Pharmacogenetics
Curtis R. Chong
Jeanne Fourie Zirkelbach
Robert B. Diasio
Bruce A. Chabner
Patients with cancer often demonstrate a variety of responses and side effects to chemotherapy. While some of these differences are due to underlying medical problems, age, sex, and organ function, genetic factors play a key role. Pharmacogenetics is the study of the host genetic contribution to variations in drug efficacy, metabolism, and toxicity. Pharmacogenomics, a term often used interchangeably, is the application of genomic technologies such as expression profiling, high-throughput gene sequencing, and single-nucleotide polymorphisms (SNPs) to study variations due to multiple genes in drug efficacy, metabolism, and toxicity.1 The promise of pharmacogenetics lies in individualized therapy with the aim of maximizing drug efficacy while reducing toxicity. A related concept, personalized therapy, is increasingly discussed, but it primarily concerns choosing the right drug for a specific patient’s tumor.2 For drugs with narrow therapeutic indices, such as many anticancer agents, knowledge of a patient’s pharmacogenetic susceptibility is key in promoting drug safety.3
Compared to other fields, the impact of pharmacogenetics in oncology is greater because chemotherapeutic agents affecting a variety of tissues and tumors are chemically diverse. The metabolism of anticancer drugs is typically very complex, and the therapeutic window is a careful balance between enzyme systems involved in activation and detoxification. Polymorphisms in either system can have profound effects on drug efficacy or toxicity. Tumors also evolve resistance to drugs, either at the target level as shown for imatinib or through enhanced detoxification, as shown for multidrug resistance transporters.
Pharmacogenetics has the potential to lower healthcare costs, streamline drug development, improve drug safety, and reduce disparities between ethnic groups (because of racial differences in expression of gene variants). The NIH now mandates inclusion of minorities in NIH-supported human research,4 and the higher incidence of mutations (or gene variants) such as those affecting the EGFR receptors in lung cancer patients of East Asian ancestry highlights the importance of understanding these differences.5 By identifying patients most likely to benefit from a drug, pharmacogenetic technologies may reduce the number needed to treat, resulting in healthcare savings.6 Addition of pharmacogenetics to post-marketing surveillance, or Phase IV studies, may likewise improve drug safety by identifying patients most susceptible to adverse drug effects.6
Translation of pharmacogenomic research has produced diagnostic tests that allow physicians to tailor therapy to specific patients for several drugs. The U.S. FDA now recommends that patients treated with the monoclonal antibody EGF receptor inhibitors cetuximab or panitumumab be tested for K-ras mutations since patients with the wild type gene respond better.7 Careful selection of patients based on pharmacogenetic profiles is routinely employed to identify patients with variants in methyl thiopurine metabolism for pediatric ALL treatment.8 Other pharmacogenetic tests that attempt to predict toxicity of specific drugs are available, as listed in Table 6-1. To encourage pharmacogenomics/genetics in new drug development, the FDA published a Guidance for Industry: Pharmacogenomic Data Submission that created a pathway for submitting genomic data during an investigational new drug application.8 Currently, approximately 10% of labels for drugs approved by the FDA contain pharmacogenomic information, and an estimated one fourth of all outpatients receive drugs with pharmacogenomic label information.9
The majority of clinically relevant pharmacogenetic variants occur in drug-metabolizing enzymes, transporters, or targets.10 Genetic differences cause variation of drug targets at a molecular level (pharmacodynamics) and in differences in drug metabolism and absorption (pharmacokinetics). Examples include drug transporters, such as the P-glycoprotein MDR1, drug-inactivating enzymes, and drug targets such as the B2-adrenergic receptor, and angiotensin-converting enzyme.11 Extensive work has detailed genetic differences in phase I metabolism (hydrolysis, oxidation/reduction) by enzymes such as cytochrome P450s, and in phase II metabolism (glucuronidation, sulfation, methyl/acetylation).3 For example, considerable population differences in drug response due to certain cytochrome P450 isoforms led pharmaceutical companies to avoid drug candidates primarily metabolized by highly polymorphic alleles such as CYP2D6.2
Pharmacogenetic testing has several key advantages over direct monitoring of plasma drug levels. Monitoring plasma drug samples is impractical in most clinical settings and requires close coordination and special laboratory capabilities. Single plasma levels may not predict toxicity if patients are predisposed to slower drug elimination. It can be difficult and expensive to develop assays for numerous drug metabolites. On the other hand, pharmacogenetic testing requires rigorous validation in clinical trials as delivery of suboptimal doses of chemotherapy may preclude effective treatment.8 “Environmental” conditions such as drug-drug interactions, organ dysfunction, age, or protein binding may introduce variables that change drug disposition and diminish the utility of pharmacogenetic test results. For example, studies of cytochrome P450 2C19 activity in patients with advanced cancer found metabolism to be much slower than predicted by genotype, including one study performed in the absence of renal or hepatic failure.12,13
