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Abstract

Pharmacogenetics and pharmacogenomics strive to explain the interindividual variability in response to drugs due to genetic variation. For certain drugs, genetic tests can reduce adverse drug reactions and improve treatment efficacy. In this review, we will briefly consider some successful tests introduced into clinical practice and potential future developments.

Introduction

Pharmacogenetics and pharmacogenomics study the relationship between genetic variation and response to or toxicity from drugs. The first use of the term pharmacogenetics was reported in the 1950s, proposing an inherited basis for the haemolytic anaemia experienced by some soldiers taking antimalarial treatment.¹ It has since broadened to describe the study of germline, or inherited, genetic variants (e.g. single-nucleotide polymorphisms, copy number changes) and their relevance to drug response. In contrast, the study of somatic, or acquired, genetic changes particularly in tumour tissue and their association with drug response is referred to as pharmacogenomics. Pharmacogenomics is also used to describe the study, functions and interactions of all genes relevant to variability of drug response. However, there is a large overlap between pharmacogenetics and pharmacogenomics and the terms are often used interchangeably.

Pharmacogenetics

Due to technological advances and large-scale DNA sequencing projects, pharmacogenetics research has made tremendous progress in recent years, with the identification of numerous inherited variants that influence drug response. As a result, many drug labels have been updated with information about the relevance of pharmacogenetic biomarkers (Table 1). However, the introduction of pharmacogenetic testing into clinical practice has been relatively slow and there are few pharmacogenetic tests being carried out in the clinic.^2–4 In the UK, there are only few situations where a pharmacogenetic test is mandated prior to treatment. Successful examples that have been adopted into the routine clinical practice so far have focused on the prediction of rare serious adverse drug reactions (ADRs) and their avoidance through the use of pretreatment testing. In this section, we will briefly consider some examples of pharmacogenetic tests used to predict ADRs or response to treatment in clinical practice and those where the evidence base is developing (Table 1), although they have not been adopted into routine practice yet.

Table 1

FDA valid genomic biomarkers in the context of approved drug labels. Inherited genetic variants

Drug	Marker	Test
Codeine	CYP2D6	Information only
Atomoxetine	CYP2D6	Information only
Fluoxetine	CYP2D6	Information only
Tamoxifene	CYP2D6-CYP2C19	Information only
Clopidogrel	CYP2C19	Information only
Voriconazole	CYP2C19	Information only
Celecoxib	CYP2C9	Information only
Warfarin	CYP2C9	Recommended
Warfarin	VKORC1	Recommended
Atorvastatin	LDL receptor	Information only
Rasburicase	G6PD	Required
Primaquine	G6PD	Information only
Isoniazide	NAT	Information only
Caecitabine	DPD	Information only
Niotinib	UGT1A1	Required
Irinotecan	UGT1A1	Recommended
Azathioprine	TPMT	Recommended
Capecitabine	DPD	Information only
Maraviroc	CCR5	Required
Carbamazepine	HLA-B*1502	Required (in Han Chinese and some areas of south-east Asia)
Abacavir	HLA-B*5701	Required

CYP2D6, cytochrome P-450 (isoenzyme CYP2D6); CYP2C9, cytochrome P-450 (isoenzyme CYP2C9); CYP2C19, cytochrome P-450 (isoenzyme CYP2C19); CCR5, chemokine C-C motif receptor; DPD, dihydropyrimidine dehydrogenase; G6PD, glucose-6-phosphate dehydrogenase; NAT, N-acetyltransferase; TPMT, thiopurine methyltransferase; UGT1A1; glucuronosyl transferase 1 family, polypeptide 1; VKORC1, vitamin K epoxide reductase

Adverse drug reactions

Thiopurine methyltransferase and thiopurines

Thiopurine drugs, including 6-mercaptopurine and azathioprine, are cytotoxic, immunosuppressive agents used in the prevention of transplant rejection, acute lymphoblastic leukaemia and in the treatment of many inflammatory diseases. Thiopurine methyltransferase (TPMT) is a key enzyme in the conversion of thiopurines to their active metabolites, 6-thioguanine nucleotides and the inactive metabolite, 6-methylmercaptopurine. Several variants (polymorphisms) in the TPMT gene have been identified and are predicted to reduce or abolish the function of the encoded enzyme.⁵ TPMT enzyme activity is highly variable, with 89–94% of the population having high activity, 6–11% having intermediate activity and rare individuals (0.3%) having very low activity.^6,7 Three variant alleles called TMPT*2, TMPT*3A and TMPT*3C account for 80–95% of the reduced function alleles.^8–10 Individuals with deficient enzyme activity are highly sensitive to the effects of 6-mercaptopurine and azathioprine and are at high risk of developing severe, life-threatening myelosuppression at standard doses.¹¹ TPMT deficiency is usually determined by measuring erythrocyte enzyme activity. However, it may be inaccurate after a recent blood transfusion¹² and can be supplemented by genotyping tests.¹³ Following guidance by professional groups and regulatory authorities, there has been a considerable increase in the UK in the uptake of TPMT testing to guide thiopurine prescription.^2,4,13

HLA-B*5701 and abacavir

Abacavir is a nucleoside reverse-transcriptase inhibitor effective against infection with the human immunodeficiency virus (HIV). In White populations, between 5% and 8% of patients will experience a hypersensitivity reaction to abacavir, characterized by fever, skin rash, gastrointestinal tract and/or respiratory symptoms.¹⁴ This can result in a fatal reaction if patients are re-challenged with the drug. In 2002, two independent studies demonstrated that susceptibility to abacavir hypersensitivity syndrome was related to the major histocompatibility complex class I allele HLA-B*5701. ^15,16 HLA-B*5701 status correlated with hypersensitivity reactions as determined by skin-patch tests rather than those determined by clinical observation. Hence, it provided a more accurate predictor of adverse reaction and made complex skin-patch tests redundant. The clinical utility of the genetic testing was confirmed in a prospective randomized controlled trial (PREDICT-1), where patients were randomized to a HLA-B*5701 prescreening arm or to an arm without genetic testing.¹⁷ In addition, economic analyses demonstrated that genetic testing for HLA-B*5701 was cost-effective.^18–20 On the basis of these studies, HIV treatment guidelines have been revised to mandate HLA-B*5701 screening in routine practice prior to abacavir treatment.

