ca cancer j clin, 2009 - pharmacogenetics and pharmacogenomics of anticancer agents

DOI: 10.3322/caac.20002 2009;59;42-55 CA Cancer J Clin

R. Stephanie Huang and Mark J. Ratain Pharmacogenetics and pharmacogenomics of anticancer agents

This information is current as of June 7, 2011

http://caonline.amcancersoc.org/cgi/content/full/59/1/42located on the World Wide Web at:

The online version of this article, along with updated information and services, is

http://caonline.amcancersoc.org/subscriptions/individuals only): , go to (USCA: A Cancer Journal for CliniciansTo subscribe to the print issue of

Print ISSN: 0007-9235. Online ISSN: 1542-4863. Williams Street NW, Atlanta GA 30303. (©American Cancer Society, Inc.) All rights reserved.

is owned, published, and trademarked by the American Cancer Society, 250CANovember 1950. Society by Wiley-Blackwell. A bimonthly publication, it has been published continuously since

is published six times per year for the American CancerCA: A Cancer Journal for Clinicians

by on June 7, 2011 (©A

merican C

ancer Society, Inc.)

caonline.amcancersoc.org

Dow

nloaded from

http://caonline.amcancersoc.org/cgi/content/full/59/1/42

http://caonline.amcancersoc.org/subscriptions/

http://caonline.amcancersoc.org:80

Pharmacogenetics and Pharmacogenomics ofAnticancer Agents

R. Stephanie Huang, PhD1,2 and Mark J. Ratain, MD2,3

AbstractLarge interindividual variation is observed in both the response and toxicity associated with anticancer therapy. Theetiology of this variation is multifactorial, but is due in part to host genetic variations. Pharmacogenetic andpharmacogenomic studies have successfully identified genetic variants that contribute to this variation insusceptibility to chemotherapy. This review provides an overview of the progress made in the field ofpharmacogenetics and pharmacogenomics using a five-stage architecture, which includes 1) determining the role ofgenetics in drug response; 2) screening and identifying genetic markers; 3) validating genetic markers; 4) clinicalutility assessment; and 5) pharmacoeconomic impact. Examples are provided to illustrate the identification,validation, utility, and challenges of these pharmacogenetic and pharmacogenomic markers, with the focus on thecurrent application of this knowledge in cancer therapy. With the advance of technology, it becomes feasible toevaluate the human genome in a relatively inexpensive and efficient manner; however, extensive pharmacogeneticresearch and education are urgently needed to improve the translation of pharmacogenetic concepts from bench tobedside. CA Cancer J Clin 2009;59:42-55. ©2009 American Cancer Society.

To earn free CME credit for successfully completing the online quiz based on this article, go to http://CME.AmCancerSoc.org.

IntroductionIt has long been observed that interpatient variability in response to medications is associated with a spectrum ofoutcomes, ranging from failure to demonstrate an expected therapeutic effect to an adverse reaction resulting insignificant patient morbidity and mortality, as well as increasing healthcare costs.1,2 Interpatient variation is due, at leastin part, to genetics. The term “pharmacogenetics” represents the study of genetic factors that influence response todrugs and chemicals and was first termed in 1959.3 Recently, advances in large genome scale sequencing andimprovements in bioinformatic tools in processing large amounts of data have led to the transition of pharmacogeneticsto pharmacogenomics, involving studies of the entire spectrum of genes in the human genome.3

The goal of the emerging disciplines of pharmacogenetics and pharmacogenomics (abbreviated jointly as PGx)is to personalize therapy based on an individual’s genotype. To date, the success of PGx has spread across all fieldsof medicine. Genetic information has been used in the identification of disease risk (eg, the BRCA1 mutation testto evaluate breast cancer risk), choice of treatment agents (eg, CYP2D6 in breast cancer treatment; HLA-B*1502for carbamazepine), and guiding drug dosing (eg, CYP2C9 and VKORC1 for warfarin dosing, UGT1A1 foririnotecan, and TPMT for 6-mercaptopurine and azathioprine). This is particularly important for chemothera-

1Instructor of Medicine, Section of Hematology and Oncology, Department of Medicine, University of Chicago, Chicago, IL; 2Committee on Clinical Pharma-cology and Pharmacogenomics, Cancer Research Center, University of Chicago, Chicago, IL; 3Leon O. Jacobson Professor of Medicine, Section of Hematologyand Oncology, Department of Medicine, University of Chicago, Chicago, IL.

Corresponding author: Mark J. Ratain, MD, Section of Hematology and Oncology, Department of Medicine, University of Chicago, 5841 S. Maryland Avenue, MC2115,Chicago, IL, 60637; [email protected]

DISCLOSURES: Dr. Huang was supported by GM 007019. Dr. Ratain has received royalties related to UGT1A1 genotyping, is a coinventor of pending related patents,and has stock ownership in Applera and Illumina. No other conflict of interest relevant to this article was reported.

�2009 American Cancer Society. doi:10.3322/caac.20002

Available online at http://cajournal.org and http://cacancerjournal.org

PGx of Anticancer Agents

42 CA: A Cancer Journal for Clinicians


merican C



Dow

nloaded from


peutic agents, which in general affect both tumor andnontumor cells and thus have a narrow therapeuticindex, with the potential for life-threatening toxicity.Medical oncologists and hematologists are striving toindividualize cancer treatment in an effort to maxi-mize efficacy and minimize toxicity in patients. Iden-tifying host genetic variations that contribute to drugefficacy and/or the risk of toxicity will provide ameans with which to tailor therapy. Genetic variationcould explain variations including pharmacokinetics,alterations in activity or expression of the target, orproteins involved in the mechanism of action of thedrug. PGx studies of anticancer agents are potentiallycomplicated by somatic mutations in the tumor, al-though this is unlikely to impact toxicity.

In the scope of anticancer PGxs, genotypic infor-mation can encompass, but is not limited to, singlenucleotide polymorphisms (SNPs; a change in whicha single base in the DNA differs from the usual baseat that position), haplotypes (a set of closely linkedgenetic markers present on one chromosome thattend to be inherited together), microsatellites or sim-ple sequence repeats (polymorphic loci present inDNA that consist of repeating units of 1-6 base pairsin length), insertion and/or deletion and copy num-ber variations (CNVs; genetic trait of differences inthe number of copies of a particular sequence presentin the genome of an individual), and aneuploidy (achange in the number of chromosomes that can leadto a chromosomal abnormality) and loss of heterozy-gosity in the tumor. Phenotype is defined as thecharacteristics determined by genetic, environmentalfactors or their combination. Phenotype can takemany different forms. For example, it could simplybe eye color, or it can be a pharmacokinetic finding(eg, a specific metabolite formation), a clinicalmarker (eg, tumor volume), or a more complicatedtrait (eg, overall survival after treatment). Interest-ingly, researchers from different fields may definephenotypes differently. For example, mRNA expres-sion is treated as a phenotype by geneticists becauseit is a product of DNA; however, clinicians oftenlump gene and gene products (eg, RNA and protein)together as genetic predictors.4 A clear definition ofphenotype is critical both in conducting and interpret-ing PGx studies. As an example, when evaluating thegenetic contribution to platinum agent-induced toxicityin patients with non-small cell lung cancer, a geneticpolymorphism in the ERCC1 gene (C8092A) was

found to be associated with an increased risk of grade 3or 4 gastrointestinal toxicity (defined by the NationalCancer Institute Common Toxicity Criteria version3.0). However, when using overall toxicity or hemato-logic toxicity as the phenotype of interest, no genotype-phenotype associations were identified.5 Furthermore,the treatment conditions under which the phenotypeswere obtained may affect the interpretation of the gen-otype-phenotype association. Through a meta-analysis,Hoskins et al demonstrated that the UGT1A1*28 poly-morphism is associated with an increasing risk of he-matologic toxicities only at medium or high doses ofirinotecan.6

This review will provide an overview of theprogress made in the field of PGx using a five-stagearchitecture (Fig. 1). Although considerable efforthas been applied to identifying gene expressionmarkers that affect drug response, this review willfocus mainly on the germline genetic effects on drugsensitivity. Examples will be provided to illustrate theidentification, validation, utility, and challenges ofthese PGx markers with a focus on the current ap-plication of PGx knowledge in cancer therapy.

Determining the Role of Genetics inDrug ResponseBefore conducting a PGx study, it is important todetermine whether genetic variation is likely to havea significant impact on the phenotype of interest.Heritability analysis is often used as an approach ingenetics to screen for the presence of a heritable trait.The goal of heritability analysis is to determine howmuch of the variation in phenotype can be attributed

FIGURE 1. Five Stages of Pharmacogenetics and Pharmacogenomics inCancer Therapy.

