A pharmacogenetic study to investigate the role of dietary carcinogens in the etiology of colorectal cancer

Christoph Sachse1,*, Gillian Smith1,*, Murray J.V. Wilkie1, Jennifer H. Barrett2, Robin Waxman3, Frank Sullivan4, David Forman3, D. Timothy Bishop2 and C.Roland Wolf1,5 the Colorectal Cancer Study Group**

1 Biomedical Research Centre, Ninewells Hospital and Medical School, Dundee DD1 9SY,
2 Cancer Research UK Genetic Epidemiology Laboratory, St James’s University Hospital, Leeds LS9 7TF,
3 Centre for Cancer Research, Arthington House, Cookridge Hospital, Leeds LS16 6QB,
4 Tayside Centre for General Practice, University of Dundee, Dundee DD2 4AD, UK


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Susceptibility to colorectal cancer, one of the most common forms of cancer in the Western world, has been associated with several environmental and dietary risk factors. Dietary exposure to food derived heterocyclic amine carcinogens and polycyclic aromatic hydrocarbons have been proposed as specific risk factors. Many polymorphic Phase I and Phase II drug metabolizing enzymes are responsible for the metabolism and disposition of these compounds and it is therefore possible that inheritance of specific allelic variants of these enzymes may influence colorectal cancer susceptibility. In a multicenter case–control study, 490 colorectal cancer patients and 593 controls (433 matched case–control pairs) were genotyped for common polymorphisms in the cytochrome P450 (CYP1A1, CYP1A2, CYP1B1, CYP2A6, CYP2C9, CYP2C19 and CYP2D6), glutathione S-transferase (GSTM1, GSTP1 and GSTT1), sulfotransferase (SULT1A1 and SULT1A2), N-acetyl transferase 2 (NAT2), NAD(P)H:quinone oxidoreductase (NQO1), methylenetetrahydrofolate reductase (MTHFR), and microsomal epoxide hydrolase (EPHX1) genes. Matched case-control analysis identified alleles associated with higher colorectal cancer risk as carriage of CYP1A1*2C (OR = 2.15, 95% CI 1.36–3.39) and homozygosity for GSTM1*2/*2 (OR = 1.53, 95% CI 1.16–2.02). In contrast, inheritance of the CYP2A6*2 (OR = 0.51, 95% CI 0.28–1.06), CYP2C19*2 (OR = 0.72, 95% CI 0.52–0.98) and the EPHX1His113 alleles were associated with reduced cancer risk. We found no association with colorectal cancer risk with NAT2 genotype or any of the other polymorphic genes associated with the metabolism and disposition of heterocyclic amine carcinogens. This data suggests that heterocyclic amines do not play an important role in the aetiology of colorectal cancer but that exposure to other carcinogens such as polycyclic aromatic hydrocarbons may be important determinants of cancer risk.

Abbreviations: 95% CI, 95% confidence interval; AA, aromatic amine; CYP, cytochrome P450; EPHX1, microsomal epoxide hydrolase; GST, glutathione S-transferase; HA, heterocyclic amine; MTHFR, methylenetetrahydrofolate reductase; NAT2, N-acetyl transferase 2; NQO1, NAD(P)H:quinone oxidoreductase; OR, odds ratio; PAH, polycyclic aromatic hydrocarbon; PCR, polymerase chain reaction; PhIP, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine; RFLP, restriction fragment length polymorphism; SNP, single nucleotide polymorphism; SULT, sulfotransferase.


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Colorectal cancer, second only to lung cancer, is a major cause of cancer death in the western world (1). Comparison of colorectal cancer incidence rates in different countries reveals marked regional differences in disease incidence, suggesting that environmental factors including local carcinogen exposure and diet may be important determinants of cancer risk. Migrants from countries with relatively low colorectal cancer incidence (e.g. Asian countries) to ‘western’ societies rapidly assume the incidence rate of their adopted country (2), supporting the hypothesis that regional dietary or carcinogen exposures are important risk factors.

Specific components of the western diet including meat consumption (particularly red and/or well-done meat) and dietary fat (particularly polyunsaturated fatty acids) have been proposed as risk factors which influence susceptibility to colorectal cancer (35). Data from both in vitro and in vivo studies suggest that exposure to heterocyclic amines (HAs) such as 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), aromatic amines (AAs) including 4-aminobiphenyl (4-ABP), and polycyclic aromatic hydrocarbons (PAHs) such as benzo[a]pyrene significantly increase colorectal cancer risk (68). Dietary HAs are formed during frying and broiling of meat and fish by the pyrolysis of amino acids and proteins (9), whereas PAHs are derived from vegetable oils (10,11). Both AAs and PAHs are also present at significant levels in tobacco smoke (12). AA, HA and PAH compounds are known to be metabolized by a variety of Phase I and Phase II drug metabolizing enzymes, including cytochrome P450s, glutathione S-transferases and N-acetyl transferases, which catalyse the various activation and detoxification pathways illustrated in Figure 1Go.