HLA-B*1502 and carbamazepine

Carbamazepine is a widely used drug for the treatment of epilepsy. In rare cases, carbamazepine causes life-threatening hypersensitivity reactions, including Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis. The risk of these events is estimated to be one to six per 10,000 new users in countries with mainly Caucasian populations. However, the incidence in several Asian countries is estimated to be about 10-fold higher.^21,22 A striking genetic association was detected in a cohort of Han Chinese in Taiwan, where the HLA-B*1502 allele was present in 100% of people with carbamazepine-induced SJS, and only 3% of carbamazepine-tolerant people.²³ These findings were replicated in subsequent series across Asia.^24–28 However, this association was not found among people with European ancestry.^29,30 Based on these studies, regulatory agencies, including the European Medicines Agency (EMEA) and the US Food and Drug Administration (FDA), recommended HLA testing in at-risk populations prior to initiating therapy.

Response to treatment

CYP2C19 and clopidogrel

Clopidogrel inhibits platelet aggregation and is widely used, alone or in combination, with aspirin to treat patients with a variety of cardiovascular disorders. Clopidogrel is a prodrug requiring several biotransformation steps, mediated mainly by cytochrome P-450 isoenzymes (CYP), to generate an active metabolite.³¹ Recently, many large studies have identified loss-of-function alleles in CYP2C19 (especially *2 and *3) as important risk factors predicting reduced clopidogrel efficacy, resulting in a significantly increased risk for myocardial infarction and stent thrombosis.^32–35 Moreover, a genome-wide association study (GWAS), where hundreds of thousands of single-nucleotide polymorphisms are assayed in a single experiment and their frequencies compared between cases and controls, has confirmed that the CYP2C19*2 genotype was associated with a diminished platelet response to clopidogrel treatment and poorer cardiovascular outcomes.³⁶ Genotyping testing may have an important impact in practice as carriers of the loss-of-function alleles may benefit more from an alternative platelet inhibitor, such as prasugrel, that does not require similar hepatic transformation, or dose adjustment. Ongoing studies are underway to establish the optimum way to integrate pharmacogenetic testing into anti-platelet treatment.

CYP2C9, vitamin K epoxide reductase complex 1 and oral anticoagulants

Coumarin-based oral anticoagulants (COAs), warfarin, acenocoumarol and phenprocoumon are used worldwide for the treatment and prevention of thromboembolic disease. COA therapy can be difficult to manage because of the narrow therapeutic window and a large inter- and intra-patient variability in the dose − response relationship, which may result in recurrent thrombosis or bleeding complications, especially during the initial phase of treatment. Evidence over the last decade proved that a significant proportion of the inter-individual dose variability related to common genetic variants in two genes: CYP2C9, which encodes the main metabolizing enzyme and vitamin K epoxide reductase complex 1 (VKORC1), which encodes the drug target.^37–43 Previously, only clinical factors, including age, gender and body mass index, contributing to 12–15% of dose variability, could be used to estimate dose.⁴³ The combination of genotype with clinical factors accounts for 55–60% of the variability in dose requirements, improving estimates of optimal dose.⁴⁴ Recently, The International Warfarin Pharmacogenetics Consortium demonstrated that the algorithm based on genetic testing of CYP2C9 and VKORC1 was significantly better than using either a clinical algorithm or a fixed-dose approach in achieving the target international normalized ratio, traditionally used to guide dose titration and an improvement in anticoagulation control.⁴⁵

The warfarin label was initially modified by the FDA in 2007 to include genotype information and recently updated with specific ranges of initial doses assigned to each genotype representing the expected steady-state maintenance doses. However, studies to date have not demonstrated significant improvements in health outcome (e.g. serious bleeding events and thromboembolic complications)^46–48 and robust evidence of beneficial effects on patient outcome is needed before pharmacogenetic testing can be routinely introduced to modify oral anticoagulation therapy.⁴⁹ Large, multicentre, randomized trials for COAs are on the way in the USA (Clarification of Optimal Anticoagulant through Genetics [COAG] trial) and in Europe (The European Pharmacogenetics of Anticoagulant Therapy Trial [EU-PACT]), which will assess the benefits, disadvantages and cost-effectiveness of the newly developed, genotype-guided dosing algorithms in daily practice.

