Polymorphisms in glutathione S-transferases and non-melanoma skin cancer risk in Australian renal transplant recipients

Anthony A. Fryer1,6, Helen M. Ramsay2, Tracy J. Lovatt1, Peter W. Jones3, Carmel M. Hawley4, David L. Nicol4, Richard C. Strange1 and Paul N. Harden5

1 Human Genomics Research Group, Institute for Science and Technology in Medicine, Keele University School of Medicine, University Hospital of North Staffordshire, Stoke-on-Trent, Staffordshire, UK, 2 Department of Dermatology, University Hospital of North Staffordshire, Stoke-on-Trent, Staffordshire, UK, 3 Department of Mathematics, Keele University, Keele, Staffordshire, UK, 4 Renal Transplant Unit, Princess Alexandra Hospital, Brisbane, Queensland, Australia and 5 Department of Renal Medicine, University Hospital of North Staffordshire, Stoke-on-Trent, Staffordshire, UK

6 To whom correspondence should be addressed Email: anthony.fryer{at}uhns.nhs.uk


    Abstract
 Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 
Caucasian renal transplant recipients from Queensland, Australia have the highest non-melanoma skin cancer (NMSC) risk worldwide. Although ultraviolet light (UVR) exposure is critical, genetic factors also appear important. We and others have shown that polymorphism in the glutathione S-transferases (GST) is associated with NMSC in UK recipients. However, the effect of high UVR exposure and differences in immunosuppressive regimen on these associations is unknown. In this study, we examined allelism in GSTM1, GSTM3, GSTT1 and GSTP1 in 361 Queensland renal transplant recipients. Data on squamous (SCC) and basal cell carcinoma (BCC), UVR/tobacco exposure and genotype were obtained. Associations with both NMSC risk and numbers were examined using logistic and negative binomial regression, respectively. In the total group, GSTM1 AB [P = 0.049, rate ratio (RR) = 0.23] and GSTM3 AA (P = 0.015, RR = 0.50) were associated with fewer SCC. Recipients were then stratified by prednisolone dose (≤7 versus >7 mg/day). In the low-dose group, GSTT1 null (P = 0.006, RR = 0.20) and GSTP1 Val/Val (P = 0.021, RR = 0.20) were associated with SCC numbers. In contrast, in the high-dose group, GSTM1 AB (P = 0.009, RR = 0.05), GSTM3 AB (P = 0.042, RR = 2.29) and BB (P = 0.014, RR = 5.31) and GSTP1 Val/Val (P = 0.036, RR = 2.98) were associated with SCC numbers. GSTM1 AB (P = 0.016) and GSTP1 Val/Val (P = 0.046) were also associated with fewer BCC in this group. GSTP1 associations were strongest in recipients with lower UVR/tobacco exposure. The data confirm our UK findings, suggesting that protection against UVR-induced oxidative stress is important in NMSC development in recipients, but that this effect depends on the immunosuppressant regimen.

Abbreviations: BCC, basal cell carcinoma; GST, glutathione S-transferase; HR, hazard ratio; NMSC, non-melanoma skin cancer; OR, odds ratio; RR, rate ratio; SCC, squamous cell carcinoma; UVR, ultraviolet radiation


    Introduction
 Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 
The human cytosolic glutathione S-transferase (GST) supergene family currently comprises eight families of genes (mu, pi, theta, alpha, sigma, kappa, zeta and omega) encoding enzymes involved in the detoxification of a variety of potentially mutagenic compounds, including ultraviolet radiation (UVR)-induced oxidative stress (1). Although polymorphism in many of these genes has been identified, enzymes of the mu (GSTM1, GSTM3), theta (GSTT1) and pi (GSTP1) families have been studied in most detail. Homozygosity for null alleles in GSTM1 and GSTT1 results in gene deletion and production of no enzyme. Similarly, some alleles (e.g. in GSTM3 and GSTP1) encode low activity enzymes. Individuals homozygous for these alleles may therefore be at a greater risk of malignancy. The association between polymorphisms in GST have already been examined extensively with respect to cancer susceptibility and outcome in a range of cancers (1,2). In particular, we have shown previously associations between these genes and risk of sporadic non-melanoma skin cancer (NMSC) (35).

NMSC is the most common malignancy following renal transplantation, affecting 26% of UK recipients and 72% of Australian recipients after 10 years (6,7). Although mortality associated with NMSC remains relatively low, significant morbidity may result from the frequent surgical treatment needed in the management of the multiple lesions found in some of the recipients. Indeed, in our series of Australian transplant patients, >20% of recipients had >10 NMSC, and 6.1% had over 50 tumours. It is recognized that early diagnosis of NMSC reduces morbidity and mortality (8). Given the large number of patients at risk (approximately 300 000 in Europe, USA and Australia combined) (9), identification of the mechanism by which some patients develop NMSC while others do not may allow the development of targeted surveillance strategies.

