Association of NAD(P)H:quinone oxidoreductase (NQO1) null with numbers of basal cell carcinomas: use of a multivariate model to rank the relative importance of this polymorphism and those at other relevant loci
Annette Clairmont,
Helmut Sies,
Sudarshan Ramachandran1,
John T. Lear2,
Andrew G. Smith2,
Bill Bowers3,
Peter W. Jones4,
Anthony A. Fryer1 and
Richard C. Strange1,5
Institut für Physiologische Chemie 1, Heinrich Heine Universität, Postfach 101007, D-40001 Düsseldorf, Germany,
1 Clinical Biochemistry Research Laboratory, School of Postgraduate Medicine, Keele University, Centre for Cell & Molecular Medicine, North Staffordshire Hospital, Hartshill, Stoke-on-Trent, Staffordshire ST4 7QB,
2 Department of Dermatology, North Staffordshire Hospital, Stoke-on-Trent, Staffordshire,
3 Department of Dermatology, Royal Cornwall Hospitals, Truro, Cornwall and
4 Department of Mathematics, Keele University, Staffordshire, UK
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Abstract
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Glutathione S-transferase GSTM1 B and GSTT1 null, and cytochrome P450 CYP2D6 EM have been associated with cutaneous basal cell carcinoma (BCC) numbers, although their quantitative effects show that predisposition to many BCC is determined by an unknown number of further loci. We speculate that other loci that determine response to oxidative stress, such as NAD(H):quinone oxidoreductase (NQO1) are candidates. Accordingly, we assessed the association between NQO1 null and BCC numbers primarily to rank NQO1 null in a model that included genotypes already associated with BCC numbers. We found that only 14 out of 457 cases (3.1%) were NQO1 null. This frequency did not increase in cases with characteristics linked with BCC numbers including gender, skin type, a truncal lesion or more than one new BCC at any presentation (MPP). However, the mean number of BCC in NQO1*0 homozygotes was greater than in wild-type allele homozygotes and heterozygotes, although the difference was not quite significant (P = 0.06). These data reflect the link between NQO1 null and BCC numbers in the 42 MPP cases rather than the whole case group. We identified an interaction between NQO1 null and GSTT1 null that was associated with more BCC (P = 0.04), although only four cases had this combination. The relative influence of NQO1 null was studied in a multivariate model that included: (i) 241 patients in whom GSTM1 B, GSTT1 null and CYP2D6 EM genotype data were available, and (ii) 101 patients in whom these genotypes, as well as data on GSTM3, CYP1A1 and melanocyte-stimulating hormone receptor (MC1R) genotypes were available. NQO1 null (P = 0.001) and MC1R asp294/asp294 (P = 0.03) were linked with BCC numbers, and the association with CYP2D6 EM approached significance (P = 0.08). In a stepwise regression model only these genotypes were significantly associated with BCC numbers with NQO1 null being the most powerful predictor.
Abbreviations: BCC, cutaneous basal cell carcinoma; MC1R, melanocyte-stimulating hormone receptor; MPP,multiple presentation phenotype; NQO1, quinone oxidoreductase; PM, poor metabolizers; ROS,reactive oxygen species; SPP, single presentation phenotype.
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Introduction
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Cutaneous basal cell carcinomas (BCCs) are the most common cancers in Caucasians. A striking characteristic of this cancer is the considerable phenotypic variation demonstrated by patients (13). Thus, in our series, the number of primary lesions suffered by individual cases varied between 1 and 30 BCC (46). The factors that determine these differences remain unclear, although the occurrence of such continuous variation suggests the importance of genegene and geneenvironment interactions. This view is supported by the finding that BCC numbers are associated with host characteristics including skin type 1, male gender and polymorphism in several genes that encode detoxicating enzymes (4). Thus, the GSTM1 AB and CYP1A1 ile/ile genotypes are associated with reduced risk, and GSTM1 B, GSTT1 null, and cytochrome P450 CYP2D6 EM and CYP1A1 m1m1 with increased risk of many tumours (48). Furthermore, we identified interaction terms, including between GSTM1 null/skin type 1, GSTM3 AA/skin type 1 and CYP2D6 EM/male gender, that were associated with a greater effect on tumour numbers than the individual genotypes (main effects). However, the quantitative effect of these interactions (assessed by the rate ratios), as well as those between the genotypes, show that risk of multiple lesions must be determined by an unknown number of further genes that are either untested candidates or unidentified (48). Indeed, the relative importance of those already identified is unknown.