CYP2D6 and tamoxifen

Tamoxifen, a selective oestrogen receptor modulator, has been successfully used in the treatment of oestrogen-receptor-positive breast cancer for more than 30 years. Tamoxifen efficacy depends on the biotransformation, predominantly via the enzyme CYP2D6, to its active metabolite endoxifen.⁵⁰ CYP2D6 activity can be reduced both by genetic variation or concurrent use of drug inhibitors (e.g. fluoxetine and paroxetine), which, in turn, can significantly reduce endoxifen plasma concentrations.^51–53 In 2005, a retrospective analysis suggested that the CYP2D6 genotype predicted tamoxifen efficacy.⁵⁴ These data prompted the FDA to re-label tamoxifen to incorporate information about the genetic factors and drug interactions that may affect the efficacy of the drug. Several studies addressing the interaction between the CYP2D6 genotype and outcomes in women treated with tamoxifen in adjuvant and metastatic settings have been published since and reported inconsistent results.⁵⁵ Recently, the analysis of large cohorts from the USA, Germany and UK reinforced the hypothesis that among women with early breast cancer treated with tamoxifen, there is an association between CYP2D6 variation and clinical outcomes, such that the presence of two functional CYP2D6 alleles is associated with better clinical outcomes.^56,57 Although commercial tests for CYP2D6 genotyping are available, uncertainty due to the conflicting results has led to hesitation with regards to the use of this test in practice.⁵⁸

The International Tamoxifen Pharmacogenetics Consortium was established to collect the worldwide experience relating to genetic variation in CYP2D6, and the outcomes of women treated with adjuvant tamoxifen and results of the analysis are awaited with interest. Moreover, analyses of the companion pharmacogenetic studies on the large, prospective, randomized controlled trials of tamoxifen versus aromatase inhibitors are ongoing and will help to clarify the value of the CYP2D6 genotype in tailored adjuvant endocrine treatment.

Pharmacogenomics

In cancer, variability in response to certain drugs can involve somatic (acquired) genetic changes in the tumour tissue. These somatic changes can be simple DNA sequence variants (mutations) or more complex chromosomal rearrangements leading to altered gene expression or function. These genetic alterations are often characteristic for a specific tumour type and allow a molecular characterization of tumours that can provide information regarding disease prognosis, treatment response or new targets for drug development (Table 2).

Table 2

FDA valid genomic biomarkers in the context of approved drug labels

Drug	Marker	Test
Cetuximab	EGFR	Required
Panitumumab	EGFR	Required
Trastuzumab	HER2	Required
Lapatinib	HER2	Required
Tamoxifene	ER	Required
Anastrozole	ER	Required
Exemestane	ER	Required
Letrozole	ER	Required
Cetuximab	KRAS	Required
Panitumumab	KRAS	Required
Busulfan	Ph1 chromosome	Required
Dasatinib	Ph1 chromosome	Required
Tretinoin	PML/ RAR (alpha) fusion gene	Recommended
Imatinib	c-Kit expression	Required

EGFR, epidermal growth factor receptor; ER, oestrogen receptor; HER-2, human epidermal growth factor receptor 2; Phl, Philadelphia chromosome; PML/RAR, promyelocytic leukaemia–retinoic acid receptor

The dawn of molecular-targeted therapy in oncology arrived with the discovery of anti-hormonal therapy targeted to the oestrogen receptor in the 1960s.⁵⁹ Molecular predictors have been successfully used in clinical trials of various anticancer drugs including trastuzumab^60,61 and lapatinib,⁶² by evaluating HER2 overexpression in breast cancers, and imatinib by evaluating the presence of the Philadelphia chromosome in chronic myelogenous leukaemia.⁶³ More recently, notable examples of the successful use of genetic markers in early-phase drug development include the detection of BRCA1 and BRCA2 mutations, which indicate sensitivity to the poly(ADP-ribose) polymerase inhibitor, olaparib⁶⁴ and of the p.V600E BRAF mutation that predicts response to the mutant BRAF selective inhibitor PlX4032 in melanoma.⁶⁵ Integration of pharmacogenetics and pharmacogenomics into the drug development pipeline may enable evaluation of the genetic contribution to safety, potentially lowering barriers to registration, as well as providing the rationale for efficacy and enabling co-development of genetic in vitro diagnostics.⁶⁶ In oncology, it is likely that many future drugs will be licensed with companion diagnostic tests. In the following section, we briefly discuss some examples of pharmacogenomic tests currently used in cancer therapy.

Prediction of tumour recurrence in breast cancer

Recently, a number of commercialized multi-gene prognostic and predictive tests have entered the complex and expanding landscape of breast cancer diagnostics.⁶⁷ Multi-gene expression analysis has been used to refine prognosis to identify groups, which do or do not benefit from the addition of chemotherapy to endocrine adjuvant therapy. The multigene assays, 21-gene recurrence score Oncotype DX^® (Genomic Health, Renwood City, CA, USA) and 70-gene signature MammaPrint^® (Agendia BV, Amsterdam, The Netherlands; and Agendia Inc, Irvine, CA, USA) are the most widely used.⁶⁸ In February 2007, Agendia's MammaPrint^® became the first in vitro diagnostic multivariate index assay to receive clearance from the FDA. Specifically, the 70-gene microarray-based test was originally developed as a general prognostic test in untreated patients. It gauges the risk of breast recurrence within five years following surgery, and stratifies patients into either low risk or high risk of distant recurrence. The realtime polymerase chain reaction-based Oncotype DX^® was developed specifically as a prognostic and predictive test for the benefit of chemotherapy in women with node-negative, oestrogen receptor (ER)-positive breast cancer who have been treated with tamoxifen. It assesses the expression of 21 genes and yields a recurrence score between 0 and 100, which correlates with metastatic disease within 10 years. Oncotype DX^® is similar to MammaPrint^® in that both tests place their highest weight on gene expression in three major pathways: proliferation, ER and human epidermal growth factor receptor-2 (HER2). However, MammaPrint^® is more generally applicable while Oncotype DX has the advantages of ease of use on formalin-fixed, paraffin-embedded tissues and the ability to serve as both a prognostic and predictive test for certain hormonal and chemotherapeutic agents. Two large, prospective trials are ongoing that aim to evaluate the clinical usefulness of both tools in comparison with the existing clinical prognostic tools: the Microarray in Node-Negative Disease May Avoid Chemotherapy trial for MammaPrint^® (MINDACT), and the Trial Assigning Individualized Options for Treatment trial for Oncotype DX^® (TAILORx).