Pharmacogenetic testing is not a substitute for close clinical monitoring of patients, but can be an additional clinical data point used in formulating a treatment plan or anticipating toxicity, and is especially useful in identifying patients at risk for extreme toxicity or poor response.8
Pharmacogenetic testing is not a substitute for close clinical monitoring of patients, but can be an additional clinical data point used in formulating a treatment plan or anticipating toxicity, and is especially useful in identifying patients at risk for extreme toxicity or poor response.8
TABLE 6.1 Public resources for pharmacogenetics | ||||||||||
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TABLE 6.2 Companies offering pharmacogenetic tests in oncology | |||||||||||||||||||||||||||||||||||||||||
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For oncologists, pharmacogenetics promises to minimize variations in therapeutic response and drug toxicity. Numerous gene variants that influence the efficacy and toxicity of cancer chemotherapeutics have been identified. Genetic testing of tumor and host is growing in importance as a tool for optimizing clinical trials and clinical practice. In this chapter, we discuss the scientific basis for pharmacogenetics and review the impact of key host variants on toxicity and response to cancer therapeutic agents. A list of public resources for clinicians wishing to incorporate pharmacogenetics into clinical practice is provided in Table 6-2. A list of laboratories offering pharmacogenetic testing (and their Web sites) is provided in Table 6-1.
Impact of Genetic Variation on Cancer Chemotherapy
Human genetic variability is a determinant of anticancer drug efficacy and safety. This variability, which is the basis of the disciplines of pharmacogenetics and pharmacogenomics, encompasses an array of different types of DNA sequence modifications as well as individual differences in gene expression and regulation. In the present overview, we focus on the most common form of variation in genetic sequence, known as SNP. A polymorphism is defined as a “Mendelian or monogenic trait that exists in the population in at least two phenotypes (and presumably at least two genotypes), neither of which is rare—that is, neither of which occurs with a
frequency of less than 1% to 2%.”14 Such polymorphisms may include nonsynonymous SNPs, which are within the open reading frame of the gene and may result in significant amino acid substitutions in the encoded protein, affecting protein function or quantity. Other SNPs are characterized as synonymous polymorphisms in the coding region of the DNA, or SNPs in promoter and enhancer regions of a gene that affect transcription and gene regulation, and intronic SNPs, which may lead to splice variants.1,3,11,15, 16, 17 In addition to these SNPs, other sources of variation in DNA sequence include insertions, deletions, and gene duplications, all of which contribute to the complex and multifactorial phenotypes of drug efficacy and safety.
frequency of less than 1% to 2%.”14 Such polymorphisms may include nonsynonymous SNPs, which are within the open reading frame of the gene and may result in significant amino acid substitutions in the encoded protein, affecting protein function or quantity. Other SNPs are characterized as synonymous polymorphisms in the coding region of the DNA, or SNPs in promoter and enhancer regions of a gene that affect transcription and gene regulation, and intronic SNPs, which may lead to splice variants.1,3,11,15, 16, 17 In addition to these SNPs, other sources of variation in DNA sequence include insertions, deletions, and gene duplications, all of which contribute to the complex and multifactorial phenotypes of drug efficacy and safety.
Although virtually all drugs are susceptible to the consequences of genetic variability, the application of pharmacogenetic concepts may be especially important in anticancer chemotherapeutic treatment. Anticancer agents frequently are prodrugs that require enzymatic bioactivation to their cytotoxic active forms, while the active forms of these compounds may also undergo further enzymatic detoxification. In both instances, the involved enzyme systems may exhibit genetic polymorphisms and therefore small but significant changes in anticancer drug metabolism, distribution, transport, or excretion due to modifications such as decreased production of an altered protein (e.g., an enzyme) or increases in the protein amount can lead to interpatient variability in drug effect. Anticancer agents generally have a relatively narrow therapeutic index. In the current treatment strategy, anticancer agents are administered in “standard” doses to patients. This uniform approach to pharmacotherapy ignores interindividual variability in drug metabolism and disposition as part of an individualized drug treatment plan.