Selection of candidate genes in studies of factors that determine outcome in cancer is problematical. We have proposed that, as the glutathione S-transferase (GST) loci appear to be critical in cellular response to oxidative stress, other polymorphic genes that utilize the products of reactive oxygen species (ROS) activity are also candidates for outcome in BCC (9). Accordingly, we have assessed the association between polymorphism in the NAD(P)H:quinone oxidoreductase (NQO1) gene and BCC numbers. NQO1 is a flavoprotein that catalyses the reduction of quinones, quinone amines and azo dyes, thereby protecting cells from ROS generated from these compounds by the activity of reducing enzymes such as cytochrome P450 reductase (10). NQO1 is the product of a polymorphic gene on chromosome 16q2.2 that contains a redox-sensitive antioxidant response element (11) and, in human mononuclear cells, is up-regulated by UVB radiation (12). Two alleles have been identified; the less common encodes an inactive protein and is termed null (13,14). Importantly, allelic variants at NQO1 have been associated with susceptibility to lung and renal tumours, suggesting that it is a candidate for cancer susceptibility/outcome (15,16).
We now describe studies to determine whether polymorphism in NQO1 is associated with BCC numbers. In particular, we wished to assess this association in a multivariate model that included other genetic factors that have been linked with the numbers of lesions. Accordingly, we determined, first whether NQO1 null is associated with characteristics found in patients with large numbers of BCC. These include male gender, skin type 1, the presence of a truncal lesion and the multiple presentation phenotype (MPP) (4). MPP cases comprise about 15% of our unselected cohort, and are characterized by the presence of two or more new BCC at the first or a later presentation to a dermatologist (4). MPP cases suffer markedly more lesions (mean 5.4) than the remaining cases who have only one new lesion at any single presentation (SPP). SPP1 cases present only once (mean 1.0 BCC) and SPP2 cases (mean 2.4 BCC) more than once. Furthermore, the association between BCC numbers and allelic variants found in the unselected cases, results from the influence of these genes in the MPP patients and is not found in the SPP cases. Importantly, MPP cases do not appear to have had more UV exposure, suggesting that they inherit an inadequate response to even normal levels of UV (4). Secondly, we determined whether NQO1 null was associated with BCC numbers. The influence of NQO1 null was considered alone and in interaction terms with genotypes previously shown to be associated with BCC numbers. These were: GSTM1 B, GSTT1 null, GSTM3 AA, CYP2D6 EM, CYP1A1 ile/val and val/val, CYP1A1 m1m1 and melanocyte-stimulating hormone receptor (MC1R) genotypes (48). MC1R was included as certain allelic variants, including asp294his, have been associated with red hair (1720), a risk factor for BCC. Indeed, we unexpectedly found in 311 cases that homozygotes for the wild-type asp294 allele suffer more BCC than homo- and heterozygotes for the his294 allele (20). Our main aim in this study was to determine the relative importance (on the basis of P value and rate ratio) of the association of NQO1 null and BCC numbers, compared with that of the genotypes previously identified. Since gender and age at first tumour presentation are associated with BCC numbers, all the analyses were corrected for these factors and normalized for follow-up time (4).