CA CANCER J CLIN 2009;59:42-55

43VOLUME 59 � NUMBER 1 � JANUARY/FEBRUARY 2009


merican C



Dow

nloaded from


to genetic variance. Heritability measures can rangefrom 0 to 1. A heritability measure close to 1 impliesthat nearly all variations in the population result fromvariations in genotypes.7 A heritability measure closeto 0 for a trait implies that nearly all variations aredue to environmental causes. A significant heritablecomponent for a given phenotype provides a strongfoundation for follow-up genetic analysis.

To estimate the heritability of complex humanphenotypic traits, twin studies have been commonlyused because identical (monozygotic) twins share(approximately) the same genotype whereas noniden-tical (dizygotic) twins do not. If monozygotic anddizygotic twins share similar environments, the dif-ferences in the phenotype of interest may be expectedto be due to differences in genotype. Heritability canalso be estimated in large pedigrees, which comparesthe variances within family pedigrees with thoseamong the population.

Clinically, alcoholism8 and cigarette smoking9

have been found to be strongly heritable. Further-more, Faraday et al10 evaluated the ex vivo plateletfunction before and after aspirin ingestion in 1880subjects. These platelet function phenotypes weregrouped as cyclooxygenase-1 (COX-1)–dependent ifarachidonic acid was the platelet stimuli or if athromboxane metabolite was measured. All othermeasures of platelet function testing were deemedCOX-1–independent (eg, whole blood aggregation),which represents residual platelet function after as-pirin exposure. The authors performed heritabilityanalyses on both COX-1–dependent and COX-1–independent phenotypes and found phenotypes indi-rectly related to COX-1 were strongly and consis-tently heritable in both white and African Americanpopulations, whereas COX-1–dependent pheno-types were only heritable in the white population.10

This provides a strong genetic basis for the adequacyof platelet suppression by aspirin. Luciano et al dem-onstrated that the heritability of coffee-attributedsleep disturbance was approximately 0.4, which sug-gest that 40% of the overall variation in sleep distur-bance is due to genetic factors.11 However, a herita-bility study of toxic drugs (eg, most anticanceragents) is not possible in unaffected family members.Instead, an approach using cell lines from large ped-igrees has been used for several cytotoxic agents,including bleomycin,12 cisplatin,13 docetaxel,14 flu-orouracil (5-FU),14 and daunorubicin.15

Screening and IdentifyingGenetic MarkersOnce the genetic contribution is confirmed, the nextstep is to identify the causative genetic markers (orgenetic markers correlated with the causative marker)for the phenotypes of interest, which can be as spe-cific as gene expression, or as broad as overall survival.In general, there are 2 approaches used to evaluatehow genetic variation contributes to human varia-tions in drug response and toxicity: candidate geneand genome-wide. Candidate gene approaches focuson one or more candidate genes or pathways, aregenerally hypothesis-driven, and are chosen based onevidence that the gene product is involved in varia-tions in pharmacokinetics or pharmacodynamics. Incontrast, a genome-wide approach gives equal weightto all genes in the genome, is hypothesis-generating,and can be used when little is known regardinggene-drug effect in an effort to be unbiased.

Candidate Gene ApproachThe choice of candidate genes is based on the currentknowledge of human pathophysiology, pharmacol-ogy, and cancer biology. The hypothesis is that ge-netic variations in genes that play an important rolein the pharmacokinetics or pharmacodynamics of adrug would likely affect the drug’s efficacy and/ortoxicity. A positive finding through a candidate geneapproach is easy to interpret and can yield clinicallyrelevant information. However, a negative result canbe interpreted in many different ways. Often, thesample size is too small to detect an effect, there maybe a lack of inclusion of the causal genetic polymor-phism, or there may be a true absence of an effect. Inoncology, the candidate gene approach has focusedon genes encoding substances involved in the metab-olism or transport of anticancer agents, as well asdrug targets and downstream events leading toapoptosis.16,17 These studies are usually conductedusing clinically relevant samples (eg, blood, liver, orintestinal tissues or tumor specimens), which repre-sent either drug toxicity or functional sites. Ofcourse, the germline DNA sequence remains thesame regardless of the tissue of origin. Therefore, thesample collection site is often based on practicalissues, as well as the phenotypes of interest (eg, incases of tissue-specific gene expression). PGx re-search can either focus on known SNPs (ie, genotyp-




merican C



Dow

nloaded from


ing) or the identification of new SNPs in candidategenes (ie, sequencing).

Although candidate gene approaches have hadreasonable success in identifying genetic variants thatare important in specific phenotypes (eg, drug me-tabolism, the mechanisms of action of drugs), clini-cally relevant phenotypes, such as drug toxicity orresponse, are more complex and therefore likely toinvolve multiple genes or pathways. Thus, instead ofsearching for a “dramatic genetic effect” produced byone gene, it is more realistic to consider a group ofgenetic variants, each with a moderate effect, whichtogether result in an overall genetic effect in drugefficacy or toxicity. Furthermore, to our knowledge,the functions of many of the 20,000 to 25,000 genesin the human genome18 have not been well studied todate. To resolve these issues, a broader approach hasbeen used.

Genome-wide ApproachGenome-wide approaches in PGx refer to the globalstudy of genetic variations within the human genomefor their effects on drug treatment. The hypothesis isthat any genetic variant in the human genome cancontribute to variation in drug effect. Therefore,these studies are not biased toward current knowl-edge of gene function and have the potential toidentify multiple genetic variants that contribute tocomplex clinical traits. Recent advances in genomictechnology such as genome scale microarray geno-typing platforms (which identify SNPs and CNVs),microarray-based comparative genomic hybridization(array CGH; which detects chromosome copy num-ber changes), and transcriptional level gene expres-sion platforms (which measure mRNA level geneexpression), along with the development of softwareto accomplish the analysis of these large data sets,have allowed researchers to perform genome-wideassociation study (GWAS) between genetics andphenotypes.

GWAS is an examination of genetic variationsacross the human genome, designed to identify ge-netic associations with observable traits such as bloodpressure or weight, or with/without a disease or con-dition. As with all PGx studies, a clearly definedphenotype of interest is essential. Phenotypes evalu-ated in GWAS can be either qualitative/categoricfactors (response/no response, alive/dead) or quanti-tative/continuous measures (tumor volume, minimal

residual disease). Analyzing genome scale geneticdata requires large computational capacity and gen-erally has a high risk of false discovery. Given a Pvalue of .05, one can expect 5 false-positive findingsafter 100 tests. When 1 million tests are performed,a large number of positive findings can be false dis-coveries. Many statistical methods have been appliedto reduce the false discovery rate, including usingstringent P value cutoff values (eg, Bonferroni cor-rection). Another substantial challenge associatedwith GWAS is the interpretation of statistically sig-nificant findings.

Several national and international collaborativeefforts have provided large amounts of genetic andexpression information from different samplesincluding human lymphoblastoid cell lines(LCLs; International HapMap),19 tumor cell lines(NCI-60; available at: http://dtp.nci.nih.gov/docs/misc/common_files/cell_list.html; Accessed Novem-ber 20, 2008), blood,20 and tumor biopsy samples.21

These international efforts have all had the commonprinciple of public data sharing. LCLs were derivedfrom peripheral blood B-lymphocytes that have un-dergone in vitro Epstein-Barr virus transformation toresult in immortalization. In particular, the Interna-tional HapMap LCLs were derived from individualswith no apparent disease. Using LCLs, Huang et aldeveloped a “triangle approach” that integrates SNPgenotype, gene expression, and in vitro cellular sen-sitivity to drugs to identify genetic variants that con-tribute to sensitivity to chemotherapeutic agentsthrough their effect on gene expression.22,23 The sta-tistical associations of the triangle approach result ina final set of SNPs that comprise a “pharmacogeneticsignature” that determines susceptibility to chemo-therapeutic-induced cytotoxicity. A follow-up multi-variate model was performed to limit the number ofgenetic variants identified through this model thatexplain the observed human variations in cellularsensitivity to chemotherapy. The pharmacogeneticsignature SNPs are interesting candidates for bothfollow-up clinical and bench studies. These studiesrepresent a new paradigm in studies of drug pharma-cology by evaluating the entire genome for geneticvariations that may influence the expression of genesthat are important in drug sensitivity. Because thetriangle approach involves multiple testing, which isinherently associated with false discovery, replication,as with all GWAS, is imperative.




merican C



Dow

nloaded from


Given the similar goal and complementary natureof candidate gene and genome-wide approaches, onecan imagine that a combined candidate and genome-wide approach would likely provide a list of geneticvariants that contribute to complex phenotypes thatcan be tested in the clinical trials.