A number of clinical factors mediate NMSC risk. These include duration of immunosuppression, older age at transplantation, pre-transplant NMSC and high UVR exposure (7,10,11). Fair skinned transplant recipients living in sub-tropical areas of Australia are particularly susceptible and have the highest NMSC rate in the world (12,13). The importance of UVR exposure in relation to post-transplant NMSC is further supported by the identification of UVR-specific mutations in the p53 tumour suppressor gene in NMSC from both the general and renal transplant populations (14,15). UVR-induced oxidative stress with the generation of reactive oxygen species and consequent DNA damage appears to be a key factor in UVR-induced carcinogenesis (16). A genetically determined variation in the systems that repair or modulate such UVR-induced oxidative damage, such as the GST, may therefore have a role in determining the phenotypic variation in NMSC patients following transplantation.

Only two studies, both from the UK, have examined previously GST genotypes in relation to post-transplant NMSC risk (17,18). Our group has shown that the GSTM1 null genotype is significantly associated with increased squamous cell carcinoma (SCC) risk, particularly in those with high UVR exposure (17). An association between GSTP1*Ile105 homozygosity and greater numbers of SCC was also identified, particularly in those with a high UVR exposure. In contrast, a group from Oxford, UK (18), did not find any association between NMSC risk and either GSTM1 or T1 genotypes, although the GSTP1*C (Val105 + Val114) allele was associated with SCC development. UVR exposure was not specifically considered in the latter study. These findings highlight the difficulties of replicating genetic association studies (19). Much of this failure has been suggested to be due to heterogeneity within the study groups (population stratification), effect modification by other factors and/or the impact of confounders (19,20). In this study, we have attempted to address these potential problems by (i) using the same genotyping methodology and UVR exposure questionnaire as our UK study, (ii) using the same operator to collect the clinical and UVR data and (iii) examining interactions between immunosuppressive regimen/UVR exposure and genetic factors to take into account differences between the studies.

The primary aim of this study was to examine whether associations between NMSC risk/tumour number and allelism at GSTM1, GSTM3, GSTP1 and GSTT1 observed in our previous study of UK recipients could be replicated in Australian renal transplant recipients.

We were, however, aware that the two populations differed in two critical aspects: UVR exposure levels and immunosuppression regimen. Indeed, this population was selected in order to also examine whether the higher level of UVR exposure in this region would overwhelm the impact of the associations with GST genotype seen in transplant patients from more temperate climates. Furthermore, the immunosuppression protocol used in our original UK population aims to wean recipients off prednisolone following transplantation, whereas in Queensland the majority of patients receive long-term prednisolone. Furthermore, glucocorticoids have been shown to increase both SCC and basal cell carcinoma (BCC) risk, even in patients not on other immunosuppressants (21,22) and expression of GST is regulated by glucocorticoids via a response element in the promoter (23). Accordingly, the impact of GST polymorphisms may be mediated by exposure to glucocorticoids, including the commonly used immunosuppressant, prednisolone.

We therefore also had two specific secondary aims in the likely event that similar associations with susceptibility in the total group were not identified. First, we examined the relationship between genotype and UVR exposure using a similar approach to that used in our previous UK study (17). Secondly, we investigated the potential interaction between genotype and immunosuppressive regimen. Thus, to allow a more direct comparison between the two groups and to investigate the impact of glucocorticoid dose on the associations between NMSC and GST polymorphisms, we focused on analysis following partitioning of the Australian patients into two groups based on median prednisolone maintenance dose.


    Material and methods
 Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 
Patients
398 unrelated adult (>16 years old) renal transplant recipients were recruited from the Princess Alexandra Hospital, Brisbane, Southeast Queensland between July 1999 and April 2000 with local hospital ethics committee approval and written informed consent from all participants. All patients were examined for NMSC by a full body skin examination by a dermatologist (H.M.R.). The distribution of skin cancer in this population has been reported previously (24). Thirty-seven non-Caucasian patients were excluded: leaving a cohort of 361 Caucasians. 3979 histologically proven NMSC arose in 187 of these patients (51.8%) after transplantation comprising 1817 invasive SCC in 135 patients, 1012 in situ SCC (Bowen's disease) in 121, 916 BCC in 143 and 227 keratoacanthoma in 61 patients, one sweat gland tumour, and six unspecified. In this report, only invasive SCC and BCC were studied and recurrent lesions were excluded from the count of primary NMSC. The clinical characteristics and distribution of maintenance immunosuppressive regimens in this group are summarized in Table I. Data on UVR exposure and other demographic data have been presented previously (7).