Chemotherapeutic drug response is a complex outcome, or phenotype, that is affected by interactions between a network of different genes, including interactions between host and tumor genomes, as most anticancer agents do not selectively target tumor tissue. Genetic polymorphisms in pharmacokinetic pathways may collectively impact drug efficacy and host or tumor toxicity through regulation of drug bioavailability, retention, and efflux and detoxification or metabolism in host or tumor cells. Genetic polymorphisms may further occur in genes that encode drug targets or signal pathways involved in drug response as well as in genes that influence tumor or disease characteristics such as invasiveness and drug resistance. The complexity of variability in human drug response may be additionally affected by differences in the frequencies and types of genetic polymorphisms that are prevalent in ethnically defined populations as well as the specific characteristics of the drugs and disease status, all of which may impact out come. A major aim of pharmacogenetics and pharmacogenomics is to discern which genetic polymorphisms are important in drug response and how knowledge of this variability can be used in the individualization of drug therapy.
Genotypic Tests and Dose Adjustment or Drug Selection in Individual Patients
Once a particular pharmacogenetic syndrome has been identified, pharmacokinetic analysis may be of limited clinical feasibility due to its labor-intensiveness. In addition, observation of changes in drug concentration alone does not provide an understanding of the pathways responsible for drug metabolism. Therefore, genotypic or phenotypic tests can be more beneficial than pharmacokinetic studies in therapeutic drug monitoring and the individualization of drug therapy. Its potential advantages over pharmacokinetic analysis are summarized below:
Genotypic and phenotypic tests are less invasive, as they require a single blood, plasma, serum, urine, or tissue sample for assessment of polymorphisms that may affect drug pharmacokinetics and response.
Genotypic or phenotypic tests can help predict drug response and toxicity. Drug treatment may be altered to prevent potentially lethal toxicity or lack of efficacy due to genetic polymorphisms in genes that influence drug effects.
The genotypic or phenotypic profile may also be informative in combination treatment with other therapeutic agents.
The genotypic or phenotypic profile may be applicable to the individual patient’s treatment with a drug in the same or a different drug class (e.g., metabolized through the same polymorphic drug-metabolizing enzyme).
The genotypic or phenotypic test may provide insight into pharmacodynamic variability and the mechanistic basis for variability in drug response or may help in the identification of patients possibly at risk for rapid disease progression or tumor invasiveness.
Research Strategies in Pharmacogenetics
Candidate Gene Approach
The candidate gene approach to pharmacogenetic investigation attempts to link a phenotype with an alteration in a specific gene through hypothesis-based testing. Recognition that specific genes contribute to variation in drug toxicity occurred in the 1950s with three key discoveries11 (Fig. 6-1). Alving et al.18 identified a relationship between glucose-6-phosphate dehydrogenase deficiency and hemolysis in patients treated with primaquine. Kalow correlated acetylcholinesterase deficiency and prolonged paralysis from succinylcholine.19 Evans et al.20 found that the rate of isoniazid acetylation influenced the development of peripheral neuropathy. Since then, variation in numerous other genes has been shown to affect drug efficacy and toxicity, with a 2009 review reporting 541 genes studied.21
Even more potential for discovery exists in the over 1.4 million SNPs in the human genome, and 60,000 SNPs in gene-encoding regions.22 SNPs are common variations that occur at a given location when two DNA sequences are compared,23 for example:
ATGTA
ATCTA
SNPs occur every 100 to 300 bases and can have a variety of effects—they may be silent (synonymous), producing no change in amino acid sequence, or may change a single amino acid (nonsynonymous) that greatly affects protein function. They may introduce a stop codon, which produces a truncated protein.24 SNPs that occur in the promoter or enhancer regions of a gene may affect RNA expression and protein levels while SNPs in intron-exon boundaries may lead to splice variants. Within the field of oncology, SNPs
have been associated with numerous variations in responsiveness and side effects of chemotherapeutic agents.10 The C677T polymorphism in 5,10-methylenetetrahydrofolate reductase (MTHFR) slows the activation of leucovorin rescue and in some studies is associated with increased methotrexate toxicity. Glutathione-S-transferase enzymes metabolize drugs through glutathione conjugation. The GSTP1 Ile105Val mutation is associated with lower enzyme activity and increased survival for oxaliplatin/5-fluorouracil (5-FU) regimens (24.9 months for the V105 homozygote versus 13.3 months for the I105 homozygote).25,26 The Arg399Gln SNP in the DNA repair protein XRCC1 is associated with resistance to oxaliplatin/5-FU (discussed below).10 Lapatinib, a tyrosine kinase inhibitor metabolized by cytochrome P450 enzymes, is associated with diarrhea and rash in patients with the CYP2C19*2/*2 SNP.27 In addition to SNP variants, nucleotide insertions, deletions, repeats, and variations in copy number also contribute to genetic diversity.28 As technologies to identify SNPs improve, more associations will be added.
