cell lines.An automated method named multidimensional protein identification technology or MudPIT, has been developed for the large-scale analysis of complex protein/peptide mixtures by Yates and co-researchers [30, 31]. This technology hasbeen impressive in its ability to identify large numbers of proteins, many infrequently seen in previous proteomic studies, including low-abundance proteins liketransmembrane proteins, transcription factors and protein kinases [31].
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