View this table:
[in this window]
[in a new window]
 
Table I. Clinical characteristics of Caucasian Queensland renal transplant recipients

 
Demographic, clinical and environmental exposure data
A structured questionnaire was completed by a single dermatologist (H.M.R.), blinded to previous dermatological records as described previously (7,11,24). Demographic information collected retrospectively included age, racial origin and gender. UVR exposure was estimated utilizing a validated questionnaire and scoring system (6,11,24) and considered in three categories: chronic exposure, acute exposure and individual response to UVR. Parameters used as markers of chronic UVR exposure were: number of years worked in an outdoor occupation, years resident in a hot climate and cumulative UVR exposure (calculated from the average number of hours spent outdoors each week during the periods: teenage years, 20–40, 40–60 and >60 years of age. Weekdays and weekends were considered separately to help differentiate between work and leisure times and to assist recall.) Acute UVR exposure was considered in terms of frequency of childhood sunburn and sunbathing scores [determined from the frequency of sunbathing during the same four periods described for cumulative exposure. These were then scored (0 = never, 1 = rarely, 2 = occasionally, 3 = frequently) and the cumulative score calculated.] Data on individual response to UVR was assessed from pigmentary factors such as skin type and natural hair and eye colour at age 21 years. Other environmental exposure data gathered included arsenic (grouped as yes, no, possible), ionizing radiation and tobacco smoking (7). In cases where arsenic exposure was listed as ‘yes’ or ‘possible’, source of exposure was requested on the questionnaire. Exposure to arsenic in Queensland is derived largely from use of farm animal dips. Cause of end-stage renal failure; number, types(s) and date(s) of transplants(s); immunosuppressant therapy and number of HLA-mismatches was extracted from case notes and Australia and New Zealand Dialysis and Transplantation registry (ANZDATA) summaries. Maintenance immunosuppressant regimen was taken as the stable dose (mg/kg body wt/day 12 months after the date of transplantation) for each agent. Duration of immunosuppression was calculated by summing the total time that immunosuppression was given for each allograft.

Identification of genotypes
DNA was extracted from peripheral blood leukocytes by standard ‘salting-out’ methodology (25). GSTM1 A, B, A/B and null genotypes were identified using a PCR-based amplification refractory mutation system approach with allele-specific primers (26). GSTM3 AA, AB and BB genotypes were identified using primers to exon 6/7 (27). GSTP1 Ile/Ile, Ile/Val and Val/Val genotypes were identified by PCR with digestion with Alw261 to identify the A-G transition at position 1578 (28). GSTT1 null and expressing subjects were also identified using PCR (26). Because some DNA samples were not available or refractory to amplification, it was not possible to obtain complete genotype data on all patients (GSTM1 n = 337, GSTM3 n = 336, GSTT1 n = 333, GSTP1 n = 338).

Strategy for data analysis
Data were collated using a Microsoft Access database and the Stata software package (version 8, Stata Corporation, College Station, TX) was used for statistical analyses. All regression analyses were corrected for age at transplantation, duration of immunosuppression and male gender as these factors have been shown previously to be associated with NMSC risk and numbers (7).

Our strategy for analysis of the data was as follows.

Primary analyses. We used logistic regression models to examine the association between GST genotype and susceptibility to NMSC using the presence of invasive SCC and the presence of BCC as endpoints as per our previous study (17). As previously, we also assessed associations between GST genotype and the number of tumours accrued using negative binomial regression analysis, normalized for follow-up time, with number of SCC and number of BCC as outcome measures. A rate ratio (RR), defined as the multiplicative effect of a change of a covariate by 1 was calculated (for these data usually being a change from 0 to 1). For example, the rate ratio for males [1] against females [0] represents mean number BCC in males/mean number BCC in females, when gender alone (i.e. not in the presence of other covariates) is considered. In the negative binomial regression, this will change in the presence of other covariates and following normalization for duration of follow-up.

Some patients (n = 103) developed both BCC and invasive SCC and are therefore represented in the analyses of both groups. Consequently, these analyses are not independent and the application of a standard correction for multiple testing (e.g. Bonferroni correction) at this stage would be inappropriate since it is over-conservative when applied to non-independent analyses (29). Furthermore, we were seeking to confirm previously generated a priori hypotheses (from our UK data) and therefore did not use correction for multiple testing in these primary analyses.

Secondary analyses. In order to assess the relationship between genotype and UVR in predicting NMSC risk, we selected sunbathing exposure data as our primary UVR stratifier for two reasons. First, this was the parameter used in our previous UK study to assess the interaction between genotype and UVR, and secondly, in our experience, sunbathing score provides the best discriminator of sun-seeking behaviour. In contrast, high cumulative exposure can be attained either by low levels of exposure over long periods (e.g. farmers) or by higher levels over shorter time periods, both of which, based on previous data in skin cancer, can have very different (even opposite) effects on risk. We selected a lower cut-off (≤2 versus >2) than our UK study (≤3 versus >3) as the intensity of exposure is higher in Queensland than in North Staffordshire.

In the case of immunosuppressive regimen, we elected to stratify by prednisolone dose for three reasons: (i) this appeared to be the major difference between the UK and Australian populations in immunosuppressive regimen (6,7), (ii) glucocorticoids have been associated with NMSC risk, even in patients not on other immunosuppressants (21,22) and, (iii) because of the potential role of glucocorticoids in regulating GST expression (23). We selected a cut-off of the median dose (≤7 versus >7 mg/day), as there is currently no a priori reason to select a specific cut-off.

