European Journal of Pharmacology 625 (2009) 122–130
`
`Contents lists available at ScienceDirect
`
`European Journal of Pharmacology
`
`j o u r n a l h o me p a g e : w w w.e l sev i e r. c om / l oc a te / e j p h a r
`
`Review
`The effect of genetic variability on drug response in conventional
`breast cancer treatment
`Emilia Wiechec, Lise Lotte Hansen ⁎
`Institute of Human Genetics, The Bartholin Building, University of Aarhus, DK-8000 Aarhus C, Denmark
`
`a r t i c l e
`
`i n f o
`
`a b s t r a c t
`
`Article history:
`Received 2 July 2009
`Received in revised form 20 August 2009
`Accepted 26 August 2009
`Available online 18 October 2009
`
`Keywords:
`Personalized medicine
`Breast cancer
`Drug response
`SNP
`Chemotherapy
`
`Contents
`
`The conventional breast cancer diagnosis based mainly upon histopathology, hormone and HER-2 receptor status,
`will in the future be combined with information on genomic and epigenetic profiles of the individual patient. This will
`lead to an optimal personalized therapy, directed towards specific genomic aberrations, avoiding unnecessary
`toxicity, side effects and chemotherapeutic drugs for which the patient evolves resistance. Breast cancer is a very
`heterogeneous malignancy, expressing a considerable variation in genomic aberrations from deletions and
`amplifications comprising entire chromosomes to minor regions. A wide spectrum of differently expressed genes
`and mutations has been identified, adding information to the highly complex picture of the tumor genome. The vast
`majority of breast cancer incidents is of somatic origin and may be caused by a combination of the individual genetic
`profile and environmental exposure. A major contributor to the variation in genetic profile is the single nucleotide
`polymorphisms (SNPs), which are highly abundant throughout the genome, and both current and future
`methodologies have the potential to screen millions of SNP genotypes in one analysis. Identification of specific SNP
`genotypes affecting transcriptional activity and thereby the outcome for the patient, of genes involved in DNA repair,
`metabolizing of chemotherapeutic drugs and drug target genes will determine the outcome for the patient. This will
`be an essential part of the development of personalized treatment of cancer. In this review the focus is on clinically
`relevant SNPs in genes implicated in drug metabolism and disposition as well as their influence on breast cancer
`therapy toxicity and/or efficacy.
`
`© 2009 Elsevier B.V. All rights reserved.
`
`1.
`2.
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`6.
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`8.
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`Introduction .
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`SNP analysis .
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`Drug metabolism .
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`Drug transporters
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`Drug metabolizing phase I enzymes .
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`5.1.
`Cytochrome P450 .
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`Drug metabolizing phase II enzymes
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`6.1.
`Sulfotransferases
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`6.2.
`Glutathione S-transferase pi
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`6.3.
`NAD(P)H: quinone oxidoreductase 1 .
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`6.4.
`Carboxylesterase 2
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`DNA biosynthesis-associated target genes .
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`7.1.
`5,10-Methylenetetrahydrofolate reductase
`7.2.
`Thymidylate synthase .
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`7.3.
`Dihydropirymidine dehydrogenase .
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`7.4.
`Cytidine deaminase .
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`7.5.
`Ribonucleotide reductase M1
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`DNA repair-associated target genes .
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`123
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`
`⁎ Corresponding author. Tel.: +45 8942 1680, +45 2899 2180 (Cell phone); fax: +45 8612 3173.
`E-mail address: lotte@humgen.au.dk (L.L. Hansen).
`
`0014-2999/$ – see front matter © 2009 Elsevier B.V. All rights reserved.
`doi:10.1016/j.ejphar.2009.08.045
`
`AVENTIS EXHIBIT 2042
`Mylan v. Aventis, IPR2016-00712
`
`

`
`E. Wiechec, L.L. Hansen / European Journal of Pharmacology 625 (2009) 122–130
`
`Additional anticancer drug-associated genes
`9.
`Conclusions .
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`10.
`References
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`123
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`127
`128
`128
`
`1. Introduction
`
`Breast cancer is the most common malignancy in women presenting
`a lifetime risk of 8%. Breast cancer mortality has declined briefly over the
`past years but is still the leading cause of cancer death for women (Boyle
`and Ferlay, 2005a,b; Cardis et al., 2006; Ferlay et al., 2007).