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Materials and methods
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Patients
Four-hundred-and-fifty-seven unrelated Northern European Caucasians with one or more histologically proven BCC were recruited from Dermatology out-patient clinics in the North Staffordshire Hospital and Royal Cornwall Hospitals, with Ethics Committee approval and informed consent. These cases were recruited between 1991 and 1995, and have been described in detail elsewhere (4,21). The case group represents about 40% of the patients seen. Thus, although we attempted to recruit all BCC patients, many were inadvertently missed in busy clinics. The characteristics (age at diagnosis, gender, skin type) of the cases were typical for BCC patients seen in English hospital clinics. None of those approached refused to participate. We excluded recurrences from the total number of primary BCC, and patients with basal cell naevus syndrome, xeroderma pigmentosum or BCC combined with another malignancy (cutaneous or internal). We recruited patients at their first presentation, as well as those returning with further tumours or for routine follow-up, and obtained their retrospective clinical history. All cases were examined by a dermatologist to obtain information on the times of appearance of BCC and their numbers at each presentation, as well as their smoking history (4). As arsenic is associated with truncal BCC, we questioned patients regarding ingestion of arsenic-containing medicines or drinking water from potentially contaminated wells. No patients subject to such exposure were identified. In a few patients, radiotherapy was used to treat primary BCC. In no cases were further lesions identified at the same site. Patients were classified as MPP if they had more than one BCC at first or a later presentation (these being new tumours not present at an earlier clinic visit; ref. 4). This group included patients who had noted or whose general practitioner had noted more than one lesion, as well as patients who were unaware of additional lesions. These were identified by the clinician at the same clinic visit.
Identification of NQO1, GST, CYP2D6 and MC1R alleles
DNA was extracted (recovery about 80%), using a standard phenolchloroform method, from leucocyte DNA obtained from 5 ml peripheral blood collected into EDTA. PCR conditions and the primers used in the NQO1 genotyping assay, carried out in the Heinrich Heine Universität laboratories during 1996, are described (15). Briefly, the amplified DNA fragment was digested with HinfI and electrophoresed on 2% agarose gel. DNA from cell lines HepG2 and RTMMC112 was used as standards for the major and null alleles. All other genotyping was carried out in the Keele University laboratories between 1993 and 1998. GSTM1 genotypes were identified using a PCR assay that identifies GSTM1*0 homozygotes and GSTM1*A/GSTM1*B heterozygotes, and the GSTM1 A and GSTM1 B phenotypes (4). It does not distinguish GSTM1*0/GSTM1*A and GSTM1*A/GSTM1*A, or the equivalent GSTM1 B genotypes. GSTM3 genotypes were identified using primers to exon 6/7 of GSTM3 (8). GSTM3*B was differentiated from GSTM3*A by digestion with MnlI. GSTT1 null and expressing subjects were also identified using PCR (4). Two mutant CYP2D6 alleles, CYP2D6*4 (G
A transition at intron 3/exon 4) and CYP2D6*3 (base pair deletion in exon 5) were identified in separate PCR assays. Homozygotes or compound heterozygotes for these alleles were classed as poor metabolizers (PM). Heterozygotes for either CYP2D6*4 or CYP2D6*3, and wild-type CYP2D6*1 were classified as HET, while homozygotes for CYP2D6*1 are EM. Some subjects classed as wild-type homozygotes could be heterozygotes for uncommon variant alleles, such as CYP2D6*5 (gene deletion; ref. 4). Similarly, heterozygotes for CYP2D6*4 or CYP2D6*3, and CYP2D6*5 were classed as PM. Two mutant CYP1A1 alleles (exon 7 Ile-Val and 3' flanking region MspI mutations) were detected using PCR (6). PCR-restriction fragment length polymorphism-based assays were used to identify the val92met and asp294his MC1R alleles (20,22).
