Pharmacogenetics, pharmacogenomics and airway disease

The availability of a draft sequence for the human genome will revolutionise research into airway disease. This review deals with two of the most important areas impinging on the treatment of patients: pharmacogenetics and pharmacogenomics. Considerable inter-individual variation exists at the DNA level in targets for medication, and variability in response to treatment may, in part, be determined by this genetic variation. Increased knowledge about the human genome might also permit the identification of novel therapeutic targets by expression profiling at the RNA (genomics) or protein (proteomics) level. This review describes recent advances in pharmacogenetics and pharmacogenomics with regard to airway disease.     

Advances in pharmacogenomic research and development

Technological achievements in the last 5 to 10 yr and their application to sequencing and polymorphism discovery in the human genome have fostered a renewed interest in the genetic basis of drug response. Consequently, the field of pharmacogenetics/pharmacogenomics has been gaining momentum, fueled not only on technology but also on results of empirical studies of the human genome and on genetic epidemiology studies of real drugs in patient populations. This review discusses some of the recent advances in pharmacogenomic research and development over the last few years that include understanding the architecture of the human genome, the creation of population deoxyribonucleic acid (DNA)/data banks, assessment of the clinical validity of genetic markers, and experience with regulatory aspects of pharmacogenomics.     

Dog models of naturally occurring cancer

Studies using dogs provide an ideal solution to the gap in animal models for natural disease and translational medicine. This is evidenced by approximately 400 inherited disorders being characterized in domesticated dogs, most of which are relevant to humans. There are several hundred isolated populations of dogs (breeds) and each has a vastly reduced genetic variation compared with humans; this simplifies disease mapping and pharmacogenomics.?Dogs age five- to eight-fold faster than do humans, share environments with their owners, are usually kept until old age and receive a high level of health care. Farseeing investigators recognized this potential and, over the past decade, have developed the necessary tools and infrastructure to utilize this powerful model of human disease, including the sequencing of the dog genome in 2005. Here, we review the nascent convergence of genetic and translational canine models of spontaneous disease, focusing on cancer.     

Pharmacogenetics and pharmacogenomics in oncology therapeutic antibody development

Pharmacogenetics and pharmacogenomics are keys to the success of personalized medicine, prescribing drugs based on a patient's individual genetic and biological profile. In this review, we will focus on the application of pharmacogenetics and pharmacogenomics in developing monoclonal antibody (MAb) therapeutics in oncology. The significance of pharmacogenomics in MAb therapeutics is highlighted by the association between polymorphisms in Fc receptors and clinical response to anti-CD20 MAb rituximab (Rituxan) or anti-ganglioside GD2 MAb 3F8, as well as the potential link between polymorphisms in HER2 and cardiac toxicity in patients treated with the anti-HER2 MAb trastuzumab (Herceptin). The dependence on gene copy number or expression levels of HER2 and epidermal growth factor receptor (EGFR) for therapeutic efficacy of trastuzumab and cetuximab (Erbitux), respectively, supports the importance of selecting suitable patient populations based on their pharmacogenetic profile. In addition, a better understanding of target mutation status and biological consequences will benefit MAAb development and may guide clinical development and use of these innovative therapeutics. The application of pharmacogenetics and pharmacogenomics in developing MAb therapeutics will be largely dependent on the discovery of novel surrogate biomarkers and identification of disease- and therapeutics-relevant polymorphisms. Challenges and opportunities in biomarker discovery and validation, and in implementing clinical pharmacogenetics and pharmacogenomics in oncology MAb development and clinical practice will also be discussed.     

