Role of pharmacodynamic, pharmacogenetic and pharmacogenomic biomarkers of cancer chemotherapy with...

Pteridines / Vol. 20 / Special issue

115 GJ Peters et al. : Role of pharmacodynamics, pharmacogenetic and pharmacogenomics biomarkers of cancer chemotherapy with antifolates

PteridinesVol. 20, Special issue, pp. 115-127

Role of Pharmacodynamic, Pharmacogenetic and Pharmacogenomic Biomarkers of Cancer Chemotherapy with Antifolates

GJ Peters1§, R.J. Honeywell1, L.G. Leon1, CJ van Groeningen1,5, G Jansen3, B Ylstra2, GA Meijer2, E Giovannetti1,4

1 Department of Medical Oncology, 2 Pathology, 3 Reumatology, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam.

4 Dept. of Internal Medicine, Division of Pharmacology, University of Pisa, Pisa, Italy Ziekenhuis Amstelveen5, Amstelveen, The Netherlands

Abstract

Folate metabolism is the target of two major anticancer drug groups: folate antagonists and thymidylate synthase inhibitors, including methotrexate (MTX), 5-fluorouracil (5FU) and pemetrexed (PMX). These agents have a high degree of variation in antitumor activity and toxicity. These variations can arise from variability in pharmacokinetics and/or pharmacodynamics, and the study of the genetic basis of interindividual variability in drug disposition and effects can improve outcomes and reduce toxicity.Several pharmacogenetic studies have investigated folate-related targets for treatment of colorectal, lung and hematologic malignancies, such as thymidylate synthase (TS) and methylenetetrahydrofolate reductase (MTHFR).Resistance to both 5FU and PMX has been associated with TS overexpression, while a disturbed folate homeostasis due to the MTHFR C677T polymorphism was associated with increased toxicity of MTX. Decreased transport (either via the reduced folate carrier or the proton-coupled folate transporter) or polyglutamylation may also confer resistance to PMX, while dihydropyrimidine dehydrogenase (DPD) deficiency might lead to fatal toxicity because of reduced 5FU metabolism.However, clinical data do not unequivocally support the influence of these single biomarkers, and advances in gene array technology, high-resolution genotyping, and bioinformatics can greatly contribute to the expansion of pharmacogenetic research methodology to pharmacogenomics, allowing the study of the entire genome. A recent study reported significant correlations between DNA copy number profiles and response to therapy, showing an association of chromosomal aberrations in 13q and 1p36 to the outcome of fluoropyrimidine-based chemotherapy in colorectal cancer. Large, well-designed studies are needed to confirm these early findings and the use of these biomarkers in effective clinical decision making.

§Correspondence : Dr. GJ Peters, Department of Medical Oncology, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands; T: +31-20-4442633; F: +31-20-4443844; Email: [email protected]



Introduction

Antifolates are the oldest of the antimetabolite class of anticancer agents and were among the first modern anticancer drugs. These drugs have a high degree of variation in antitumor activity and toxicity; predicting the clinical outcome and limiting toxicity are the two main challenges faced by the oncologists.

Chemotherapy of cancer is usually determined by the clinicopathological staging and type of the tumor. Although different drugs may have the same target, their activity is disease specific. E.g. colon cancer is being treated by a combination of a fluoropyrimidine (targeting thymidylate synthase [TS]) with another cytotoxic agent, either the platinum derivative oxaliplatin or the topoisomerase I inhibitor, irinotecan (1), while recent evidence has shown that antifolates, in particular pemetrexed (PMX), also a TS inhibitor, are a good alternative for a subset of patients with lung non-squamous adenocarcinoma (2). On the other hand sqaumous non-small cell lung cancer (NSCLC) patients benefit more from a combination of the antimetabolite gemcitabine and cisplatin. Hematological disorders in children can often be cured by drugs which are ineffective or less active in adults, such as thiopurines and methotrexate (MTX) (3). MTX, an inhibitor of dihydrofolate reductase (DHFR), is effective against pediatric acute lymphoblastic leukemia (ALL), but not against NSCLC, while PMX, which also inhibits DHFR (4), is effective against NSCLC. Both PMX and 5-fluorouracil (5FU) (as the nucleotide FdUMP) are potent inhibitors of thymidylate synthase (TS), but 5FU is ineffective against NSCLC. Not withstanding this fact, fluoropyrimidines, including 5FU, are an essential component for every treatment protocol of colorectal cancer, but PMX is ineffective against colon cancer (5). These findings suggest that besides the pathological difference between these types of cancer, there are a number of other genetic differences which determine the efficacy of cancer chemotherapy.