`Breast cancer is a multifactorial disease, and less than 10% of all
`incidents are considered caused by defects in single genes (monogenic).
`For the majority of incidents, the multiple steps leading to breast
`tumorigenesis are not fully elucidated despite a comprehensive effort
`worldwide. New breast cancer susceptibility genes have been identified,
`though less penetrant as the well characterized BRCA1 and BRCA2.
`Epigenetic studies, especially targeting changes in the methylation pat-
`tern of tumor DNA are promising new markers for risk, early diagnosis
`and therapy prediction. Genomic aberrations as single nucleotide poly-
`morphisms (SNPs) and copy number variations are used in association
`studies comparing genotype frequencies and copy number variations
`between affected and non-affected individuals to assess new cancer
`susceptibility genes and markers predicting therapy response and drug
`resistance. Mapping of the variety of epigenetic and genomic alterations
`in tumor genomes and correlating these finding with tumor character-
`istics, prognosis and response to therapy are the first steps towards
`generating personalized therapy.
`The choice of breast cancer therapy is based on tumor character-
`istics such as size, histopathology, estrogen and progesterone receptor
`status, the level of HER-2 expression, and lymph node infiltration.
`Therapy includes surgery (lumpectomy, mastectomy), radiotherapy,
`hormonal therapy, chemotherapy, and immunotherapy. Neoadjuvant
`radiotherapy can be used in combination with an early diagnosis in
`order to diminish the size of the tumor prior to surgery.
`Breast tumors with high expression of estrogen and progesterone
`receptors are treated with estrogen receptor inhibitors as tamoxifen.
`Recently, a new group of estrogen synthesis inhibitors, the aromatase
`inhibitors have been implemented in treatment of postmenopausal
`breast cancer (Brueggemeier, 2004; Gibson et al., 2007). This group
`of anticancer drugs seems to be more attractive in comparison to
`tamoxifen, mostly due to lower toxicity. Furthermore, a list of cytotoxic
`drugs applied either separately or in combination chemotherapy com-
`prises an efficient strategy for treatment of advanced or metastatic
`breast cancer. However, the outcome of anticancer therapy varies
`greatly from patient to patient, and it is becoming clear that the indi-
`vidual genetic profile plays a dominant role. Loss of the efficacy of the
`treatment followed by the severe toxicity as: myelosuppression,
`secondary leukemia, moist desquamation of the skin, nausea, fatigue,
`and diarrhea are common events in ineffective response to
`pharmacotherapeutics.
`Most interpatient differences in the therapy efficacy and/or
`toxicity lies in the genetic variability described by SNPs and copy
`number variations, which affect the anticancer drug metabolism
`pathways and target genes of the chemotherapeutics used in cancer
`therapy. The comprehensive impact of heritable polymorphisms on
`drug response and therapy-induced toxicity has been studied in-
`tensively in the past decades, rapidly increasing after the release of
`the first draft of the human genome sequence, and is known as
`pharmacogenetics (Gibson et al., 2007; Nebert, 1982; Sjoqvist, 1999).
`The importance of genetic variations in prediction of the anticancer
`drug activity prompts the development of personalized medicine
`where the choice of treatment is based on the individual's genetic
`profile. This individualized genotype map results in various pheno-
`typic properties in regard to changes of drug mechanism of action as
`
`well as the efficacy of treatment. The pharmacokinetics of an ad-
`ministered drug can be altered by genetic variations on the level of
`genes involved in drug uptake, activation, distribution, anticipated
`action, and excretion (Fig. 1).
`In this review we emphasize the predictive role of SNPs in cancer
`treatment. As examples we describe the genetic variants in the genes
`responsible for transport of cytotoxic agents, metabolism and drug-
`associated target genes with focus on their impact on breast cancer
`therapy toxicity/efficacy. The key genes implicated in the metabolism
`of anticancer drugs and therapy responsive genes as well as the
`predicted effect of genetic polymorphisms within these genes in
`anticancer therapy are listed in Tables 1 and 2 respectively.