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Fig. 1. Involvement of various polymorphic drug metabolizing enzymes in the metabolism and activation of AAs, HAs, and PAHs. For simplicity, not all pathways of metabolism are shown. UGTs, UDP glucuronosyltransferases.

 
Glutathione S-transferases GSTM1 and GSTT1 facilitate the inactivation of toxic compounds by forming hydrophilic glutathione conjugates. In contrast, a number of enzymes including CYP1A1, CYP1A2, NAT2, SULT1A1 and SULT1A2 activate HAs and PAHs to mutagenic products (1316). Several additional enzymes including CYP1B1, CYP2C9, CYP2C19 and CYP2D6 (1719) as well as microsomal epoxide hydrolase (EPHX1) and NADPH:quinone oxidoreductase (NQO1) have also been shown to metabolize these compounds using hepatic microsomal preparations in vitro or using recombinant enzyme systems (20,21).

Dietary folate supplements have been shown to be protective against colorectal adenoma formation (22), while low folate diets in combination with high alcohol consumption have been associated with a significantly higher colorectal cancer risk (23). Methylenetetrahydrofolate reductase (MTHFR) catalyses the conversion of 5,10-methylenetetrahydrofolate, required for purine and thymidine synthesis, to 5-methylenetetrahydrofolate, required for the synthesis of methionine. A common polymorphism in MTHFR (677C->T) leading to reduced enzyme activity has previously been proposed to influence colorectal cancer susceptibility (24,25).

Extensive genetic polymorphism in these and other drug metabolizing enzymes results in a diverse population distribution of catalytic activities (26,27). For example, polymorphisms in GSTM1, GSTT1 and CYP2D6 result in ‘null alleles’ leading to a complete loss of enzyme function, while the other polymorphisms (e.g. CYP2C9, GSTP1) result in single amino acid changes with less predictable and often substrate-specific effects on catalytic activity. The inheritance of many DME alleles has now been associated with cancer susceptibility and is the subject of many recent review articles (28).

There are now several studies investigating the influence of genetic polymorphism on colorectal cancer susceptibility. In most cases, these investigations have focussed on only a limited number of candidate genes such as CYP1A1, the GSTs and NAT2 (Figure 1Go). Among previous studies, inheritance of the CYP1A1*2C allele has been associated with increased colon cancer risk [e.g. Kiss et al. (29): OR = 1.57, 95% CI 0.9–2.7], as has the GSTM1 ‘null’ genotype [e.g. Zhong et al. (30): OR = 1.90, 95% CI 1.3–2.8], the GSTT1 ‘null’ genotype [e.g. Deakin et al. (31): OR = 1.88, 95% CI 1.28–2.77], and the NAT2 ‘fast acetylator’ genotype [e.g. Lang et al. (32): OR = 2.48, 95% CI 1.0–6.0, Roberts-Thomson et al. (33): OR = 1.9, 95% CI 1.0–3.3]. Many of these studies were relatively small, however, while a recent large study of 1542 colorectal cancer cases and 1860 controls (34) failed to show a significant effect of GSTM1 deficiency or fast NAT2 acetylation on colorectal cancer susceptibility. The ultimate determinant of ‘genetic susceptibility’ is likely to be complex, possibly arising from synergistic interactions between allelic variants of multiple genes including activating and detoxifying enzymes and the environment. This may explain why many previous studies have reported contradictory findings. These differences could arise from genetic differences in the populations studied, regional dietary differences and local carcinogen exposures. In addition, many previous studies have considered relatively small populations, leading to difficulties in assessing the true statistical significance of the data. There is therefore a need for larger, more comprehensive studies where multiple polymorphisms are studied simultaneously so that a true estimate of risk associated with these polymorphisms can be made within a defined population.

Here we describe a comprehensive case–control genotyping analysis, designed to investigate the influence of specific alleles of a wide range polymorphic carcinogen metabolizing enzymes on colorectal cancer susceptibility.