Therapy selection

Trastuzumab in breast cancer

Trastuzumab is one of the most successful examples of cancer treatment that targets a specific genetic alteration and highlights the importance of incorporating genetic analysis in the development and application of new therapies. In the late 1980s, it was established that overexpression of the human epidermal growth factor receptor-2 was present in approximately one-third of breast cancer patients and was associated with worse prognosis.⁶⁰ This observation led to the development of trastuzumab, a humanized recombinant monoclonal antibody (mAb) directed against the HER2 receptor protein on breast cancer cells. In patients with metastatic HER2-positive breast cancer, trastuzumab alone or with chemotherapy increases time to disease progression and improves survival.⁶¹ Evidence from multiple randomized trials also demonstrated that trastuzumab decreases the risk of recurrence and mortality when added to adjuvant chemotherapy regimens for resected HER2-positive breast cancer.⁶⁹ This information is considered in breast cancer guidelines, and regulatory authorities have acknowledged the importance of accurately determining HER2 status in tumours to select the most appropriate treatment regimen.

Anti-epidermal growth factor receptor therapies in colorectal cancer

KRAS is a major component of the epidermal growth factor receptor (EGFR) signalling pathways. Mutations in KRAS are found in about 30–40% of sporadic colorectal cancers.^70,71 In the presence of specific mutations KRAS is constitutively activated, and subsequent signalling events are unregulated and independent from EGFR control.⁷² In 2008, three large studies of anti-EGFR-mAb treatment, one with panitumumab⁷³ and two with cetuximab,^74,75 demonstrated that patients with KRAS somatic mutations did not benefit from therapy. Subsequently, retrospective analyses from three randomized clinical trials confirmed the increased efficacy of anti-EGFR mAbs in patients with wild-type KRAS.^76–78 As a result of this consistent data from independent analyses, incorporating thousands of patients, the EMEA and FDA have restricted approval of cetuximab and panitumumab to patients with KRAS wild-type tumours.

Anti-EGFR therapies in Lung cancer

Recently, EGFR tyrosine kinase inhibitors (TKI), gefitinib and erlotinib, have been licensed for use in non-small cell lung cancer (NSCLC). Interestingly, clinical trials of EGFR-TKI have consistently demonstrated higher tumour response rates in women of east Asian origin, those with adenocarcinoma histology and in individuals with a history of never having smoked.⁷⁹ In 2004, three independent groups offered further insight into the mechanisms that underlie NSCLC sensitivity to TKIs and correlated responses to gefitinib or erlotinib with the presence of somatic activating mutations clustered in EGFR exons 18–21.^80–82 Interestingly, these somatic mutations were more frequently observed in patients with clinical features associated with response to an EGFR-TKI, such as adenocarcinoma histology, Asian ethnicity and a non-smoking history. Retrospective and prospective studies have demonstrated that patients with EGFR mutations, particularly individuals harbouring exon 19 deletion, have response rates to EGFR-TKIs ranging from 54% to 94%.⁷⁹ Recently, two phase III trials have reinforced the role of EGFR mutation as a clinically relevant predictive marker for selection of gefitinib treatment.^83,84 As a result, in 2009, the EMEA approved gefitinib for the treatment of adults with locally advanced or metastatic NSCLC with activating mutations of EGFR across all lines of therapy.

Challenges and future perspective

Pharmacogenetics has great potential to aid drug discovery, minimize side-effects and identify patients sensitive or resistant to specific treatments. However, the translation of this knowledge into clinical practice remains limited. Many reasons have been cited for the limited adoption of testing (Box 1), including the lack of awareness about the utility, the scarcity of trials proving the utility and cost-effectiveness, the lack of clinical testing services, the lack of incentives for diagnostic companies to invest in the development and licensing of tests, the unclear regulatory framework and concerns regarding costs and the reimbursement system.^3,4,85–88 This is in contrast somewhat to somatic pharmacogenomic testing in oncology where there has been a rapid adoption with a more robust evidence base and clearer recommendations from professional groups and regulatory authorities. Between 2000 and 2008, 33 new oncology-targeted drugs were approved by the EMEA, of which nine (27%) had pharmacogenomic data in the label.⁸⁹ During the last few years, regulatory agencies have added pharmacogenetic information into the labels for several drugs, but although a priori genetic testing remains advised or recommended, it is seldom mandatory due to the lack of data demonstrating proven clinical validity or utility and supportive cost-effectiveness studies (Table 1). Randomized, prospective studies should be performed to evaluate the cost–benefit ratio of a pharmacogenetic test before a test is recommended for routine clinical use. The PREDICT-1 study with abacavir provides an attractive exemplar, where drug sales rose sharply after the publication of the results, as clinicians could be more confident to prescribe the drug where testing defined individuals at significantly reduced risk of serious hypersensitivity. Randomized clinical trials are underway to establish the utility of pharmacogenetics for some drugs, including warfarin and clopidogrel, but they may be unrealistic where an adverse event is very rare, e.g. for carbamazepine or allopurinol and SJS. Alternative strategies include interrogation of randomized trials retrospectively where biological materials are available, as with KRAS testing in colorectal cancer or to pool data from different groups in meta-analyses e.g. International Tamoxifen Pharmacogenetics Consortium. Moreover, randomized trials are expensive to conduct and there may be limited perceived added value to conduct a study where the intervention is the test and the drug is cheap or off-patent. Box 1