`
`2. SNP analysis
`
`A single nucleotide polymorphism (SNP) is defined as a variation of
`one nucleotide in which one allele is present in more than 1% of the
`studied population. SNPs are biallelic though tri- or tetraallelic forms
`have been found (Huebner et al., 2007). Non-biallelic SNPs are rare and
`can be overlooked as many frequently used genotyping methodologies
`fail to detect the additional alleles (Huebner et al., 2007).
`It is estimated that the genome contains approximately 10 million
`SNPs of which 3.1 million are validated via the HapMap project (2003;
`Frazer et al., 2007). In the second phase of the HapMap project 270
`individuals from four geographical diverse populations were geno-
`typed for 2.1 million SNPs, which means that 25–30% of all genomic
`SNPs with a minor allele frequency ≥0.05 are validated (Frazer et al.,
`2007). The SNP density is in average one genotyped SNP per 875 bp
`(or 1.14 SNP/1000 bp) though not distributed evenly through out the
`genome. The SNP frequency is lower in genomic regions, conserved
`betweeen spieces including coding regions than in non-coding parts
`of the genome (Li and Sadler, 1991; Nickerson et al., 1998).
`SNPs in non-coding genomic regions, which are less conserved
`among spieces, are generally frequent and highly plymorphic, making
`them usefull for population based studies of evolution or as physical or
`genetic markers in genome-wide search for new disease susceptibility
`genes. In selected patient cohorts undergoing cancer therapy, these SNP
`
`Fig. 1. Influence of SNPs on toxicity/efficacy of breast cancer therapy. Interpatient variability
`plays a crucial role in selecting the accurate treatment option as well as predicting its clinical
`outcome such as response to treatment and toxicity.
`
`

`
`124
`
`E. Wiechec, L.L. Hansen / European Journal of Pharmacology 625 (2009) 122–130
`
`Table 1
`List of candidate genes with impact on the anticancer drug metabolism, drug interactions and therapy efficacy.
`
`Name
`
`Cytogenetic location
`
`Function of the gene product
`
`Drug transporter; implicated in energy-dependent transport of
`cytotoxic agents out of the cell
`Organic cation transporter involved in transport of various compounds
`including hormones, neurotransmitters and xenobiotics (doxorubicin)
`Phase I enzyme in drug metabolism; metabolism of estrogens in human
`breast tissue; synthesis of cholesterol and lipids
`Phase I enzyme in metabolism of anticancer drugs cyclophosphamide;
`synthesis of cholesterol and lipids
`Phase I enzyme involved in metabolism of antiestrogens such as tamoxifen
`
`Phase I enzyme in drug metabolism; biosynthesis of estrogens
`
`Phase II enzyme in drug metabolism; catalyzes the sulfate conjugation of
`drugs, hormones and xenobiotics as a detoxication mechanism for phenolic and
`estrogenic compounds (4-hydroxy-tamoxifen)
`Phase II enzyme in drug metabolism; catalyzes the conjugation of a reduced
`glutathione to smooth the excretion of xenobiotics from the body
`Phase II enzyme in drug metabolism; reduces quinone-based anticancer agents
`to hydroquinones protecting against oxidative stress, production
`of reactive-oxygen species and carcinogenesis
`Phase II enzyme required for the transformation of the pro-drug,
`capecitabine into 5-Fluorouracil
`Enzyme responsible for metabolism of vitamin B9 (folate)
`required in DNA synthesis
`Enzyme implicated in conversion of deoxy-uridine monophosphate (dUMP)
`into deoxy-thymidine monophosphate (dTMP) which is essential in DNA synthesis
`Enzyme involved in degradation of pyrimidines (uracil and thymine)
`and uracil analogue used in chemotherapy, 5-Fluorouracil
`Enzyme involved in the retrieval of pyrimidines and detoxifying
`the anticancer drug, gemcitabine
`The base excision repair (BER) protein capable to restore DNA single-strand
`breaks emerged due to exposure to ionizing radiation and alkylating agents