    Materials and methods
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Patient and control recruitment
A total of 490 patients with colorectal cancer were recruited in the period August 1997–February 2001 at either Ninewells Hospital, Dundee, Perth Royal Infirmary, Leeds General Infirmary, St James’s Hospital, Leeds or York District Hospital. The study was approved by the Tayside Committee on Medical Research Ethics, the York Research Ethics Committee and the Leeds Health Authority/St James’s and Seacroft University Hospitals Local Research Ethics Committee. Written informed consent was obtained from all study participants.

Patients (45–80 years) were invited to participate if they were Caucasian, had incident colorectal cancer (ICD-9 classification 153.0–153.9, 154.0–154.1), and had no history of familial adenomatous polyposis coli (FAP), inflammatory bowel disease, ulcerative colitis, diverticular disease or previous malignancy. Healthy population-based controls (GP controls), with no history of previous cancer, were recruited by age, sex and general practitioner matching of incident cases. Multiple GP controls were recruited for some cases, while no matching control was available for a minority of cases. In total, 490 cases and 593 controls were recruited, with 433 matched case–control pairs. The demographic and descriptive statistics of cases and controls are given in Table IGo.


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Table I. Demographic and descriptive statistics of cases and controls
 
All patients and controls were mentally competent to be interviewed by an experienced research nurse in order to provide dietary and lifestyle information which was recorded in a Food Frequency Questionnaire.

Molecular genetic analyses of polymorphisms
All patients and controls gave a 10 ml venous blood sample, which was stored in EDTA blood containers at –20°C. Genomic DNA was extracted from 200 ml of whole blood, using a QIAamp 96 spin blood kit (Qiagen), according to the Manufacturer’s instructions and stored in 10 mM Tris–HCl, 1 mM EDTA at 4°C.

All study participants were genotyped for the most common and functionally relevant polymorphisms in drug metabolizing enzymes involved in HA and PAH carcinogen metabolism. A compilation of the alleles, primer sequences and reaction conditions for all genotyping methods are summarized in Table IIGo and Table IIIGo.


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Table II. MADGE-gel based genotyping analysis
 

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Table III. Taqman-based genotyping analysis
 
PCR and PCR-RFLP assays (Table IIGo) were adapted from literature methods (3538) and used to identify the following alleles: CYP1A2*1C (–3858G->A), CYP1A2*1D (–2464delT), CYP1A2*1F (–164C->A), CYP1B1*3 (4326C->G), CYP2A6*2 (479T->A), CYP2A6*3 (CYP2A6/CYP2A7 hybrid), GSTT1*2, GSTM1*2, NQO1*2 (Pro187Ser), NQO1*3 (Arg139Trp), SULT1A1*2 (Arg213His), SULT1A2*2 (Asn235Thr), MTHFRAla222Val, EPHX1Tyr113His, EPHX1His139Arg. All PCR-RFLP tests were modified for small scale reactions (10 µl), and were optimized for high-throughput analysis using the MADGE gel system (Madge Biosystems) allowing simultaneous analysis of 96 samples on one microtitre plate formatted polyacrylamide gel.

The presence of additional alleles was detected using novel high-throughput TaqMan allelic discrimination tests: CYP1A1*2 (3801T->C), CYP1A1*2B (2455A->G), CYP2C9*2 (430C->T), CYP2C9*3 (1075A->C), CYP2C19*2 (681G->A), CYP2D6*3 (2549A->del), CYP2D6*4 (1846G->A), GSTP1Ile105Val, GSTP1Ala114Val, and the NAT2 SNPs NAT2481C->T, NAT2590G->A, NAT2803A->G and NAT2857G->A (defining ‘slow’ NAT2 alleles NAT2*5A, NAT2*5B, NAT2*5C, NAT2*6A and NAT2*7B, respectively). CYP2C9*2 and CYP2C19*2 genotyping analyses were performed using pre-developed assay reagents for allelic discrimination of cytochrome P450 (PE Biosystems), according to the manufacturer’s instructions. Primer and probe sequences for all other Taqman genotyping assays are given in Table IIIGo. All TaqMan probes were synthesized by PE Applied Biosystems and oligonucleotide primers by MWG Biotech. Following PCR amplification, end-point fluorescence was read using an Applied Biosystems ABI PRISM 7700 Sequence Detector or ‘Taqman’. Genotypes were assigned using Allelic Discrimination Software (Applied Biosystems SDS Software v1.7a). Appropriate controls representative of each genotype and multiple no template controls were included in each analysis.