Validating Genetic Markers

Replication and ValidationReplication is an important principle in all geneticstudies. This is particularly important when a ge-nome-wide approach is used to obtain potential ge-netic markers. Several large GWAS that focused onidentifying disease risk-associated genetic markershave set good examples in using replication samples.For example, a GWAS conducted in 14,000 cases of7 common diseases and 3000 controls confirmedmany previously identified disease-associated loci andfound compelling evidence that some loci confer riskfor more than 1 of the diseases studied.20 Further-more, disease-related loci have also been identifiedand replicated in patients who have prostate cancer,24

bipolar disorder,25 and colorectal cancer.26

If a genotype-phenotype association is replicated,functional studies are usually performed to gain a betterunderstanding of the nature of the association and iden-tify the causative variant. There are many reasons forfailing to replicate the initial genotype-phenotype asso-ciation. It can be that the initial association occurred bychance, or the genetic effect may be smaller than hy-pothesized based on prior studies, potentially due tofactors such as disease status, comorbidity, the admin-istration of other drugs, or patients’ demographic char-acteristics. Unless there are distinguishable characteris-tics between the initial screen data set and thesubsequent replication data set(s), failure in replicationsuggests the particular variation is not a sole candidatemarker for a large-scale follow-up study.

Large genetic effect sizes as well as well-definedphenotypes are critical in the success of clinical val-idation. In addition, consistency of potential con-founding factors (eg, patients’ demographic charac-teristics) between the discovery set and validationdata set is important. The design of a clinical vali-dation study needs to consider such variabilities totest the hypothesis generated from the initial screen-ing data set. Exploring the clinical implication of

genetic predictors in other populations will broadenthe utility of PGx in practice.

Clinical Utility AssessmentOnce validated, PGx markers can be measured beforethe initiation of therapy. The information will betterinform prescribers as to whether the patient is at anincreased risk for nonresponse and/or developingdrug-associated toxicities, and can therefore guidetheir choices of treatment/dose to the individual pa-tient based on the drugs’ therapeutic index. Ideally,an accurate, rapid genotyping assay is required forfast turnaround time. Large prospective clinical stud-ies are also required to provide guidance regardingalternative treatments or dosages. Lastly, the educa-tion of prescribers, payers, and patients is essential.

Practical GenotypingA genotyping assay needs to be specific to the geneticvariants of interest and sensitive in identifying thecausal allele. Genotyping is generally performed bycommercial and academic reference laboratories, aswell as by a growing number of hospital laboratories.These assays vary from tests for a single geneticvariation (UGT1A1 promoter polymorphism, MayoMedical Laboratory27; TaqMan SNP GenotypingAssays, Applied Biosystems [available at: https://products.appliedbiosystems.com/ab/en/US/adirect/ab?cmd�catNavigate2&catID � 602849; Accessed No-vember 20, 2008]; GSTM1 CNV, Applied Biosystems[available at: https://products.appliedbiosystems.com/ab/en/US/adirect/ab?cmd�catNavigate2&catID�603644;Accessed November 20, 2008]), for series of genes(CYP2D6 and CYP2C19 on AmpliChip CYP450 Test,Roche Diagnostics),28 for hundreds to thousands of genevariants (Genome-wide Human SNP Array 6.0, Af-fymetrix; Agilent Human Genome CGH Microarray244A, Agilent; and Illumina 550K Infinium Human-Hap550 SNP Chip, Illumina), or for the entire humangenome (23andMe).29 A list of laboratories and clinics thatperform genetic tests and consultations can be foundon a National Institutes of Health-funded website(GeneTests),30 although only a small minority of ge-netic tests listed on this site are pharmacogenetic tests.In order for this genetic information to be clinicallyuseful, it must be available within a timeframe that isrelevant for the therapeutic decisions it is intended toguide.




merican C



Dow

nloaded from


In addition to genotyping, gene expression profilingand enzyme activity tests (phenotyping assays) may beused as surrogates for genetic variability. For example,in the evaluation of predictive markers for drug sensi-tivity, Holleman et al generated gene expression predic-tion markers for chemoresistance in 173 children withacute lymphoblastic leukemia (ALL). These predictionmarkers were confirmed in an independent cohort of 98ALL patients treated at a separate institute.31 Morerecently, Potti et al developed gene expression signa-tures that predict sensitivity to chemotherapeutic drugsusing NCI-60 cell lines.4 Each signature was validatedin an independent set of cancer cell lines. The authorsfurther demonstrated that many of these signaturesappear to predict clinical response in patient popula-tions.4 In clinical practice, estrogen receptor, progester-one receptor, and HER-2/neu status have been com-monly used as predictors of breast cancer prognosis. Adiagnostic assay, Oncotype DX, quantifies the likeli-hood of breast cancer recurrence and assesses the benefitfrom chemotherapy in women with newly diagnosed,early stage breast cancer. This test has been recom-mended in the 2007 Update of Recommendations forthe Use of Tumor Markers in Breast Cancer from theAmerican Society of Clinical Oncology32 and the Na-tional Comprehensive Cancer Network (NCCN) 2008Clinical Practice Guidelines in Oncology Breast Can-cer (available at; http://www.nccn.org/professionals/physician_gls/PDF/breast.pdf; Accessed Novem-ber 20, 2008). It is worth mentioning that allexpression prediction markers are currently gener-ated in neoplastic cells. To the best of our knowl-edge, germline gene expression signatures have notbeen extensively studied as cancer PGx markers.

For enzyme activity tests, examples include thethiopurine S-methyltransferase (TPMT) activity testin red blood cells,33 which is used for guiding theprescription of 6-mercaptopurine or azathioprine,and the CYP3A activity test using midazolam34 orthe erythromycin breath test (which measures liverCYP3A4 catalytic activity)35 to evaluate potentialdrug-drug interactions (eg, between ketoconazoleand cyclosporine). The advantage of testing geneexpression or enzyme activity is that it theoreticallywould have a higher correlation with clinical pheno-types, assuming that the assay is well validated. How-ever, gene expression may change after drug exposureand measurement of enzyme activity before everytreatment adds additional cost and time, and is un-

likely to be cost-effective. Conversely, an individual’sgermline DNA sequence remains unchanged over aperson’s lifetime, and there is no need to reanalyze.36

Interpretation of the Data: HealthcareProfessional EducationThe complexity of human genetics makes the interpre-tation of single-assay results difficult. Genetic variationsthat contribute to drug effect can take on differentforms. They could be a single SNP, a haplotype (a set ofSNP combinations), or a gene CNV (gene deletion orduplication). Different ethnic populations may havedifferent variations in allele frequency.37,38 Furthermore,the effect of any specific genetic variant will vary bydrug. Therefore, the education of prescribers regardingPGx is a major challenge.

Evidence-based PGx DosingMany clinicians acknowledge the importance of ge-netics in drug response and are enthusiastic aboutusing genetic information to guide therapy. Al-though our knowledge of the relation between spe-cific genetic variants and clinical outcomes is increas-ing, we know far less regarding how to individualizetherapy. However, if PGx studies are routinely in-corporated into large (ie, phase 3) clinical trials, wewill gain knowledge concerning the predictive valueof PGx, which will eventually enable the individual-ization of therapy.

Pharmacoeconomic ImpactPGx is expected to improve patients’ treatment out-comes by increasing efficacy and decreasing toxicity,and eventually reducing overall healthcare costs.Given the high incidence of cancer- and treatment-associated toxicity as well as the cost of treatingcancer and protecting patients from toxicity, it isparticularly promising to demonstrate a pharmaco-economic benefit using PGx testing. With the in-creasing number of PGx findings, continuing educa-tion for prescribers and payers concerning updatedPGx information is critical. Both retrospective andprospective trials evaluating the pharmacoeconomicimpact of PGx testing in cancer therapy will likelyprovide answers for policy making in the incorpora-tion of PGx testing into clinical practice; however,one should keep in mind that it will not be feasible toconduct randomized trials of each and every diagnos-




merican C



Dow

nloaded from


tic test, and the economic value of such tests can bemodeled using decision analysis techniques.