`Enzyme involved in the repair of DNA abasic sites generated spontaneously or
`by radiation-derived genotoxic agents
`Enzyme from the primary antioxidant defense group catalyzing conversion of
`
`superoxide (O2−) into hydrogen peroxide (H2O2) and oxygen
`Enzyme from the host defense system group producing hypochlorous acid (HOCl)
`from hydrogen peroxide which possess strong antimicrobial activity
`Enzyme involved in production of deoxyribonucleotides necessary
`for DNA synthesis and repair
`Cytokine controlling cell growth, proliferation, differentiation and apoptosis
`Protein involved in a number of cellular processes such as cell growth,
`differentiation, migration, angiogenesis
`Protein involved in regulation of DNA damage response and cell cycle control
`Protein involved in a variety of cellular mechanisms such as:
`apoptosis, cell cycle, DNA repair; important tumor suppressor
`in many types of cancer
`
`Gene
`
`MDR1
`
`Multidrug resistance 1
`
`7q21.1
`
`SLC22A16
`
`Solute carrier family 22, member 16
`
`6q21–22.1
`
`CYP1B1
`
`CYP2B6
`
`CYP2D6
`
`CYP19A1
`
`SULT1A1
`
`Cytochrome P450, family 1, subfamily B,
`polypeptide 1
`Cytochrome P450, family 2, subfamily B,
`polypeptide 6
`Cytochrome P450, family 2, subfamily D,
`polypeptide 6
`Cytochrome P450, family 19, subfamily A,
`polypeptide 1; Aromatase
`Sulfotransferase family 1A, member 1
`
`GSTP1
`
`Glutathione S-transferase pi 1
`
`NQO1
`
`NAD(P)H: quinone oxidoreductase 1
`
`CES2
`
`Carboxylesterase 2
`
`2p21
`
`19q13.2
`
`22q13.1
`
`15q21.1
`
`16p12.1
`
`11q13.2
`
`16q22.1
`
`16q22.1
`
`MTHFR
`
`5,10-Methylenetetrahydrofolate reductase
`
`1p36.3
`
`TS
`
`DPD
`
`CDA
`
`XRCC1
`
`APE1
`
`SOD2
`
`MPO
`
`RRM1
`
`TGFβ1
`FGFR4
`
`ATM
`TP53
`
`Thymidylate synthase
`
`Dihydropirymidine dehydrogenase
`
`Cytidine deaminase
`
`X-ray repair complementing defective repair in
`Chinese hamster cells 1
`Apurinic/apyrymidinic endonuclease 1
`
`Superoxide dismutase 2
`
`Myeloperoxidase
`
`Ribonucleotide reductase M1
`
`Transforming growth factor beta 1
`Fibroblast growth factor receptor 4
`
`Ataxia telangiectasia mutated
`Tumor protein 53
`
`18p11.32
`
`1p22
`
`1p36.2–p35
`
`19q13.2
`
`14q11.2–q12
`
`6q25.3
`
`17q23.1
`
`11p15.5
`
`19q13.1
`5q35.1
`
`11q22–q23
`17p13.1
`
`association studies can lead to identification of SNP genotypes involved
`in therapy response and resistance.
`Non-synonomous SNPs may affect the amino acid composition of a
`protein, either as missense or non-sense mutations. Most protein
`coding regions are highly conseved among spieces and therefore, non-
`synomous SNPs are characterized by a low frequency and a minor
`allele frequency. Likewise, SNPs in regulatory regions as promoters, 5′
`or 3′ UTRs, microRNAs, enhancer or silencer elements may affect the
`transcriptional activity of genes and therefore, are rare SNPs with
`minor allele frequency.
`The vast majority of SNPs reported to public databases are highly
`polymorphic SNPs, but it is estimated that more than 60% of all SNPs in
`the human genome have a minor allele frequency <5% (Gorlov et al.,
`2008; Wong et al., 2003). Low minor allele frequency SNPs include
`SNPs in coding and regulatory regions and in combination with the
`new high throughput genotype detecting methodologies, which pro-
`vide the possibility to screen large populations for a high number of
`SNPs, these SNPs have a strong potential as disease risk markers (Zhu
`et al., 2004). Rare low minor allele frequency SNPs are included in
`genotyping platforms, which will facilitate the identification of causal
`SNPs in case–control association studies, provided the samle size is
`
`large (Gorlov et al., 2008). SNP genotypes either alone or in com-
`bination as haplotypes are important tools in the search for the origin
`of multifactorial diseases in which multiple affected genes and
`enviromental factors can be combined to the set of the disease.