have been associated with numerous variations in responsiveness and side effects of chemotherapeutic agents.10 The C677T polymorphism in 5,10-methylenetetrahydrofolate reductase (MTHFR) slows the activation of leucovorin rescue and in some studies is associated with increased methotrexate toxicity. Glutathione-S-transferase enzymes metabolize drugs through glutathione conjugation. The GSTP1 Ile105Val mutation is associated with lower enzyme activity and increased survival for oxaliplatin/5-fluorouracil (5-FU) regimens (24.9 months for the V105 homozygote versus 13.3 months for the I105 homozygote).25,26 The Arg399Gln SNP in the DNA repair protein XRCC1 is associated with resistance to oxaliplatin/5-FU (discussed below).10 Lapatinib, a tyrosine kinase inhibitor metabolized by cytochrome P450 enzymes, is associated with diarrhea and rash in patients with the CYP2C19*2/*2 SNP.27 In addition to SNP variants, nucleotide insertions, deletions, repeats, and variations in copy number also contribute to genetic diversity.28 As technologies to identify SNPs improve, more associations will be added.
 FIGURE 6-1 The DNA sequence for the same allele may differ among individuals by virtue of a change in single base (in this case, a C to T change), creating a variant, or polymorphism, that may or may not have functional significance. (Reprinted with implied consent of copyright holder David Hall from www. wikipedia.org [http://en.wikipedia.org/wiki/Single_nucleotide_polymorphism]. This file is licensed under the Creative Commons Attribution ShareAlike 3.0 License. Official license.) |
Family Studies
Cancer chemotherapy drugs are too toxic for the family study approach to assessing patterns of inheritance of drug response used for drugs from other therapeutic classes.29 Other phenotypic tests such as assessment of the activity of a drug-metabolizing enzyme or determination of substrate levels in family members can define the pattern of inheritance.
Once a pharmacokinetic or pharmacodynamic alteration has been defined in an individual patient, studies in the family can provide insight into whether the genetic polymorphism is an autosomal or sex-linked trait and whether the pattern of inheritance is dominant, codominant, or recessive. With availability of data from the human genome project and the functional assignment of enzyme activity to a particular gene, it is becoming possible to delineate the inheritance of a specific gene. Techniques that can identify a specific DNA sequence or SNP, such as allele-specific polymerase chain reaction-based (PCR-based) methods, should make this technically straightforward.30
Population Studies
Population studies are aimed at the assessment of the frequency of the pharmacogenetic syndrome within the general population as well as frequency differences between populations. As with family studies, population studies can use either phenotypic or genotypic tests. The frequency of individuals with particular phenotypic characteristics can be estimated using the Hardy-Weinberg equation.31 Population studies to assess the specific phenotype or activity of a particular protein may show unimodal or bimodal patterns of distribution. A unimodal distribution in the activity of a particular enzyme, such as a Gaussian or normal distribution pattern, suggests mutations or genetic alterations that lead to a range of activities in the population studied. In contrast, bimodal distributions may indicate mutations that lead to reduced or greater than normal activity in a subset of the population.32 The evaluation of particular phenotypes in population studies related to chemotherapeutic drug metabolism may require assessments using a safer probe drug that is metabolized through the same potential polymorphic drug-metabolizing enzyme but without posing a risk of toxicity to the healthy individual participating in the study. Results from a population study comparing cancer patients to healthy volunteers indicated that cancer stage may also influence the phenotype of an important drug-metabolizing enzyme CYP2C19, for which genotype normally predicts phenotype in the healthy population.13,33 In this study, patients with advanced cancer had the extensive metabolizer genotype; however, 25% of the patients displayed a poor metabolizer phenotype. This discordance between phenotype and genotype and the decreased activity of CYP2C19 observed in terminally ill cancer patients may influence the clinical efficacy and toxicity of therapeutic agents (e.g., cyclophosphamide) and should be investigated with respect to other drug-metabolizing enzymes.13 The characterization of genes and related phenotypes involved in anticancer drug pharmacokinetic or pharmacodynamic variability or those involved in cancer predisposition may be limited to investigations using individuals with the particular cancer or those already being treated with a particular chemotherapeutic agent.