Examples

TamoxifenTamoxifen, a selective estrogen receptor modulator,has been successfully used in the treatment of breastcancer for more than 30 years39 and has been ap-proved for breast cancer prevention since 1998. Untilrecently, clinically useful predictors (other than thepresence of estrogen and progesterone receptors) thatidentify those individuals most likely to benefit fromtamoxifen therapy or develop toxicity have been lack-ing. Recent studies have identified allelic variations inCYP2D6 to be an important determinant of tamox-ifen’s activity (and toxicity), because CYP2D6 is re-sponsible for the formation of tamoxifen’s activemetabolite.40-43

CYP2D6 is responsible for the metabolism of 25%of all drugs currently on the market that undergometabolism44 and its genetic polymorphism signifi-cantly affects the metabolism of approximately50% of those.45 To date, more than 71 differentfunctional CYP2D6 gene variants have been de-scribed (available at: http://www.cypalleles.ki.se/cyp2d6.htm; Accessed November 20, 2008), andthese are divided into alleles causing abolished (null),decreased, normal, and ultra-rapid enzyme activity.The most important null alleles are CYP2D6*4(splice defect) and CYP2D6*5 (gene deletion),whereas the most common alleles with severely re-duced activity are CYP2D6*10, CYP2D6*17, andCYP2D6*41 (splicing defect). The CYP2D6 gene issubject to many CNVs. A detailed summary ofCYP2D6 genetic variations and their functional con-sequences can be found in a recent review by In-gelman-Sundberg et al.45 The CYP2D6 alleles aresubject to very significant interethnic differences inwhich poor metabolizers (the 2 null allele carriers) arefound mainly in Europe and ultra-rapid metabolizers(individuals having more than 2 normal CYP2D6alleles) are found in North Africa and Oceania; in-termediate metabolizers (carriers of a reduced func-tional allele) are to a great extent located in Asia dueto the high prevalence of the CYP2D6*10 allele.46

It has been shown that tamoxifen is metabolizedby CYP2D6 to 4-hydroxy-tamoxifen and endox-

ifen,42 which exhibit approximately 100 times greateraffinity for the estrogen receptor than the parentdrug, tamoxifen.42,47,48 Goetz et al reported a shorterrecurrence-free survival time and lower disease-freesurvival rate in tamoxifen-treated women who werehomozygous for the null allele CYP2D6*4 (poor me-tabolizers) compared with women who were het-erozygous or homozygous for the wild-type allele(intermediate or extensive metabolizers).40 These ho-mozygous variant carriers also experienced less severehot flashes when compared with wild-type allele car-riers.40 The same group of authors estimated thatwomen who were poor CYP2D6 metabolizers hadthe highest risk of breast cancer recurrence (hazardsratio of 3.12; P � .007). CYP2D6 metabolism, asmeasured by genetic variation and enzyme inhibition,was found to be an independent predictor of the riskof breast cancer recurrence in postmenopausalwomen receiving tamoxifen for the treatment of earlybreast cancer.49 These findings were confirmed byseveral other groups.50 In addition, breast cancer pa-tients in a Japanese population who carried theCYP2D6*10 allele were found to have a significantlyhigher incidence of disease recurrence with adjuvanttamoxifen monotherapy.51 Furthermore, medicationsthat decrease CYP2D6 activity, such as antidepres-sants, were also shown to decrease the efficacy oftamoxifen treatment.40,42 These research findingsled an advisory committee of the US Food and DrugAdministration (FDA) to unanimously recommend alabel change for tamoxifen in 2006 (available at: http://www.fda.gov/ohrms/dockets/ac/06/briefing/2006-4248B1-01-FDA-Tamoxifen%20Background%20Summary%20Final.pdf; Accessed November 20, 2008), including mentionof CYP2D6 genotype testing as an option for womenbefore they are prescribed tamoxifen. However, theFDA label change recommending CYP2D6 genotypetesting before tamoxifen treatment is still pending. Al-though we believe that the overall data supportthis proposed label change, prospective studies arewarranted.52

At the same time, inferring CYP2D6 phenotypefrom genotype is increasingly challenging, consider-ing the growing number of alleles and their range ofactivity. Gaedigk et al proposed an “active score”system that categorized individuals of white or Afri-can American heritage into different groups based onthe metabolism profiles of 672 subjects for dextro-methorphan, a CYP2D6 probe drug, over 25




merican C



Dow

nloaded from


CYP2D6 allelic variants.53 Furthermore, the Ampli-Chip technology allowed for the identification of theCYP2D6 genotype and reported individuals as poormetabolizers, intermediate metabolizers, extensivemetabolizers, or ultra-rapid metabolizers. This testwas approved by the US FDA on December 24, 2004and has been adapted by several commercial geno-typing companies (eg, DNAdirect).54

To our knowledge, with the exception of ongoingclinical trials (available at: http://www.clinicaltrial.gov; Accessed November 20, 2008), CYP2D6 geno-typing has not been routinely incorporated into clin-ical practice. However, given the broad spectrum ofCYP2D6 substrates, the relatively high frequency ofCYP2D6 genetic variations, and their confirmed rolein multiple drug treatments, it would not be surpris-ing if CYP2D6 genotyping were gradually adoptedinto clinical practice. Interestingly, a recent modelinganalysis suggested that CYP2D6 genotyping may beused for determining the optimal adjuvant endocrinetherapy for postmenopausal breast cancer patients. Inthis analysis, 5-year disease-free survival outcomeswere found to be similar or perhaps even superiorwith tamoxifen compared with aromatase inhibitorsin patients who were carriers of the wild-typeCYP2D6. Based on their findings, the authors con-cluded that endocrine therapy tailored to theCYP2D6 genotype could be considered for womenwho are newly diagnosed with breast cancer, partic-ularly those who have concerns about either the rel-ative toxicity or the increased cost of aromatase in-hibitors.55

Notwithstanding the pharmacogenetic developmentsmentioned above, there are still significant variations inoutcome that are not explained by CYP2D6 genotype.Therefore, candidate gene studies have taken place toevaluate other genes of interest. For example, geneticpolymorphisms and CNVs in SULT1A1, a phase 2enzyme that is important in tamoxifen metabolism,have been evaluated for their effects on tamoxifen me-tabolism56; CYP3A5*3 genotypes have been tested as anoutcome predictor in breast cancer patients treated withtamoxifen.57 Furthermore, estrogen-regulated genesidentified through global gene expression array analysishave been evaluated in breast cancer cell lines.58 Theexpression of epidermal growth factor receptor andHER2,43 HOXB13, and IL-17BR expression ratios41

were studied in patient tumor samples. With the in-creasing knowledge of human genetics and PGx, it is

likely that more genetic polymorphisms/genes will beidentified that will eventually provide a comprehensiveexplanation of the genetic contributions to tamoxifentreatment.

6-mercaptopurine6-mercaptopurine is commonly used for the treat-ment of ALL. It is a prodrug that is activatedby hypoxanthine guanine phosphoribosyl transferaseto 6-thioguanine nucleotides (TGN), which areincorporated into DNA. TPMT inactivates 6-mer-captopurine by S-methylation and thereby decreasesthe formation of active TGN in hematopoietictissues (available at: http://www.pharmgkb.org/do/serve?objIdA2040&objCls�Pathway; Accessed No-vember 20, 2008).59 As 1 of the classic PGx examplesin cancer therapy, TPMT activity in human beingswas found to be trimodally distributed,33 with ap-proximately 90% of individuals having high activity,10% having intermediate activity, and 0.3%having low or undetectable enzyme activity. TPMTactivity has been shown to correlate with 6-mercapto-purine toxicity and therapeutic efficacy60; the higher theTPMT activity, and therefore less formation of theactive TGNs, the less 6-mercaptopurine toxicity andthe higher risk of disease recurrence after 6-mercapto-purine therapy.61,62

To the best of our knowledge, PGx studies haveidentified at least 21 nonsynonymous variations inTPMT to date, 17 of which were shown to havereduced TPMT activity.63,64 Among these geneticvariations, TPMT*2, TPMT*3A, and TPMT*3C ac-count for greater than 90% of cases with low orintermediate TPMT enzyme activity.59 Therefore, bygenotyping patients for these 3 variants before6-mercaptopurine therapy, the majority of patientswho are at greatest risk for severe toxicity can beidentified and decisions regarding the need for dosereductions or other modifications can be made beforethe patient is exposed to the drug.

In 2003, a US FDA advisory committee recom-mended the addition of pharmacogenetic informa-tion concerning TPMT polymorphisms and treat-ment toxicity to the drug label for 6-mercaptopurine.This led to changes to the label for 6-mercaptopurinein 2004, with TPMT testing and dosage recommen-dations provided for TPMT-deficient patients (avail-able at: http://www.fda.gov/medwatch/SAFETY/2004/jul_PI/Purinethol_PI.pdf; Accessed November




merican C



Dow

nloaded from


20, 2008). Based on a recent study, TPMT genotyp-ing has been assessed as being cost-effective in chil-dren with ALL. After considering TPMT genotyp-ing costs, estimates of the frequency of TPMTdeficiency, rates of thiopurine-mediated myelosup-pression in TPMT-deficient individuals, and myelo-suppression-related hospitalization costs in 4 Euro-pean countries, the study found that the cost perlife-year gained by TPMT genotyping in ALL pa-tients was €2100, based on genotyping costs of €150per patient.65

Currently, pretherapy TPMT genotyping and ac-tivity tests are only routinely ordered at a limitednumber of academic centers,66 one of which is St.Jude Children’s Research Hospital. Children’s On-cology Group ALL trial protocols include TPMTgenotyping when persistent myelosuppression is ob-served. A similar relation between TPMT genotypeand toxicity has been demonstrated for azathio-prine,67 which has led to the use of genotype-guideddosing by gastroenterologists using this antimetabo-lite for patients with inflammatory bowel disease.68 Itis likely that there is more use of this particularly testin gastroenterology than oncology, because the severeneutropenia associated with TPMT deficiency can beavoided in this clinical context. Furthermore, thelimited utilization of TPMT genotyping could be dueto different hospital policies or other practical issues(eg, genotyping capacity and slow turnaround time).Comprehensive evaluations regarding cost-effective-ness in different populations would be helpful.69 Inaddition, patients who share the same TPMT geno-types still exhibit considerable variations in their re-sponse to 6-mercaptopurine, suggesting that otherunidentified genetic variations may contribute to thetoxicity and response of 6-mercaptopurine.