`Haplotypes can be established by SNP genotypes along the chromo-
`somes in sperm cells, via family studies or in large populations.
`Haplotypes are inherited in blocks (haplotype blocks), which rarely
`are interferred by recombination. Haplotype blocks, therefore,
`represent genotypes in linkage disequilibrium and are important in
`the search for disease susceptibility genes or genes affecting drug
`response. SNP genotypes in genomic regions between haplotype
`blocks are not in linkage disequilibrium and may represent recom-
`bination hot spots (Jeffreys et al., 2005). Data from phase II of the
`HapMap project identified 32,996 recombination hotspots in the
`human nuclear genome. No marked difference was found between
`chromosomes in the concentration of recombination hotspots (Frazer
`et al., 2007).
`The rapidly increasing amount of validated SNPs across the genome
`is a valuable tool to identify new disease susceptibility genes for mul-
`tifactorial diseases. Association studies comparing SNP genotypes be-
`tween individuals expressing the same disease phenotype and a cohort
`
`

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`
`125
`
`Table 2
`Genetic polymorphisms influencing the drug response and toxicity in breast cancer treatment.
`
`Drug
`
`Drug target gene
`
`Variant allele
`
`Effect of the polymorphism on the efficacy/toxicity of drug therapy and
`clinical outcome
`
`CYP2D6*4/*4
`CYP2D6*10/*10
`CYP2D6*4
`SULT1A1*2/*2 (homozygous variant)
`Rs4646 (GT or TT)
`
`Higher risk of disease recurrence (Goetz et al., 2005)
`Higher risk of disease recurrence (Kiyotani et al., 2008)
`Lower risk of disease recurrence, severe hot flashes (Wegman et al., 2005)
`Increased risk of death (Nowell et al., 2002)
`High response to letrozole, improved treatment efficacy (Colomer et al., 2008)
`
`Increased risk of disease progression and death (Bewick et al., 2008)
`Chemotherapy induced increased risk of disease progression and death
`(Bewick et al., 2008)
`Improved survival outcome (Bewick et al., 2008)
`Decreased risk of death (Ambrosone et al., 2005)
`
`Severe leucocytopenia (Nakajima et al., 2007)
`Decreased chemosensitivity of breast cancer cells (Sohn et al., 2004)
`Increased risk of developing secondary leukemia (Guillem et al., 2007)
`
`Increased chemosensitivity to 5-Fluorouracil (Sohn et al., 2004)
`Neurotoxicity and death, myelosuppression (Raida et al., 2001; Takimoto et al., 1996;
`van Kuilenburg, 2004; van Kuilenburg et al., 2001)
`Higher incidence of grade 3 hand–foot syndrome and grade 3–4 diarrhea
`(Ribelles et al., 2008)
`Better response to capecitabine and longer time to progression of the malignancy
`(Ribelles et al., 2008)
`Poor disease-free survival, decreased sensitivity to neoadjuvant chemotherapy
`(Toyama et al., 2007; Xu et al., 2005)
`Low frequency of neutropenia, poor overall survival, indicator of resistance to
`gemcitabine (Rha et al., 2007)
`Significant decrease in gemcitabine clearance; increased risk for neutropenia with
`co-administration of 5-Fluorouracil, cisplatin or carboplatin (Sugiyama et al., 2007)
`Treatment-specific reduced survival (Nordgard et al., 2008)
