http://www.springerprotocols.com/cdp/access/showWebFeedListing This feed provides the latest 25 protocols in the given category. http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_1 The era of increased application of pharmacodynamic biomarker measures for early-phase drug development is upon us in response to the introduction to the clinic of targeted therapeutics. This unprecedented opportunity to perform measures of human physiology responding to pharmacologic intervention requires an understanding of sample collection, handling (preanalytical variables), and assay qualification for the results to be informative and allow decisions to be made on the development of the therapeutics under investigation. The literature is replete with biomarkers for many different applications from diagnostic to prognostic to pharmacodynamic. However, few studies have either described fully or even undertaken the necessary studies into each stage of the measurement of a biomarker from collection through to assay. In this chapter, we present insight into some of these issues with the aim of increasing the general understanding of the use of biomarkers in clinical development. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_10 Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential in order to reduce the cost of discovery and increase the throughput. In this chapter, we will discuss and describe a case study of a unique proteomic method that uses a non-gel, label-free LC/MS-based protein quantification technology. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_11 Proteomic analysis has proved to be key to determining drug mechanisms and assessing toxicologic potential during preclinical screening studies. A major goal in proteomics is to accurately measure changes in the relative abundance of large sets of proteins in complex biological systems as a function of experimental parameters, such as drug dose or exposure time. Until recently, top-down quantitative proteomics has been restricted to two-dimensional gel analyses or two-plex mass tagging. A new top-down approach based on isobaric mass tagging (ExacTag) for highly multiplexing (up to 10-plex) protein quantification is presented, involving chemically tagging cysteine or lysine residues of intact proteins isolated from cells, tissues, or biological fluids. As many as 10 labeled samples are then combined, fractionated, proteolytically digested, and analyzed by gel electrophoresis or liquid chromatography–tandem mass spectrometry. Proteins are identified using public domain search engines, such as Mascot (Matrix Science Ltd., London, UK) and quantified using an in-house developed software package. During the fragmentation, the tag-labeled peptides generate a set of low mass reporters that are unique to each sample. Measurement of the intensity of these reporters allows the relative quantification of the peptides and consequently the proteins from which they originated. The capabilities of the approach are demonstrated by analysis of the HeLa cell nucleolar proteome after treatment with the metabolic inhibitor actinomycin D for various time periods. A total of 440 proteins are qualitatively identified and quantified. The quantification data demonstrate that the nucleolar proteome changes significantly over time in response to differences in growth conditions, which is consistent with previous observations from several groups. The highly multiplexed and quantitative nature of the new technology should herald in new opportunities to provide diagnostic and functional insights into the proteomics discovery process. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_12 The ProteinChip SELDI System and chip arrays provide a sensitive, high-throughput methodology for protein biomarker discovery. The combination of retentate chromatography and time-of-flight mass spectrometry allows for the detection of increased peak numbers even when processing microliter sample volumes. The multiple chip chemistries allow the flexibility for user-defined protocols that can facilitate protein purification strategies. In addition, ProteinChip arrays can be designed to characterize antibody-antigen and other protein-protein interactions. This review will update the reader on the current SELDI methods and protocols that are especially pertinent to protein biomarker discovery. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_13 The sandwich ELISA microarray is a powerful screening tool in biomarker discovery and validation because of its ability to simultaneously probe for multiple proteins in a miniaturized assay. The technical challenges of generating and processing the arrays are numerous. However, careful attention to possible pitfalls in the development of one’s antibody microarray assay can overcome these challenges. In this chapter, we describe in detail the steps that are involved in generating a reliable and reproducible sandwich ELISA microarray assay. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_14 Metabonomics as an important component of functional genomics and system biology has gained increasing interest in drug development and biomarker discovery. Comprehensive metabonomics investigations are primarily a challenge for analytical chemistry. The main advantages of liquid chromatography–mass spectrometry (LC-MS) technique include high sensitivity, high resolution, and wide dynamic range. LC-MS–based technology platforms combined with multivariate statistical methods are used to explore the complex metabolite patterns of biofluids. In this chapter, the methodology and application of high-performance liquid chromatography (HPLC)-MS–based metabonomics in biomarker discovery are reviewed. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_15 Gas chromatography–mass spectrometry (GC/MS)-based metabolomics profiling methods have been developed and used for plant metabolite profiling since the 1980s. Only during the past few years has the technology been more widely used for metabolomics studies in animals and humans with the aim of toxicology and biomarker discovery, disease diagnosis and classification. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_16 Metabolomics provides a powerful set of tools for pharmaceutical and clinical research in a number of important areas that include drug development, early disease detection, patient stratification for treatment, and information on disease processes. With its ability to discover new metabolic markers, metabolomics (as well as metabolic profiling and metabonomics) is highly effective for drug development by providing early preclinical indications of efficacy and toxicity. The most information-rich techniques currently employed in metabolomics-based studies today are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). NMR spectra of untreated biosamples provide an overview of all metabolites present, and the complete spectrum can be used as a fingerprint of metabolic status. Analysis by multivariate statistical methods is used to identify potential biomarkers of altered metabolism that can improve the understanding of the health and disease processes. Current trends and recent advances in NMR-based metabolomics are focused on the development of advanced NMR methods, improved multivariate statistical data analysis, and a number of efforts to identify altered metabolites and pathways. Applications in the areas of toxicology, inborn errors of metabolism, cardiovascular disease, and cancer detection are described, and the prospects and the future directions of the technology are highlighted. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_17 In recent years, proteomics has driven developments of mass spectrometric approaches. Simultaneously, the research community has regained a major interest in lipids, with mass spectrometry unambiguously facilitating the development of lipidomics. Quantitative determination of molecular lipids is essential for addressing the role of lipids in cellular membranes and in metabolic dysfunctions, potentially leading to a disease state. Lipidomics has therefore evoked great interest in academic research laboratories and in the pharmaceutical industry, particularly in biomarker and drug discovery. A high-throughput oriented lipidomics methodology enabling quantitative analysis of the glycerophospholipidome in an automated fashion is described in this chapter. The methodology explicitly shows enormous potential and promises to play a key role in cell biology, molecular medicine, and drug discovery. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_2 Large-scale gene expression profiling with microarray platforms represents a new approach to identify much needed, novel mechanism-based biomarkers of toxicity for use in preclinical and clinical studies. These biomarkers may have diagnostic and/or predictive values and may consist of single gene products or of gene sets or gene expression signatures. Derivation and validation of these molecular markers involves supervised classification methods of reference data with sophisticated statistical methodologies. In this chapter, we review the methods for the identification and development of toxicity biomarkers with gene expression profiling. This chapter also describes how these novel multigene molecular markers can be integrated in a discovery pipeline, using the examples of hepatotoxicity, nephrotoxicity, and blood-based markers to illustrate successful or promising applications in toxicology. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_3 One of the primary goals of genome-wide expression profiling is to identify subsets of gene transcripts that can be associated with specific biological conditions. Once these gene expression “signatures” have been elucidated, they can be used in screening assays to identify compounds that induce similar gene expression changes. To increase the throughput of these screening assays, we have optimized the development of a fluorescent microsphere–based, flow cytometric platform that allows the specific and sensitive screening of up to 100 transcripts per sample in a 96-well plate format. This chapter will outline experimental details of such an experiment using an estrogenic gene expression signature as a specific example. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_4 Biomarkers have shown great potential in molecular classification and targeted treatment of human diseases. Biomarkers are also expected to play an increasingly important role in all phases of drug development as well as regulatory decision making. However, translating biomarker discovery into clinically useful tests in a time- and cost-effective manner remains a significant challenge. Real-time polymerase chain reaction (PCR) technology, in particular TaqMan®-based real-time PCR gene expression assays, provides a simple, robust, and practical tool that has shown great potential in bridging the gaps between biomarker discovery and clinical practice. In this chapter, we will survey the principle of this technology and its wide applications in biomarker discovery and validation. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_5 Serial analysis of gene expression (SAGE) has been extensively used to evaluate gene expression in a variety of biological contexts. In this review, we provide a general overview of the SAGE methodology and its major applications. Furthermore, we provide a detailed, day-by-day based protocol for SAGE. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_6 The data generated from the Human Genome Project has led to an explosion of technology for low-, medium-, and high-throughput genotyping methods. Pyrosequencing is a genotyping assay based on sequencing by synthesis. Short runs of sequence around each polymorphism are generated, allowing for internal controls for each sample. Pyrosequencing can also be used to identify triallelic, indel, and short-repeat polymorphisms, as well as determining allele percentages for DNA methylation or pooled sample assessment. Assays details for pyrosequencing of clinically relevant polymorphisms and DNA methylations are described in this chapter. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_7 There are a number of approaches that have been used in the past to describe and analyze the hormonal influences and mechanisms that govern primate endometrial responses as well as the regulation of cellular responses in many complex heterogeneous tissues. These have included gross anatomy, morphology/histology, hormonal manipulation, steroid binding assays, and immunohistochemical and in situ hybridization analyses. Transmission and scanning electron microscopy as well as ultrasound have also been used to study uterine (endometrial) structure. Recently, a number of new and powerful cellular and molecular techniques have been added to our arsenal of approaches to study tissue and cell-type gene and protein expression. These include quantitative (real-time) PCR analysis of gene expression, differential display, gene microarray analyses, proteomic analysis, and laser capture microdissection (LCM). LCM is a new technology that has substantially expanded our ability to examine cell-type–specific and region-specific responses in complex cellular tissues. Importantly, this technique allows the retrieval of specific cells from specific morphologic units within the tissue of interest. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_8 Two-dimensional polyacrylamide gel electrophoresis (2-DE) is one of the most widely used and versatile methods of protein expression profiling among a rapidly growing arsenal of proteomics technologies. 2-DE combines two orthogonal and independent electrophoretic steps: isoelectric focusing (IEF) and sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE). At present, 2-DE is capable of simultaneously detecting and quantifying up to several thousand protein spots in the same gel image. As an example to illustrate the power of 2-DE, we provide comprehensive step-by-step instructions for the application of 2-DE to clinically collected human plasma samples to determine whether specific plasma proteins or protein expression patterns could serve as biomarkers for the development of a specific adverse side effect that arises upon treatment with an experimental drug. These instructions provide detailed information on how to deplete high-abundant proteins from human plasma, apply the depleted plasma proteins to immobilized pH gradient gels, perform IEF and SDS-PAGE separation, and perform silver staining to visualize proteins. The basic 2-DE protocol described here could easily be applied to other tissue types. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-463-6_9 Difference in-gel electrophoresis (DIGE) is a recent adaptation of conventional two-dimensional gel electrophoresis (2-DE) that incorporates novel fluorescent labels, has multiplex attributes, and boasts software-assisted image analysis. Combined, these characteristics offer significant benefits in accuracy and reproducibility to quantify differential protein expression levels between biological samples. The DIGE technique and materials required to perform it are described in detail within. The principles behind consistent gel image acquisition and reliable image analysis are also considered. Within the context of biomarker and drug target discovery, this method simplifies analysis, increases sample throughput, and represents a reliable 2-DE platform. 2008-03-10T04:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_1 Pharmacogenomics may have a deep impact on every drug treatment protocol to bring the right drug to the right patient. While pharmacogenomics can help achieve individualized medicine, the study of systems biology can help us understand the key issues in pharmacogenomics at different levels. These key issues include the associations between structure and function, the correlations between genotype and phenotype, and the interactions among gene, drug, and environment. Utilizing bioinformatics in pharmacogenomics that is conducted in a systemic way can help integrate information from different levels. At the molecular level, the detailed features of a gene and the relationship between genetic structure and function need to be explored. These detailed features include sequence analytic information such as sequence retrieval and structural modeling, sequence varia tion information, and sequence patterns that can correlate sequence structure to functional motifs. At the cellular level, the interactions and networks among those molecules should be examined. Higher degrees of understanding at the tissue and organism levels can help establish the correlations between genotype and pheno-type. The application of bioinformatics methods in pharmacogenomics and systems biology should enable a more profound understanding of diseases at different levels and lead to both individualized and systems medicine. To facilitate up-to-date bio-informatics support, an integrated search engine and updated collections of tools are freely available at http://sysmed.pharmtao.com. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_10 Pharmacological treatment in Alzheimer's disease (AD) accounts for 10–20% of direct costs, and fewer than 20% of AD patients are moderate responders to conventional drugs (donepezil, rivastigmine, galantamine, meman tine), with doubtful cost-effectiveness. Both AD pathogenesis and drug metabolism are genetically regulated complex traits in which hundreds of genes cooperatively participate. Structural genomics studies demonstrated that more than 200 genes might be involved in AD pathogenesis regulating dysfunctional genetic networks leading to premature neuronal death. The AD population exhibits a higher genetic variation rate than the control population, with absolute and relative genetic vari ations of 40–60% and 0.85–1.89%, respectively. AD patients also differ in their genomic architecture from patients with other forms of dementia. Functional genomics studies in AD revealed that age of onset, brain atrophy, cerebrovascular hemodynamics, brain bioelectrical activity, cognitive decline, apoptosis, immune function, lipid metabolism dyshomeostasis, and amyloid deposition are associated with AD-related genes. Pioneering