IrinotecanIrinotecan is commonly used for the treatment ofpatients with colorectal and lung cancers. However,up to 30% of patients experience unacceptably severediarrhea or neutropenia, depending on the dose andschedule used.70 The prodrug irinotecan is convertedby carboxylesterases to a more active metabolite, SN-38. UDP-glucuronosyltransferase 1A1 (UGT1A1) isthe major UGT1A isoform that conjugates SN-38 toan inactive SN-38 glucuronide71; however, geneticvariations in other glucuronosyltransferases (eg,UGT1A7 and UGT1A9)72-74 and transporters (eg,

ABCB1, ABCC2, and ABCG2)75-77 have also beensuggested to contribute to the variability in irinotecanpharmacokinetics and toxicity.

In white populations, the UGT1A1*28 polymor-phism (the presence of an additional TA repeat in theTATA box of the UGT1A1 promoter [TA6]) is themost common variant associated with Gilbert syn-drome, a benign form of familial hyperbilirubinemia.78

The insertion of an additional repeat (TA7) is associ-ated with a decrease in UGT1A1 expression and theconsequently decreased glucuronidation of its targets.78

The association between UGT1A1*28 and irinotecantoxicity was first demonstrated by Iyer et al,71 and hasbeen confirmed in multiple studies, although the impactof this polymorphism is highly dependent on the irino-tecan dose administered.6

Based on PGx evidence, the US FDA has approvedthe addition of a warning to the irinotecan label(available at: http://www.fda.gov/medwatch/SAFETY/2005/Jun_PI/Camptosar_PI.pdf; Accessed November20, 2008), as well as the marketing of the InvaderUGT1A1 Molecular Assay (Third Wave Technolo-gies) for the detection of UGT1A1*28.27,69,79 The base-line serum bilirubin level has also been evaluated inpredicting toxicity or efficacy among patients receivingirinotecan for metastatic colorectal cancer. Althoughmodest elevations in bilirubin are associated with in-creased grade 3 to 4 neutropenia in patients treated withweekly irinotecan, the baseline serum bilirubin is notreported to reliably predict overall irinotecan-relatedtoxicity or efficacy.80 Additional methods, includingDNA sequencing and fragment analysis, have beencompared with the Invader assay. All 3 methods werevaluable for genotyping the UGT1A1 (TA)n repeat,with the sequencing and size-based assays found to havethe fewest drawbacks.81

As with tamoxifen, UGT1A1 genotyping is notroutinely performed when predicting irinotecan tox-icity in current clinical practice. There are manyappropriate explanations for the low usage of thistest.27 For example, although genotyping has beenconsistently associated with the hematologic toxicityinduced by higher doses of irinotecan, the risk isreduced at the lower doses used in combination ther-apy.6 Another concern is the potentially decreasedefficacy if the irinotecan dose is prospectively reducedbecause, to our knowledge, no studies have beenperformed to date to demonstrate that efficacy ispreserved in this context. In addition, the lack of




merican C



Dow

nloaded from


established reimbursement, and the lack of educationfor clinicians regarding the potential value (and lim-itations) of testing have limited the utility ofUGT1A1 genotyping. Nevertheless, the discovery,validation of candidate genetic variants, and estab-lishment of useful genotyping methods in predictingirinotecan-related toxicity was a paradigmatic successin pharmacogenetic research and translational stud-ies.

5-FU5-FU has been widely used in the treatment of solidtumors (eg, colorectal cancer) and remains the back-bone of many combination chemotherapy regi-mens.82 Despite its clinical benefit, 5-FU is associ-ated with frequent gastrointestinal and hematologictoxicities,83 which often leads to treatment discon-tinuation. 5-FU undergoes complex anabolic andcatabolic biotransformation. Gene products involvedin this transformation include dihydropyrimidine de-hydrogenase (DPD or DPYD), which breaks down5-FU,84-88 and those drug targets (eg, thymidylatesynthase [TS or TYMS])89,90 and methylenetetrahy-drofolate reductase (MTHFR). Several of these geneshave been shown to affect 5-FU treatment outcomes.

Both genetic and nongenetic factors have beenassociated with 5-FU toxicity.82 Watters et al usedLCLs from white pedigrees to demonstrate that ap-proximately 26% to 65% of human variations insusceptibility to 5-FU-induced cytotoxicity are due togenetic components.14 In addition, both age and sexhave been shown to influence 5-FU clearance,91,92

and female sex is reportedly associated with morefrequent and severe 5-FU toxicity.93,94

Candidate gene approaches have demonstrated as-sociations between 5-FU treatment outcomes andgermline polymorphisms in DPYD, TYMS, andMTHFR. DPD, encoded by DPYD, plays a key rolein the catabolic breakdown of 5-FU. The DPYDgene is located in human chromosome 1p22 and iscomprised of 23 exons encompassing approximately950 kilobase pairs.95 To date, greater than 30 SNPsand deletion mutations have been identified withinDPYD, although the majority of these variants haveno functional consequences on enzymatic activity.The intronic variant IVS14 � 1 G � A (DPYD*2A,rs3918290), which has been found in up to 40% to50% of patients who developed grade 4 neutropenia,has been associated with DPD deficiency.96 The fre-

quency of low DPD enzymatic activity has also beenshown to vary significantly among different ethnicsubpopulations, with higher mean DPD activity re-ported in Korean subjects and lower activity reportedin African Americans when compared with whiteindividuals.97

TYMS is the primary target of 5-FU. A tandemrepeat polymorphism in the 5�-untranslated region(UTR) and a 6-base pair insertion/deletion polymor-phism in the 3�-UTR of TYMS have been reportedto be associated with altered TYMS expression andclinical response.98 In addition, MTHFR is a keyenzyme that forms the reduced folate cofactor essen-tial for TYMS inhibition by 5-FU. Two linked non-synonymous SNPs, 677C�T and 1298A�C, havebeen shown to alter enzyme activity and possibly5-FU sensitivity.99

More recently, a prospective study conducted bySchwab et al evaluated all these potential geneticpredictors of 5-FU treatment-related toxicity.82 Theyfound the DPYD*2A allele to be a risk factor forsevere mucositis and leukopenia in men but not inwomen, and the TYMS 5�-UTR tandem repeat to beassociated with diarrhea; however, the clinical utilityof these polymorphisms is limited due to poor sen-sitivity and specificity. The authors suggested thatfuture approaches using genome-wide association toidentify additional candidate genes are warranted.82

Several clinical assays have been developed assessingDPD activity, mRNA expression, and metabolite for-mation, as well as SNPs within DPYD.97 In addition toissues related to sample preparation, additional equip-ment requirements, and time consumption, one mainissue preventing the clinical application of these assays istheir limited sensitivity and specificity. For example,Morel et al have shown that the sensitivity, specificity,and positive and negative predictive values of the de-tection of the 3 major SNPs (IVS14 � 1 G�A,2846A�T, and 1679T�G) in DPYD as factors pre-dictive of 5-FU toxicity were 0.31, 0.98, and 0.62 and0.94, respectively.100 They found that only 50% to 60%of patients who carry genetic variations in DPYD de-velop severe 5-FU toxicity.100 This was recently con-firmed by Schwab et al.82 Furthermore, a less pro-nounced genetic contribution of TYMS polymorphismhas been demonstrated in a larger prospective studyconducted in 683 patients, in whom the TYMS 2/2genotype was found to increase the risk of toxicity1.56-fold82 compared with the findings of Lecomte et al




merican C



Dow

nloaded from


in a study of 90 patients, in whom the TYMS 2/2genotype was found to have a grade 3 or 4 toxicity rateof 43% whereas only 3% of patients who had the TYMS3/3 genotype developed those toxicities.101 Recently,Myriad Genetics, Inc. has marketed the TheraGuide5-FU test to predict toxicity to 5-FU (and capecit-abine). This test consists of sequencing the DPYDgene, the identification of known mutations (eg,IVS14 � 1 G�A, D949V, and I560S), and poly-merase chain reaction amplification of TYMS 5�-UTR tandem repeats. The test was designed basedon several clinical studies100-103 and was reported tohave high technical specificity and sensitivity (�1%false-positive variant call and �1% false-negativecall; available at: http://www.myriadtests.com/pro-vider/doc/TheraGuide-5-FU-Tehcnical-Specifications.pdf; Accessed November 20, 2008). However, to ourknowledge, this test has not yet been approved by theUS FDA and its clinical utility requires further study,as exemplified by the recent study by Schwab et al.82

ConclusionsWe have proposed a five-stage architecture for PGxresearch. With the exception of a few drugs/markers,the majority of current PGx research efforts are stillfocusing on the second and third stages (screening/identifying and validating genetic markers). The fieldof PGx has made enormous strides in recent yearswith rapid advances in the fields of systems biologyand genomics, which provide PGx researchers withmany new tools with which to investigate the geneticmarkers for drug response and toxicity. High-throughput technology has allowed the complete se-quencing of the genomes of 2 individuals: Dr. JamesWatson104 and Dr. J.C. Venter.105 A simplified ver-sion of human genomic interrogation has beenlaunched by a commercial company.29 Unfortunately,there is an imbalance between the rapid developmentof genotyping technology, the marketing of genetictests, and the uncertainty in interpreting the clinicalsignificance. Except for the few examples listed inthis review, we lack PGx for common chemothera-peutics such as alkylating agents. To move the fieldforward, the clinical utility and economic impact ofPGx are in need of evaluation, encompassing theeducation of prescribers and payers as well as furtherresearch providing guidance on alternative treatmentsor dosages.