`Complete clinical response to neoadjuvant doxorubicin-based chemotherapy
`(Kafka et al., 2003)
`Increased clearance of doxorubicin (Lal et al., 2008)
`Higher exposure level to doxorubicinol (Lal et al., 2007)
`Poor survival rate in epirubicin treated breast cancer patients; impairment of
`response to epirubicin; strong prognostic and predictive factor in breast cancer
`(Fagerholm et al., 2008)
`Longer progression-free survival in breast cancer patients; paclitaxel resistance
`(Gehrmann et al., 2008; Marsh et al., 2007)
`
`Reduced risk for recurrence/death (Jaremko et al., 2007)
`Poor disease-free survival and overall survival for node-positive breast cancer
`patients; poor therapy response (Thussbas et al., 2006)
`Greater radiation toxicity; better pathologic complete response to FAC
`(Rajkumar et al., 2008)
`
`Increased radiosensitivity of normal breast tissue and subsequent radiation-induced
`tissue complications (Andreassen et al., 2005, 2003)
`Lower risk for development of radiation-induced subcutaneous fibrosis
`(Andreassen et al., 2006a,b)
`Increased risk of radiation-induced subcutaneous fibrosis (Andreassen et al., 2006a)
`Lower risk of acute moist desquamation of the skin (Chang-Claude et al., 2005)
`
`Adjuvant hormonal therapy
`Tamoxifen
`
`CYP2D6
`
`SULT1A1
`CYP19A1
`
`GSTP1
`SOD2
`
`MPO
`
`CYP2B6
`MTHFR
`
`MTHFR
`DPD
`
`CES2
`
`TP53
`
`RRM1
`
`CDA
`
`TS
`MDR-1
`
`Aromatase inhibitors
`(letrozole, anastrazole)
`
`Chemotherapy
`Cyclophosphamide
`
`Methotrexate
`
`5-Fluorouracil
`
`Capecitabine
`
`Gemcitabine
`
`Mitomycin
`Doxorubicin
`
`Epirubicin
`
`GSTP1-01 (GG or AG) — Rs1695
`SOD2-01(TT) — Rs4880
`
`SOD2-01(CC) — Rs4880
`MPO-02(GG) — Rs2333227 +
`SOD2-01(CC)
`CYP2B6*1A/*1A
`Rs1801133: C677T (TA)
`Rs1801133: 677(TT/CT) +
`Rs1801131: 1298(AA)
`Rs1801133: C677T (TA)
`IVS14 +1G>A (rs3918290)
`
`6046 G>A
`
`−823 C>G
`
`72Pro>Pro (rs1042522)
`
`2455 A>G
`2464 G>A
`208 G>A
`
`5′ UTR: 28 bp 3× tandem repeat
`3435 (TT)
`
`SLC22A16
`NQO1
`
`1236 (CC)+ 2677 (GG) +3435 (CC)
`146 (GG)
`NQO1*2(SS)
`
`Paclitaxel
`
`CYP1B1
`
`CYP1B1*3 (homozygous variant)
`
`Combination chemotherapy
`CMF
`
`Neoadjuvant
`radiation/FAC/CMF
`
`Radiotherapy
`
`XRCC1
`FGFR4
`
`TGFβ1
`
`TGFβ1
`
`ATM
`
`XRCC1
`XRCC1
`APE1
`
`1196(AA)
`Arg388
`
`TGFβ1 (Pro/Pro)
`
`−509 C>T
`10 Leu/Pro
`5557 G>A
`
`399 Arg/Arg
`XRCC1399Gln
`APE1148Glu
`
`CMF (cyclophosphamide, methotrexate, 5-Fluorouracil) and FAC (cyclophosphamide, doxorubicin, 5-Fluorouracil).
`
`of unaffected individuals, may identify causative SNP genotypes or SNP
`genotypes increasing the risk of disease.
`The identification of a causative SNP or a gene is the first step
`towards development of personalized medicine. The SNP genotype may
`be decisive for the optimal treatment for each individual patient taking
`into accout the risk of resistance towards specific chemotherapeutic
`agents, change in the activity of the gene product or developing severe
`side effects. The SNPs positioned in the key genes involved in the drug
`metabolic pathway and genes associated with drug treatment in breast
`cancer are described below.