pharmacogenomics studies also demonstrated that the therapeutic response in AD is genotype-specific, with apolipoprotein E (APOE) 4/4 carriers the worst responders to conventional treatments. About 10–20% of Caucasians are carriers of defective cytochrome P450 (CYP) 2D6 polymorphic variants that alter the metabolism and effects of AD drugs and many psychotropic agents currently administered to patients with dementia. There is a moderate accumulation of AD-related genetic variants of risk in CYP2D6 poor metabolizers (PMs) and ultrarapid metabolizers (UMs), who are the worst respond ers to conventional drugs. The association of the APOE-4 allele with specific genetic variants of other genes (e.g., CYP2D6, angiotensin-converting enzyme [ACE]) negatively modulates the therapeutic response to multifactorial treatments affecting cognition, mood, and behavior. Pharmacogenetic and pharmacogenomic factors may account for 60–90% of drug variability in drug disposition and pharma-codynamics. The incorporation of pharmacogenetic/pharmacogenomic protocols to AD research and clinical practice can foster therapeutics optimization by helping to develop cost-effective pharmaceuticals and improving drug efficacy and safety. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_11 Asthma is a common disease characterized by airway inflammation and bronchorestriction. There are several common categories of medications for treating asthma; however, not all asthmatics have the same response to these medications, some of which are adverse responses that are potentially life threatening. Because interindividual responses to asthma medications can vary considerably, the potential for genetic contributions to variable drug responses is significant. This chapter reviews the most common biological pathways targeted by asthma therapy and briefly discusses the genetic contribution to varied responses to asthma therapy for four common types of asthma medications: β-agonists, anticholinergics, leukotriene modifiers, and corticosteroids. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_12 Functional studies can be utilized to give importance/relevance to clinical associations. Once a clinical genetic or pharmacogenetic association is found, molecular studies can be utilized to explore the mechanism for the association. By employing cells in culture or transgenic mice modified with specific variant genes or sequence polymorphisms of interest, pathophysiological processes and response to pharmacological agents may be tested under conditions that are not approachable in human patients. These mechanistic studies may be particularly important when it comes to pharmacogenetic associations by providing significant, clinically relevant insights into the variable responses patients show to drug therapy. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_13 It is anticipated that unraveling the human genome will have a direct impact on the management of specific diseases. Variations or mutations in genes involved in drug metabolism or disease pathophysiology in gastroenterology and hepatology are expected to have effect on response to therapy. The spectrum of diseases is vast. Thus, we focus this review on clinical pharmacogenetics of inflammatory bowel disease, Helicobacter pylori infections, gastroesophageal reflux disease, irritable bowel syndrome, liver transplantation, and colon cancer. Although only a few genotyping tests are used regularly in clinical practice, we anticipate that in the future there will be more routine use of many of the tests described in this review. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_14 Rheumatoid arthritis (RA) is a systemic inflammatory arthritis that leads to severe joint damage and is associated with high morbidity and mortality. Disease-modifying antirheumatic drugs (DMARDs) are the mainstay of treatment in RA. DMARDs not only relieve the clinical signs and symptoms of RA but also inhibit the radiographic progression of disease. Recently, a new class of disease-modifying medications, the biologic agents, has been added to the existing spectrum of DMARDs in RA. However, patients' response to these agents is not uniform, with considerable variability in both efficacy and toxicity. There are no reliable means of predicting an individual patient's response to a given DMARD prior to initiation of therapy. In this chapter, the current published literature on the pharmacogenomics of traditional DMARDs and the newer biologic DMARDs in RA is highlighted. Pharmacogenomics may help individualize drug therapy in patients with RA in the near future. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_15 Cancer pharmacogenetics is a burgeoning field. There are now many published associations between genotype and outcome or toxicity from chemotherapy treatment. Performing pharmacogenetics studies in cancer requires careful consideration of the sample type to be used (germline vs tumor); the genotyping platform to be used (medium, low, or high throughput); and the analysis and reporting of associations and observations. 2008-03-01T05:00:00Z http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-205-2_16 The development of vaccines, conventional protein based as well as nucleic acid based vaccines, and their delivery systems has been largely empirical and ineffective. This is partly due to a lack of methodology, since traditionally only a few markers are studied. By introducing gene expression analysis and bioinformatics into the design of vaccines and their delivery systems, vaccine development can be improved and accelerated considerably. Each vaccine antigen and delivery system combination is characterized by a unique genomic profile, a “fingerprint” that will give information of not only immunological and toxicological responses but also other related cellular responses e.g. cell cycle, apoptosis and carcinogenic effects. The resulting unique genomic fingerprint facilitates the establishment of molecular structure – pharmacological activity relationships and therefore leads to optimization of vaccine development. 2008-03-01T05:00:00Z