Pharmacogenetics: challenges on the road to the clinic

Complexity of genetic, epigenetic and environmental interactions

Providing scientific evidence

Providing information on cost-effectiveness

Regulatory authorities

Complexity and interdisciplinarity

Lack of funding

Service delivery

Ethical implication

Education for clinicians and patients

Algorithms or clinical practice guidelines to guide appropriate use of test

Lack of academia–industry collaboration

Pharmacogenetic tests are currently provided by a range of different laboratories (genetics, biochemistry and immunology), reflecting the molecular techniques (biochemical and DNA-based) that are required. Depending on the complexity of the test, a result can take hours to weeks and so can lead to a delay in treatment initiation. This is particularly important in situations where the treatment has to be given immediately (e.g. rapidly progressing cancer, anticoagulation). A number of groups are developing point-of-care testing approaches to address this. Inadequate education, both at undergraduate and postgraduate levels, is another barrier to the widespread uptake of pharmacogenetic tests.^86,90,91 In a recent survey of UK and Irish laboratories, lack of knowledge by clinicians was cited by the majority of responders as being among the key reasons for delayed uptake of pharmacogenetic testing.⁴

In setting up a service, establishing how patients prefer pharmacogenetic testing to be delivered is important. Initial studies suggest that integrating testing into their routine care is preferred.⁹¹ A recent discrete choice experiment study revealed that patients want to receive good-quality and timely information about whether to have a pharmacogenetic test and what the test results mean.⁹² This is in contrast to what health-care professionals prioritize in terms of a pharmacogenetics service where their focus is on the accuracy of the test and the time taken for the test result. The adoption of genetic testing into routine prescription requires health-care professionals to be familiar with the tests’ interpretation and confident to explain and incorporate the results into each patient's management.

Pharmacogenetics and pharmacogenomics will advance through new technological developments (Box 2) as seen with GWAS, e.g. the successful identification of genetic predisposition to flucloxacillin-induced liver injury^93,94 and lower cost, rapid whole genome sequencing methods. Already studies have indicated that whole genome sequencing will identify variants that correlate with response to treatment.⁹⁵ At present, these sequencing platforms are expensive and in the domain of research projects, but refinements will rapidly lead to translation into the routine diagnostic setting and the challenges that dealing with these large data-sets will pose. Box 2

Future advances

Technological advances (high-throughput sequencing platforms, microarray-based comparative genome hybridization)

Phenotyping tests

Training programmes and continuing education of medical staff

Biological samples collection from all trial participants

Sharing samples and data

Geno-stratification of patients in early-phase drug development

Use of different biological samples

Companion diagnostic tests

Close liaison between pharmacological companies and diagnostic laboratories

Conclusion

Pharmacogenetics has developed over the past 50 years from a niche discipline to a major driving force in clinical pharmacology, and it is currently one of the most actively pursued areas in applied biomedical research. Led by the advances in genetic technology, we expect the adoption of pharmacogenetic testing into clinical practice to increase significantly over the approaching decade.

DECLARATIONS

Competing interests: None.

Funding: WGN's research group is supported by the Manchester NIHR Biomedical Research Centre. RF is supported by a fellowship from the European Society of Medical Oncology (ESMO).

Ethical approval: NA.

Guarantor: WGN.

Contributorship: RF and WGN contributed equally to the conception and writing of this review.

Acknowledgements: Dr Ferraldeschi is supported through an ESMO Translational Research Fellowship. Dr Newman's work is supported through the NIHR Manchester Biomedical Research Centre.

References

Motulsky

. Drug reactions enzymes, and biochemical genetics. J Am Med Assoc 1957;165:835–7

Gurwitz

, Rodríguez-Antona

, Payne

, Improving pharmacovigilance in Europe: TPMT genotyping and phenotyping in the UK and Spain. Eur J Hum Genet 2009;7:991–8

Sheffield

, Phillimore

. Clinical use of pharmacogenomic tests in 2009. Clin Biochem Rev 2009;30:55–65

Higgs

, Gambhir

, Ramsden

, Poulton

, Newman

. Pharmacogenetic testing in the United Kingdom genetics and immunogenetics laboratories. Genet Test Mol Biomarkers. 2010;14:121–5

Zhou

. Clinical pharmacogenomics of thiopurine S-methyltransferase. Curr Clin Pharmacol 2006;1:119–28

McLeod

, Lin

, Scott

, Pui

, Evans

. Thiopurine methyltransferase activity in American white subjects and black subjects. Clin Pharmacol Ther 1994;5:15–20

McLeod

, Relling

, Liu

, Pui

, Evans

. Polymorphic thiopurine methyltransferase in erythrocytes is indicative of activity in leukemic blasts from children with acute lymphoblastic leukemia. Blood 1995;85:1897–902

Tai

, Krynetski

, Yates

, Thiopurine S-methyltransferase deficiency: two nucleotide transitions define the most prevalent mutant allele associated with loss of catalytic activity in Caucasians. Am J Hum Genet 1996;58:694–702

Tai

, Krynetski

, Schuetz

, Yanishevski

, Evans

. Enhanced proteolysis of thiopurine S-methyltransferase (TPMT) encoded by mutant alleles in humans (TPMT*3A, TPMT*2): mechanisms for the genetic polymorphism of TPMT activity. Proc Natl Acad Sci U S A 1997;94:6444–9

10.

