Pharmacogenomics: A Key Component of Personalized Therapy - 2012 PDF

Schwab and Schaeffeler Genome Medicine 2012, 4:93 http://genomemedicine.com/content/4/11/93 E D I TO R I A L Pharmacogenomics: a key component of personalized therapy Matthias Schwab1,2* and Elke Schaeffeler1,2 The goal of personalized medicine is to provide individua- mel...

Schwab and Schaeffeler Genome Medicine 2012, 4:93 http://genomemedicine.com/content/4/11/93 E D I TO R I A L Pharmacogenomics: a key component of personalized therapy Matthias Schwab1,2* and Elke Schaeffeler1,2 The goal of personalized medicine is to provide individua- melanoma ) suggest the demise of the blockbuster lized treatment and to predict the clinical outcome of model of drug development, the concept of targeted different treatments in different patients. Pharmaco- therapy is in its early stages. One reason is that mono- genomics is one of the core elements in personalized genic pharmacogenetic traits are mostly unable to explain medicine. The basic concept is that interindividual the variations in a complex phenotype such as drug res- variability in drug response is a consequence of multiple ponse. There is evidence through drug-target network factors, including genomics, epigenomics, the environ- analyses that most currently used drugs have multiple ment and a patient’s characteristics, such as gender, age targets and numerous off-target effects. Genome-wide and/or concomitant medication. Thirty years ago, approaches such as sequencing, epigenomic profiling and drug response was found to be altered by genetic poly- metabolomics will be essential for understanding the morphisms in drug-metabolizing enzymes (for example, detailed molecular architecture of disease etiology and/ the cytochrome P450 2D6 and the thiopurine S-methyl- or drug response. Genome-wide association studies transferase) , yet valid and predictive biomarkers for (GWAS) have implicated many new biological pathways, therapeutic effects and/or for avoiding severe side effects but this approach has limitations because most of the are lacking for more than 90% of drugs currently used in variants that have been associated with clinical pheno- clinical practice. Pharmacogenomics in recent years has types, such as adverse drug reactions, are not necessarily used a new generation of technologies known as ‘omics’ causal. approaches that has led to a revolution in the under- There is reasonable hope that pharmacogenomic standing of disease susceptibility and pathophysiology, research will benefit from a combination of different providing enormous potential for novel therapeutic omics technologies. Recently, multi-omics studies have strategies. shown their use in discovering potential novel thera- It is beyond doubt that pharmacogenomics promotes peutic targets. For instance, in one multi-omics study the development of targeted therapies, as was demon- the integrative personal omics profile (iPOP), which strated by the approval earlier this year of the drug combines genomic information with additional dynamic ivacaftor by the US Food and Drug Administration (FDA) omics activities (that is, transcriptomic, proteomic, meta- and the European Medicines Agency for the treatment of bolomic and autoantibody profiles), from a single a subset of cystic fibrosis patients. Ivacaftor is approved individual over a 14-month period demonstrated that only for cystic fibrosis patients bearing the specific iPOP data can be used to interpret healthy and diseased G551D genetic variant in the cystic fibrosis transmem- states, and can be helpful in the diagnostics, monitoring brane regulator (CFTR) gene, which encodes a protein and treatment of diseased states. that regulates chloride and water transport in the body The major challenge, however, is the bioinformatic and is defective in the disease. Ivacaftor targets the CFTR analysis and valid interpretation of highly complex multi- protein, increases its activity, and consequently improves omics data sets. A recent National Institutes of Health lung function. White Paper by the Quantitative and Systems Pharma- Although this and other examples (such as vemurafenib cology Workshop Group stated that: ‘Genomics is, in as an inhibitor of the BRAF V600E mutation in malignant and of itself, insufficient as a means to develop and study drugs: the operation of biological networks is strongly affected not only by changes in coding sequence or gene *Correspondence: [email protected] 1 Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Auerbachstrasse expression but also by transient responses to external 112, 70376, Stuttgart, Germany signals at the level of protein activity, posttranslational Full list of author information is available at the end of the article modification, stochastic processes, etc.’ Thus, with the help of an integrative systems pharmacology approach, © 2010 BioMed Central Ltd © 2012 BioMed Central Ltd multiple one-dimensional biomolecular-omics data sets, Schwab and Schaeffeler Genome Medicine 2012, 4:93 Page 2 of 3 http://genomemedicine.com/content/4/11/93 as well as patient history, can be linked together to achieve a better understanding of the biology behind diseases as well as drug-response phenotypes. Such a strategy should ultimately result in the identification of novel drug targets. Several important applications of pharmacogenomics are already being used in clinical practice and some of them have been approved by the FDA (for example, cetuximab/panitumumab and KRAS; vemurafenib and BRAF; warfarin and CYP2C9/VKORC1; abacavir and HLA-B*5701; carbamazepin and HLA-B*1502; thiopurines and TPMT). Other candidates have been identified (for example, tamoxifen ), but their clinical utility needs to be evaluated. To improve the translation of Genome Microbiome pharmacogenomics from bench to bedside, the dynamic Life style/Nutrition Age/Gender/BMI relationship between a patient’s phenotype (such as drug Epigenome Drugs response), which may change over time, and their genome also needs to be more deeply considered (Figure 1). The integration of non-genetic factors, such as environmental and clinical co-variates, may provide important additional phenotypic information to increase the precision of a therapeutic decision, as recently shown by warfarin algorithms. In addition to genetic varia­ tion in CYP2C9 and VKORC1, warfarin dose requirement depends on age, sex, body mass index, diet, concomitant drug therapy and ethnic background. The consideration of all these co-variates predicts up to 60% of the variability of warfarin dosage in patients. Consequently, warfarin pharmacogenomics treatment algorithms incor­ por­ating genetic and non-genetic factors have been estab­lished, extensively validated and are now publicly Figure 1. Pharmacogenomics. Interindividual variation in drug available via the Internet. response is the consequence of a combination of genetic and environmental factors as well as patient characteristics, which There has been considerable research into pharmaco­ affect the pharmacokinetics and/or pharmacodynamics of drugs. genomics in the past decade, and functional genomic Pharmacogenomics affects not only therapeutic efficacy but also approaches are likely to be used in the future as an disease susceptibility and drug development. BMI, body mass index. important resource for the prediction of clinical outcome. However, the field faces a major challenge: how can pharmacogenomics knowledge be brought to the bedside expertise of basic and clinical researchers with other as a key component of personalized medicine? In this sectors such as healthcare communities, regulators and context, electronic medical records (EMRs) and elec­ commercial partners. tronic health records (EHRs) may play a pivotal role. Abbreviations Infor­mation management and analysis of the clinical EHR, electronic health record; EMR, electronic medical record; iPOP, integrative relevance of pharmacogenomics can be improved by personal omics profile. using EMRs. EMRs will help to compare data on Competing interests treatment and outcome in thousands of patients using a The authors declare that they have no competing interests. real clinical setting, including the integration of genomic Acknowledgements and multi-omics data. Fitting EMRs/EHRs into a dynamic, The authors are supported by the German Federal Ministry of Education validated and rapidly evolving information infrastructure and Research (BMBF Virtual Liver grant 0315755 and grant 03 IS 2061C), is also crucial for pharmacogenomics. the German Research Organisation (DFG SCHW 858/1-1), the FP7 EU Initial Training Network “Fighting Drug Failure” (PITN-GA-2009-238132), and the Without doubt, pharmacogenomics is a highly attrac­ Robert Bosch Foundation in Stuttgart, Germany. tive field of research, which has been recently stimulated by multi-omics technologies. To demonstrate the clinical Author details 1 Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, relevance of pharmacogenomics in most areas of medicine, Auerbachstrasse 112, 70376, Stuttgart, Germany. 2Department of Clinical however, a concerted effort is necessary to connect the Pharmacology, University Hospital, 72076 Tuebingen, Germany. Schwab and Schaeffeler Genome Medicine 2012, 4:93 Page 3 of 3 http://genomemedicine.com/content/4/11/93 Published: 29 November 2012 6. Brauch H, Schroth W, Goetz MP, Mürdter TE, Winter S, Ingle JN, Schwab M, Eichelbaum M: Tamoxifen use in postmenopausal breast cancer: CYP2D6 References matters. J Clin Oncol 2012. doi: 10.1200/JCO.2012.44.6625. 1. Meyer UA, Zanger UM, Schwab M: Omics and drug response. Annu Rev 7. Johnson JA, Gong L, Whirl-Carrillo M, Gage BF, Scott SA, Stein CM, Anderson Pharmacol Toxicol 2012. doi: 10.1146/annurev-pharmtox-010510-100502. JL, Kimmel SE, Lee MT, Pirmohamed M, Wadelius M, Klein TE, Altman RB, 2. 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