In both cases, we used two approaches in the assessment of the relationship between UVR/immunosuppressive dose and genotype. First, we stratified patients according to the selected exposure/dose cut-off. Secondly, we examined interactions (to check for epistasis) by including in regression models variables comprising those patients with both factors (e.g. high risk genotype and high exposure; interaction term) with those with all other combinations, and the two main effect variables (high-risk genotype versus low-risk genotypes, high exposure versus low exposure). The second analysis (for interaction) was only performed where the first generated significant (uncorrected P < 0.05) results: as supporting data.

For the secondary analyses, we only considered associations with tumour numbers (rather than susceptibility) since, in our experience in both transplant and non-transplant populations, genetic factors are better predictors of NMSC tumour numbers than risk (4,16,17). Furthermore, since Australia has such high levels of UVR, this is likely to dominate susceptibility. Indeed, our previous data on NMSC prevalence in this population supports this view (24). We also excluded examination of some genotypes at this stage based on existing NMSC data from this (our primary analyses) and the previous UK studies. We therefore focused on the following comparisons: GSTM1 null versus AB, GSTM3 AA versus AB + BB, GSTT1 null versus A, GSTP1 Ile/Ile versus Val/Val, thereby minimizing the number of non-hypothesis generated significance tests. We then applied correction for multiple testing, using Holm's procedure as suggested by Rosenberger (30), by grouping the analyses into families of tests. Thus, analyses with stratification by UVR dose were considered one family, those with prednisolone as another. Interaction analyses were only performed where the stratification data were significant. These were not included in the family for the purposes of multiple testing as they represent non-independent confirmatory analyses. Analyses of SCC and BCC were considered separate families for the reasons of non-independence stated above. Consequently, each family comprised eight significance values.


    Results
 Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 
Table I shows the characteristics of the patients stratified by prednisolone dose. Patients on higher doses were significantly younger, had longer follow up and were more likely to be male. Other immunosuppressants were also significantly different between the two groups. Higher dose was also associated with more NMSC, possibly due to the increased duration of immunosuppression. Data on UVR exposure and other demographic data are presented elsewhere (7). There were no significant differences with markers of UVR exposure in the high and low prednisolone groups (data not shown).

Primary analyses: total group
Susceptibility to NMSC. Table II shows that the of GST genotype frequencies in the total group of Caucasian renal transplant recipients stratified by presence or absence of NMSC. No significant associations were found between GST genotypes and susceptibility to NMSC in the total population, although the frequency of GSTM1 AB was lower in patients with SCC.


View this table:
[in this window]
[in a new window]
 
Table II. Genetic associations with susceptibility to NMSC in the total Caucasian Queensland renal transplant recipient group

 
NMSC numbers. Associations between GST genotype and NMSC numbers in the total group are shown in Table III. GSTM1 AB and B genotypes were associated with fewer SCC although only AB achieved statistical significance (P = 0.049). When compared with the GSTM3 AB and BB genotypes combined (mean SCC numbers 6.8), subjects with the GSTM3 AA genotype demonstrated fewer SCC (mean SCC numbers 4.8; P = 0.015, RR = 0.50, 95% CI = 0.28–0.87). These results are internally consistent as GSTM1*B is in linkage disequilibrium with GSTM3*A. No other significant associations with tumour numbers were observed in the total group.


View this table:
[in this window]
[in a new window]
 
Table III. Genetic associations with numbers of NMSC in the total Caucasian Queensland renal transplant recipient group

 
Secondary analyses
Table IV shows the data obtained following stratification by sunbathing score and prednisolone dose.


View this table:
[in this window]
[in a new window]
 
Table IV. Associations between GST polymorphisms and numbers of NMSC in Caucasian Queensland renal transplant recipients stratified by sunbathing score and prednisolone dose

 
Stratification by UVR: sunbathing score. No significant interactions were found between GSTM1, GSTT1 or GSTP1 genotypes and level of UVR exposure (Table IV), although GSTM1 null versus AB approached significance (P = 0.075). When GSTM3 AA was compared with AB + BB, this genotype was particularly associated with SCC numbers in individuals with high but not low sunbathing score. Examination of the interaction between sunbathing score and GSTM3 genotype showed significant epistasis between the two (high score + GSTM3 AA genotype: P = 0.016, RR = 0.23, 95% CI = 0.07–0.76) after inclusion of the main effects in the SCC numbers binomial regression model.

Stratification by immunosuppressive regimen: prednisolone dose. After stratifying according to prednisolone dose (Table IV), GSTM1 AB was significantly associated with reduced numbers of both SCC and BCC in the high dose but not the low-dose group (Table IV). GSTM3 AA was associated with an increased risk of SCC numbers in the high dose but not the low-dose subgroup (Table IV). GSTT1 null was associated with fewer SCC in the low dose, but not the high-dose group. GSTP1 Val/Val was associated with smaller numbers of both SCC and BCC in the low-dose group, but larger SCC numbers in the high-dose subgroup. Assessment on interactions showed significant epistasis between GSTP1 and prednisolone dose with SCC numbers (P = 0.002, RR = 12.78, 95% CI = 2.62–62.3) and GSTM1 with BCC numbers (P = 0.034, RR = 0.02, 95% CI = 0.001–0.75). Interactions between prednisolone dose and GSTM3 and GSTT1 genotype with SCC numbers were not significant, suggesting a non-synergistic effect.