After an assessment of phenotypic and genotypic markers in the general population, it may be useful to undertake surveys in other populations, including patients affected with specific types of cancer or being treated with a particular chemotherapeutic agent. Such studies may define the frequency of the pharmacogenetic syndrome in the cancer patient population at risk. Other demographic factors, such as race, age, and gender, may influence the risk to specific groups.
The methodologies discussed above have had specific applications in the identification of SNPs in single genes using the candidate gene approach. The genetic polymorphisms in single genes have not thus far explained a large proportion of the individual variability in drug response, mainly because most drug response phenotypes are thought to be determined by the interactions among multiple genes as well as with the environment. Therefore, the candidate gene strategy has limited value for identifying polygenic determinants of variability in drug response. On the other hand, this approach may offer an advantage for testing “specific” biological or pharmacological hypotheses in a given and often limited clinical sample of patients. Genome-wide studies require larger numbers of subjects to achieve statistical power to identify multiple lowpenetrance genes, a requirement seldom fulfilled in small heterogeneous patient samples.
Genomic Approaches
Efforts using a candidate gene approach were highly successful in identifying genetic causes for severe drug toxicity such as related to glucose-6-phosphate dehydrogenase deficiency.34 A genome-wide scanning (GWAS) approach is now increasingly used to look for variants that influence the risk of disease and explain differences in drug effect conferred by variants in metabolic enzymes, drug transporters, and drug targets.34 Evolving technologies such as microarrays, proteomics, and mouse genetics promise to provide many exciting results that influence clinical practice. Commercial gene chips are available to measure entire classes of genes (i.e., cytochrome P450s) or the entire human genome.35 In recognition of the emerging role of pharmacogenetics in the clinic, the NIH roadmap sponsored creation of the 12-center Pharmacogenetics Research Network.2 Pharmacogenomic approaches are hampered by the requirement for large sample sizes to generate statistically significant results and by the high numbers of false-positive findings.28 For example, recent work using the International HapMap, which has genotyped 3.3 million SNPs, predicted the thiopurine methyltransferase phenotype, although 96 genes in this analysis ranked higher.36
Gene expression arrays of tumor provide an alternative approach to SNP arrays and gene variant analysis for predicting response to drugs. Arrays are primarily of value in predicting the need for, and potential success of treatment. Rather than relying on polymorphisms in a single gene, expression patterns of multiple genes or proteins can be assayed to create a “signature” reflective of a drug’s effect. These expression patterns may result from gene variants, but verification of the presence of a variant requires gene sequencing and is usually not done in conjunction with the development of predictive arrays. In contrast to the candidate gene approach, genomic experiments provide an unbiased, hypothesis generating picture of drug effects.28 Using DNA microarrays on ALL cells, 124 genes were associated with resistance or sensitivity to four chemotherapeutic drugs.37 A parallel study identified 45 genes differentially expressed in patients resistant to all four drugs.38 Microarray experiments predict the sensitivity of cancer cells to docetaxel and multidrug regimens and estimate response to treatment.39, 40, 41 Gene signature analysis has also been incorporated into clinical trials of breast cancer patients, and they seemed to predict pathologic complete response.42