Statistical analysis
Stata (release 5, Stata Corporation, College Station, TX) was used for statistical analyses. In the first set of analyses, NQO1 genotype frequencies in the total group of 457 patients were compared in cases with characteristics linked with BCC numbers. These included male gender, MPP, SPP and skin type 1. Comparisons were made using
2 tests. In the second set of analyses, we assessed the association of NQO1 null with BCC numbers (normalized for follow-up time, and corrected for age and gender). Two approaches were used to analyse count data (i.e. BCC numbers), Poisson regression and negative binomial regression. The choice of which approach to use for each data set was determined by a goodness-of-fit test. The Poisson regression model was used when the variance of a count variable was approximately equal to its mean. Negative binomial regression is commonly used to model count data, normalized for time, in biological systems (23). This approach was used when the mean and variance of the count data were not approximately equal suggesting that a Poisson regression model was inappropriate (23). Each count has a mean that is a linear function of its covariates (gender, genotypes). A rate ratio (the multiplicative effect of a change of a covariate by 1) was calculated. This allows comparison of the relative importance of individual covariates. The rate ratio approximates to the mean number of tumours in one group (e.g. males)/mean number of tumours in the complementary group (e.g. females). The value of the rate ratio will alter following correction for confounding factors, such as age and gender, as well as after normalization for follow-up time. P
0.05 was considered to be statistically significant. A complete data set for NQO1 null, GSTM1 B, GSTT1 null and CYP2D6 EM was available in 241 patients allowing interactions between NQO1 null and these risk genotypes to be assessed. The relative importance of NQO1 null in the presence of these genotypes as a predictor of BCC numbers in these 241 patients was determined using a negative binomial regression model. The best predictors were confirmed using a Poisson stepwise routine (cut-off P = 0.05). While, to our knowledge, a stepwise negative binomial routine is not available, we would not expect the variables chosen using the Poisson routine to differ substantially from those from a negative binomial distribution. To confirm this, we refitted the chosen variables using a negative binomial model (shown in analysis i of Table II
). A complete data set on NQO1, GSTM1, GSTT1, CYP2D6, MC1R, GSTM3 and CYP1A1 genotypes was available in 101 patients. Accordingly, interactions between NQO1 null and all these genotypes were assessed in these patients. The relative importance of NQO1 null in the presence of all the risk genotypes at these six loci as a predictor of BCC numbers in these 101 patients, was determined using a Poisson regression model. The missing genotype data could not be obtained as DNA samples from these patients were either exhausted or occasionally refractory to amplification. The missing samples were largely those obtained between 1993 and 1995, and were, therefore, lost at random and did not constitute a subgroup.
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Results
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Characteristics of the BCC cases
The 457 cases comprised 42 MPP patients and 26 patients with at least one truncal BCC. A further 27 patients developed more than one BCC during the study period, but demonstrated only one new lesion at each SPP2. The remaining cases demonstrated only one BCC during the study period (SPP1). The numbers of homo- and heterozygotes for the wild-type and null NQO1 alleles are shown in Table I
. Only 3.1% of the cases were homozygous for the null allele. The frequencies of the wild-type and null alleles were 0.827 and 0.173, respectively. Comparison of observed and expected genotype frequencies showed that HardyWeinberg equilibrium was achieved. Table I
also shows mean numbers of BCC in cases with different NQO1 genotypes. Data on tumour numbers is uncorrected for follow-up time and is, therefore, descriptive. However, as expected, MPP cases had markedly more tumours than other subgroups (4). The mean number of BCC in the cases with a truncal lesion was also greater than that for the total case group. NQO1 genotype frequencies were similar in males and females, patients with skin type 1 compared with those with types 24, and in the MPP cases and SPP patients (including the 27 SPP2 cases; P = 0.57). Thus, only two MPP patients and none of the 26 patients with a truncal lesion were null allele homozygotes.
Association of NQO1 genotypes with BCC numbers
We used negative binomial regression analysis to study the association between NQO1 genotypes and BCC numbers with the latter parameter as outcome after correction for age at initial presentation and gender, and normalizing for follow-up time. The mean number of BCC in wild-type/null allele heterozygotes and wild-type allele homozygotes was not different (Table I
). However, the mean number of BCC in null allele homozygotes was greater than in the wild-type homozygotes and heterozygotes combined, although the difference did not quite achieve significance (P = 0.06). Importantly, while the association between NQO1 null and BCC numbers in the SPP cases was not significant (P = 0.88, rate ratio 0.94, 95% CI 0.42, 2.11), the association in the 42 MPP cases again approached significance (P = 0.06, rate ratio 2.41, 95% CI 0.97, 5.97).