Human genome project: pharmacogenomics and drug development

Now that all 30,000 or so genes that make up the human genome have been deciphered, pharmaceutical industries are emerging to capitalize the custom based drug treatment. Understanding human genetic variation promises to have a great impact on our ability to uncover the cause of individual variation in response to therapeutics. The study of association between genetics and drug response is called pharmacogenomics. The potential implication of genomics and pharmacogenomics in clinical research and clinical medicine is that disease could be treated according to the interindividual differences in drug disposition and effects, thereby enhancing the drug discovery and providing a stronger scientific basis of each patient's genetic constitution. Sequence information derived from the genomes of many individuals is leading to the rapid discovery of single nucleotide polymorphisms or SNPs. Detection of these human polymorphisms will fuel the discipline of pharmacogenomics by developing more personalized drug therapies. A greater understanding of the way in which individuals with a particular genotype respond to a drug allows manufacturers to identify population subgroups that will benefit most from a particular drug. The increasing emphasis on pharmacogenomics is likely to raise ethical and legal questions regarding, among other things, the design of research studies, the construction of clinical trials and the pricing of drugs.     

The use of single-nucleotide polymorphism maps in pharmacogenomics

Single-nucleotide polymorphisms (SNPs), common variations among the DNA of individuals, are being uncovered and assembled into large SNP databases that promise to enable the dissection of the genetic basis of disease and drug response (i.e., pharmacogenomics). Although great strides have been made in understanding the diversity of the human genome, such as the frequency, distribution, and type of genetic variation that exists, the feasibility of applying this information to uncover useful pharmacogenomic markers is uncertain. The health care industry is clamoring for access to SNP databases for use in research in the hope of revolutionizing the drug development process. As the reality of using SNPs to uncover drug response markers is rarely addressed, this review discusses practical issues, such as patient sample size, SNP density and genome coverage, and data interpretation, that will be important for determining the applicability of pharmacogenomic information to medical practice.     

High throughput genotyping technologies.

A comprehensive genetic map containing several hundred microsatellite markers resulted from a large microsatellite mapping project. This was the first real study that introduced high throughput methods to the genetic community. This map and the concurrent technological advances, which will briefly be reviewed, led to further numerous mapping investigations of simple and complex diseases. The annotated draft sequence of approximately three billion base pairs (bp) of the human genome has been completed much sooner than many imagined, due to considerable technological advancements and the international enterprise that resulted. This was a major development for the genetics community, but is only the precursor to the next phase of studying and understanding the variation within the human genome. The awareness of the differences may help us understand the effects on the genetics of the variation between individuals and disease. It is these variations at the nucleotide level that determine the physiological differences, or phenotypes of each individual, including all biological functions at the cellular and body level. Single nucleotide polymorphisms (SNPs) will provide the next high density map, and be the genetic tool to study these genetic variations. There are many sources of SNPs and exhaustive numbers of methods of SNP detection to be considered. The focus in this paper will be on the merits of selected, varied SNP typing methodologies that are emerging to genotype many individuals with the required huge number of SNPs to make the study of complex diseases and pharmacogenomics a practical and economically viable option.     

Detecting copy number variation in the human genome using comparative genomic hybridization

Among human beings, it was once estimated that our genomes were 99.9% genetically identical. While this high level of genetic similarity helps to define us as a species, it is our genetic variation that contributes to our phenotypic diversity. As genomic technologies evolve to provide genome-wide analyses at higher resolution, we are beginning to appreciate that the human genome has a lot more variation than was once thought. Array-based comparative genomic hybridization (CGH) is one of these technologies that has recently revealed a newly appreciated type of genetic variation: copy number variation, in which thousands of regions of the human genome are now known to be variable in number between individuals. Some of these copy number variable regions have already been shown to predispose to certain common diseases, and others may ultimately have a significant impact on how each of us reacts to certain foods (e.g., allergic reactions), medications (e.g., pharmacogenomics), microscopic infections (i.e., immunity), and other aspects of our ever-changing environment.     