Correction for multiple testing. Of the analyses in Table IV, only the associations between SCC numbers and GSTT1 in the low-dose prednisolone group and GSTM1 in the high prednisolone-dose group remained significant after correction for multiple testing as described, although the association between GSTM3 and high sunbathing score approached significance (Table IV).


    Discussion
 Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 
In this study, we have examined associations between polymorphism in the GST and NMSC risk in a population of carefully characterized renal transplant recipients from Queensland, Australia. This follows on from previous studies on GST polymorphism in two UK transplant populations (17,18). In particular, we aimed first, to confirm (or otherwise) associations between genotype and NMSC risk and numbers observed in our previous study and secondly, to investigate the possible reasons for discrepancies by stratifying by level of UVR exposure and dose of immunosuppressant.

In our primary analyses, the finding of significant associations between the GSTM1 AB genotype and both risk and numbers of NMSC in the total group is consistent with findings in non-transplant BCC patients, which showed a protective effect of this genotype (3). In our previous data on UK transplant recipients (17), we identified an increased frequency of the GSTM1 null polymorphism in recipients with SCC, while Marshall et al. (18) found no difference in GSTM1 null frequencies between those with and without SCC. Given the low frequency of the AB genotype, even if our data suggesting that two copies of GSTM1 confers a moderate protective effect against NMSC is confirmed, this effect is unlikely to be clinically significant.

The demonstration of a protective effect of GSTM3 AA for SCC supports the findings of our preliminary UK study, which was limited by both the relatively small proportion of recipients with SCC and the low frequency of the GSTM3 BB genotype (17). We have now confirmed our initial observations in a larger population with larger proportions of SCC positive patients. It is notable that in the Australian population the association demonstrated was between GSTM3 genotype and SCC numbers rather than SCC risk per se, suggesting that in a population with such high UVR exposure, modifier genes such as GST influence the number of NMSC that are formed rather than susceptibility. The finding of similar associations with both GSTM1*B- and GSTM3*A-containing genotypes (both GSTM1 AB and B genotypes demonstrated lower rate ratios relative to null) is consistent with the linkage disequilibrium observed between these alleles (27). However, when both factors were included in the same negative binomial regression model, each appeared, at least to some degree, to be independently associated with SCC numbers (GSTM3 AA, P = 0.051, RR = 0.57; GSTM1 AB + B, P = 0.026, RR = 0.45).

Although we did confirm some of our UK data in the current study, there were some discrepancies. We therefore performed a number of hypothesis-based secondary analyses—stratification by UVR exposure and prednisolone dose—to examine possible reasons for these differences. In our UK cohort, we identified previously associations between GST genotypes and NMSC risk after stratification by UVR exposure; GSTM1 null was associated with risk in the recipients with high-UVR exposure group (17). Due to small numbers in our initial study, it was not possible to examine interaction between UVR and GSTM3, GSTT1 and GSTP1. In this study, we have showed that both GSTM3 AA and GSTM1 AB were particularly associated with fewer SCC in recipients with a high sunbathing score, although the latter just failed to achieve statistical significance. Furthermore, the interaction between GSTM3 genotype and UVR exposure appeared epistatic. The reason for these observations is unclear but suggest a role, at least in some patients, for mu class GST in the detoxification of the products of UVR-induced oxidative stress, substrates for GST.

Most significant associations were identified following assessment of the relationship between genotype and prednisolone dose. Associations between SCC numbers and both GSTM1 and GSTM3 were most marked in the high-dose prednisolone group. The mechanism for this effect is unclear. However, the finding of roles for mu class GST in both detoxification of potential carcinogens (e.g. from UVR exposure) as well as apoptosis via interaction with apoptosis signal-regulating kinase (31,32) may be one possible explanation for these different effects. Glucocorticoids are key regulators of the apoptotic pathways and regulate GST expression (23,32). Consequently, one might speculate that exposure to high-dose prednisolone might activate the apoptotic pathways in nascent tumour cells in the presence of active mu class GST, thereby reducing the risk of tumour development. In recipients with GSTM1 null or low activity GSTM3 variants, this apoptotic pathway is impaired leading to tumour development.