Case–control analyses
Each polymorphism was initially tested for Hardy–Weinberg equilibrium in the control population. Genotype frequencies were then compared between all cases and controls using chi-squared tests using 3 x 2 contingency tables. For polymorphisms with a low variant allele frequency, homozygotes for the variant allele were combined with heterozygotes. For certain genes, genotypes were combined on the basis of a known phenotype–genotype relationship – for example, the combination of CYP2D6 alleles CYP2D6*3 and CYP2D6*4 were classified as ‘poor metabolizers’, all combinations with allele CYP2D6*1 were termed ‘extensive metabolizers’. Similarly GSTT1*1/*1 + GSTT*1/*2 were termed ‘active metabolizers’, while inheritance of the GSTT1*2/*2 genotype identified an individual as ‘deficient metabolizer’. Combinations of alleles NAT2*5A, NAT2*5B, NAT2*5C, NAT2*6A and NAT2*7B were classified as ‘slow acetylators’, while all genotypes containing allele NAT2*4 were classified as ‘fast acetylators’. The NQO1 genotype NQO1*1/*1 was classified as an ‘active metabolizer’, genotypes NQO1*1/*2 and NQO1*1/*3 were ‘intermediate metabolizers’ and genotypes NQO1*2/*2, NQO1*3/*3, and NQO1*2/*3 were ‘slow metabolizers’. EPHX1 ‘fast’ genotypes were Y113Y/H139R, Y113Y/R139R and Y113H/R139R; ‘intermediate’ genotypes were Y113Y/H139H, Y113H/H139R and H113H/R139R; and ‘slow’ genotypes were Y113H/H139H, H113H/H139H and H113H/H139R.

For polymorphisms where the preliminary analysis demonstrated an association with colorectal cancer susceptibility (using a liberal cut-off of P = 0.10), a matched analysis was carried out on a subset of 433 matched case–control pairs using conditional logistic regression. Case–control pairs were matched for age, sex, study centre and general practitioner, factors not considered in the preliminary analysis.

Effect sizes are presented as odds ratios, with 95% confidence intervals, treating homozygosity for the most common allele as the baseline risk category.

Several possible synergistic genotype/genotype interactions are suggested by the various HA and PAH metabolic pathways (Figure 1Go) or have been proposed in previous studies. The following combinations of alleles were therefore analysed – GSTM1 ‘deficient’ plus NAT2 ‘slow‘, GSTM1 ‘deficient’ plus GSTT1 ‘deficient‘, GSTM1 ‘deficient’ plus CYP1A1 (CYP1A1*1/*2C + CYP1A1*2C/*2C), and NAT2 ‘slow’ plus CYP1A1 (CYP1A1*1/*2C + CYP1A1*2C/*2C). Based on the matched case–control analysis, a logistic model allowing for interaction was compared with a model assuming that each gene was an independent modifier of risk, using the likelihood ratio test.

All analyses were carried out using the statistical analysis software Stata (Stata Statistical Software: Release 6.0. College Station, TX: Stata Corporation, 1999).


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 Materials and methods
 Results
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Distribution of genotype frequencies in cases and controls
Results of the entire unmatched case–control analysis are presented in Table IVGo. All genotype distributions in the control group were in Hardy–Weinberg equilibrium with the exception of the mEHTyr113His allele and CYP1A1*2 (see Discussion).


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Table IV. Unmatched case–control genotyping analysis (592 controls versus 490 cases)
 
In the unmatched case–control analysis, significant associations were found for carriage of the CYP1A1*2C allele (OR = 1.84, P = 0.001) and the GSTM1*2/*2 ‘null’ genotype (OR = 1.33, P = 0.021). In contrast, variant genotypes of CYP2A6 (OR = 0.57, P = 0.070) and CYP2C19 (OR = 0.68, P = 0.007) were associated with lower colorectal cancer risk. Inheritance of the homozygous mEHTyr113Tyr genotype was also found to be a significant protective factor (OR = 0.68, P = 0.012), although the Tyr113His allele distribution within our control population was not in Hardy–Weinberg equilibrium [observed (expected) frequencies were 270 (227) Tyr/Tyr, 193 (279) Tyr/His, 129 (86) His/His; P < 0.0001)]. mEHTyr113His was therefore excluded from further matched case–control analysis.

There were no statistically significant differences in case and control allele frequencies for the other enzymes we investigated in this study (Table IVGo). In particular, we did not identify any statistically significant associations for any alleles of CYP1A2 or NAT2, enzymes which are thought to be important determinants of the metabolic fate of heterocyclic amine carcinogens.