Tai

, Fessing

, Bonten

, Enhanced proteasomal degradation of mutant human thiopurine S-methyltransferase (TPMT) in mammalian cells: mechanism for TPMT protein deficiency inherited by TPMT*2, TPMT*3A, TPMT*3B or TPMT*3C. Pharmacogenetics 1999;9:641–50

11.

Evans

, Hon

, Bomgaars

, Preponderance of thiopurine S-methyltransferase deficiency and heterozygosity among patients intolerant to mercaptopurine or azathioprine. J Clin Oncol 2001;19:2293–301

12.

Duley

, Florin

. Thiopurine therapies: problems, complexities, and progress with monitoring thioguanine nucleotides. Ther Drug Monit 2005;27:647–54

13.

Ford

, Berg

. Thiopurine S-methyltransferase (TPMT) assessment prior to starting thiopurine drug treatment; a pharmacogenomic test whose time has come. J Clin Pathol 2010;63:288–95

14.

Phillips

, Mallal

. Drug hypersensitivity in HIV. Curr Opin Allergy Clin Immunol 2007;7:324–30

15.

Mallal

, Nolan

, Witt

, Association between presence of HLA-B*5701, HLA-DR7, and HLA-DQ3 and hypersensitivity to HIV-1 reverse-transcriptase inhibitor abacavir. Lancet 2002;359:727–32

16.

Hetherington

, Hughes

, Mosteller

, Genetic variations in HLA-B region and hypersensitivity reactions to abacavir. Lancet 2002;359:1121–2

17.

Mallal

, Phillips

, Carosi

, HLA-B*5701 screening for hypersensitivity to abacavir. N Engl J Med 2008;358:568–79.

18.

Schackman

, Scott

, Walensky

, Losina

, Freedberg

, Sax

. The cost-effectiveness of HLA-B*5701 genetic screening to guide initial antiretroviral therapy for HIV. AIDS 2008;22:2025–33

19.

Nieves Calatrava

, Calle-Martín

, Iribarren-Loyarte

, Cost-effectiveness analysis of HLA-B*5701 typing in the prevention of hypersensitivity to abacavir in HIV+ patients in Spain. Enferm Infecc Microbiol Clin 2010;28:590–5

20.

Hughes

, Vilar

, Ward

, Alfirevic

, Park

, Pirmohamed

. Cost-effectiveness analysis of HLA B*5701 genotyping in preventing abacavir hypersensitivity. Pharmacogenetics 2004;14:335–42

21.

Lim

, Kwan

, Tan

. Association of HLA-B*1502 allele and carbamazepine induced severe adverse cutaneous drug reaction among Asians, a review. Neurology Asia 2008;13:15–21

22.

Farkas

(2007). Clinical Review, Adverse Events of Carbamazepine. See http://www.accessdata.fda.gov/drugsatfda_docs/nda/2007/016608s098,020712s029,021710_ClinRev.pdf (last checked 25 November 2010)

23.

Chung

, Hung

, Hong

, Medical genetics: a marker for Stevens-Johnson syndrome. Nature 2004;428:486

24.

Hung

, Chung

, Jee

, Genetic susceptibility to carbamazepine-induced cutaneous adverse drug reactions. Pharmacogenet Genomics 2006;16:297–306

25.

Chang

, Too

, Murad

, Hussein

. Association of HLA-B*1502 allele with carbamazepine-induced toxic epidermal necrolysis and Stevens-Johnson syndrome in the multi-ethnic Malaysian population. Int J Dermatol 2011;50:221–4

26.

Man

, Kwan

, Baum

, Association between HLA-B*1502 Allele and antiepileptic drug-induced cutaneous reactions in Han Chinese. Epilepsia 2007;48:1015–8

27.

Locharernkul

, Loplumlert

, Limotai

, Carbamazepine and phenytoin induced Stevens-Johnson syndrome is associated with HLA-B*1502 allele in Thai population. Epilepsia 2008;49:2087–91

28.

Mehta

, Prajapati

, Mittal

, Association of HLA-B*1502 allele and carbamazepine-induced Stevens-Johnson syndrome among Indians. Indian J Dermatol Venereol Leprol 2009;75:579–82

29.

Lonjou

, Thomas

, Borot

, A marker for Stevens–Johnson syndrome – ethnicity matters. Pharmacogenomics J 2006;6:265–68

30.

Alfirevic

, Jorgensen

, Williamson

, Chadwick

, Park

, Pirmohamed

. HLA-B locus in Caucasian patients with carbamazepine hypersensitivity. Pharmacogenomics 2006;7:813–8

31.

Savi

, Herbert

, Pflieger

, Importance of hepatic metabolism in the antiaggregating activity of the thienopyridine clopidogrel. Biochem Pharmacol 1992;44:527–32

32.

Simon

, Verstuyft

, Mary-Krause

, Genetic determinants of response to clopidogrel and cardiovascular events. N Engl J Med 2009;360:363–75

33.

Collet

, Hulot

, Pena

, Cytochrome P450 2C19 polymorphism in young patients treated with clopidogrel after myocardial infarction: a cohort study. Lancet 2009;373:309–17

34.

Mega

, Close

, Wiviott

, Cytochrome p-450 polymorphisms and response to clopidogrel. N Engl J Med 2009;360:354–62

35.

Sibbing

, Stegherr

, Latz

, Cytochrome P450 2C19 loss-of-function polymorphism and stent thrombosis following percutaneous coronary intervention. Eur Heart J 2009;30:916–22

36.