The lack of associations with both GSTP1 and GSTT1 polymorphisms and NMSC risk in the total group appears at odds with both UK studies. However, following stratification by prednisolone dose, associations between both GSTT1 and GSTP1 and NMSC numbers were revealed. Thus, GSTT1 null was associated with reduced SCC numbers in the low-dose group. This was consistent with our findings in the UK population and confirms the somewhat unexpected protective effect of the null genotype in immunosuppressed patients. This possibility, while surprising in the light of the hypothesized role of GSTT1 in protection against oxidative stress, is supported by a possible involvement of this gene in mediating immune response. It is possible that the null genotype results in increased levels of reactive oxygen species, which activate the immune response via increased arachidonic acid mobilization and eicosanoid production (23,28). An increased immune response would allow detection and removal of microtumors, which would otherwise be deficient in immunosuppressed patients. We have proposed this as a potential mechanism behind separate observations in colorectal cancer patients where GSTT1 null is associated with increased lymphocyte infiltration and increased survival (unpublished observations). However, these speculations would require further data before they could be confirmed.

The associations between GSTP1 genotype and NMSC numbers following dichotomization on prednisolone dose are particularly perplexing. In the low-dose group, relative to GSTP1 Val/Val, Ile/Ile was associated with an increased number of SCC. This is in keeping with our observations in the UK population (17), which showed that, when compared with GSTP1 Ile/Val and Val/Val genotypes combined, recipients with the Ile/Ile genotype demonstrated significantly more SCC (P = 0.002, RR = 7.6). In contrast, at higher doses in this study, homozygosity for the Ile allele was associated with fewer SCC. Interestingly, Marshall et al. (18) showed that, in their UK renal transplant population, the GSTP1*C allele (Val105 and Val114) was associated with increased SCC risk. As weaning off prednisolone is not universal UK practice, these observations may also be consistent with our findings in the Queensland population.

The mechanism for the contrasting effect of GSTP1 genotype remains to be elucidated. The functional effect of the Ile105-Val105 substitution may be substrate dependent. Thus, compared with Ile-containing enzymes, Val-containing GSTP1 was associated with a 7-fold increase in specific activity towards polycyclic aromatic hydrocarbons, but a 3-fold reduction in activity towards 1-chloro-3,4-dinitrobenzene (33,34). Furthermore, GSTP1 demonstrates dual functionality. In unstressed conditions, the enzyme acts as a detoxifying enzyme in dimeric form and monomeric GSTP1 binds to jun kinase (JNK) preventing phosphorylation of c-jun and subsequent apoptosis (31). Under conditions of stress (e.g. lead exposure, oxidative stress), GSTP1 monomer dissociates from JNK with subsequent increases in levels of apoptosis. We speculate therefore that, under the comparatively unstressed conditions of low-dose prednisolone, GSTP1 Val-containing enzymes are less efficient at detoxifying the products of oxidative stress than Ile-containing enzymes leading to increased arachidonic acid mobilization and enhancement of antitumour activity as suggested for GSTT1 null. We have previously proposed this as a potential mechanism for the protective effect of GSTP1 Val/Val polymorphism in asthma (28). Under the stress of high-dose prednisolone, we hypothesize that Val is associated with more efficient binding to JNK, less rapid restoration of kinase activity and decreased levels of apoptosis of tumour cells. Functional studies would be required to test these hypotheses.

Since it was possible that the effect seen after dichotomizing on the basis of median prednisolone may reflect effects due to other factors, we also examined the clinical characteristics of the two sets of patients. Doses of other immunosuppressants were generally similar, although mean cyclosporin dose was higher and azathioprine lower in the low-dose prednisolone group than the higher-dose group. Number of transplants, and the distributions of skin type, eye colour and hair colour were not significantly different, though the high-dose group comprised more males (71.8% versus 52.3%) and had a longer duration of immunosuppression. Despite these differences, we were unable to identify any potential confounding factors that would explain the contrasting effects of GST genotypes in the two groups.

Since our primary analysis focused on confirmation of previous data, we felt that correction for multiple testing was not appropriate. In the secondary analyses, however, we adopted a moderately conservative approach to correction for multiple analyses by using the recommendations of Rosenberger (30) in order to reduce the risk of both type 1 and type 2 errors (29). Following such correction, the associations between SCC numbers and GSTT1 null in the low-dose predisolone group and GSTM1 in the high-dose group remained significant, while that of GSTM3 with high sunbathing score approached significance (Table IV).

In summary, we have identified significant associations between risk of NMSC and polymorphism in several GST in a population of Australian renal transplant recipients. The data generally support existing data in UK populations—the exception rather than the rule in most genetic association studies (19,20). The finding of marked differences based on prednisolone dose is novel and warrants further investigation, both at a functional level and to confirm the observations identified. In the longer term, it is possible that genetic tests could be included in predictive models of skin cancer risk in transplant recipients. Indeed, we have already developed such models for conventional risk factors in this population (11) and are currently examining the impact of genetic factors, alone and in interactions with environmental risk factors, on these predictive models. This approach would allow identification of high-risk individuals for inclusion in targeted surveillance programmes.


    Acknowledgments
 
This study was supported by the British Association of Dermatologists' Geoffrey Dowling Travelling Fellowship and the St John Ambulance Travelling Fellowship in Transplantation.