To confirm our initial observations, matched case–control analysis was performed for each of the genotypes which showed a significant effect in the unmatched analysis. As illustrated in Figure 2Go, inheritance of inactive or low activity alleles of CYP2A6 (OR = 0.54, 95% CI 0.28–1.06) and CYP2C19 (OR = 0.72, 95% CI 0.52–0.98) both had a protective effect while inheritance of the GSTM1 ‘null’ genotype (OR = 1.53, 95% CI 1.16–2.02) and the CYP1A1*2C allele (OR = 2.15, 95% CI 1.36–3.39) identified individuals at increased risk of developing colorectal cancer.



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Fig. 2. Matched case-control genotyping analysis (433 case–control pairs). Only genotypes which showed an association in the unmatched analysis (i.e. with P = 0.1 in Table IVGo) were considered.

 
Interactions between enzymes
Given that some of the genotypes tested were found to significantly influence colorectal cancer risk, we further investigated the joint effect of inheriting various genotype combinations including GSTM1 null/NAT2 slow, GSTM1 null/GSTT1 null and GSTM1 null/CYP1A1*2B (Table VGo). We found no evidence for significant interactions between any of the allele combinations tested.


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Table V. Analysis of potential interaction between susceptibility genotypes
 

    Discussion
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
We have carried out a detailed and comprehensive study on the association of metabolic polymorphisms and colorectal cancer susceptibility. Epidemiological evidence suggests that specific environmental factors including dietary carcinogen exposure may be significant determinants of colorectal cancer risk. In particular, red meat consumption and dietary fat intake have been proposed to modify cancer risk. In confirmation of this hypothesis, in a recent multi-centre collaborative case–control study in three centres in the UK, we have demonstrated that red meat consumption and smoking are significantly associated with increased colorectal cancer risk (Barrett et al., in press).

It is of particular interest that we did not find the major enzymes involved in the activation and disposition of HA carcinogens to be associated with altered colorectal cancer risk. In particular and in contrast to previous studies, we did not find an association with NAT2 genotype. The majority of previous studies reported an increased cancer risk for NAT2 ‘fast acetylators’ [(e.g. Lang et al. (32): OR = 2.48, 95% CI 1.0–6.0; Roberts-Thomson et al. (33): OR = 1.9, 95% CI 1.0–3.3], although not all studies produced significant associations [e.g. Spurr et al. (55): OR = 1.22, 95% CI 0.7–2.3]. In addition, meta-analysis of six studies in Caucasian populations (56) gave an overall odds ratio of 1.31 (95% CI 1.08–1.59) suggesting that NAT2 genotype alone has only a small effect on colorectal cancer risk. In confirmation of this finding, a recent meta-analysis by Houlston and Tomlinson (57) found an odds ratio of 1.03 (95% CI 0.93–1.14) for the NAT2 fast acetylator genotype. It is important to note, however, that many meta-analyses have combined genotyping and phenotyping studies and have included data from different ethnic groups.

Several authors (33,5860) have previously suggested that NAT2 fast acetylation is particularly associated with increased colorectal cancer risk in individuals who consume well-done meat, as a direct consequence of increased exposure to heterocyclic amine carcinogens. We have confirmed the association between red meat consumption and colorectal cancer risk in our UK population, although our data does not identify NAT2 genotype as a significant modifier of increased cancer risk, suggesting that heterocyclic amine carcinogens are not the primary causative agents (Barrett et al., in press). In addition, we did not find any association between ‘doneness’ of meat, taken as a crude estimate of heterocyclic amine exposure and cancer risk.

CYP1A2 is another candidate gene of particular interest because of its role in the activation of heterocyclic amines. One common CYP1A2 polymorphism (CYP1A2*F) has previously been associated with higher enzyme activity in smokers (37) suggesting that genetically determined variation in CYP1A2 expression may influence susceptibility to smoking related cancers. Recently, we reported that multiple CYP1A2 SNPs are in linkage disequilibrium (61), although the functional effect of each of the CYP1A2 alleles on CYP1A2 phenotype is still not clear. In this study, we screened for the most common CYP1A2 alleles, CYP1A2*1F and CYP1A2*1D, (and additionally for CYP1A2*1C in samples with CYP1A2*1D since these sites are in linkage disequilibrium), but failed to detect any influence of CYP1A2 genotype on colorectal cancer risk.

Our analysis did however identify specific alleles of CYP1A1 (CYP1A1*2C), CYP2A6 (CYP2A6*2), CYP2C19 (CYP2C19*2) and GSTM1 (GSTM1*2) as statistically significant determinants of colorectal cancer risk, confirming a role for environmental mutagens in disease etiology (Figure 2Go, Table IVGo). Interestingly, some of these alleles have been implicated in the metabolism of PAH carcinogens (Figure 1Go). For example, CYP1A1 activates PAH substrates to reactive epoxide intermediates, which are then detoxified by GSTM1. The GSTM1*2 allele is a gene deletion resulting in loss of enzyme function in GSTM1*2/*2 homozygotes (39). Our finding that inheritance of the GSTM1*2 allele is significantly associated with increased colorectal cancer risk [OR 1.53 (95% CI 1.16–2.02)] is consistent with our earlier study (30) which reported an odds ratio of 1.90 (95% CI 1.3–2.8).

