American journal of pharmacogenomics : genomics-related research in drug development and clinical practice最新文献

The genomic revolution has created a wealth of information regarding the fundamental genetic code that defines the inner workings of a cell. However, it has become clear that analyzing genome sequences alone will not lead to new therapies to fight human disease. Rather, an understanding of protein function within the context of complex cellular networks will be required to facilitate the discovery of novel drug targets and, subsequently, new therapies directed against them. The past ten years has seen a dramatic increase in technologies that allow large-scale, systems-based methods for analysis of global biological processes and disease states. In the field of proteomics, several well-established methods persist as a means to resolve and analyze complex mixtures of proteins derived from cells and tissues. However, the resolving power of these methods is often challenged by the diverse and dynamic nature of the proteome. The field of activity-based proteomics, or chemical proteomics, has been established in an attempt to focus proteomic efforts on subsets of physiologically important protein targets. This new approach to proteomics is centered around the use of small molecules termed activity-based probes (ABPs) as a means to tag, enrich, and isolate, distinct sets of proteins based on their enzymatic activity. Chemical probes can be 'tuned' to react with defined enzymatic targets through the use of chemically reactive warhead groups, fused to selective binding elements that control their overall specificity. As a result, ABPs function as highly specific, mechanism-based reagents that provide a direct readout of enzymatic activity within complex proteomes. Modification of protein targets by an ABP facilitates their purification and isolation, thereby eliminating many of the confounding issues of dynamic range in protein abundance. In this review, we outline recent advances in the field of chemical proteomics. Specifically, we highlight how this technology can be applied to advance the fields of biomarker discovery, in vivo imaging, and small molecule screening and drug target discovery.

The estrogen receptors (ERs), ERalpha and ERbeta, play a central role in mediating the biological effects of estrogen. The transcription rate of estrogen target genes is determined by several parameters including the type of ligand, estrogen receptor subtype and isoform, as well as interactions with receptor-binding cofactor proteins. The ERs regulate gene expression by binding to specific response element sequences in the promoters of estrogen target genes. Alternative pathways have also been described in which the ERs modulate transcription indirectly, via protein : protein interactions. In this regulatory mode, which has been traced to activator protein (AP)-1-, cyclic adenosine monophosphate (cAMP)-, and Sp1-response elements, the ERs appear to be tethered to target gene promoters via heterologous transcription factors. It has been found that ERalpha and ERbeta have opposite effects on transcription mediated via the indirect mode of action. Moreover, recent studies suggest that ERbeta may inhibit the stimulatory effects of ERalpha on cellular proliferation. Estrogen is a key regulatory hormone that affects numerous physiological processes. Estrogen is required for female pubertal development and affects growth, differentiation and function of the female reproductive system. It has recently been suggested that estrogen also has an important role in the male urogenital tract. In addition, estrogens have profound effects in other tissues. For instance, in the skeleton estrogen prevents bone-resorption by inhibition of osteoclast function. Numerous reports have suggested that estrogen has a beneficial effect in the cardiovascular system and in the CNS; however, this has not been confirmed in randomized clinical trials. In fact, a large randomized trial on healthy postmenopausal women receiving oral estrogen plus progestin showed an increased incidence of cardiovascular disease. In addition, this study revealed an increased risk for dementia and impaired cognitive function in the group receiving oral estrogen/progestin. Additional clinical trials are required to determine which hormonal component causes these health risks or whether the effects were due to the combination of estrogen and progestin.

Among cancers, lung cancer is the single biggest killer in the US. It is estimated that lung cancer was responsible for 171900 newly diagnosed cases of cancer in the US in 2003, and for 157200 deaths. Over many years, however, there has been little improvement in the clinical outcome of lung cancer, and any improvement in the incidence or mortality from lung cancer can largely be attributed to smoking cessation and not to the success of therapy. The histopathology of lung cancer reveals that it is a disease with many faces. Lung cancer is often nonresponsive to traditional therapy, leaving few, if any, alternatives in the management of the advanced stages of the disease. The molecular pathogenesis of lung cancer, only recently illuminated, involves numerous molecular and cell biological changes revealing a very complex disease progression. Large-scale mRNA expression analysis has been recently used to classify lung cancers molecularly. These techniques have been used successfully to differentiate lung cancer histotypes based on patterns of genes expressed. The use of protein analysis to this end has also been attempted, with limited correlation with RNA experiments. This likely reflects the limited sensitivity of the technologies and complex, poorly understood post-synthesis protein modifications. In any event, there have been great strides made in understanding the nature of lung cancer from a molecular perspective; these effects represent a great advancement in the diagnosis and prognosis of lung cancer. Moreover, these advances may lead to the improvement of patient survival by guiding the choice of more efficacious therapy.