Shuldiner

, O'Connell

, Bliden

, Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA 2009;302:849–57

37.

Schalekamp

, Brassé

, Roijers

, VKORC1 and CYP2C9 genotypes and phenprocoumon anticoagulation status: interaction between both genotypes affects dose requirement. Clin Pharmacol Ther 2007;81,185–93

38.

Sconce

, Khan

, Wynne

, The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood 2005;106:2329–33

39.

Bodin

, Verstuyft

, Tregouet

, Cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) genotypes as determinants of acenocoumarol sensitivity. Blood 2005;106:135–40

40.

Cooper

, Johnson

, Langaee

, A genome-wide scan for common genetic variants with a large influence on warfarin maintenance dose. Blood 2008;112:1022–7

41.

Teichert

, Eijgelsheim

, Rivadeneira

, A genome-wide association study of acenocoumarol maintenance dosage. Hum Mol Genet 2009;18:3758–68

42.

Takeuchi

, McGinnis

, Bourgeois

, A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose. PLoS Genet 2009;5:e1000433

43.

Wadelius

, Chen

, Lindh

, The largest prospective warfarin-treated cohort supports genetic forecasting. Blood 2009;113:784–92

44.

Vladutiu

. The FDA announces new drug labeling for pharmacogenetic testing: is personalized medicine becoming a reality? Mol Genet Metab 2008;93:1–4

45.

Klein

, Altman

, Eriksson

, Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med 2009;360:753–64

46.

Caraco

, Blotnick

, Muszkat

. CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther 2008;83:460–70

47.

Anderson

, Horne

, Stevens

, Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation 2007;116:2563–70

48.

Schwarz

, Ritchie

, Bradford

, Genetic determinants of response to warfarin during initial anticoagulation. N Engl J Med 2008;358:999–1008

49.

Flockhart

, O'Kane

, Williams

, ACMG Working Group on Pharmacogenetic Testing of CYP2C9, VKORC1 Alleles for Warfarin Use. Pharmacogenetic testing of CYP2C9 and VKORC1 alleles for warfarin. Genet Med 2008;10:139–50

50.

Johnson

, Zuo

, Lee

, Pharmacological characterization of 4-hydroxy-N-desmethyl tamoxifen, a novel active metabolite of tamoxifen. Breast Cancer Res Treat 2004;85:151–9

51.

Stearns

, Johnson

, Rae

, Active tamoxifen metabolite plasma concentrations after coadministration of tamoxifen and the selective serotonin reuptake inhibitor paroxetine. J Natl Cancer Inst 2003;95:1758–64

52.

Jin

, Desta

, Stearns

, CYP2D6 genotype, antidepressant use, and tamoxifen metabolism during adjuvant breast cancer treatment. J Natl Cancer Inst 2005;97:30–9

53.

Borges

, Desta

, Li

, Quantitative effect of CYP2D6 genotype and inhibitors on tamoxifen metabolism: implication for optimization of breast cancer treatment. Clin Pharmacol Ther 2006;80:61–74

54.

Goetz

, Rae

, Suman

, Pharmacogenetics of tamoxifen biotransformation is associated with clinical outcomes of efficacy and hot flashes. J Clin Oncol 2005;23:9312–8

55.

Ferraldeschi

, Newman

. The impact of CYP2D6 genotyping on tamoxifen treatment. Pharmaceuticals 2010;3:1122–38

56.

Schroth

, Goetz

, Hamann

, Association between CYP2D6 polymorphisms and outcomes among women with early stage breast cancer treated with tamoxifen. JAMA 2009;302:1429–36

57.

Thompson

, Johnson

, Quinlan

, Comprehensive CYP2D6 genotype and adherence affect outcome in breast cancer patients treated with tamoxifen monotherapy. Breast Cancer Res Treat 2011;125:279–87

58.

Hoskins

, Carey

, McLeod

. CYP2D6 and tamoxifen: DNA matters in breast cancer. Nat Rev Cancer 2009;9:576–86

59.

Jordan

. Tamoxifen (ICI46,474) as a targeted therapy to treat and prevent breast cancer. Br J Pharmacol 2006;147(Suppl 1):S269–76

60.

Slamon

, Clark

, Wong

, Levin

, Ullrich

, McGuire

. Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. Science 1987;235:177–82

61.

Slamon

, Leyland-Jones

, Shak

, Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med 2001;344:783–92

62.

Johnston

, Trudeau

, Kaufman

, Phase II study of predictive biomarker profiles for response targeting human epidermal growth factor receptor 2 (HER-2) in advanced inflammatory breast cancer with lapatinib monotherapy. J Clin Oncol 2008;26:1066–72

63.

O'Brien

, Guilhot

, Larson

, Gathmann

, Baccarani

, Cervantes

. Imatinib compared with interferon and low-dose cytarabine for newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med 2003;348:994–1004

64.

Fong

, Boss

, Yap

, Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. N Engl J Med 2009;361:123–34

65.

Flaherty

, Puzanov

, Sosman

, Phase I study of PLX4032: proof of concept for V600E BRAF mutation as a therapeutic target in human cancer. J Clin Oncol 2009;27(Suppl 15):9000 (abstract)

66.

Akkari

, Swanson

, Crenshaw

, Pipeline pharmacogenetics: a novel approach to integrating pharmaco-genetics into drug development. Curr Pharm Des 2009;15:3754–63

67.

Pusztai

, Cristofanilli

, Paik

. New generation of molecular prognostic and predictive tests for breast cancer. Semin Oncol 2007;34(Suppl 3):S10–6

68.