In contrast to GSTM1, the functional consequences of the CYP1A1*2C allele, arising from an isoleucine to valine substitution in Exon 7 of CYP1A1 are less well defined. Schwarz et al. (40) reported that the protein encoded by the CYP1A1*2C allele had a reduced ability to form phenols and quinones as well as the carcinogenic epoxide metabolites from benzo[a]pyrene. In contrast, Crofts et al. (41) proposed an increased inducibility phenotype for CYP1A1*2C (but not for CYP1A1*2A), which may rationalize our observed increase in cancer risk, particularly in smokers. CYP1A1 has previously been considered as a susceptibility factor for several cancers (28). Although most previous studies focused on lung cancer, the CYP1A1*2C genotype was identified as a significant risk factor for colorectal cancer by Kiss et al. (29) (OR = 1.57, 95% CI 0.9–2.7) but not by Ishibe et al. (42) (OR = 1.08, 95% CI 0.65–1.8). Consistent with our data, Sivaraman et al. (43) reported a higher colorectal cancer risk associated with inheritance of the CYP1A1*2 allele in a Japanese population. There was some evidence of deviation from Hardy–Weinberg equilibrium for the CYP1A1*2C allele in our control population (P = 0.01), with fewer heterozygotes observed than expected (Table IVGo). The reasons for this are not clear, but may be attributable to the close proximity of the nucleotide changes defining the CYP1A1*2C and CYP1A1*4 alleles which may influence PCR efficiency in the minority of individuals inheriting both alleles.

In contrast to CYP1A1, the microsomal epoxide hydrolase (mEH) His113His genotype was associated with a decreased colorectal cancer risk in our unmatched case–control analysis (OR = 0.68, 95% CI 0.49–0.95, P = 0.012), consistent with data from a recent study of 464 colorectal adenomas (44), but in contrast to the results of Harrison et al. (45) who described a higher colorectal cancer risk for the mEHHis113 allele. In our population, the mEHTyr113His control genotype distribution was not in Hardy–Weinberg equilibrium (n = 592; 45.6% Tyr/Tyr, 32.6% Tyr/His, 21.8% His/His; P < 0.0001). This disequilibrium of the mEHTyr113His genotype has also been reported by Cortessis et al. (44) (n = 277; 50.2% Tyr/Tyr, 33.0% Tyr/His, 16.8% His/His; P = 0.0001), but not by Harrison et al. (45) (n = 203; 44.8% Tyr/Tyr, 48.8% Tyr/His, 6.40% His/His). Keicho et al. (46) suggested that this may be due to a silent polymorphism found in Japanese subjects in close proximity to mEHTyr113His (AAG119AAA) in the primer binding region of commonly used genotyping assays, which could result in anomalous genotyping results. Although plausible, this mechanism would not explain the apparent discrepancies between the studies of Harrison et al. (45) and Cortessis et al. (44), who used the same genotyping assay (47) and it remains to be determined whether the AAG119AAA allele exists in Caucasian populations. We did, however, observe a statistically significant difference in mEH allele frequencies between colorectal cancer patients and controls, indicating that inheritance of the mEHTyr113His allele represents a susceptibility factor for colorectal cancer.

The CYP2A6 polymorphism is of particular relevance to cancer epidemiology as the enzyme is known to metabolize a range of carcinogens including nitrosamines and Aflatoxin B1 (48,49). Inheritance of the CYP2A6*3 allele has been proposed to influence desire to smoke (50), and may therefore be a significant determinant of cancer susceptibility in smokers. Both the population frequency and the optimal assay conditions required to uniquely identify the CYP2A6*3 allele have been substantially revised in recent years, following the realization that published genotyping methods significantly over-estimated CYP2A6 allele frequencies. Using the revised genotyping assay of Chen et al. (51), CYP2A6*3 was found in only one of 1083 subjects (allele frequency 0.046% in pooled cases and controls) in the current study. This is consistent with the data of Oscarson et al. (52) where CYP2A6*3 was not found in 100 Spanish Caucasians, and suggests that routine screening for the presence of CYP2A6*3 allele is not justified in Caucasian populations. Consistent with our own findings, CYP2A6*2 was the only variant CYP2A6 allele which was found in the majority of previously published studies. A very recent report, however, suggests that the most frequent variant CYP2A6 allele in Caucasian populations which may be the most significant determinant of interindividual differences in CYP2A6 activity is CYP2A6*9, a SNP in the TATA box motif of the CYP2A6 promoter which has been associated with reduced CYP2A6 activity (53). Studies on the influence of this allele on colorectal cancer susceptibility are in progress.

