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

Biological pathways represent the relationships (reactions and interactions) between biological molecules in the context of normal cellular functions and disease mechanisms. Understanding the roles of proteins and signaling pathways expressed within disease, and their link to drug discovery and drug development are central in today's target-driven pharmaceutical processes. This article gives an overview of proteomics strategies, including global expression analysis as well as focused approaches using multidimensional separation by both gel- and liquid-phase techniques linked to mass spectrometry, as applied to two of the pathways involved in inflammatory diseases. In primary human cell studies, our group has annotated and identified thousands of proteins using both electrospray ionization and matrix-assisted laser desorption ionization (MALDI)-sequencing technology. Annotations made from gel images and chromatography fractionation, interfaced to high-end mass spectrometry sequence and structure identity, are cornerstones in cutting-edge protein expression profiling. Regarding phosphorylation mechanisms of kinases, the quantitative stoichiometry can be determined using affinity probe isolations. Another strategy involves micro-preparative sample processing, which has been used to analyze single-target phosphoproteins and their relative phospho-stoichiometry.

No specific gene has been identified for any major psychiatric disorder, including schizophrenia, in spite of strong evidence supporting a genetic basis for these complex and devastating disorders. There are several likely reasons for this failure, ranging from poor study design with low statistical power to genetic mechanisms such as polygenic inheritance, epigenetic interactions, and pleiotropy. Most study designs currently in use are inadequate to uncover these mechanisms. However, to date, genetic studies have provided some valuable insight into the causes and potential therapies for psychiatric disorders. There is a growing body of evidence suggesting that the understanding of the genetic etiology of psychiatric illnesses, including schizophrenia, will be more successful with integrative approaches considering both genetic and epigenetic factors. For example, several genes including those encoding dopamine receptors (DRD2, DRD3, and DRD4), serotonin receptor 2A (HTR2A) and catechol-O-methyltransferase (COMT) have been implicated in the etiology of schizophrenia and related disorders through meta-analyses and large, multicenter studies. There is also growing evidence for the role of DRD1, NMDA receptor genes (GRIN1, GRIN2A, GRIN2B), brain-derived neurotrophic factor (BDNF), and dopamine transporter (SLC6A3) in both schizophrenia and bipolar disorder. Recent studies have indicated that epigenetic modification of reelin (RELN), BDNF, and the DRD2 promoters confer susceptibility to clinical psychiatric conditions. Pharmacologic therapy of psychiatric disorders will likely be more effective once the molecular pathogenesis is known. For example, the hypoactive alleles of DRD2 and the hyperactive alleles of COMT, which degrade the dopamine in the synaptic cleft, are associated with schizophrenia. It is likely that insufficient dopaminergic transmission in the frontal lobe plays a role in the development of negative symptoms associated with this disorder. Antipsychotic therapies with a partial dopamine D2 receptor agonist effect may be a plausible alternative to current therapies, and would be effective in symptom reduction in psychotic individuals. It is also possible that therapies employing dopamine D1/D2 receptor agonists or COMT inhibitors will be beneficial for patients with negative symptoms in schizophrenia and bipolar disorder. The complex etiology of schizophrenia, and other psychiatric disorders, warrants the consideration of both genetic and epigenetic systems and the careful design of experiments to illumine the genetic mechanisms conferring liability for these disorders and the benefit of existing and new therapies.

In the past 10 years, progress made in cancer biology, genetics, and biotechnology has led to a major transition in cancer drug design and development. There has been a change from an emphasis on non-specific, cytotoxic agents to specific, molecular-based therapeutics. Mechanism-based therapy is designed to act on cellular and molecular targets that are causally involved in the formation, growth, and progression of human cancers. These agents, which may have greater selectivity for cancer versus normal cells, and which may produce better anti-tumor efficacy and lower host toxicity, can be small molecules, natural or engineered peptides, proteins, antibodies, or synthetic nucleic acids (e.g. antisense oligonucleotides, ribozymes, and siRNAs). Novel targets are identified and validated by state-of-the-art approaches, including high-throughput screening, combinatorial chemistry, and gene expression arrays, which increase the speed and efficiency of drug discovery and development. Examples of oncogene-based, molecular therapeutics that show promising clinical activity include trastuzumab (Herceptin), imatinib (Gleevec), and gefitinib (Iressa). However, the full potential of oncogenes as novel targets for cancer therapy has not been realized and many challenges remain, from the validation of novel targets, to the design of specific agents, to the evaluation of these agents in both preclinical and clinical settings. In maximizing the benefits of molecular therapeutics in monotherapy or combination therapy of cancer, it is necessary to have an understanding of the underlying molecular abnormalities and mechanisms involved. This is the first part of a four-part review in which we discuss progress made in the last decade as it relates to the discovery of novel oncogenes and signal transduction pathways, in the context of their potential as targets for cancer therapy. This part delineates the latest discoveries about the potential use of growth factors and protein tyrosine kinases as targets for therapy. Later parts focus on intermediate signaling pathways, transcription factors, and proteins involved in cell cycle, DNA damage, and apoptotic pathways.