风湿病治疗药物的药物基因组学研究及进展

风湿病的传统治疗以激素和甲氨蝶呤为代表的改善病情药物为主,随着分子水平研究的深入,以肿瘤坏死因子α阻断剂为代表的多种靶向生物制剂进入临床。药物的选择性治疗必须依靠基因组及药物遗传学的研究,对不同患者疗效及药物毒副反应作个体化的分析,从而正确的选择药物。本文就风湿病的传统的甲氨蝶呤和TNF-α阻断剂在药物基因组学预测药物的疗效及副作用等进行综述。     

Polymorphisms of pro-inflammatory genes and prostate cancer risk: a pharmacogenomic approach

In this paper, we consider the role of the genetics of inflammation in the pathophysiology of prostate cancer (PCa). This paper is not an extensive review of the literature, rather it is an expert opinion based on data from authors’ laboratories on age-related diseases and inflammation. The aim is the detection of a risk profile that potentially allows both the early identification of individuals at risk for disease and the possible discovery of potential targets for medication. In fact, a major goal of clinical research is to improve early detection of age-related diseases, cancer included, by developing tools to move diagnosis backward in disease temporal course, i.e., before the clinical manifestation of the malady, where treatment might play a decisive role in preventing or significantly retarding the manifestation of the disease. The better understanding of the function and the regulation of inflammatory pathway in PCa may help to know the mechanisms of its formation and progression, as well as to identify new targets for the refinement of new treatment such as the pharmacogenomics approach.     

Mining the pharmacogenomics literature--a survey of the state of the art

This article surveys efforts on text mining of the pharmacogenomics literature, mainly from the period 2008 to 2011. Pharmacogenomics (or pharmacogenetics) is the field that studies how human genetic variation impacts drug response. Therefore, publications span the intersection of research in genotypes, phenotypes and pharmacology, a topic that has increasingly become a focus of active research in recent years. This survey covers efforts dealing with the automatic recognition of relevant named entities (e.g. genes, gene variants and proteins, diseases and other pathological phenomena, drugs and other chemicals relevant for medical treatment), as well as various forms of relations between them. A wide range of text genres is considered, such as scientific publications (abstracts, as well as full texts), patent texts and clinical narratives. We also discuss infrastructure and resources needed for advanced text analytics, e.g. document corpora annotated with corresponding semantic metadata (gold standards and training data), biomedical terminologies and ontologies providing domain-specific background knowledge at different levels of formality and specificity, software architectures for building complex and scalable text analytics pipelines and Web services grounded to them, as well as comprehensive ways to disseminate and interact with the typically huge amounts of semiformal knowledge structures extracted by text mining tools. Finally, we consider some of the novel applications that have already been developed in the field of pharmacogenomic text mining and point out perspectives for future research.     

MicroRNA pharmacogenomics: post-transcriptional regulation of drug response

The field of pharmacogenomics aims to predict which drugs will be most effective and safe for a particular individual based on their genome sequence or expression profile, thereby allowing personalized treatment. The bulk of pharmacogenomic research has focused on the role of single nucleotide polymorphisms, copy number variations or differences in gene expression levels of drug metabolizing or transporting genes and drug targets. In this review paper, we focus instead on microRNAs (miRNAs): small noncoding RNAs, prevalent in metazoans, that negatively regulate gene expression in many cellular processes. We discuss how miRNAs, by regulating the expression of pharmacogenomic-related genes, can play a pivotal role in drug efficacy and toxicity and have potential clinical implications for personalized medicine.     

Assessing gene-gene interactions in pharmacogenomics

In pharmacogenomics studies, gene-gene interactions play an important role in characterizing a trait that involves complex pharmacokinetic and pharmacodynamic mechanisms, particularly when each involved feature only demonstrates a minor effect. In addition to the candidate gene approach, genome-wide association studies (GWAS) are widely utilized to identify common variants that are associated with treatment response. In the wake of recent advances in scientific research, a paradigm shift from GWAS to whole-genome sequencing is expected, because of the reduced cost and the increased throughput of next-generation sequencing technologies. This review first outlines several promising methods for addressing gene-gene interactions in pharmacogenomics studies. We then summarize some candidate gene studies for various treatments with consideration of gene-gene interactions. Furthermore, we give a brief overview for the pharmacogenomics studies with the GWAS approach and describe the limitations of these GWAS in terms of gene-gene interactions. Future research in translational medicine promises to lead to mechanistic findings related to drug responsiveness in light of complex gene-gene interactions and will probably make major contributions to individualized medicine and therapeutic decision-making.     