The e lucidat ion of the human genome offers numerous possibilities to characterize these differences. This enables us to use these differences to tailor therapy of a specific type or cancer. Another important aspect is to administer the less toxic type of therapy to a specific patient, which is a critical issue, as demonstrated by the 106,000 deaths and 2.2 million serious events

caused by chemotherapy related adverse drug reactions in the U.S. each year.

Pharmacogenetic testing offers an outstanding opportunity to improve efficacy and safety. Much of current clinical interest is at the level of pharmacogenetics, involving variation in genes involved in drug metabolism with a particular emphasis on improving drug safety. However, there is still a great deal of conflicting evidence that has as yet prevented the acceptance of any of the studied biomarkers for antifolates for clinical use.

This paper a ims to br ie f ly summarize current knowledge on the potential role of pharmacogenetics and pharmacogenomics biomarkers of antifolates activity, dealing with the reasons for numerous reported discrepancies, and suggesting the integration of new technologies with carefully designed prospective trials in order to discover/validate clinically useful biomarkers.

Pharmacogenetics and pharmacogenomics T h e t e r m s p h a r m a c o g e n o m i c s a n d

pharmacogenetics tend to be used interchangeably, and a precise, consensus definition of either remains elusive. Both aim to use novel genetic/genomic technologies to improve new drug discovery and further characterize older drugs. Pharmacogenetics is generally regarded as the study or clinical testing of one or a few genetic variations that gives rise to different drug responsiveness. Hence, pharmacogenetics considers one or at most a few genes of interest, while pharmacogenomics considers the entire genome. Pharmacogenetics often deals with germline genes which may affect the pharmacokinetic/-dynamic response of a drug. Pharmacogenetics may also deal with somatic aberrations in the tumors affecting the pharmacodynamic response to a drug. Pharmacogenomics almost exclusively deals with somatic aberrations.

Both deal with a branch of pharmacology, focusing on the influence of genetic variation on drug response in patients by correlating gene expression or polymorphisms with a drug’s efficacy or toxicity. By doing so, this field aims to develop rational means to optimize drug therapy, with respect to the patients’ characteristics, to ensure maximum efficacy with minimal adverse effects. A summary of potentially important genetic polymorphisms in folate metabolism is given in Table 1.



Such approaches promise the advent of “personalized medicine”, in which drug selection and dosage and drug combinations are optimized for each individual’s unique genetic makeup. In particular, there are a number of anticipated benefits of the application of pharmacogenetics/-genomics in the treatment of cancer, such as (i) design more relevant and specific anticancer drugs based on the knowledge of genes and proteins, (ii) the possibility to improve drug safety when administered for the first time to a patient, (iii) to create more accurate methods to determine appropriate drug dosages (preventing under- or overdosing), (iv) screening patients in an early phase for the likelihood to develop cancer, (v) improvement of drug discovery strategies and approval processes, (vi) decrease in costs of health care.

Pharmacogenetics/-genomics will assist to improve the standard trial-and-error method of matching patients with the right drugs and dosage. It will be possible to analyze a patient’s genetic profile and prescribe the best available drug therapy from the beginning. Not only will

this take the guesswork out of finding the right drug and dosage, it will accelerate recovery time and increase safety as the likelihood of adverse reactions is eliminated. Pharmacogenetics/-genomics has the potential to dramatically reduce the number of deaths and hospitalizations that occur each year worldwide as the result of adverse drug response. In addition, it has the potential to take care of interethnic differences in drug handling.