`
`3. Drug metabolism
`
`The biotransformation of xenobiotics from their lipophilic structure
`into water-soluble and excretal form involves a number of metabolizing
`enzymes and is carried out mainly in the liver. Moreover, drug ab-
`sorption, delivery and their secretion across biological membranes
`profoundly affect their pharmacokinetics, and are affected by drug
`transporters. The two major phases, phases I and II in drug metabolism
`lead to complete modification and inactivation of an administered drug
`to facilitate its removal from the body via urine and feces (David Josephy
`
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`
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`
`et al., 2005; Liska, 1998). The initial phase I is implicated in drug
`activation/inactivation and preparation for phase II transformation
`characterized by oxidation, reduction and hydrolysis reactions. Phase II
`transformation of drugs involves conjugation of a drug or its initially
`transformed phase I metabolite with an endogenous substrates in the
`liver as a result of acetylation, amino acid conjugation, glucuronidation,
`sulfate conjugation and glutathione conjugation. The kidneys can suc-
`cessfully excrete these phase II hydrophilic conjugates. The efficiency of
`all the mentioned steps in drug metabolism as well as the host response
`to the drug treatment is highly dependent on the genetic polymorph-
`isms in the drug metabolizing enzymes, patients' age and the health-
`status of drug detoxifying organs (George et al., 1990; Nolin et al., 2008;
`O'Mahony and Woodhouse, 1994; Prescott et al., 1975; Woodhouse and
`Wynne, 1988). Any failure in this machinery caused by these factors,
`with a special distinction of SNP genotypes present in the drug-
`responsive genes might lead to therapy toxicity or drug resistance.
`
`4. Drug transporters
`
`The ABC transporters (ATP-Binding Cassette transporters) comprise
`a family of transmembrane proteins which use ATP hydrolysis as a
`power source for transport activity (Dean et al., 2001; Higgins, 1992).
`They have recently attracted a lot of attention due to their high
`expression in (cancer) stem cells (Hombach-Klonisch et al., 2008;
`Klonisch et al., 2008) Seven major subfamilies of the ABC transporters
`genes exist, however, only three of them (ABCB, ABCC, ABCG) are
`involved in drug transport including anticancer drugs (Gillet et al., 2004;
`Gottesman et al., 2002). Genetic polymorphisms affecting these trans-
`porters contribute to interpatient differences in drug response. One of
`the 49 members of ABC transporters, the P-glycoprotein encoded by the
`multidrug resistance gene MDR1 (ABCB1) plays an important role in
`efflux transport of the chemotherapeutic agent, doxorubicin used in
`breast cancer treatment (Klein et al., 1999). A substantial number
`of SNPs in the MDR1 gene, their influence on the gene function and
`response to drug therapy has been reported (Dey, 2006; Fromm, 2002;
`Kim, 2002; Sai et al., 2003; Saito et al., 2002). However, little is known
`about importance of genetic variations in MDR1 to the breast cancer
`chemotherapy. A synonymous SNP consisted of C-to-T transition at
`nucleotide 3435 in exon 26 has shown a considerable advantage in
`neoadjuvant chemotherapy. The 3435 TT genotype was associated with
`complete response to chemotherapy in patients treated with doxoru-
`bicin (Kafka et al., 2003). In another study, the clearance of this drug was
`significantly improved in breast cancer patients possessing the
`combined 1236 CC+2677 GG+3435 CC genotype (Lal et al., 2008).
`The other class of transporters, which play a critical role in drug
`absorption and elimination, are organic cation transporters (OCT). As
`the name suggests, they utilize the ion gradient across the membrane
`in order to facilitate transport of substrates against the electrochemi-
`cal difference (Koepsell et al., 2007, 2003; Okabe et al., 2005). The
`influx cation transporter — SLC22A16 was evaluated in Asian breast
`cancer patients in regard to response to treatment with doxorubicin.
`The 146 GG genotype was linked to higher exposure level to doxorubicin
`(Lal et al., 2007).
`
`5. Drug metabolizing phase I enzymes
`
`5.1. Cytochrome P450
`
`Cytochromes P450 (CYP) comprise a comprehensive family of
`isoenzymes involved in drug metabolism as phase I enzymes, ubiqui-
`tously expressed in the liver and intestine. They catalyze the mono-
`oxygenase reaction in order to inactivate (or activate) drugs and toxic
`compounds. Among human cytochromes P450 four families stand out,
`CYP1, CYP2, CYP3 and CYP19, which are involved in metabolism of
`anticancer drugs, as tamoxifen, aromatase inhibitors, cyclophospha-
`mide, and paclitaxel (Gonzalez and Nebert, 1990; Kivisto et al., 1995). A
`
`number of genetic polymorphisms in the CYP genes has been linked to
`the outcome of the drug therapy in breast cancer patients (Ingle, 2008).