The standard methods for establishing the diagnosis of acute leukemias are cytomorphology and cytochemistry in combination with multiparameter immunophenotyping. Cytogenetics, fluorescence in situ hybridization, and PCR-based assays add important information regarding biologically defined and prognostically relevant subgroups, and allow a comprehensive diagnosis of well-defined subentities. In the clinical setting, a better understanding of the clinical course of distinct, biologically defined disease subtypes is the basis for a selection of disease-specific therapeutic approaches. As knowledge of deregulated pathways in leukemia increases and accelerates the development of new therapeutics, a detailed and comprehensive diagnostic tool is required. Microarray technology, which quantifies gene expression intensities of thousands of genes in a single analysis, has the potential to become an essential tool for the molecular classification of leukemias. It may, therefore, be used as a routine method for diagnostic purposes in the near future. Furthermore, gene expression profiling may also lead to the detection of new biologically defined and clinically relevant subtypes in leukemia and guide therapeutic decision-making in the future.

Genomics patents are controversial on religious, ethical, legal, and economic grounds. An economic approach is desirable for valuing the patent system generally, and genomics patents in particular, in terms of its stated constitutional objective, which is to 'promote progress'. Several types of criticisms and warnings have been issued regarding the suitability of genomics inventions for patent protection; here these are evaluated in the context of more general concerns about the efficacy of the patent system. As with the patent system more generally, it is difficult to specify an alternative mechanism for producing inventions that has attributes (such as decentralized resource allocation, speed of therapeutic discovery, and financing by beneficiaries) that are predictable enough to serve as a benchmark against which to judge the current regime, which is dominated by genomics patents. The current patent regime can be expected to produce commercializable therapies reasonably reliably, while many proposed alternatives hearken back to a regime that did not produce commercializable therapies with as great speed or variety. Therefore, the onus appears to lie on the critics to create a model with the desirable properties of the patent system, but with fewer of its acknowledged weaknesses, such as 'monopoly' pricing and 'patent thickets'.

Introduction: The hybridization intensities derived from microarray experiments, for example Affymetrix's MAS5 signals, are very often transformed in one way or another before statistical models are fitted. The motivation for performing transformation is usually to satisfy the model assumptions such as normality and homogeneity in variance. Generally speaking, two types of strategies are often applied to microarray data depending on the analysis need: correlation analysis where all the gene intensities on the array are considered simultaneously, and gene-by-gene ANOVA where each gene is analyzed individually.

Aim: We investigate the distributional properties of the Affymetrix GeneChip signal data under the two scenarios, focusing on the impact of analyzing the data at an inappropriate scale.

Methods: The Box-Cox type of transformation is first investigated for the strategy of pooling genes. The commonly used log-transformation is particularly applied for comparison purposes. For the scenario where analysis is on a gene-by-gene basis, the model assumptions such as normality are explored. The impact of using a wrong scale is illustrated by log-transformation and quartic-root transformation.

Results: When all the genes on the array are considered together, the dependent relationship between the expression and its variation level can be satisfactorily removed by Box-Cox transformation. When genes are analyzed individually, the distributional properties of the intensities are shown to be gene dependent. Derivation and simulation show that some loss of power is incurred when a wrong scale is used, but due to the robustness of the t-test, the loss is acceptable when the fold-change is not very large.

Small interfering RNA (siRNA) molecules are short sequences of double-stranded RNA 19-27 bp in length, which suppress expression of target genes by inducing the breakdown of the cognate mRNA through mechanisms that are still being elucidated. siRNA molecules can be chemically synthesized or prepared through digestion of larger double-stranded RNA molecules using recombinant dicer or RNAase III enzyme. siRNA molecules can also be encoded by plasmid or virus vectors or expressed in transgenic animals. Design of siRNA sequences that efficiently suppress target genes can sometimes be challenging, although digestion of large double-stranded RNA species with recombinant dicer or RNAase III may remove the necessity for testing multiple candidate siRNA. Exogenous siRNA can suppress translation for varying amounts of time depending on the half-life of the protein targeted. Vector-mediated approaches may improve duration but their use can be limited by the permanency and efficiency of transduction. Potential therapeutic targets for siRNA include viral and non-viral pathogens, cancer, neurodegenerative diseases, septic shock and macular degeneration. Suppression of expression via siRNA is also an extremely useful research tool for ascertaining gene function. Looking ahead to clinical applications, it will be important to know the consequences of inadvertent suppression of non-targeted sequences. If safety can be established, siRNA has the potential to significantly impact the field of molecular medicine.