Antifolate-specific pharmacokinetic, -dynamic and -genetic biomarkers

MTX is an inhibitor of DHFR and decreases intracellular levels of reduced folates, such as 5,10-methylenetetrahydrofolate (5,10-CH2-THF) (3) which is required for DNA synthesis and for maintaining the balance of the deoxynucleotide pool.(3) Methylenetetrahydrofolate reductase (MTHFR) catalyzes the reduction of 5,10-CH2-THF to 5-CH3-THF, the predominant circulatory form of folate and carbon donor for the remethylation of homocysteine to methionine (Figure 1). MTHFR is located on the short (p)

Table 1. Potentially relevant genetic polymorphisms in folate metabolizing enzymes

Gene Enzyme alteration Effect on enzyme General effectMTHFR methylene tetrahydrofolate

reductase677C>T Decreased activity Altered folate

homeostasisMTHFR 1298A>C Altered folate

homeostasisMS methionine synthase 2756A>G Altered SAH/SAM

ratioMTRR methionine synthase reductase 66A>G Altered SAH/SAM

ratioSHMT serine-

hydroxymethyltransferase1420C>T

FPGS Folylpolyglutamate synthetase 1270C>T137C>T

Decreased activity Decrease in polyglutamates

RFC reduced folate carrier 80G>A Lower transport rate Folate depletion; increased extracellular folates

PCFT proton coupled folate transporter

337C>T Altered pH optimum Folate malabsorption

TYMS thymidylate synthase 2R3R Increased transcription

More dTMP synthesis

G>C in 2nd repeat

Decreased transcription

Less dTMP synthesis

6bp deletion in 3’UTR

Decreased transcription

NNMT nicotinamide N-methyltransferase

IVS -151C>T

Determines plasma homocysteine levels

From references: 8,12,17,20,24,27



arm of chromosome 1, at position 36.3 (1p36.3). Up to 12-15% of Caucasian individuals are homozygous for a C→T polymorphism located at nucleotide 677, and the resulting substitution of alanine to valine increases thermolability and reduces activity of MTHFR (6). The latter increases the risk of cardiovascular disease, neural tube defects and several cancers, including colorectal carcinomas and ALL, although evidence to support these purported relationships is controversial (6, 7, 8).

An accumulation of 5,10-CH2-THF resulting from the MTHFR C677T polymorphism may also have an effect on the response to MTX, which suggested that the TT genotype may be associated with an increased toxicity of MTX in leukemia patients (9, 10).

TS is a key-enzyme in de novo DNA synthesis which catalyzes the conversion of deoxyuridine monophosphate (dUMP) to deoxythymidine monophosphate (dTMP), and is another critical target for MTX (11). Inhibition of this enzyme

results in deoxythymidine triphosphate (dTTP) depletion, chromosome breaks and cell death (11). The TS gene is located on chromosome 18p11.32 and has a unique tandem repeat sequence in the enhancer region (TSER) that has been shown to be polymorphic (12), containing either two (2R) or three (3R) 28-bp repeats. In colorectal cancer, the presence of the 3R versus 2R was shown to influence gene expression in vitro and in vivo and was postulated to be associated with treatment outcome (13, 14). Moreover, in childhood ALL, homozygosity for the 3R, was reported to be associated with poorer outcome compared to the presence of at least one 2R allele (15). Recently two additional polymorphisms have been described which seem to have functional consequences: the G>C substitution (G116C) within the second 28-bp repeat of TSER3R alleles (3RG>3RC), will result in a decreased transcriptional activity. Furthermore a 6-bp deletion in the 3’UTR can also decrease transcriptional activity (Table 1).

Fig. 1: Uptake and metabolism of the antifolates MTX (methotrexate) and PMX (pemetrexed) by the RFC and the PCFT. Folic acid can also be taken up by the folate receptor (FR). MTX and PMX can also be effluxed by Multidrug resistance pumps MRP and BCRP. MTX and PMX can be polyglutamylated (PGn) in the cells, which both inhibit dihydrofolate reductase (DHFR), while PMX-PGn can also inhibit TS and glycinamide aspartate transformylase (GARFT), the latter leading to inhibition of purine de novo nucleotide synthesis and of RNA and DNA. TS inhibition will deplete dihydrofolate (FH2), which is normally reduced by DHFR to FH4, which can methylated by SHMT to 5,10-methylene-tetrahydrofolate (CH2-FH4). In another cycle CH2FH4 can be reduced by MTHFR to CH3FH4, and by MS, MTRR converted back to FH4, methylating S-adenosyl-homocysteine (SAH) to S-adenosyl-methionine (SAM). Other abbreviations see Table 1.