CYP2C19 has not previously been extensively studied as a determinant of cancer susceptibility and no carcinogenic CYP2C19 substrates have been investigated or identified. There are no studies to date on the influence of CYP2C19 genotype on colorectal cancer susceptibility; although recent data suggests an under-representation of the CYP2C19*2 allele in bladder cancer patients (54). While the bladder cancer data was not statistically significant, it is consistent with our observation that the CYP2C19*2 allele associated with reduced CYP2C19 activity was under-represented in colorectal cancer.

CYP2C9 genotype was not found to be a determinant of colorectal cancer susceptibility in our population. We assayed for the presence of two allelic variants of CYP2C9 – CYP2C9*2 which contains a single arginine to cysteine substitution (Arg144Cys) and CYP2C9*3 in which an isoleucine residue is replaced by a leucine residue (Ile359Leu) (65). Both these alleles have been associated with decreased CYP2C9 activity towards a variety of substrates including warfarin (66). Like CYP2C19, CYP2C9 is not known to metabolize carcinogens or mutagens although murine Cyp2c enzymes have been implicated in PAH metabolism (67). A recent report suggests that there may be an interaction between the CYP2C9 and UGT1A6 polymorphisms both of which metabolize nonsteroidal anti-inflammatory drugs (NSAIDs) like aspirin and which are known to be protective against colon cancer (68).

The MTHFR Ala222Val polymorphism has been proposed to alter folate metabolism and, as a consequence, influence DNA synthesis and repair (24). Consistent with previous reports, we did not find an association between MTHFR genotype and colorectal cancer susceptibility although, interestingly, alcohol consumption has been proposed to have a modifying effect on MTHFR genotype. We are currently correlating MTHFR genotype with alcohol and folate consumption in our study population (Forman et al., manuscript in preparation).

In addition, our data did not indicate that inheritance of allelic variants of GSTT1, CYP1B1, CYP2D6, NQO1 and GSTP1 influenced colorectal cancer susceptibility (Table IVGo). We failed to find any significant association for the GSTT1 ‘null’ genotype (OR = 1.19, 95% CI 0.84–1.69 for GSTT1*2/*2 vs. GSTT1*1/*1 and OR = 1.29, 95% CI 0.94–1.77 for the ‘null’ vs. ‘active’ genotypes). This is comparable to previous reports of GSTT1 allele frequencies in colon cancer (63) (OR = 0.86, 95% CI 0.4–1.8) and colorectal cancer (64) (OR = 1.21, 95% CI 0.63–2.00), although one previous colorectal cancer study described a significantly increased cancer risk associated with the GSTT1 null genotype (31) (OR = 1.88, 95% CI 1.28–2.77). In contrast to our data, the CYP1B1Leu432Val polymorphism was previously associated with an increased risk of colorectal cancer (OR = 1.93, 95% CI 1.15–3.24) in a German population (69). CYP1B1 is known to be expressed in the GI tract and over-expressed in colorectal tumours (70) where one can speculate that it may contribute to local carcinogen activation. While GSTP1 and CYP2D6 genotypes have not been consistently associated with altered colorectal cancer susceptibility, the NQO1C609T allele has been associated with increased colorectal cancer risk (OR = 2.9, 95% CI 1.19–6.97), an association which was more pronounced in individuals with tumours containing K-ras mutations (71) (OR = 6.5, 95% CI 1.39–34.9). We have performed a detailed characterization of mutations in APC, K-ras and p53 in tumours from our cancer patients and are currently correlating genotype with tumour mutation spectra.

There are several additional drug metabolizing enzymes which have been shown to be involved in carcinogen activation in vitro, e.g. CYP2B6, CYP3A4 and CYP3A5 (72,73), for which allelic variants have only recently been reported and detailed information on allele frequencies is not yet available. The CYP3A4*1B allele (an A to G substitution in the CYP3A4 gene promoter) is very rare in Caucasians; in this study, we did not find any CYP3A4*1B alleles in 207 samples randomly chosen from cases and controls (data not shown). Inheritance of the CYP3A4*2 allele has previously been associated with susceptibility to prostate cancer (74) and treatment-associated leukaemia (75), although the sequence change associated with the CYP3A4*2 allele was not associated with altered enzyme activity in in vitro experiments (76). The functional relevance of additional CYP3A4 alleles is not yet clear. Recently, a number of CYP2B6 alleles have been described (77) but which have not yet been studied as modifiers of cancer risk.