One of the first pharmacogenomic tests available is the Oncotype DX, which is recommended in the 2007 Update of Recommendations for the Use of Tumor Markers in Breast Cancer from the American Society of Clinical Oncology and the National Comprehensive Cancer Network 2008 Clinical Practice Guidelines in Oncology Breast Cancer.35,43 Oncotype DX is used to identify which newly diagnosed, node-negative, ER-positive breast cancer patients may benefit from tamoxifen, and may not need adjuvant chemotherapy.43 The Oncotype DX assay uses RT-PCR to gauge the expression of 21 genes, including those involved in proliferation (Ki67, STK 15, surviving, cyclin B1, MYBL2), invasion (stromelysin 3, cathepsin L2), HER2 (GRB7, HER2), estrogen (ER, PGR, BCL2, SCUBE2), miscellaneous (GSTM1, CD68, BAG1), and five reference genes.44 RNA extracted from paraffin-embedded tissue is used.44 Gene expression levels are analyzed by an algorithm that calculates a recurrence score that predicts the likelihood of distant recurrence in tamoxifen-treated patients.44 The goal of the assay is to identify patients with a good prognosis that may avoid adjuvant chemotherapy.45
The use of the Oncotype DX assay in predicting the likelihood of recurrence in women with node-negative ER-positive breast cancer treated with tamoxifen was validated in a trial of 668 patients from the National Surgical Adjuvant and Bowel clinical trial.44 The recurrence score was used to cluster patients into low-, intermediate-, and high-risk groups. In the patient population studied, 51%, 22%, and 27% of patients fell in the low-, intermediate-, or high-risk groups, respectively, with a 6.8%, 14.3%, and 30.5% chance of distant recurrence at 10 years, respectively.44 The Oncotype DX assay provided additional information beyond tumor grade as determined by three pathologists.44 One limitation of the Oncotype DX assay is that results may be influenced by the tumor block selected.46
Other genomics based tests include MammaPrint (FDA approved 2007), which uses a 70-gene profile to classify tumors from stage I or II breast cancer patients as low or high risk for recurrence47 and the Rotterdam Signature, a 76-gene profile that does not overlap with MammaPrint or Oncotype DX. Medicare covers Oncotype DX, which has shown to be cost-effective. If used to classify a hypothetical cohort of 100 patients, Oncotype DX was estimated to result in an increase in quality-adjusted survival by 8.6 years and reduce cost by $202,828.48 A prospective validation of Oncotype DX is underway in a randomized clinical trial (TAILORx).49
In the following section, discussion will be considered for the important SNP variants that influence response to and toxicity of commonly used anticancer drugs. The list of potentially important variants is not all-inclusive; the actual confirmation of an important role for a given variant requires characterization of protein function and large-scale trials, which are often beyond the scope of funding available for such research. Thus, many of the variants of interest have only been assessed through retrospective analysis of toxicity or response patterns in trials not designed for pharmacogenetic study. For most of these variants, understanding of the impact on drug metabolism, transport, or target interaction in human patient populations is incomplete. As will be seen below, genetic variants in drug-metabolizing enzymes are of particular relevance in explaining variable drug responses, especially toxicity. The relationship between polymorphism and toxicity is best established by data demonstrating that the variant affects enzyme activity, that enzyme
activity predicts pharmacokinetic behavior, and that drug levels or AUC predict efficacy or toxicity.
activity predicts pharmacokinetic behavior, and that drug levels or AUC predict efficacy or toxicity.
Gene Variants and Anticancer Drug Response
Fluorouracil
The phosphorylated form of 5-FU inhibits thymidylate synthase (TS), blocking DNA synthesis and repair.32 Capecitabine is an oral prodrug that is metabolized to fluorouracil.50 These agents are used in the treatment of breast and colorectal cancers, in over two million patients a year.51 Fluorouracil is inactivated by dihydropyridine dehydrogenase (DPD) in the liver, and this enzyme accounts for 80% of removal in cancer patients.52 Genetic variations in both DPD and TS affect fluorouracil efficacy and toxicity.