DHFR and TS are important antifolate targets. However, before affecting these targets a drug needs to be taken up by the cell. The major transporter for uptake of reduced folates and antifolates such as MTX and PMX, is the reduced folate carrier (RFC) (16). The RFC1 80G>A polymorphism results in a change of arginine-27 to histidine-27 and is associated with an increased risk of ALL (8) which increased 1.5 times in A-allelic carriers and 2.1 times in 80AA homozygotes. Patients carrying the RFC1 80A allele may have lower folate or methotrexate

(MTX) uptake, which might increase ALL risk and decrease MTX efficacy. The RFC1 80G>A allele frequency of 500 blood-bank donors was 38% (17). Two other transporters play a role in uptake of folates and antifolates. The folate receptor (FR) or folate binding protein (FBP) is a high affinity, low capacity transporter for oxidized folates (16), while the recently characterized proton-coupled folate transporter (PCFT) has a high capacity at a low pH of about 5.5, a high expression in lung cancer and preferentially transports PMX (18). This transporter has also a high expression in gut cells, is likely responsible for uptake of nutritional folates, but also MTX when given orally such as in rheumatoid arthritis (19). Recently mutations have been identified which change the pH optimum of the transporter for PMX and which can confer resistance (20).

Patients with the other MTHFR polymorphism the 1298AC variant or the MTRR 66 G-allele showed decreased in vitro MTX sensitivity of pediatric ALL blasts (17).

These polymorphisms alone or together may also affect the efficacy of PMX. Therefore, identification of these polymorphisms may be an important pharmacogenetic determinant to predict response or toxicity to chemotherapy.

However, these effects may be different among different populations since ethnic variations in the frequency of both the C677T MTHFR and the TSER polymorphic tandem repeat sequences have been described earlier (21, 22, 23).

Pharmacodynamic biomarkers of TS inhibition

From the TS inhibitors widely used in the clinic, two main types can be distinguished, based on the two substrates of the enzyme: 1) inhibitors targeting dUMP and 2) inhibitors targeting 5,10-CH2THF. 5FU is the precursor of FdUMP, a ‘suicide’ inhibitor of TS which

forms a stable ternary complex when sufficient 5,10-CH2THF is present. Leucovorin is a precursor of 5,10-CH2THF, and is usually given in combination with 5FU (1). The other group of inhibitors are anti-folates which target the folate substrate, either as a competitive or non-competitive inhibitor. Tomudex (Raltitrexed, RTX) and ALIMTA (Pemetrexed, PMX) are registered antifolates (4, 26). Both drugs enter the cell by means of the RFC while PMX is also a substrate for the PCFT which has a high expression in lung cancer cells and in the gut (18). Upon entry both drugs will be converted by folylpolyglutamate synthetase (FPGS) into multiple polyglutamate forms, usually up to the pentaglutamate form. This increases the affinity to TS and results in the most potent inhibition of TS. The polyglutamate form of PMX is also a potent inhibitor of glycinamide ribonucleotide formyltransferase (GARFT), in contrast to that of RTX. Additionally the PMX polyglutamate also inhibits DHFR.

FPGS is a polymorphic gene that presents many SNPs in the general population. Five non-synonymous coding SNPs, resulting in altered protein sequence, were studied and it was reported that cells expressing Arg424Cys and Ser457Phe variants of FPGS presented a 2-fold

reduction in protein expression compared with wild type. This might have pharmacogenetic implications in patients treated with antifolate therapy. Indeed, it is suggested that patients bearing this polymorphisms may need higher doses of drug to reach a significant level of intracellular polyglutamates than patients who have the wild type genotype (27).

RTX is registered for treatment of colon cancer, in which it has a similar efficacy as the 5FU-leucovorin combination (1). PMX is registered for treatment of NSCLC and mesothelioma. Single agent PMX showed response rates of 20% and approximately 40% in combination with cisplatin in NSCLC (28, 29, 30). Results of a large prospective randomized study comparing PMX with docetaxel in the second line treatment of 571 patients with advanced NSCLC indicated similar response rates (9.1 versus 8.8%) and median OS (7.9 versus 8.5 months) for the two agents but the toxicity profile favoured PMX (31). The combination of PMX/cisplatin is the only effective registered treatment for mesothelioma (32). The response rate for the PMX/cisplatin combination was 41%, while that



of cisplatin alone was 17%, with a median overall survival of 12.1 and 9.3 months, respectively. Other antifolates which are in development include the so-called non-classical antifolates of which AG337 (Nolatrexed) is an example. This compound is lipophilic and does not need a transporter to be taken up by the cell and can not be polyglutamated (33). It will bypass resistance due either an RFC or FPGS deficiency (34). Therefore the drug is an excellent model for pure TS inhibitors.