Pharmacogenetics of cardiovascular drugs.

Pharmacogenetics is a field aimed at understanding the genetic contribution to inter-patient variability in drug efficacy and toxicity. Treatment of cardiovascular disease is, in most cases, guided by evidence from well-controlled clinical trials. Given the solid scientific basis for the treatment of most cardiovascular diseases, it is common for patients with a given disease to be treated in essentially the same manner. Thus, the clinical trials have been very informative about treating large groups of patients with a given disease, but are slightly less informative about the treatment of individual patients. Pharmacogenetics and pharmacogenomics have the potential of taking the information derived from large clinical trials and further refining it to select the drugs with the greatest likelihood for benefit, and least likelihood for harm, in individual patients, based on their genetic make-up. In this paper, the current literature on cardiovascular pharmacogenetics is emphasised, and how the use of pharmacogenetic/pharmacogenomic information may be particularly useful in the future in the treatment of cardiovascular diseases is also highlighted.     

Recent efforts to model human diseases in vivo in Drosophila

Upon completion of sequencing the Drosophila genome, it was estimated that 61% of human disease-associated genes had sequence homologs in flies, and in some diseases such as cancer, the number was as high as 68%. We now know that as many as 75% of the genes associated with genetic disease have counterparts in Drosophila. Using better tools for mutation detection, association studies and whole genome analysis the number of human genes associated with genetic disease is steadily increasing. These detection efforts are outpacing the ability to assign function and understand the underlying cause of the disease at the molecular level. Drosophila models can therefore advance human disease research in a number of ways by: establishing the normal role of these gene products during development, elucidating the mechanism underlying disease pathology, and even identifying candidate therapeutic agents for the treatment of human disease. At the 49(th) Annual Drosophila Research Conference in San Diego this year, a number of labs presented their exciting findings on Drosophila models of human disease in both platform presentations and poster sessions. Here we can only briefly review some of these developments, and we apologize that we do not have the time or space to review all of the findings presented which use Drosophila to understand human disease etiology.     

TILLING,high-resolution melting (HRM), and next-generation sequencing (NGS) techniques in plant mutation breeding

Induced mutations have been used effectively for plant improvement. Physical and chemical mutagens induce a high frequency of genome variation. Recently, developed screening methods have allowed the detection of single nucleotide polymorphisms (SNPs) and the identification of traits that are difficult to identify at the molecular level by conventional breeding. With the assistance of reverse genetic techniques, sequence variation information can be linked to traits to investigate gene function. Targeting induced local lesions in genomes (TILLING) is a high-throughput technique to identify single nucleotide mutations in a specific region of a gene of interest with a powerful detection method resulted from chemical-induced mutagenesis. The main advantage of TILLING as a reverse genetics strategy is that it can be applied to any species, regardless of genome size and ploidy level. However, TILLING requires laborious and time-consuming steps, and a lack of complete genome sequence information for many crop species has slowed the development of suitable TILLING targets. Another method, high-resolution melting (HRM), which has assisted TILLING in mutation detection, is faster, simpler and less expensive with non-enzymatic screening system. Currently, the sequencing of crop genomes has completely changed our vision and interpretation of genome organization and evolution. Impressive progress in next-generation sequencing (NGS) technologies has paved the way for the detection and exploitation of genetic variation in a given DNA or RNA molecule. This review discusses the applications of TILLING in combination with HRM and NGS technologies for screening of induced mutations and discovering SNPs in mutation breeding programs.     