    References
 Top
 Abstract
 Introduction
 Material and methods
 Results
 Discussion
 References
 

  1. Strange,R.C. and Fryer,A.A. (1999) The glutathione S-transferases: influence of polymorphism on susceptibility to non familial cancers. In Boffetta,P., Caporaso,N., Cuzick,J., Lang,M. and Vineis,P. (eds) Metabolic Polymorphisms and Cancer. IARC Scientific Publications, IARC, Lyon, pp. 303–322.
  2. Ramachandran,S., Fryer,A.A., Lovatt,T., Lear,J., Smith,A.G. and Strange,R.C. (2001) Susceptibility and modifier genes in cutaneous basal cell carcinomas and their associations with clinical phenotype. J. Photochem. Photobiol. B, 63, 1–7.[CrossRef][ISI][Medline]
  3. Heagerty,A.H., Fitzgerald,D., Smith,A., Bowers,B., Jones,P., Fryer,A.A., Zhao,L., Alldersea,J. and Strange,R.C. (1994) Glutathione S-transferase GSTM1 phenotypes and protection against cutaneous tumours. Lancet, 343, 266–268.[CrossRef][ISI][Medline]
  4. Yengi,L., Inskip,A., Gilford,J. et al. (1996) Polymorphism at the glutathione S-transferase, GSTM3 locus: Interactions with cytochrome P450 and glutathione S-transferase genotypes as risk factors for multiple cutaneous basal cell carcinoma. Cancer Res., 56, 1974–1977.[Abstract]
  5. 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) Tumor site in cutaneous basal cell carcinoma: influence of glutathione S-transferase, GSTT1 and cytochrome P450, CYP1A1 genotypes and their interactions. J. Invest. Dermatol., 108, 519–522.[ISI][Medline]
  6. Ramsay,H.M., Fryer,A.A., Smith,A.G. and Harden,P.N. (2000) Clinical risk factors associated with non-melanoma skin cancer in renal transplant recipients. Am. J. Kidney Dis., 36, 167–176.[ISI][Medline]
  7. Ramsay,H.M., Fryer,A.A., Hawley,C.M., Smith,A.G., Nicol,D.L. and Harden,P.N. (2003) Factors associated with non-melanoma skin cancer following renal transplantation in Queensland, Australia. J. Am. Acad. Dermatol., 49, 397–406.[CrossRef][ISI][Medline]
  8. Kasiske,B.L., Vazquez,M.A., Harmon,W.E., Brown,R.S., Danovitch,G.M. and Gaston,R.S. (2000) Recommendations for the outpatient surveillance of renal transplant recipients. J. Am. Soc. Nephrol., 11, S1–S86.[Abstract/Free Full Text]
  9. Reece,S.M., Harden,P.N., Smith,A.G. and Ramsay,H.M. (2002) A model for nurse-led skin cancer surveillance following renal transplantation. Nephrol. Nurs. J., 29, 257–260.[Medline]
  10. Harden,P.N., Fryer,A.A., Reece,S., Smith,A.G. and Ramsay,H.M. (2001) Annual incidence and predicted risk of non-melanoma skin cancer in renal transplant recipients. Transplant Proc., 33, 1302–1304.[CrossRef][ISI][Medline]
  11. Carroll,R.P., Ramsay,H.M., Fryer,A.A., Hawley,C.M., Nicol,D.L. and Harden,P.N. (2003) Incidence and prediction of non melanoma skin cancer post-renal transplant: a prospective study in Queensland Australia. Am. J. Kidney Dis., 41, 676–683.[CrossRef][ISI][Medline]
  12. Bouwes Bavinck,J.N., Hardie,D.R., Green,A., Cutmore,S., MacNaught,A., O'Sullivan,B., Siskind,V., Van Der Woude,F.J. and Hardie,I.R. (1996) The risk of skin cancer in renal transplant recipients in Queensland, Australia: a follow-up study. Transplantation, 61, 715–721.[ISI][Medline]
  13. Hardie,I.R. (1995) Skin cancer in transplant recipients. Transplant Rev., 9, 1–16.
  14. McGregor,J.M., Berkhout,R.J., Rozycka,M., ter Schegget,J., Bouwes Bavinck,J.N., Brooks,L. and Crook,T. (1997) p53 mutations implicate sunlight in post-transplant skin cancer irrespective of human papillomavirus status. Oncogene, 15, 1737–1740.[CrossRef][ISI][Medline]
  15. Ziegler,A., Leffell,D.J., Kunala,S. et al. (1993) Mutation hotspots due to sunlight in the p53 gene of nonmelanoma skin cancers. Proc. Natl Acad. Sci. USA, 90, 4216–4220.[Abstract/Free Full Text]
  16. Lear,J.T., Smith,A.G., Strange,R.C. and Fryer,A.A. (2000) Detoxifying enzyme genotypes and susceptibility to cutaneous malignancy. Br. J. Dermatol., 142, 8–15.[CrossRef][ISI][Medline]