Pharmacodynamic biomarkers for TS inhibition focus either on the enzyme itself, the metabolites or the effect on substrates or products. The approach is dependent on the inhibitor. Since FdUMP forms a stable ternary complex it can be isolated from cells or tumors and quantified. This enabled investigators to follow the inhibition of TS in tumors of patients given 5FU for at up to 48 hr; leucovorin addition enhanced this inhibition (35). The extent of inhibition was related to the response to subsequent therapy with 5FU. However, this is a very cumbersome approach since it requires post-treatment removal of the tumor, which should be processed immediately. Hence an alternative approach focused on the measurement of plasma deoxyuridine. Inhibition of TS will result in an increase of the substrate

dUMP, which will be degraded to deoxyuridine and subsequently measured in plasma (36). This approach has been used to investigate the efficacy of anti-folate TS inhibitors in order to determine whether a sufficiently high dose or correct schedule was used.

In our studies, two anti-folate TS inhibitors were tested in patients and TS inhibition was followed by the accumulation of deoxyuridine. Single agent PMX induced a moderate increase in deoxyuridine (about 2 fold), however, when PMX was combined with irinotecan, this increase was much higher (Fig. 2A). Apparently irinotecan enhances the PMX induced inhibition of TS, similar to the enhancement of 5FU induced TS inhibition by irinotecan (38). The effect of PMX could also be enhanced by the PKCß inhibitor enzastaurin (39). For the lipophilic antifolate TS inhibitor AG337 we investigated whether two different oral tablet formulations would give a better bioavailability then the immediate release capsule. Accumulation of deoxyuridine by the capsule was rapid, followed by a rapid decline as well. The two formulation induced deoxyuridine more slowly, indicating a slow release; the ER tablet (coated and more resistant) had an even slower release (Fig. 2B). These data show that deoxyuridine accumulation can serve excellently

Fig. 2: Accumulation of deoxyuridine in plasma of cancer patients following treatment with the anti-folate TS inhibitors PMX and Nolatrexed (AG337, Thymitaq).A: Effect of PMX (500 mg/m2) and PMX (500 mg/m2) in combination with irinotecan. Pretreatment levels were normalized to 100%. Values are means of 2-7 patients; SD was less then 40%B: Comparison of three formulations of the lipophilic TS inhibitor AG337: CAP, an immediate release capsule, used in Phase 1-2 studies; (300 mg/m2): TAB, a delayed release tablet (300 mg fixed dose); and ER, Entero-resistant tablet (300 mg fixed dose). Values are means of 9 patients; SD was <25%. The TAB was given at day 1, after a washout ER was given at day 2 (or the reversed), followed by the capsule every 6 hr from day 3-7 and a treatment free period from day 8-21. At the 2nd cycle only the capsule was given, for 5 days, every 3 weeks. Values were normalized to pretreatment levels and the percentage difference with pre-treatment values is shown

A B



as a surrogate marker for TS inhibit ion. Development of AG337 was discontinued after its failure in a randomized study with hepatocellular carcinoma.

An alternative for deoxyuridine accumulation is PET evaluation of 18F-3’-fluorothymidine. This compound is activated by thymidine kinase and being trapped within the tumor; when dTTP is depleted trapping of 18F-FLT will increase (40). Summarized, deoxyuridine accumulation is an excellent biomarker for overall TS inhibition; its most likely application will consist in the prediction of toxic side effects of TS inhibition.

Pharmacogenetic biomarkers of TS inhibitors.Since TS inhibi t ion and TS levels are

associated with the efficacy of 5FU (35), TS has been further evaluated for its potential as prognostic or predictive marker. In a retrospective study it was found that a low level of TS and of dihydropyrimidine dehydrogenase (DPD), correlated with response to a 5FU regimen (41). Therefore a study was initiated using high levels of TS and/or DPD as an exclusion criteria for 5FU treatment. In selected patients (both with a low cut-off level), 5FU was given as a bolus injection midway a 2 hr leucovorin infusion; patients with a high TS and/or DPD would receive the alternative treatment with irinotecan and oxaliplatin. Since the retrospective study observed a response rate of >60%, the observed response rate of 35% was somewhat unexpectedly low. Furthermore, removal of the tumor and subsequent determination of gene expression proved to be impractical (42).