PGx has great relevance in cancer therapy becausecytotoxic chemotherapeutic agents are, in general,nonspecific with a narrow therapeutic index, oftenresulting in serious or even fatal toxicities. In addi-tion, most agents are only effective in a subset ofpatients receiving the drug.106 Many exciting newPGx markers have been identified in both germlineand cancer DNA through either candidate gene orgenome-wide approaches. The techniques are well-established for the candidate gene approach, and thecost is considerably less when compared with thegenome-wide approach. There is a greater rationalefor studying the genetic variants that arise from acandidate gene study in a clinical setting. However,because response to chemotherapy is likely to bemultigenic, the genome-wide approach will be morelikely to identify subtle changes in several genes con-ferring sensitivity to a drug, and may even identify asingle polymorphism with a large effect, such as wasrecently demonstrated for statin-induced myopa-thy.107 For the clinician, the outcome of these studieswill be similar to those of any new investigativetechnology. The first results will need to be verifiedin similar populations by independent groups. Then,the usefulness of the variants for clinical practice willdepend on their improving diagnostic prediction orfostering changes in prevention or treatment strate-gies. There is a compelling need for more, and moreefficient, epidemiologic studies so that these newapproaches can be exploited. To meet this need,scientists and clinicians must collect information, in-formed consent, and tissue samples in the expectationof future studies that will address potential futurequestions.108

On May 21, 2008, President Bush signed theGenetic Information Nondiscrimination Act(GINA), which protects Americans against discrim-ination based on their genetic information, into law.The long-awaited measure, which was debated inCongress for 13 years, will pave the way for people totake full advantage of the promise of personalizedmedicine without fear of discrimination (available at:http://www.genome.gov/24519851; Accessed No-vember 20, 2008). The Genomics and PersonalizedMedicine Act was introduced by Senator BarackObama to overcome the scientific barriers, adversemarket pressures, and regulatory obstacles that havestood in the way of better medicine109 (available at:http://www.govtrack.us/congress/bill.xpd?bill�s109-3822;




merican C



Dow

nloaded from


Accessed November 20, 2008). The US FDA has alsotaken the initiative in aiming to facilitate the integration ofPGx into drug development and clinical practice.110

In summary, although there are still questions tobe answered, PGx researchers now have improvedtools with which to take cancer treatment to the nextlevel. With increasing numbers of novel PGx mark-ers being identified and validated, oncologists willhave a new means with which to make treatmentdecisions for their patients to maximize benefit and

minimize toxicity for each patient based on the ge-netic composition of the individual.

AcknowledgementsThe authors thank Drs. M. Eileen Dolan, PeterO’Donnell, Ryan Munoz, and Christine Hartford aswell as Ms. Amy Stark for their critical review of thearticle.

References1. Adverse Drug Events: The Magnitude of

Health Risk is Uncertain Because of Lim-ited Incidence Data. Washington, DC: USGeneral Accounting Office; 2000.

2. Bates D, Gawande A. Error in medicine:what have we learned? Ann Intern Med.2000;132:763-767.

3. Meyer UA. Pharmacogenetics–5 decadesof therapeutic lessons from genetic diver-sity. Nat Rev Genet. 2004;6:669-676.

4. Potti A, Dressman HK, Bild A, et al.Genomic signatures to guide the use ofchemotherapeutics. Nat Med. 2006;12:1294-1300.

5. Suk R, Gurubhagavatula S, Park S, et al.Polymorphisms in ERCC1 and grade 3 or 4toxicity in non-small cell lung cancer pa-tients. Clin Cancer Res. 2005;11:1534-1538.

6. Hoskins J, Goldberg R, Qu P, et al.UGT1A1*28 genotype and irinotecan-in-duced neutropenia: dose matters. J NatlCancer Inst. 2007;99:1290-1295.

7. Griffiths AJ, Miller JH, Suzuki DT, et al.An Introduction to Genetic Analysis. NewYork: W.H. Freeman and Co.; 1996.

8. Oroszi G, Goldman D. Alcoholism: genesand mechanisms. Pharmacogenomics.2004;5:1037-1048.

9. Schnoll R, Johnson T, Lerman C. Geneticsand smoking behavior. Curr PsychiatryRep. 2007;9:349-357.

10. Faraday N, Yanek L, Mathias R, et al. Her-itability of platelet responsiveness to aspi-rin in activation pathways directly and in-directly related to cyclooxygenase-1.Circulation. 2007;115:2490-2496.

11. Luciano M, Zhu G, Kirk K, et al. “Nothanks, it keeps me awake”: the geneticsof coffee-attributed sleep disturbance.Sleep. 2007;30:1378-1386.

12. Cloos J, Nieuwenhuis E, Boomsma D, etal. Inherited susceptibility to bleomycin-induced chromatid breaks in cultured pe-ripheral blood lymphocytes. J Natl CancerInst. 1999;91:1125-1130.

13. Dolan ME, Newbold KG, Nagasubrama-nian R, et al. Heritability and linkage anal-ysis of sensitivity to cisplatin-induced cy-totoxicity. Cancer Res. 2004;64:4353-4356.

14. Watters JW, Kraja A, Meucci MA, et al.Genome-wide discovery of loci influenc-

ing chemotherapy cytotoxicity. Proc NatlAcad Sci U S A. 2004;101:11809-11814.

15. Duan S, Bleibel W, Huang R, et al. Map-ping genes that contribute to daunorubi-cin-induced cytotoxicity. Cancer Res.2007;67:5425-5433.

16. Bosch T, Meijerman I, Beijnen J, SchellensJ. Genetic polymorphisms of drug-me-tabolising enzymes and drug transporters inthe chemotherapeutic treatment of cancer.Clin Pharmacokinet. 2006;45:253-285.

17. Efferth T, Volm M. Pharmacogenetics forindividualized cancer chemotherapy.Pharmacol Ther. 2005;107:155-176.

18. US Department of Energy Office of Sci-ence, Office of Biological and Environ-mental Research, and Human GenomeProgram. Human Genome Project Informa-tion. Available at: http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml. Accessed May 21, 2008.

19. International HapMap Project. About theHapMap. Available at: http://www.hap-map.org/thehapmap.html.en. AccessedMay 30th, 2008.

20. The Wellcome Trust Case Control Consor-tium. Genome-wide association study of14,000 cases of 7 common diseases and3,000 shared controls. Nature. 2007;447:661-678.

21. Forbes S, Clements J, Dawson E, et al.COSMIC 2005. Br J Cancer. 2006;94:318-322.

22. Huang RS, Duan S, Bleibel WK, et al. Agenome-wide approach to identify geneticvariants that contribute to etoposide-in-duced cytotoxicity. Proc Natl Acad Sci U SA. 2007;104:9758-9763.

23. Huang RS, Duan S, Shukla SJ, et al. Iden-tification of genetic variants contributingto cisplatin-induced cytotoxicity by use ofa genomewide approach. Am J HumGenet. 2007;81:427-437.

24. Thomas G, Jacobs K, Yeager M, et al. Mul-tiple loci identified in a genome-wide as-sociation study of prostate cancer. NatGenet. 2008;40:310-315.

25. Sklar P, Smoller J, Fan J, et al. Whole-genome association study of bipolar disor-der. Mol Psychiatry. 2008;13:558-569.

26. Tomlinson I, Webb E, Carvajal-CarmonaL, et al. A genome-wide association studyidentifies colorectal cancer susceptibilityloci on chromosomes 10p14 and 8q23.3.Nat Genet. 2008;40:623-630.

27. Ratain MJ. From bedside to bench to bed-side to clinical practice: an odyssey withirinotecan. Clin Cancer Res. 2006;12:1658-1660.