Combinations of NQO1 null and other risk genotypes
Since these data suggested an association between NQO1 null and increased BCC numbers, we determined in 241 patients whether combinations of NQO1 null, and smoking (ever or never cigarette smokers), GSTT1 null (frequency in these cases 18.0%) or CYP2D6 EM (frequency in these cases 64.2%) were associated with increased BCC numbers. None of the patients with NQO1 null also had skin type 1 (frequency in these cases 15.8%) or GSTM1 B (frequency in these cases 13.3%). We used negative binomial regression analysis with BCC numbers as the dependent variable, and the interaction term (NQO1 null and smoking, GSTT1 null or CYP2D6 EM) as the independent variable in the presence of the main effects, and correction for gender, age at diagnosis and normalized for follow-up. Cases with both NQO1 null and GSTT1 null had more BCC (P = 0.04, rate ratio 4.9, 95% CI 1.1, 22.0), although only four cases had both these genotypes. Interactions between NQO1 null, and smoking or CYP2D6 EM were not associated with increased BCC numbers. In the 101 cases in whom a complete data set was also available on GSTM3 AA, CYP1A1 m1m1, CYP1A1 ile/val and val/val, MC1R asp294/asp294, MC1R val92/met92 and met92met (17,21), no interaction terms that were significantly associated with BCC numbers were identified. As expected, the frequencies of the risk genotypes in the cases (Table II
) were not significantly different to those previously reported in control individuals (6,8,20,21).
Model with best predictors for BCC numbers
We next determined the relative influence of NQO1 null in a multivariate model predicting BCC numbers (normalized for follow-up time) that included the characteristics and genotypes. In the first analysis in 241 patients, we included NQO1 null together with male gender, age at diagnosis, CYP2D6 EM, GSTM1 B and GSTT1 null. In the presence of these characteristics and genotypes, NQO1 null was the only genotype to achieve significance (P = 0.023), although the association with CYP2D6 EM was almost significant (P = 0.066; Table II
). We also used a stepwise predictive Poisson regression model, refitted using negative binomial regression (P = 0.05 as cut-off). Only NQO1 null, CYP2D6 EM and age at diagnosis were significantly associated with BCC numbers. In a second analysis in 101 cases, we included in the multivariate model the following genotypes that have previously been associated with increased numbers of BCC: CYP2D6 EM, GSTM1 B, GSTT1 null, GSTM3 AA, CYP1A1 m1m1, CYP1A1 ile/val and val/val, MC1R asp294/asp294 and MC1R val92/met92 and met92/met92 genotypes. We again found that NQO1 null was the best predictor of BCC numbers on the basis of P value and rate ratio. CYP2D6 EM and MC1R asp294/asp294 were also significantly associated with increased numbers of lesions (Table II
).
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Discussion
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While UV is a critical causative factor in the pathogenesis of BCC (1,2), recent studies suggest that the inter-individual differences in clinical phenotype that characterize this disease are not just the result of variations in exposure, but are also mediated by allelic variation at certain loci (4,5,21). Such genes include loci that encode enzymes that detoxify ROS and their products, suggesting that NQO1 is also a candidate. Accordingly, we determined whether NQO1 null is associated with either of the two high-risk phenotypes identified so far: MPP and the presence of a truncal lesion (4). We then determined whether NQO1 null alone, or in combination with other genes, was associated with BCC numbers. Analysis using a stepwise routine showed that in the presence of genotypes at six other loci, NQO1 null was the best predictor of BCC numbers. Since a complete data set on six genes was available in only 101 cases, the results, while consistent in the different analyses described, must be viewed as preliminary.
The frequency of NQO1 null in our cases was similar to that previously reported in Northern European Caucasian controls (15). As shown in Table I
, we also found that the frequency of NQO1 null was not increased in high risk subgroups, such as patients with truncal tumours or the MPP. We previously reported that patients with these phenotypes suffer increased numbers of lesions compared with other cases, although the mechanism(s) is unclear (4). In the context of the MPP, we believe this subgroup largely comprises individuals who demonstrate rapid formation of tumours. This characteristic appears to be relatively common in BCC patients (24), although the factors that define MPP patients and the risk of numerous tumours are largely unknown. Importantly, patients with this phenotype do not appear to have suffered excess exposure to UV (4), although they do include an increased proportion of cases with skin type 1 and CYP2D6 EM. As shown in Table I
they suffer markedly more lesions than other BCC patients.