  17. Ramsay,H.M., Harden,P.N., Reece,S., Smith,A.G., Jones,P.W., Strange,R.C. and Fryer,A.A. (2001) Polymorphisms in glutathione S-transferases are associated with altered risk of non-melanoma skin cancer in renal transplant recipients: a preliminary analysis. J. Invest. Dermatol., 117, 251–255.[CrossRef][ISI][Medline]
  18. Marshall,S.E., Bordea,C., Haldar,N.A., Mullighan,C.G., Wojnarowska,F., Morris,P.J. and Welsh,K.I. (2000) Glutathione S-transferase polymorphisms and skin cancer after renal transplantation. Kidney Int., 58, 2186–2193.[CrossRef][ISI][Medline]
  19. Colhoun,H.M., McKeigue,P.M. and Davey Smith,G. (2003) Problems of reporting genetic associations with complex outcomes. Lancet, 361, 865–872.[CrossRef][ISI][Medline]
  20. Cardon,L.R. and Palmer,L,J. (2003) Population stratification and spurious allelic associations. Lancet, 361, 598–600.[CrossRef][ISI][Medline]
  21. Karagas,M.R., Cushing,G.L. Jr, Greenberg,E.R., Mott,L.A., Spencer,S.K. and Nierenberg,D.W. (2001) Non-melanoma skin cancers and glucocorticoid therapy. Br. J. Cancer, 85, 683–686.[CrossRef][ISI][Medline]
  22. Sorensen,H.T., Mellemkjaer,L., Nielsen,G.L., Baron,J.A., Olsen,J.H. and Karagas,M.R. (2004) Skin cancers and non-hodgkin lymphoma among users of systemic glucocorticoids: a population-based cohort study. J. Natl Cancer Inst., 96, 709–711.[Abstract/Free Full Text]
  23. Hayes,J.D. and Pulford,D.J. (1995) The glutathione S-transferase supergene family: regulation of GST and the contribution of the isoenzymes to cancer chemoprotection and drug resistance. Crit. Rev. Biochem. Mol. Biol., 30, 445–600.[Abstract]
  24. Ramsay,H.M., Fryer,A.A., Hawley,C.M., Smith,A.G., Nicol,D.L. and Harden,P.N. (2002) Non-melanoma skin cancer risk in the Queensland renal transplant population. Br. J. Dermatol., 147, 950–956.[CrossRef][ISI][Medline]
  25. Miller,S.A., Dykes,D.D. and Polesky,H.F. (1988) A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res., 16, 1215.[ISI][Medline]
  26. Elexpuru-Camiruaga,J., Buxton,N., Kandula,V. et al. (1996) Susceptibility to astrocytoma and meningioma: influence of allelism at glutathione S-transferase, GSTT1 and GSTM1 and cytochrome P450, CYP2D6 loci. Cancer Res., 55, 4237–4239.[ISI]
  27. Inskip,A., Elexperu-Camiruaga,J., Buxton,N. et al. (1995) Identification of polymorphism at the glutathione S-transferase, GSTM3 locus: evidence for linkage with GSTM1*A. Biochem. J., 312, 713–716.[ISI][Medline]
  28. Fryer,A.A., Bianco,A., Hepple,M., Alldersea,J., Jones,P.W., Strange,R.C. and Spiteri,M.A. (2000) Polymorphism at the glutathione S-transferase, GSTP1, locus: A new marker for bronchial hyperresponsiveness and asthma. Am. J. Respir. Crit. Care Med., 161, 1437–1442.[Abstract/Free Full Text]
  29. Perneger,T.V. (1998) What's wrong with Bonferroni adjustments. Br. Med. J., 316, 1236–1238.[Free Full Text]
  30. Rosenberger,W.F. (1996) Dealing with multiplicities in pharmacoepidemiological studies. Pharmacoepidemiol. Drug Safety, 5, 95–100.[CrossRef]
  31. Adler,V., Yin,Z., Fuchs,S.Y. et al (1999) Regulation of JNK signalling by GSTp. EMBO J., 18, 1321–1334.[Abstract/Free Full Text]
  32. Townsend,D.M. and Tew,K.D. (2003) Cancer drugs, genetic variation and the glutathione-S-transferase gene family. Am. J. Pharmacogenomics, 3, 157–172.[Medline]
  33. Hu,X., Xia,H., Srivastava,S.K., Herzog,C., Awasthi,Y.C. Ji,X., Zimniak,P. and Singh,S.V. (1997) Activity of four allelic forms of glutathione S-transferase hGSTP1-1 for diol epoxides of polycyclic aromatic hydrocarbons. Biochem. Biophys. Res. Commun., 238, 397–402.[CrossRef][ISI][Medline]
  34. Watson,M.A., Stewart,R.K., Smith,G.B.J., Massey,T.E. and Bell,D.A. (1998) Human glutathione S-transferase P1 polymorphisms: relationship to lung tissue enzyme activity and population frequency distribution. Carcinogenesis, 19, 275–280.[Abstract]
Received July 16, 2004; revised September 15, 2004; accepted September 17, 2004.