28. Roche Dianostics. AmpliChip. Availableat: http://www.amplichip.us/index.php.Accessed May 30, 2008.

29. 23andMe Inc. 23andMe genetics just gotpersonal. Available at: https://www.23andme.com/. Accessed May 30, 2008.

30. Pagon RA, Terry E, Espeseth M, et al.GeneTests. Available at: http://www.genetests.org/. Accessed May 30, 2008.

31. Holleman A, Cheok M, den Boer M, et al.Gene-expression patterns in drug-resis-tant acute lymphoblastic leukemia cellsand response to treatment. N Engl J Med.2004;351:533-542.

32. Harris L, Fritsche H, Mennel R, et al.American Society of Clinical Oncology2007 update of recommendations for theuse of tumor markers in breast cancer.J Clin Oncol. 2007;25:5287-5312.

33. Weinshilboum R, Sladek S. Mercaptopu-rine pharmacogenetics: monogenic inher-itance of erythrocyte thiopurine methyl-transferase activity. Am J Hum Genet.1980;32:651-662.

34. Gorski J, Hall S, Jones D, et al. Regioselec-tive biotransformation of midazolam bymembers of the human cytochrome P4503A (CYP3A) subfamily. Biochem Pharma-col. 1994;47:1643-1653.

35. Chiou W, Jeong H, Wu T, Ma C. Use of theerythromycin breath test for in vivo as-sessments of cytochrome P4503A activityand dosage individualization. Clin Phar-macol Ther. 2001;70:305-310.

36. Riegert-Johnson D, Macaya D, Hefferon T,Boardman L. The incidence of duplicategenetic testing. Genet Med. 2008;10:114-116.

37. International HapMap Consortium,Frazer K, Ballinger D, et al. A second gen-eration human haplotype map of over 3.1million SNPs. Nature. 2007;449:851-861.

38. International HapMap Consortium. Ahaplotype map of the human genome. Na-ture. 2005;437:1299-1320.

39. Early Breast Cancer Trialists’ Collabora-tive Group (EBCTCG). Effects of chemo-therapy and hormonal therapy for earlybreast cancer on recurrence and 15-yearsurvival: an overview of the randomisedtrials. Lancet. 2005;365:1687-1717.




merican C



Dow

nloaded from


40. Goetz MP, Rae JM, Suman VJ, et al. Phar-macogenetics of tamoxifen biotransforma-tion is associated with clinical outcomesof efficacy and hot flashes. J Clin Oncol.2005;23:9312-9318.

41. Goetz MP, Suman VJ, Ingle JN, et al. A2-gene expression ratio of homeobox 13and interleukin-17B receptor for predic-tion of recurrence and survival in womenreceiving adjuvant tamoxifen. Clin CancerRes. 2006;12(7 pt 1):2080-2087.

42. Jin Y, Desta Z, Stearns V, et al. CYP2D6genotype, antidepressant use, and tamox-ifen metabolism during adjuvant breastcancer treatment. J Natl Cancer Inst. 2005;97:30-39.

43. Massarweh S, Osborne C, Creighton C, et al.Tamoxifen resistance in breast tumors isdriven by growth factor receptor signalingwith repression of classic estrogen receptorgenomic function. Cancer Res. 2008;68:826-833.

44. Eichelbaum M, Ingelman-Sundberg M,Evans WE. Pharmacogenomics and indi-vidualized drug therapy. Annu Rev Med.2006;57:119-137.

45. Ingelman-Sundberg M, Sim SC, Gomez A,Rodriguez-Antona C. Influence of cyto-chrome P450 polymorphisms on drugtherapies: pharmacogenetic, pharmaco-epigenetic and clinical aspects. PharmacolTher. 2007;116:496-526.

46. Sistonen J, Sajantila A, Lao O, et al. CYP2D6worldwide genetic variation shows highfrequency of altered activity variants andno continental structure. PharmacogenetGenomics. 2007;17:93-101.

47. Clarke R, Liu M, Bouker K, et al. Anties-trogen resistance in breast cancer and therole of estrogen receptor signaling. Onco-gene. 2003;22:7316-7339.

48. Jordan VC, Collins MM, Rowsby L,Prestwich G. A monohydroxylated metab-olite of tamoxifen with potent antioestro-genic activity. J Endocrinol. 1977;76:305-316.

49. Goetz M, Knox S, Suman V, et al. Theimpact of cytochrome P450 2D6 metabo-lism in women receiving adjuvant tamox-ifen. Breast Cancer Res Treat. 2007;101:113-121.

50. Schroth W, Antoniadou L, Fritz P, et al.Breast cancer treatment outcome with ad-juvant tamoxifen relative to patientCYP2D6 and CYP2C19 genotypes. J ClinOncol. 2007;25:5187-5193.

51. Kiyotani K, Mushiroda T, Sasa M, et al.Impact of CYP2D6*10 on recurrence-freesurvival in breast cancer patients receiv-ing adjuvant tamoxifen therapy. CancerSci. 2008;99:995-999.

52. Desta Z, Flockhart D. Germline pharma-cogenetics of tamoxifen response: havewe learned enough? J Clin Oncol. 2007;25:5147-5149.

53. Gaedigk A, Simon S, Pearce R, et al. TheCYP2D6 activity score: translating geno-type information into a qualitative mea-sure of phenotype. Clin Pharmacol Ther.2008;83:234-242.

54. DNAdirect. DNAdirect. Your Genes. YourHealth. Your Choices. Available at: http://www.dnadirect.com/. Accessed May 30,2008.

55. Punglia R, Burstein H, Winer E, WeeksJ. Pharmacogenomic variation of CYP2D6and the choice of optimal adjuvant endo-crine therapy for postmenopausal breast

cancer: a modeling analysis. J Natl CancerInst. 2008;100:642-648.

56. Gjerde J, Hauglid M, Breilid H, et al. Ef-fects of CYP2D6 and SULT1A1 genotypesincluding SULT1A1 gene copy number ontamoxifen metabolism. Ann Oncol. 2008;19:56-61.

57. Wegman P, Elingarami S, Carstensen J, etal. Genetic variants of CYP3A5, CYP2D6,SULT1A1, UGT2B15 and tamoxifen re-sponse in postmenopausal patients withbreast cancer. Breast Cancer Res. 2007;9:R7.

58. Lim Y, Li L, Desta Z, et al. Endoxifen, asecondary metabolite of tamoxifen, and4-OH-tamoxifen induce similar changes inglobal gene expression patterns in MCF-7breast cancer cells. J Pharmacol Exp Ther.2006;318:503-512.

59. Petros W, Evans WE. Pharmacogenomicsin cancer therapy: is host genome vari-ability important? Trends Pharmacol Sci.2004;25:457-464.

60. Yong W, Innocenti F. Translation of phar-macogenetic knowledge into cancer ther-apeutics. Clin Adv Hematol Oncol. 2007;5:698-706.

61. Lennard L, Lilleyman J, Loon JV, Wein-shilboum R. Genetic variation in responseto 6-mercaptopurine for childhood acutelymphoblastic leukaemia. Lancet. 1990;336:225-229.

62. Stanulla M, Schaeffeler E, Flohr T, et al.Thiopurine methyltransferase (TPMT) ge-notype and early treatment response tomercaptopurine in childhood acute lym-phoblastic leukemia. JAMA. 2005;293:1485-1489.

63. McLeod HL, Siva C. The thiopurineS-methyltransferase gene locus–implica-tions for clinical pharmacogenomics.Pharmacogenomics. 2002;3:89-98.

64. Schaeffeler E, Fischer C, Brockmeier D, etal. Comprehensive analysis of thiopurineS-methyltransferase phenotype-genotypecorrelation in a large population of Ger-man-Caucasians and identification ofnovel TPMT variants. Pharmacogenetics.2004;14:407-417.

65. van den Akker-van Marle M, Gurwitz D,Detmar S, et al. Cost-effectiveness of phar-macogenomics in clinical practice: a casestudy of thiopurine methyltransferasegenotyping in acute lymphoblastic leuke-mia in Europe. Pharmacogenomics. 2006;7:783-792.

66. Hartford C, Dolan M. Identifying geneticvariants that contribute to chemotherapy-induced cytotoxicity. Pharmacogenomics.2007;8:1159-1168.

67. Zhou S. Clinical pharmacogenomics ofthiopurine S-methyltransferase. Curr ClinPharmacol. 2006;1:119-128.

68. Givens RC, Watkins PB. Pharmacogenet-ics and clinical gastroenterology. Gastro-enterology. 2003;125:240-248.

69. Maitland M, Vasisht K, Ratain M. TPMT,UGT1A1 and DPYD: genotyping to ensuresafer cancer therapy? Trends PharmacolSci. 2006;27:432-437.

70. Rothenberg M. Efficacy and toxicity of iri-notecan in patients with colorectal cancer.Semin Oncol. 1998;25(5 suppl 11):39-46.