We also examined the data for an association between NQO1 null and BCC numbers. Unfortunately, this genotype is found in only a minority of BCC patients and, even though descriptive data (Table I
) showed NQO1*0 homozygotes suffered more BCC than those with the other NQO1 genotypes, the association only approached significance (P = 0.06). Previous studies showed that associations between GSTM1 B, GSTT1 null, and CYP2D6 EM and BCC numbers reflect the influence of these genes only in the MPP cases. The data obtained also indicate that the influence of NQO1 null was exerted in the MPP cases, rather than all cases. Thus, the P value approached significance, even though only 42 cases were available. Therefore, the data support the view that this subgroup comprises patients who inherit a predisposition to larger numbers of BCC than other patients (4). Clearly, in the context of NQO1, a much larger case group would be needed to confirm these findings and, in particular, study genegene interactions.
Studies showing associations between genotypes and cancer susceptibility/outcome are often based on the effects of individual genes. Such studies consider the main, rather than interactive effect of a gene, even though the main effect could be undetectable, while an interactive or epistatic effect is considerable (25). Thus, recent studies in the mouse show that lung cancer susceptibility genes are frequently involved in one or more pairwise, interlocus interactions (26). The importance of epistatic effects in determining BCC numbers is shown by the finding that interactive terms between GSTM1 and CYP2D6 genotypes, and male gender or skin type 1 are associated with tumour numbers (4,6). In the context of NQO1, only the interaction term with GSTT1 null was associated with BCC numbers, although only four cases had this combination of genotypes. Importantly, no cases demonstrated the combination of NQO1 null and GSTM1 B, even though this interaction would be predicted to confer high-risk of many BCC. We identified an interaction between NQO1 null and GSTM1 null, which, while significantly associated with BCC numbers, was determined by the strength of the NQO1 null effect. This result might be expected as it is GSTM1 B, rather than GSTM1 null, that is associated with BCC numbers (4). We next used negative binomial regression analysis to determine which factors are linked with BCC numbers in the presence of other characteristics. In the first analysis in 241 cases, we found that only NQO1 null and age at diagnosis were significant, although the association with CYP2D6 EM approached significance. This analysis was refined using a stepwise approach; only NQO1 null, age and CYP2D6 EM were significant. In a second analysis, we used a Poisson regression model to study 101 cases in whom data were also available on MC1R, CYP1A1 and GSTM3 genotypes. We found that NQO1 null remained the best predictor of tumour numbers with both CYP2D6 EM and MC1R asp294/asp294 also significantly associated with BCC numbers. The complete list of factors included in both these models is shown in Table II
.
These data demonstrate some common problems in molecular epidemiology studies. Thus, the frequency of interesting alleles, such as NQO1*0, is often low. Even in our relatively large case group, we identified only 14 homozygotes for this allele. Importantly, while the association between NQO1 null and BCC numbers approached significance, this genotype was the most powerful predictor of BCC numbers in a model that included other risk genotypes. The influence of this gene, like that of others studied so far, appears to be predominantly exerted in the MPP cases indicating the need to study patient subgroups. We believe this is the first study in which genotypes at such a number of genes encoding proteins involved in a wide range of biochemical functions have been ranked to determine which has the strongest influence on a marker of outcome. This analysis, performed initially in 241 cases, showed NQO1 null to be the best predictor of BCC numbers in the presence of GSTM1, GSTT1 and CYP2D6 genotypes. This result was confirmed in 101 of these cases in whom data were also available on MC1R, CYP1A1 and GSTM3 genotypes. Clearly, these data must be interpreted with caution as the number of cases, particularly in the second analysis, was small given the frequencies of some of the genotypes studied. Nonetheless, they demonstrate an approach that may be useful in assessing the influence of allelic variants.
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Acknowledgments
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We dedicate this paper to Professor Lars Ernster for his support over many years. This work was supported by the Cancer Research Campaign (project grant SP2402/0101), DFG, Sonderforschungsbereich 503, Project B1 and NFCR Bethesda, MD, USA.