Background: Current structural genomics projects are being driven by two main goals; to produce a representative set of protein folds that could be used as templates for comparative modeling purposes, and to provide insight into the function of the currently unannotated protein sequences. Such projects may reveal that a newly determined protein structure shares structural similarity with a previously observed structure or that it is a novel fold. The manner in which structure can be used to suggest the function of a protein will depend on the number and diversity of homologous sequences and the extent to which these sequences are functionally characterized.

Method and results: Using sequence searching methods, we analyzed structural genomics target sequences to ascertain if they were members of functionally characterized protein families, protein families of unknown function, or orphan sequences. This analysis provided an indication of what could be expected to emerge from structural genomics projects. Matches were found to approximately 25% of the current functionally unannotated protein families in the PFAM database (protein families database of alignments and hidden Markov models). The 16% of strict orphan sequences will be the most problematic if their structures reveal novel folds. However, out of the remaining target sequences that match families whose members are largely of unknown function, 28% are particularly interesting in that they are part of protein families with considerable sequence diversity.

Conclusion: The determination of a new structure of a member of these families is likely to offer considerable insight into possible functional roles of these proteins even if it is a new fold. Mapping the sequence conservation onto the structure may reveal functionally important residues for further study by experimental methods.

Traditionally, anatomic staging systems have been used to determine predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in patients with cancer. With new targeted therapies, the role of biomarkers is increasingly promising, suggesting an integrated approach using the genetic make-up of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or in differential diagnosis (identifying individuals who are likely to respond to specific drugs). To be clinically useful, a marker must favorably affect clinical outcomes such as decreased toxicity, increased overall and/or disease-free survival, or improved quality of life. This paper focuses on possible clinical trial designs for assessing the utility of a predictive marker(s) for toxicity or clinical efficacy. We consider the scenario of single and multiple markers as well as present alternative solutions based on the prevalence of a marker. Our designs rest on the assumption that the methods for assessment of the biomarker are established and the initial results show promise with regard to the predictive ability of a marker. Additional research is clearly warranted to achieve the goal of 'predictive oncology'.

The epidemiologic approach enables the systematic evaluation of potential improvements in the safety and efficacy of drug treatment which might result from targeting treatment on the basis of genomic information. The main epidemiologic designs are the randomized control trial, the cohort study, and the case-control study, and derivatives of these proposed for investigating gene-environment interactions. However, no one design is ideal for every situation, and methodological issues, notably selection bias, information bias, confounding and chance, all play a part in determining which study design is best for a given situation. There is also a need to employ a range of different designs to establish a portfolio of evidence about specific gene-drug interactions. In view of the complexity of gene-drug interactions, pooling of data across studies is likely to be needed in order to have adequate statistical power to test hypotheses. We suggest that there may be opportunities (i) to exploit samples from trials already completed to investigate possible gene-drug interactions; (ii) to consider the use of the case-only design nested within randomized controlled trials as a possible means of reducing genotyping costs when dichotomous outcomes are being investigated; and (iii) to make use of population-based disease registries that can be linked with tissue samples, treatment information and death records, to investigate gene-treatment interactions in survival.