71. Iyer L, King C, Whitington P, et al. Geneticpredisposition to the metabolism of irino-tecan (CPT-11). Role of uridine diphos-phate glucuronosyltransferase isoform1A1 in the glucuronidation of its active

metabolite (SN-38) in human liver micro-somes. J Clin Invest. 1998;101:847-854.

72. Carlini L, Meropol N, Bever J, et al.UGT1A7 and UGT1A9 polymorphismspredict response and toxicity in colorectalcancer patients treated with capecitabine/irinotecan. Clin Cancer Res. 2005;11:1226-1236.

73. Han J, Lim H, Shin E, et al. Comprehen-sive analysis of UGT1A polymorphismspredictive for pharmacokinetics and treat-ment outcome in patients with non-small-cell lung cancer treated with irinotecanand cisplatin. J Clin Oncol. 2006;24:2237-2244.

74. Innocenti F, Liu W, Chen P, et al. Haplotypesof variants in the UDP-glucuronosyltrans-ferase1A9 and 1A1 genes. PharmacogenetGenomics. 2005;15:295-301.

75. de Jong F, Scott-Horton T, Kroetz D, et al.Irinotecan-induced diarrhea: functionalsignificance of the polymorphic ABCC2transporter protein. Clin Pharmacol Ther.2007;81:42-49.

76. Sai K, Kaniwa N, Itoda M, et al. Haplotypeanalysis of ABCB1/MDR1 blocks in a Jap-anese population reveals genotype-depen-dent renal clearance of irinotecan. Phar-macogenetics. 2003;13:741-757.

77. Zhou Q, Sparreboom A, Tan E, et al. Phar-macogenetic profiling across the irinote-can pathway in Asian patients with can-cer. Br J Clin Pharmacol. 2005;59:415-424.

78. Bosma PJ, Chowdhury JR, Bakker C, et al.The genetic basis of the reduced expres-sion of bilirubin UDP-glucuronosyltrans-ferase 1 in Gilbert’s syndrome. N EnglJ Med. 1995;333:1171-1175.

79. Hasegawa Y, Sarashina T, Ando M, et al.Rapid detection of UGT1A1 gene polymor-phisms by newly developed Invader as-say. Clin Chem. 2004;50:1479-1480.

80. Meyerhardt J, Kwok A, Ratain M, et al.Relationship of baseline serum bilirubinto efficacy and toxicity of single-agent iri-notecan in patients with metastatic colo-rectal cancer. J Clin Oncol. 2004;22:1439-1446.

81. Baudhuin L, Highsmith W, Skierka J, etal. Comparison of 3 methods for genotyp-ing the UGT1A1 (TA)n repeat polymor-phism. Clin Biochem. 2007;40:710-717.

82. Schwab M, Zanger U, Marx C, et al. Roleof genetic and nongenetic factors forfluorouracil treatment-related severe tox-icity: a prospective clinical trial by theGerman 5-FU Toxicity Study Group. J ClinOncol. 2008;26:2131-2138.

83. [no authors listed] Toxicity of fluorouracilin patients with advanced colorectal can-cer: effect of administration schedule andprognostic factors. Meta-Analysis GroupIn Cancer. J Clin Oncol. 1998;16:3537-3541.

84. Diasio R, Beavers T, Carpenter J. Familialdeficiency of dihydropyrimidine dehydro-genase. Biochemical basis for familialpyrimidinemia and severe 5-fluorouracil-induced toxicity. J Clin Invest. 1988;81:47-51.

85. Etienne M, Lagrange J, Dassonville O, etal. Population study of dihydropyrimidinedehydrogenase in cancer patients. J ClinOncol. 1994;12:2248-2253.

86. Fleming R, Milano G, Thyss A, et al. Cor-relation between dihydropyrimidine de-hydrogenase activity in peripheral mono-nuclear cells and systemic clearance of




merican C



Dow

nloaded from


fluorouracil in cancer patients. CancerRes. 1992;52:2899-2902.

87. Lu Z, Zhang R, Diasio R. Dihydropyrimi-dine dehydrogenase activity in human pe-ripheral blood mononuclear cells and liv-er: population characteristics, newlyidentified deficient patients, and clinicalimplication in 5-fluorouracil chemother-apy. Cancer Res. 1993;53:5433-5438.

88. Okuda H, Nishiyama T, Ogura K, et al. Le-thal drug interactions of sorivudine, a newantiviral drug, with oral 5-fluorouracilprodrugs. Drug Metab Dispos. 1997;25:270-273.

89. Ceppi P, Volante M, Ferrero A, et al. Thy-midylate synthase expression in gastroen-teropancreatic and pulmonary neuroen-docrine tumors. Clin Cancer Res. 2008;14:1059-1064.

90. Kuo S, Wang H, Chow K, et al. Expressionof rTSbeta as a 5-fluorouracil resistancemarker in patients with primary breastcancer. Oncol Rep. 2008;19:881-888.

91. Milano G, Etienne M, Cassuto-Viguier E,et al. Influence of sex and age on fluorou-racil clearance. J Clin Oncol. 1992;10:1171-1175.

92. Port R, Daniel B, Ding R, Herrmann R.Relative importance of dose, body surfacearea, sex, and age for 5-fluorouracil clear-ance. Oncology. 1991;48:277-281.

93. Chansky K, Benedetti J, Macdonald J. Dif-ferences in toxicity between men andwomen treated with 5-fluorouracil ther-apy for colorectal carcinoma. Cancer.2005;103:1165-1171.

94. Sloan J, Goldberg R, Sargent D, et al.Women experience greater toxicity withfluorouracil-based chemotherapy for colo-rectal cancer. J Clin Oncol. 2002;20:1491-1498.

95. Wei X, Elizondo G, Sapone A, et al. Char-acterization of the human dihydropyrimi-dine dehydrogenase gene. Genomics.1998;51:391-400.

96. Van Kuilenburg A, Meinsma R, Zoetek-ouw L, Van Gennip A. Increased risk ofgrade IV neutropenia after administrationof 5-fluorouracil due to a dihydropyrimi-dine dehydrogenase deficiency: highprevalence of the IVS14�1g�a mutation.Int J Cancer. 2002;101:253-258.

97. Yen J, McLeod H. Should DPD analysis berequired prior to prescribing fluoropyri-midines? Eur J Cancer. 2007;43:1011-1016.

98. Marsh S. Thymidylate synthase pharma-cogenetics. Invest New Drugs. 2005;23:533-537.

99. Etienne-Grimaldi M, Francoual M, For-mento J, Milano G. Methylenetetrahydro-folate reductase (MTHFR) variants andfluorouracil-based treatments in colorec-tal cancer. Pharmacogenomics. 2007;8:1561-1566.

100. Morel A, Boisdron-Celle M, Fey L, et al.Clinical relevance of different dihydropy-rimidine dehydrogenase gene single nu-cleotide polymorphisms on 5-fluorouraciltolerance. Mol Cancer Ther. 2006;5:2895-2904.

101. Lecomte T, Ferraz J, Zinzindohoue F, etal. Thymidylate synthase gene polymor-phism predicts toxicity in colorectal can-

cer patients receiving 5-fluorouracil-basedchemotherapy. Clin Cancer Res. 2004;10:5880-5888.

102. Ichikawa W, Takahashi T, Suto K, et al.Orotate phosphoribosyltransferase genepolymorphism predicts toxicity in patientstreated with bolus 5-fluorouracil regimen.Clin Cancer Res. 2006;12:3928-3934.

103. Pullarkat S, Stoehlmacher J, Ghaderi V, etal. Thymidylate synthase gene polymor-phism determines response and toxicity of5-FU chemotherapy. PharmacogenomicsJ. 2001;1:65-70.

104. Wheeler DA, Srinivasan M, Egholm M, etal. The complete genome of an individualby massively parallel DNA sequencing.Nature. 2008;452:872-877.

105. Levy S, Sutton G, Ng P, et al. The diploidgenome sequence of an individual hu-man. PLoS Biol. 2007;5:e254–e286.

106. Rodriguez-Antona C, Ingelman-SundbergM. Cytochrome P450 pharmacogeneticsand cancer. Oncogene. 2006;25:1679-1691.

107. SEARCH Collaborative Group, Link E,Parish S, et al. SLCO1B1 variants and sta-tin-induced myopathy–a genomewidestudy. N Engl J Med. 2008;359:789-799.

108. Christensen K, Murray JC. What genome-wide association studies can do for medi-cine. N Engl J Med. 2007;356:1094-1097.

109. Obama B. The genomics and PersonalizedMedicine Act of 2006. Clin Adv HematolOncol. 2007;5:39-40.

110. Lesko L, Woodcock J. Translation of phar-macogenomics and pharmacogenetics: aregulatory perspective. Nat Rev Drug Dis-cov. 2004;3:763-769.




merican C



Dow

nloaded from


ca cancer j clin, 2009 - pharmacogenetics and pharmacogenomics of anticancer agents

Documents