The blood pressure (BP) response to any single antihypertensive drug is characterized by marked interindividual variation, and the known predictors of response are of limited value in identifying the optimum drug for an individual patient. Analysis of genetic variation has the potential to improve our understanding of determinants of antihypertensive drug response in order to individualize drug selection. Genetic variation can influence both pharmacokinetic and pharmacodynamic mechanisms underlying variation in drug response. Classic pharmacogenetic investigations have identified variations in single genes that have a large effect on antihypertensive drug metabolism and are inherited in a Mendelian fashion. These include a polymorphism in the CYP2D6 gene, encoding a cytochrome p450 family member involved in phase I drug metabolism, and polymorphisms in genes encoding enzymes involved in phase II drug metabolism, including N-acetyltransferase (NAT2), catechol-O-methyltransferase (COMT), and phenol sulfotransferase (P-PST, SULT1A1). Although these polymorphisms have major effects on the pharmacokinetic profiles of both commonly used antihypertensive drugs such as metoprolol (CYP2D6), and lesser used drugs such as hydralazine (NAT2), methyldopa (COMT), and minoxidil (SULT1A1), they have not been shown to influence variation in the antihypertensive effect of these drugs at conventional doses. Interest is now focused on identifying genetic polymorphisms that influence the pharmacodynamic determinants of antihypertensive response. Using a candidate gene approach, such polymorphisms have been identified in genes encoding alpha-adducin (ADD1), subunits of G-proteins (GNB3 and GNAS1), the beta(1)-adrenergic receptor (ADRB1), endothelial nitric oxide synthase (NOS3), and components of the renin-angiotensin-aldosterone system (angiotensinogen [AGT], angiotensin converting enzyme [ACE], the angiotensin type I receptor [AGTR1], and aldosterone synthase [CYP11B2]). These polymorphisms have been shown to influence the BP response to diuretics (ADD1, GNB3, NOS3, and ACE), beta-blockers (GNAS1 and ADRB1), ACE inhibitors (AGT, ACE, and AGTR1), angiotensin receptor blockers (ACE and CYP11B2), and clonidine (GNB3).An emerging consensus from these studies is that single gene effects on antihypertensive drug responses are small, and even the combined effects of all presently known polymorphisms do not account for enough variation in response to be clinically useful. New genome-wide scanning techniques may lead to the identification of genes previously unsuspected of influencing drug response. Additional requirements for pharmacogenetic approaches to become clinically useful are the characterization of the effects of haplotypes and multi-locus genotypes on drug response, and consideration of gene-by-environment interactions. Such studies will require huge sample sizes and novel statistical methods, but the theoretical and technical framework is in place to make t

The endometrium undergoes cyclic changes in response to circulating ovarian steroid hormones as it prepares for implantation. This dynamic tissue is well suited to microarray expression profiling for elucidation of molecular players participating in the maturation of the endometrium and during the process of implantation. Recent advances in sequencing the human and mouse genomes and the availability of microarray technology and bioinformatic analyses have made elucidating these molecular participants and dialogs a reality. Analysis of the window of implantation, a temporal and spatially unique period in which the endometrium is receptive to embryonic implantation, has revealed numerous processes to be occurring simultaneously or sequentially. These include cell cycle regulation, angiogenesis, immune modulation of implantation, defense mechanisms put into place by antibacterial agents and detoxicants, secretion of unique products, transport of ions and water, growth factor actions, steroid hormone action and metabolism, and production of extracellular matrix proteins, unique cell surface glycoproteins, and a variety of transcription factors, to name a few. Several groups have recently conducted studies with human endometrium, and remarkable similarities exist with mouse. Also, many genes and gene families involved in the unique differentiation process of stromal cell decidualization are conserved. In addition, infertility associated with endometriosis is partly implantation-based, and gene profiling of such tissue during the window of implantation has revealed additional insight into mechanisms underlying infertility in this disorder. Global profiling of genes in the endometrium, decidua, and at the interface between the trophoblast and the decidua, has provided remarkable in sight into endometrial maturation and implantation.

Dust mites are a major source of indoor allergens. They contain a large number of components that react with immunoglobulin (Ig) E in individuals with allergies and are capable of inducing sensitization, and allergic respiratory and cutaneous diseases. With a significant proportion of the population affected in some way by mite allergies, it is essential that we improve our understanding of these organisms so that control strategies could be defined and its allergens better understood. Thus, we have initiated a project using the expressed sequence tagging (EST) strategy to study the major species of dust mites associated with allergic diseases, in particular, the American house dust mite, Dermatophagoides farinae, as well as Blomia tropicalis, the most prevalent mite in domestic tropical dwellings. The work has recently been expanded to include 'storage' mites such as Tyrophagus putrescentiae, Acarus siro, Lepidoglyphus destructor, Glycyphagus domesticus, Suidasia medanensis, and Aleuroglyphus ovatus. More than 50% of the initial 3000 ESTs from the D. farinae and B. tropicalis dust mites showed significant matches to known genes and were categorized into eight functional groups (such as proteins involved in metabolism, gene expression, protein synthesis, cell signaling, etc.). Of specific interest, however, were the homologs to known mite allergens, in addition to a number of sequences bearing significant homology to allergens from non-mite sources previously not known to exist in mites. The availability of these allergen sequences has facilitated their expression and subsequent characterization in our laboratory in terms of their IgE-binding reactivity. The wealth of sequence information, generated via the EST project, has also facilitated the identification of polymorphic forms of allergens, the investigation of differential gene expression under various environmental conditions via DNA microarrays, as well as the analysis of protein level expression profiling via the proteomics approach. Additionally, ESTs have also ameliorated the understanding of the phylogenetic relationships between mites, and enabled the isolation of gene products crucial for life processes so that mite control strategies can be more effectively devised. Taken together, the utilization of the EST strategy has opened up numerous new avenues by which the allergist can engage more effectively in the study of dust mites with the ultimate aim of developing appropriate treatment regimens for mite-induced allergy.