Kim

, Paik

. Gene-expression-based prognostic assays for breast cancer. Nat Rev Clin Oncol 2010;6:340–7

69.

Baselga

, Perez

, Pienkowski

, Bell

. Adjuvant trastuzumab: a milestone in the treatment of HER-2-positive early breast cancer. Oncologist 2006;11(Suppl 1):4–12

70.

Andreyev

, Norman

, Cunningham

, Oates

, Clarke

. Kirsten ras mutations in patients with colorectal cancer: the multicenter ‘RASCAL’ study. J Natl Cancer Inst 1998;90:675–84

71.

Andreyev

, Norman

, Cunningham

, Kirsten ras mutations in patients with colorectal cancer: the ‘RASCAL II’ study. Br J Cancer 2001;85:692–6

72.

Bos

. Ras oncogenes in human cancer: a review. Cancer Res 1989;49:4682–9

73.

Amado

, Wolf

, Peeters

, Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J Clin Oncol 2008;26:1626–34

74.

De Roock

, Piessevaux

, De Schutter

, KRAS wild-type state predicts survival and is associated to earlyradiological response in metastatic colorectal cancer treated with cetuximab. Ann Oncol 2008;19:508–15

75.

Lièvre

, Bachet

, Boige

, Cayre

, Le Corre

, Buc

, KRAS mutations as an independent prognostic factor in patients with advanced colorectal cancer treated with cetuximab. J Clin Oncol 2008;26:374–9

76.

Tol

, Koopman

, Cats

, Chemotherapy, bevacizumab, and cetuximab in metastatic colorectal cancer. N Engl J Med 2009;360:563–72

77.

Van Cutsem

, Köhne

, Hitre

, Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer. N Engl J Med 2009;360:1408–17

78.

Bokemeyer

, Bondarenko

, Makhson

, Fluorouracil, leucovorin, and oxaliplatin with and without cetuximab in the first-line treatment of metastatic colorectal cancer. J Clin Oncol 2009;27:663–71

79.

Califano

, Blackhall

, Finocchiaro

EGFR tyrosine kinase inhibitors in non-small cell lung cancer patients: how do we interpret the clinical and biomarker data?

Targ Oncol 2008;3:173–86

80.

Paez

, Jänne

, Lee

, EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 2004;304:1497–500

81.

Lynch

, Bell

, Sordella

, Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 2004;350:2129–39

82.

Pao

, Miller

, Zakowski

, EGF receptor gene mutations are common in lung cancers from ‘never smokers’ and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A 2004;101:13306–11

83.

Douillard

, Shepherd

, Hirsh

, Molecular predictors of outcome with gefitinib and docetaxel in previously treated non-small-cell lung cancer: data from the randomized phase III INTEREST trial. J Clin Oncol 2010;28:744–52

84.

Mok

, Wu

, Thongprasert

, Gefitinib or carboplatin- paclitaxel in pulmonary adenocarcinoma. N Engl J Med 2009;361:947–57

85.

Deverka

. Pharmacogenomics, evidence, and the role of payers. Public Health Genomics 2009;12:149–57

86.

Newman

, Payne

. Removing barriers to a clinical pharmacogenetics service. Personalized Med 2008;5:471–80

87.

Nielsen

, Moldrup

. The diffusion of innovation: factors influencing the uptake of pharmacogenetics. Community Genet. 2007;10:231–41

88.

Gurwitz

, Zika

, Hopkins

, Gaisser

, Ibarreta

. Pharmacogenetics in Europe: barriers and opportunities. Public Health Genomics 2009;12:134–41

89.

Eichler

, Aronsson

, Abadie

, Salmonson

. New drug approval success rate in Europe in 2009. Nat Rev Drug Discov 2010;9:355–6

90.

Baars

, Scherpbier

, Schuwirth

, Deficient knowledge of genetics relevant for daily practice among medical students nearing graduation. Genet Med 2005;7:295–301

91.

Fargher

, Eddy

, Newman

, Patients’ and healthcare professionals’ views on pharmacogenetic testing and its future delivery in the NHS. Pharmacogenomics 2007;8:1511–9

92.

Payne

, Fargher

, Tricker

, Valuing pharmacogenetics testing services: a comparison of patients and healthcare professionals'preferences. Value Health (in press)

93.

Daly

, Donaldson

, Bhatnagar

, Shen

, Pe'er

, Floratos

, HLA-B*5701 genotype is a major determinant of drug-induced liver injury due to flucloxacillin. Nat Genet 2009;41:816–9

94.

Daly

. Genome-wide association studies in pharmacogenomics. Nat Rev Genet 2010;11:241–6

95.

Ashley

, Butte

, Wheeler

, Chen

, Klein

, Dewey

, Clinical assessment incorporating a personal genome. Lancet 2010;375:1525–35

Pharmacogenetics and pharmacogenomics: a clinical reality

Abstract

Introduction

Pharmacogenetics

Adverse drug reactions

Thiopurine methyltransferase and thiopurines

HLA-B*5701 and abacavir

HLA-B*1502 and carbamazepine

Response to treatment

CYP2C19 and clopidogrel

CYP2C9, vitamin K epoxide reductase complex 1 and oral anticoagulants

CYP2D6 and tamoxifen

Pharmacogenomics

Prediction of tumour recurrence in breast cancer

Therapy selection

Trastuzumab in breast cancer

Anti-epidermal growth factor receptor therapies in colorectal cancer

Anti-EGFR therapies in Lung cancer

Challenges and future perspective

Pharmacogenetics: challenges on the road to the clinic

Future advances

Conclusion

DECLARATIONS

References