To date, more than 25 alleles of NAT1 have been reported (78). Due to limited information about the population frequencies and functional consequences of the various NAT1 alleles, we did not include NAT1 genotyping analysis in the current study.

In addition to the sulfotransferases SULT1A1 and SULT1A2, which showed no significant association with colorectal cancer risk in our population, SULT1A3 has also been implicated in the metabolism of HA carcinogens (16). The extent to which genetic polymorphisms influence SULT1A3 activity is not yet fully understood. Similarly, Malfatti and Felton (79) have suggested a role for the UDP-glucuronosyltransferases UGT1A1, UGT1A4 and UGT1A9 in PhIP glucuronidation. The role of UDP-GT polymorphisms on cancer susceptibility will be an interesting area for further study.

Combined effects and interactions
From the pathways of HA and PAH carcinogen metabolism illustrated in Figure 1Go, one might predict that inheritance of various allele combinations would lead to an increased cancer risk. From our data, assuming no interaction between genotypes, the theoretical maximum combined odds ratio for the GSTM1 ‘deficient’ plus (CYP1A1*1/*2B or *2B/*2B) genotype compared with the baseline GSTM1 ‘active’ plus CYP1A1*1/*1 would be 3.30 [1.53 (CYP1A1) x 2.15 (GSTM1)]. To investigate whether such combined effects occurred, we tested several interactions between the different susceptibility genotypes (Table VGo). Interactions were chosen based on the metabolic pathways of HA and PAH carcinogens and were genotype combinations which had previously been investigated in other epidemiological studies or were suggested by in vitro studies. For example, Vaury et al. (80) described increased CYP1A1 inducibility in GSTM1 deficient compared with GSTM1 active cell lines. In contrast, however, we found no evidence for significant interactions between the various susceptibility genotypes tested in our study population. Recently, a further synergistic interaction of the GSTM1 null allele GSTM1*2/*2 with the GSTM3*A/*B allele (a 3 bp deletion in intron 6) has been proposed (81).

In conclusion, therefore, we have performed a comprehensive study of the influence of inheriting various alleles of HA and PAH carcinogen metabolizing enzymes on susceptibility to colorectal cancer and have shown that inheritance of the cytochrome P450 CYP1A1*2B allele or the glutathione S-transferase GSTM1*2/*2 ‘null’ allele confers an increased risk of disease, while inheritance of the CYP2C19*2, CYP2A6*2 or EPHX1 His113His alleles appears to be protective.

Certain of these data are novel and others are consistent with previous reports. Where our results contradict previous findings, this could indicate differences in environmental or dietary factors between study groups.

The influence of specific dietary and lifestyle factors (e.g. smoking and red meat consumption) on the development of colorectal cancer and the interaction of these factors with susceptibility genotypes has been proposed to be a critical determinant of colorectal cancer susceptibility (33). In order to address these issues, we are currently correlating the genotyping data presented here with individual dietary and environmental carcinogen exposures.


    Notes
 
5 To whom correspondence should be addressed Email: Margaret.Rooney{at}cancer.org.uk Back

** Contributed equally to this paper Back

** The Colorectal Cancer Study Group: Jenny Barrett2, D.Timothy Bishop2, Alan R.Boobis6, David Forman3, R.Colin Garner7, Nigel Gooderham8, Tracy Lightfoot7, Christoph Sachse1, Gillian Smith1, Robin Waxman3 and C.Roland Wolf1. Back

6 Addresses: Department of Clinical Pharmacology, Imperial College School of Medicine, Hammersmith Hospital, Du Cane Road, London W12 0NN, Back

7 Jack Birch Unit for Environmental Carcinogenesis, University of York, YO1 5DD Back

8 Department of Molecular Toxicology, Sir Alexander Fleming and Building, Imperial College of Science, Technology and Medicine, London SW7 2AZ, UK Back


    Acknowledgments
 
All authors wish to acknowledge the magnificent efforts of our team of research nurses in Dundee, Leeds and York who were responsible for all patient and control recruitment. We are indebted to all general practitioners who allowed us to approach their patients in order to recruit our control populations. We acknowledge financial support from the Food Standards Agency (Contracts T01003, TO1004 and T01005).


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received May 23, 2002; revised July 11, 2002; accepted July 12, 2002.