Next to the use of gene expression of TS as a predictive biomarker, it might also be used as a prognostic biomarker. However, these data are inconsistent, due to limitations in studying these biomarkers in a relevant patient population. In addition most of these studies have been performed with immunohistochemistry (IHC). From these studies it seemed apparent that a high TS levels was related with a poor survival, when the evaluation was limited to advanced disease (43, 44). However, in the adjuvant setting TS does not seem to have a prognostic nor predictive value. Actually in these patients TS was related with a high proliferation rate, which seemed to be a more important marker for efficacy of chemotherapy. Hence TS alone does not reflect the complete pharmacogenetic situation and many other factors in combination must be underlying

chemotherapy response.IHC for TS requires a tumor biopsy specimen,

which needs to be stained. Its potential as a predictive parameter is therefore limited, since such an assay (staining) must be validated for each patient. Alternatively the use of polymorphism analysis might not face these problems, since DNA can be isolated from white blood cells. Since TS is also regulated by the double and triple repeat, several studies have evaluated the presence of these repeats in relation to drug bioavailability. Similar to the gene expression, the overall picture of the genetic polymorphisms is not consistent. In our study we did not observe an association between TSER genotype and response to 5-FU (25). Collectively, it seems doubtful that the TSER genotype can be used to predict whether a tumor has a high TS level or not. The regulation of TS expression is influenced by multiple events occurring at both the transcriptional, post-transcriptional and translational level. These events are associated to cell-cycle regulation, proliferation and apoptosis pathways, and are often disrupted in tumors. However, it can be expected that physiological regulation processes are present within normal tissues, so that TS phenotype can be related to the TSER genotype. We previously postulated that 5-FU mediated side effects are predominantly due to its incorporation into RNA, while TS levels might be less important in mediating side effects because of the short half-life of 5-FU. In the commonly used continuous infusions, the concentrations of 5-FU are too low to allow high incorporation of 5-FU into RNA. However, because of the long 5-FU exposure, TS in normal tissues will be inhibited contributing to toxicity (45). Therefore, a TSER 3 genotype in normal cells may encode for a higher tolerability to 5-FU based regimes (24, 25, 35). However, a prospective pharmacogenetic approach in a uniform population of patients is warranted, since not all literature data are consistent (34).

For MTHFR it has been shown that the C677T genotype shows an increased risk for toxicity to the antifolate methotrexate (46). Since MTHFR competes with TS for 5,10-CH2THF, a lower activity of MTHFR, as encoded by the TT genotype, might either enhance the effect of 5FU (by stabilization of the ternary complex) (1) or decrease the effect of pemetrexed (by competition of 5,10-CH2THF with pemetrexed). However, several other papers subsequently



challenged the conclusion and a more diverse picture did arise. (Table 2; Figure 3). In the initial study more responses to fluoropyrimidines were observed in a group of patients with the MTHFR T677T polymorphism compared to patients without this polymorphism (odds ratio 2.86; confidence interval 1.06-7.73) (47). Similar data were observed in subsequent studies, but less pronounced (48, 49, 50). However, a recent study by Derwinger et al (51) and ourselves (Fig. 3), show opposite data, in which a better response was found in patients with the MTHFR C677C genotype. An explanation of this diversity may be the different types of tissues that have been examined or the different treatment protocols for the patients, in which the modulation of the 5,10-CH2THF pools does not takes place because of

folate supplementation. One of the reasons fo r some of these

discrepancies is the use of either germline DNA for studying the SNPs or tumor DNA. Although a general there is a good concordance between germline and somatic DNA (tumor), there may be differences. Therefore pharmacogenetic studies which usually focus on germline DNA, may have a better predictive value for drug safety then tumor response. However, when there is also an association between pharmacokinetics (affected by e.g. SNPs) and response, germline pharmacogenetics is related to response. On the other when specific aberrations are studied in tumor RNA and DNA, this is more likely related to drug efficacy. Since pharmacogenomics usually focuses on tumor DNA, in which somatic aberrations are likely to be found, pharmacogenomics offers great promise for personalized therapy.