Prediction of personalized drugs based on genetic variations provided by DNA sequencing technologies

Recent reports of death and illness caused by adverse drug reactions have boosted rational drug design research. It has been shown through sequencing of the entire human genome that human genetic variations play a key role in adverse reactions to drugs as well as in differences in the effectiveness of drug treatments. The advent of high-throughput DNA sequencing technologies with bioinformatics of system biology have allowed the easy identification of genetic variations and all other pharmacogenetic variants in a single assay, thus permitting truly personalized drug treatment. This would be particularly valuable for many patients with chronic diseases who must take many medications concurrently. In this review, we have focused on pharmacogenomics for the prediction of variable drug responses between individuals with relevant genetic variations through new DNA sequencing technologies and provided directions for personalized drug therapy in the future.     

Pharmacogenomics of breast cancer targeted therapy: focus on recent patents

Adjuvant endocrine therapy as well as other forms of targeted therapy such as HER2 inhibitors and antiangiogenic agents reduce the risk of recurrence and improve survival among women with hormone receptor positive breast cancer. However, a significant percentage of women who receive targeted therapy as adjuvant or metastatic treatment do not benefit from this therapy, while a number of women who initially respond will eventually develop disease progression and relapse while on therapy. The observed variability in treatment response to targeted breast cancer treatment could be partly explained by pharmacogenomics. This paper reviews evidence on the role of pharmacogenomics of breast targeted therapy focusing on the clinical relevance of genetic variation. In particular, this article reviews the role of pharmacogenomics of tamoxifen, aromatase inhibitors, HER-2 inhibitors and anti-angiogenic agents. In addition, recent patents in the field are presented that provide promising steps in the field of personalized treatment of breast cancer, although future studies are needed for determining the clinical benefit of the proposed inventions. Finally, we present a testable hypothesis to aide the search for biologically meaningful genetic variation Specifically, we suggest the publication of negative results in the field of pharmacogenomics and pharmacoproteomics, will benefit future research in the field.     

Chapter 7: Pharmacogenomics

There is great variation in drug-response phenotypes, and a “one size fits all” paradigm for drug delivery is flawed. Pharmacogenomics is the study of how human genetic information impacts drug response, and it aims to improve efficacy and reduced side effects. In this article, we provide an overview of pharmacogenetics, including pharmacokinetics (PK), pharmacodynamics (PD), gene and pathway interactions, and off-target effects. We describe methods for discovering genetic factors in drug response, including genome-wide association studies (GWAS), expression analysis, and other methods such as chemoinformatics and natural language processing (NLP). We cover the practical applications of pharmacogenomics both in the pharmaceutical industry and in a clinical setting. In drug discovery, pharmacogenomics can be used to aid lead identification, anticipate adverse events, and assist in drug repurposing efforts. Moreover, pharmacogenomic discoveries show promise as important elements of physician decision support. Finally, we consider the ethical, regulatory, and reimbursement challenges that remain for the clinical implementation of pharmacogenomics.

What to Learn in This Chapter

• Interactions between drugs (small molecules) and genes (proteins)
• Methods for pharmacogenomic discovery
  • Association- and expression-based methods
  • Cheminformatics and pathway-based methods
• Database resources for pharmacogenomic discovery and application (PharmGKB)
• Applications of pharmacogenomics into a clinical setting

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

Targeting G protein-coupled receptor signaling in asthma

The complex disease asthma, an obstructive lung disease in which excessive airway smooth muscle (ASM) contraction as well as increased ASM mass reduces airway lumen size and limits airflow, can be viewed as a consequence of aberrant airway G protein-coupled receptor (GPCR) function. The central role of GPCRs in determining airway resistance is underscored by the fact that almost every drug used in the treatment of asthma directly or indirectly targets either GPCR–ligand interaction, GPCR signaling, or processes that produce GPCR agonists. Although many airway cells contribute to the regulation of airway resistance and architecture, ASM properties and functions have the greatest impact on airway homeostasis. The theme of this review is that GPCR-mediated regulation of ASM tone and ASM growth is a major determinant of the acute and chronic features of asthma, and multiple strategies targeting GPCR signaling may be employed to prevent or manage these features.