Most of the candidate gene studies in bipolar disorder have focused on the major neurotransmitter systems that are influenced by drugs used in the treatment of this disorder. The monoamine oxidase A (MAOA) and the tryptophan hydroxylase (TPH1, TPH2) genes are two of the candidates that have been tested in a series of association studies using unrelated or family-based controls. This review summarizes the existing association studies regarding these genes. Most of these studies were based on the unrelated case-control design with samples of 50 to 600 subjects. Regarding MAOA, three meta-analyses with partially overlapping samples supported a modest effect of this gene in bipolar disorder in female Caucasians. However, as several studies could not replicate these findings, more work is necessary to demonstrate unequivocally the involvement of MAOA in bipolar disorder and establish the biological mechanism underlying the genetic association. With respect to TPH1 and TPH2, the majority of studies did not provide evidence for an association between these genes and bipolar disorder. The genes are more likely to be related to suicidal behavior than to bipolar disorder.

Ovarian cancer is the leading cause of death from gynecologic malignancies among American women and the fourth most frequent cause of death from cancer in women in Europe and the US. Despite appropriate surgical and chemotherapeutic intervention, the 5-year survival in patients with metastatic cancer remains poor. Currently available screening methods, including CA125, additional biomarkers, and transvaginal ultrasound lack the necessary sensitivity and specificity to provide accurate and cost-efficient screening for the general population or the ability to assess who will benefit most from each treatment. These limitations have prompted the study of proteomic technology and its application in ovarian cancer diagnostics. Proteomics is the study of molecules in the functional protein pathways of normal or diseased states. Clinical trials are currently being conducted to assess the sensitivity and specificity of serum proteomic patterns and additional clinical trials are designed to evaluate the effects of molecularly targeted agents on protein signaling pathways in human subjects. Overcoming both scientific and practical limitations will lead to increased knowledge of deranged protein networks in cancer cells. Clinical trials in proteomics may result in improved early detection, better monitoring, new drugs and molecularly targeted therapeutics, and individualized therapies.

In the last few years, DNA methylation has become one of the most studied gene regulation mechanisms in carcinogenesis as a result of the cumulative evidence produced by the scientific community. Moreover, advances in the technologies that allow detection of DNA methylation in a variety of analytes have opened the possibility of developing methylation-based tests. A number of studies have provided evidence that specific methylation changes can alter the response to different therapeutic agents in cancer and, therefore, be useful biomarkers. For example, the association of the methylation status of DNA repair genes such as MGMT and MLH1 illustrate the two main mechanisms of response to DNA damaging agents. Loss of methylation of MGMT, and the subsequent increase in gene expression, leads to a reduction in response to alkylating agents as a result of enhanced repair of drug-induced DNA damage. Conversely, the increase in methylation of MLH1 and its resulting loss of expression has been consistently observed in drug-resistant tumor cells. MLH1 encodes a mismatch repair enzyme activated in response to DNA damage; activation of MLH1 also induces apoptosis of tumor cells, and thus loss of its expression leads to resistance to DNA-damaging agents. Other methylation-regulated genes that could serve as biomarkers in cancer therapy include drug transporters, genes involved in microtubule formation and stability, and genes related to hormonal therapy response. These methylation markers have potential applications for disease prognosis, treatment response prediction, and the development of novel treatment strategies.

Objective: The aim of this study was to address the presently controversial question of whether cytochrome P450 (CYP) 3A5 polymorphism is associated with hypertension.

Method: We studied 373 elderly (age > or =75 years) Finnish (Caucasian) patients from the ongoing DEBATE (Drugs and Evidence Based Medicine in the Elderly) trial. The patients were classified into those with a history of hypertension (n = 229) and those without a history of hypertension (n = 144) on the basis of a detailed questionnaire on each patient's medical history and an interview. The patients were genotyped for the CYP3A5 6986A/G single nucleotide polymorphism (SNP) [CYP3A5*1/*3 alleles].

Results: The proportion of individuals with the CYP3A5*1/*3 genotype, i.e. CYP3A5 expressors, was significantly higher among patients with a diagnosis of hypertension than among patients without (18.3% vs 9.0%, p = 0.016). The corresponding odds ratio was 2.26 (95% CI 1.17, 4.38). The allele and genotype frequencies for the two control SNPs, ABCB1 (MDR1) 3435C/T and SLCO1B1 521T/C, did not differ between the two groups.

Conclusion: This work lends support to the theory that the polymorphic CYP3A5 enzyme may be involved in regulation of blood pressure. The possible role of CYP3A5 as a genetic contributor to hypertension susceptibility warrants further study.