Pharmacogenomics of TS inhibitorsBecause our prospective study towards

selection of patients based on TS and DPD only yielded a 35% response rate we wondered why the remaining 65% of the patients did not respond. In order to answer this question we performed an array-CGH on tumor samples from patients treated with a 5FU or PMX regimen. Array-CGH is a powerful technique which is based on the estimation of copy numbers in the DNA. This allows to determine gains and losses in particular regions of the various chromosomes. In a recent study array-CGH was used to determine whether outcome of treatment to a fluoropyrimidine containing regimen could be associated with copy number variations (CNV, i.e. gains-losses in various chromosomal regions) (52). Patients received a combination of Xeloda (Capecitabine) with irinotecan (CAPIRI). Clear differences were observed between the responders and non-responders (Fig. 4). This was apparent in chromosome 18 (higher loss in responders), where TS is located. However, two other regions also showed a considerable change between the two groups. A loss in chromosome 1p36 was also associated with a longer survival (<0.01), as well as a gain in 13q (p<0.03). Interestingly, MTHFR is located on 1p36, but the gains could not be evaluated down to the gene level. Hence, both analysis of the whole genome and of separate regions can be used to predict outcome of therapy of a combination regimen.

Table 2: Association between MTHFR 677TT and 5FU response

Reference N-source CC CT TTCohen (47) 42-WBC 47 67 100Etienne (48) 98-meta 40 21 56Jakobse (49) 88-WBC 33 21 66Marcuello (50) 94-WBC 56 52 42Derwinger (51) 141-blood Good Poor (p 0.003)This study 30-meta 55 10

Values represent the response rate (%) to a 5FU-leucovorin treatment protocol in each polymorphism group. The polymorphisms were determined in the number of patients designated with N in DNA from the following sources: white blood cells (WBC), total blood or in the metastasis of a colon tumor. The normal distribution in Caucasians is CC: 44.2%, CT 45.0% and TT 10.9% (8).

Fig. 3: Effect of the MTHFR polymorphisms on the efficacy of 5FU, given as a hepatic artery infusion for 24 hr, every week (1000 mg/m2). PR, partial response, SD, stable disease, PD, progressive disease.



Conclusions

Antifolate and non-antifolate TS inhibitors are widely used in the treatment of various malignancies and inflammatory diseases. Although aberrations in TS itself play an important role in the efficacy of these drugs, there are pronounced differences between the various diseases. These are partly related to the drugs themselves, since pyrimidine analogs are dependent on additional parameters affecting their metabolism then folate analogs. Activation pathways and transport mechanisms are different as well. However, there are similarities in the role of folate homeostasis affecting the efficacy of these drugs. Additional interfering parameters come together with the use of combinations, which are widely used in each disease type. These combinations can often interfere directly with the TS inhibitor itself.

The use of pharmacogenetic biomarkers will enable to optimize personalized therapy: the

right drug at the right time to the right patients. Selection of a biomarker is dependent on the target; for TS the target has been validated, and confirmed retrospectively and prospectively in randomized studies. Its implementation into the clinic is however hampered by its prognostic role in the nature of the disease, which is different from its predictive role in chemotherapy. Additionally TS plays a different role in adjuvant therapy and in therapy of advanced disease. In combination regimens, the role of TS often changes, which means that validation of TS as a biomarker has to start from scratch for that application. In combination regimens, more parameters will play a role, which can not always be determined from the mechanisms of action from each drug separately. Therefore a pharmacogenomic approach will be helpful. Especially array-CGH will be a robust platform to do such an analysis, since it enables to prospectively evaluate these parameters.

Fig. 4: Gains and losses in tumor DNA from patients treated with a combination of capecitabine (1000 mg/m2, twice daily for 14 days) with irinotecan (250 mg/m2 on day1 every 21 days). Data from 16 responders and 16 non-responders are given (ref. 52). The X-axis represents the chromosome number, each chromosome separated by a line, while the centromer is indicated by a broken line. The Y-axis the frequency of gains (0 to +1), or losses (0 to –1). Reproduced with permission of the journal from (52).



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23. Giovannetti E, Ugrasena DG, Supriyadi E, Vroling L, Azzarello A, De Lange D, Peters GJ, Veerman AJP, Cloos J (2008). Methylenete t rahydrofola te reductase (MTHFR) C677T and thymidylate synthase p romote r (TSER) po lymorph i sms in Indonesian children with and without leukemia. Leuk. Res 32; 19-24.

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