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Notes
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5 To whom correspondence should be addressed Email: paa00{at}keele.ac.uk 
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References
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-
Karagas,M.R. and Greenberg,E.R. (1995) Unresolved issues in the epidemiology of basal cell and squamous cell skin cancer. In Mukhtar,H. (ed.) Skin Cancer: Mechanisms and Human Relevance. CRC Press, Boca Raton, FL, pp. 7986.
-
Kricker,A., Armstrong,B.K., English,D.R. and Heenan,P.J. (1995) A doseresponse curve for sun exposure and basal cell carcinoma. Int. J. Cancer, 60, 482488.[ISI][Medline]
-
Lear,J.T., Tan,B.B., Smith,A.G., Bowers,W., Jones,P.W., Heagerty,A.H., Strange,R.C. and Fryer,A.A. (1997) Risk factors for basal cell carcinoma in the UK: case-control study in 806 patients. J. Royal Soc. Med., 90, 371374.[Abstract]
-
Ramachandran,S., Lear,J.T., Ramsay,H., Smith,A.G., Bowers,B., Hutchinson,P.E., Jones,P.W., Fryer,A.A. and Strange,R.C. (1999) Presentation with multiple cutaneous basal cell carcinomas: association of glutathione S-transferase and cytochrome P450 genotypes with clinical phenotype. Cancer Epidemiol. Biomarkers Prevent., 8, 6167.[Abstract/Free Full Text]
-
Heagerty,A.H.M., Fitzgerald,D., Smith,A., Bowers,B., Jones,P., Fryer,A., Zhao,L., Alldersea,J. and Strange,R.C. (1994) Glutathione S-transferase GSTM1 phenotypes and protection against cutaneous malignancy. Lancet, 343, 266268.[ISI][Medline]
-
Lear,J.T., Heagerty,A.H.M., Smith,A. et al. (1996) Multiple cutaneous basal cell carcinomas: glutathione S-transferase (GSTM1, GSTT1) and cytochrome P450 (CYP2D6, CYP1A1) polymorphisms influence tumour numbers and accrual. Carcinogenesis, 12, 18911896.
-
Lear,J.T., Smith,A.G., Heagerty,A.H.M., Bowers,B., Jones,P.W., Gilford,J., Alldersea,J., Strange,R.C. and Fryer,A.A. (1997) Truncal site and detoxifying enzyme polymorphisms significantly reduce time to presentation of further primary cutaneous basal cell carcinoma. Carcinogenesis, 18, 14991503.[Abstract]
-
Yengi,L., Inskip,A., Gilford,J. et al. (1996) Polymorphism at the glutathione S-transferase locus GSTM3: interaction with cytochrome P450 and glutathione S-transferase genotypes as risk factors for multiple basal cell carcinoma. Cancer Res., 56, 19741977.[Abstract]
-
Strange,R.C. and Fryer,A.A. (1999) The glutathione S-transferases: influence of polymorphism on susceptibility to cancer. In Boffetta,P., Caporaso,N., Cuzick,J., Lang,M. and Vineis,P. (eds) Metabolic Polymorphisms and Cancer. IARC Scientific Publications, Lyon, France (in press).