`The metabolic pathway of the two major, estrogen receptor-
`positive breast cancer drugs, tamoxifen and aromatase inhibitors are
`influenced by cytochrome P450 enzymes. The member of CYP2 family,
`CYP2D6 enzyme, transforms antiestrogenic tamoxifen into its sec-
`ondary metabolite, 4-hydroxy-N-desmethyl-tamoxifen known as
`endoxifen (Stearns et al., 2003; Stearns and Rae, 2008). Functional
`SNPs within this gene are reported to be implicated in the long-term
`outcome of the tamoxifen-based therapy. Breast cancer patients
`carrying the CYP2D6*4/*4 or CYP2D6*10/*10 alleles have much higher
`risk of disease recurrence in comparison to having the CYP2D6*4
`allele (Goetz et al., 2005; Kiyotani et al., 2008; Wegman et al., 2005).
`Aromatase inhibitors block the cytochrome CYP19 (aromatase)
`synthesizing endogenous estrogen from androgens (Brueggemeier,
`2004). Therefore, they have considerable impact on current adjuvant
`treatment of breast cancer (Smith, 2003; Smith and Dowsett, 2003).
`The CYP19A1 rs4646 SNP is linked to higher efficacy of the treatment
`as well as higher response to aromatase inhibitors (Colomer et al.,
`2008).
`Alkylating agents, as cyclophosphamides are one of the chemo-
`therapeutic drugs applied to treat breast cancer. It requires metabolic
`activation to the primary metabolite, 4-hydroxycyclophosphamide
`(4-OH-CPA) by various cytochrome P450 enzymes including CYP2B6
`(Chang et al., 1993; Code et al., 1997). One of the allelic variant,
`CYP2B6*1A/1A was found to correlate with development of severe
`leucocytopenia in cancer patients (Nakajima et al., 2007).
`A further example of anticancer drugs metabolized by cytochromes
`P450 including CYP2C8, CYP3A4 and CYP3A5 is the microtubule tar-
`get, paclitaxel (Steed and Sawyer, 2007). However, little is known about
`genetic polymorphisms in CYPs and paclitaxel toxicity in breast cancer.
`Surprisingly, recent studies have shown that the CYP1B1*3 polymor-
`phism in the breast tissue-associated CYP1B1 gene is linked with longer
`progression-free survival and paclitaxel resistance in breast cancer
`(Gehrmann et al., 2008; Marsh et al., 2007).
`
`6. Drug metabolizing phase II enzymes
`
`6.1. Sulfotransferases
`
`The enzyme Sulfotransferase 1A1 (SULT1A1) catalyzes the sulfation
`reaction of various phenolic and estrogenic substrates including
`transformation of 4-hydroxy-tamoxifen (Falany et al., 1994). Analysis
`of genetic variants has shown that patients treated with tamoxifen, who
`are homozygous for the SULT1A1*2 allele, had three fold higher risk
`of death when compared with patients carrying the SULT1A1*1allele
`(Nowell et al., 2002).
`
`6.2. Glutathione S-transferase pi
`
`Glutathione S-transferase pi 1 (GSTP1) is an important enzyme in
`conjugation of hydrophobic compounds with a reduced glutathione, thus
`increasing their-water solubility and often facilitating excretion (Coles
`and Kadlubar, 2003). Metabolites of widely used chemotherapeutics
`in treatment of breast cancer, cyclophosphamides and doxorubicin com-
`prise the substrates for GSTP1 activity (Stearns et al., 2004). The rs1695
`(GG or AG) genotype was found to correlate significantly with unfavorable
`prognosis for breast cancer patients treated with alkylating agents
`(Bewick et al., 2008).
`
`6.3. NAD(P)H: quinone oxidoreductase 1
`
`NAD(P)H: quinone oxidoreductase 1 (NQO1) catalyzes reduction
`of quinines, quinone amines and nitro substrates utilizing NADP or
`NADPH as reducing cofactors (Edwards et al., 1980; Ross et al., 2000;
`Siegel et al., 2004). Moreover, this reductase is capable to inactivate
`
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`
`127
`
`DNA damaging reactive-oxygen species and has been described as a
`cancer preventive enzyme (Huggins and Fukunishi, 1964). Recently,
`the NQO1*2 homozygosity among patients tr