Dihydropyridine Dehydrogenase
DPD exhibits a wide interindividual variation in activity of up to 20-fold, and patients with low or negligible DPD activity are unable to efficiently inactivate 5-FU, leading to decreased catabolism, which can produce severe 5-FdUMP-mediated gastrointestinal, hematopoietic, and neurological toxicities.53, 54, 55, 56, 57 An estimated 3% and 0.1% of the population are heterozygous and homozygous, respectively, for inactivating mutations in DPD that involve a splice error leading to an exon deletion.32 These patients are at increased risk for severe myelosuppression, neurologic, and gastrointestinal side effects due to fluorouracil toxicity.32 Indeed, decreased DPD activity was detected in 60% of patients with grade 3 to 4 toxicity on fluorouracil.58 DPD also appears to serve a critical role in tumor response to 5-FU, with low intratumor expression of DPD shown to predict favorable response to this agent and increased survival time in patients with colorectal cancer.59 Pharmacokinetic studies in patients receiving 5-FU by continuous infusion have demonstrated that plasma 5-FU levels have a circadian variation. This circadian variation was further shown to inversely correlate with the circadian variation in DPD activity from peripheral blood mononuclear cells, suggesting that plasma 5-FU levels are regulated by DPD.60 There is also considerable variation in DPD activity across different ethnicities.61
More than 50 sequence variations in the DPYD gene have been identified, producing multiple complex heterozygote genotypes that are inherited in an autosomal codominant fashion.62 Analyses of the prevalence of the specific variant alleles have shown that the most common inactivating allele (DPYD*2A), accounting for 25% of patients with toxicity, is characterized by a G to A transition at the invariant GT splice donor site flanking exon 14 of the DPYD gene.57,63 This mutation leads to truncated mRNA due to skipping of exon 14, which results in a nonfunctional protein.57,64,65 A second single nucleotide polymorphism associated with DPD deficiency is DPYD*13, which is characterized by a T to G transition at a domain important to enzyme activity.66
Familial studies have indicated that DPD deficiency is inherited in an autosomal codominant fashion and that DPD deficiency most likely results from multiple mutations at a single gene locus. For instance, a profoundly deficient patient with heterozygous mutations for both DPYD*13 and DPYD*2A and a spouse with normal DPD activity had two partially deficient offspring (one child being heterozygous for the DPYD*2A variant allele and one child being heterozygous for the DPYD*13 variant allele).66 To date, however, the identified DPYD variant alleles do not explain all observed cases of DPD deficiency as many patients with severe 5-FU toxicity have no detected mutations in the DPYD gene.67
Previous reports of sequence variations in this gene have not consistently predicted DPD enzyme activity and identified patients at risk for 5-FU-mediated toxicity due to DPD deficiency.67, 68, 69, 70 Less than 50% of patients with severe toxicity from fluorouracil treatment have mutations in the DPYD gene or decreased DPD activity.71 This suggests that in addition to the investigation of variations in the DPYD gene, further investigations should explore other markers that may act alone or together with DPD to produce 5-FU toxicity.
Several tests are used to assess for DPD deficiency in a research setting, including radioimmunoassay and sequencing, and a 13C-uracil breath test shows great promise for application in the clinic.51,72 The gold-standard for testing is considered to be measurement of DPD activity in peripheral blood mononuclear cells, with activity levels correlating with heterozygosity for the DPYD*2A allele.73 In this assay, radiolabeled 5-FU is incubated with patient cells and the rate of catabolite formation is measured by HPLC.74,75 PCR-based testing is available commercially for the DYPD*2A mutation, which accounts for 52% of patients with complete or severe DPD deficiency and is found in 1% of Caucasians (Table 6-2).56,76,77 Commercial tests are also available to measure fluorouracil levels in patients receiving continuous infusion (Table 6-2). The use of genetic screening for DPD deficiency should be used cautiously given patients with mutations do not always experience severe toxicity, creating the risk of an unnecessary dose reduction in chemotherapy.61 For example, a study of 487 patients in France found of 10 patients with a DYPD*2A allele 6 experienced severe toxicity while 4 did not.78
Thymidylate Synthase
Like polymorphisms in genes important for drug metabolism, polymorphisms in the genes for drug targets are also important determinants of drug response and disease outcome. TS is the main target of 5-FU. The 5-FU metabolite FdUMP produces a stable complex with TS and a methyl cofactor, leading to inhibition of dTMP synthesis and DNA synthesis.79 Variability in response to 5-FU has been linked to several TS gene (TYMS) genetic polymorphisms.80, 81, 82
To date, several polymorphisms in the TYMS gene have been identified. A polymorphism within the 5′-promoter enhancer region (TSER) of the TYMS gene consists of tandem repeats of 28 base pairs ranging from two (TSER*2) to nine (TSER*9) copies.83 The role of most of these alleles in TS expression is currently unknown; however, patients homozygous for the TSER*3 genotype have increased intratumor TS messenger RNA levels84 and elevated TS protein levels85 compared with patients with the homozygous TSER*2 genotype.84,86,87 Two additional polymorphisms have been identified. The first is a single nucleotide polymorphism within the second repeat of the TSER*3 allele (G→C, 3RG and 3RC
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