-
Xie,T., Belinsky,M., Xu,Y. and Jaiswal,A.K. (1995) ARE- and TRE-mediated regulation of gene expression. Response to xenobiotics and antioxidants. J. Biol. Chem., 270, 68946900.[Abstract/Free Full Text]
-
Waleh,N.S., Calaoagan,J., Murphy,B.J., Knapp,A.M., Sutherland,R.M. and Laderoute,K.K. (1998) The redox-sensitive human antioxidant responsive element induces gene expression under low oxygen conditions. Carcinogenesis, 19, 13331337.[Abstract]
-
Alvarez,S. and Boveris,A. (1997) Antioxidant adaptive response in human blood mononuclear cells exposed to UVB. J. Photochem. Photobiol. B Biol., 38, 152157.[ISI][Medline]
-
Eickelmann,P., Schulz,W.A., Rohde,D., Schmitz-Dräger,B. and Sies,H. (1994) Loss of heterozygosity at the NAD(P)H: NQO1 locus associated with increased resistance against mitomycin C in a human bladder carcinoma cell line. Biol. Chem. Hoppe-Seyler, 375, 439445.[ISI][Medline]
-
Rosvold,E.A., McGlynn,K.A., Lustbader,E.D. and Buetow,K.H. (1995) Identification of an NAD(P)H:quinone oxidoreductase polymorphism and its association with lung cancer and smoking. Pharmacogenetics, 5, 199206.[ISI][Medline]
-
Schulz,W.A., Krummeck,A., Rosinger,I., Eickelmann,P., Neuhaus,C., Ebert,T., Schmitz-Drager,B.J. and Sies,H. (1997) Increased frequency of a null allele for NAD(P)H:quinone oxidoreductase in patients with urological malignancies. Pharmacogenetics, 7, 235239.[ISI][Medline]
-
Weincke,J.K., Spitz,M., McMillan,A. and Kelsey,K.T. (1997) Lung cancer in Mexican-Americans and African-Americans is associated with the wild-type genotype of the NAD(P)H: quinone oxidoreductase polymorphism. Cancer Epidemiol. Biomarkers Prevent., 6, 8792.[Abstract]
-
Valverde,P., Healy,E., Jackson,I., Rees,J.L. and Thody,A.J. (1995) Variants of the melanocyte-stimulating hormone receptor gene are associated with red hair and fair skin in humans. Nature Genet., 11, 328330.[ISI][Medline]
-
Box,N.F., Wyeth,J.R., O'Gorman,L.E., Martin,N.G. and Sturm,R.A. (1997) Characterization of melanocyte stimulating hormone receptor variant alleles in twins with red hair. Hum. Mol. Genet., 6, 18911897.[Abstract/Free Full Text]
-
Sturm,R.A., Box,N.F. and Ramsay,M. (1998) Human pigmentation genetics: the difference is only skin deep. Bioessays, 20, 111.[ISI][Medline]
-
Ichii Jones,F., Ramachandran,S., Lear,J.T., Smith,A., Bowers,B., Ollier,W,E.R., Jones,P.W., Fryer,A.A. and Strange,R.C. (1999) The melanocyte stimulating hormone receptor polymorphism: association of the V92M and A294H alleles with basal cell carcinoma. Clin. Chim. Acta (in press).
-
Lear,J.T., Smith,A.G., Bowers,B., Heagerty,A.H.M., Jones,P.W., Gilford,J., Alldersea,J., Strange,R.C. and Fryer,A.A. (1997) Truncal tumour site is associated with high risk of multiple basal cell carcinoma and is influenced by glutathione S-transferase, GSTT1 and cytochrome P450, CYP1A1 genotypes and their interaction. J. Invest. Dermat., 108, 519522.[Abstract]
-
Ichii-Jones,F., Lear,J.T., Heagerty,A.H.M. et al. (1998) Susceptibility to malignant melanoma: influence of skin type and polymorphism in the melanocyte stimulating hormone receptor gene. J. Invest. Dermat., 111, 218221.[Abstract]
-
Drinkwater,N.R. and Klotz,J.H. (1981) Statistical methods for the analysis of tumor multiplicity data. Cancer Res., 41, 113119.[Abstract]
-
Hoy,E.E. (1996) Nonmelanoma skin carcinoma in Albuquerque, New Mexico. Cancer, 77, 24892495.[ISI][Medline]
-
Frankel,W.N. and Schork,N.J. (1996) Who's afraid of epistasis? Nature Genet., 14, 371373.[ISI][Medline]
-
Fijnemann,R.J.A., Jansen,R.C., van der Valk,M.A. and Demant,P. (1998) High frequency of interactions between lung cancer susceptibility genes in the mouse: mapping of Sluc5 to Sluc14. Cancer Res., 58, 47944798.[Abstract]
Received January 6, 1999;
revised March 8, 1999;
accepted March 11, 1999.