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Experimental Therapeutics, Molecular Targets, and Chemical Biology |
1 Lawrence Livermore National Laboratory, Livermore, California and 2 University of Arkansas for Medical Sciences; 3 Central Arkansas Veterans Healthcare System, Little Rock, Arkansas
Requests for reprints: Michael A. Malfatti, Lawrence Livermore National Laboratory, 7000 East Avenue, L452, Livermore, CA 94550. Phone: 925-422-5732; Fax: 925-422-2282; E-mail: malfatti1{at}llnl.gov.
| Abstract |
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| Introduction |
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Heterocyclic amines require metabolic activation to a bioreactive species before they can interact with DNA to form adducts. The bioactivation of PhIP to its carcinogenic form is highly dependent on the cytochrome P4501A2 (CYP1A2)-mediated hydroxylation of the exocyclic amine group to form the corresponding 2-hydroxyamino-1-methyl-6-phenylimidazo[4,5-b]pyridine (N-hydroxy-PhIP; refs. 11, 12). Subsequent esterification by sulfotransferases and/or acetyltransferases generates the highly electrophilic O-sulfonyl and O-acetyl esters, respectively. These esters are capable of covalently binding DNA (13, 14). N-hydroxy-PhIP can also form the less reactive glucuronide conjugates at the N2 amine nitrogen or the N3 ring nitrogen, which can be excreted through the urine or bile or be transported to other tissue where further metabolism can occur (15, 16). This pathway is a predominant step in the biotransformation of PhIP in humans (17).
Studies have shown that the rate of heterocyclic amine metabolism can be influenced by enzyme phenotype and/or genotype. A correlation between CYP1A2 activity levels and urinary excretion of heterocyclic amine metabolites was observed in human populations fed well-done cooked meat. High levels of CYP1A2 activity were associated with reduced levels of unmetabolized PhIP in the urine, indicating that more PhIP is being converted to the bioactive N-hydroxy derivative compared with urinary heterocyclic amine levels from individuals with low CYP1A2 activity (1820). In addition, polymorphisms in the UDP-glucuronosyltransferase 1A1 (UGT1A1) gene were associated with a decreased ability to detoxify N-hydroxy-PhIP via glucuronidation in human liver samples due to reduced UGT1A1 activity (21).
Enzyme polymorphisms can lead to interindividual variation in DNA adduct formation as well. A positive correlation was reported between the level of DNA adducts and the level of CYP1A2 activity in human liver microsomes incubated with PhIP. As CYP1A2 activity increased, there was a concomitant increase in PhIP-DNA adduct levels, suggesting that DNA adducts can be used as an indicator of interindividual variability in the metabolic activation of heterocyclic amines (22). Furthermore, increases in bioactivation and DNA adduct formation due to phenotypic differences in CYP1A2 and N-acetyltransferase 2 (NAT2) activity have been implicated as increased colon cancer risk factors associated with heterocyclic amine exposure (23). Therefore, susceptibility to the carcinogenic risks associated with heterocyclic amine exposure can depend on exposure levels as well as specific enzyme phenotypes that can affect the bioactivating capacity of certain metabolizing enzymes.
The relationship between PhIP-DNA adduct formation, metabolism, and exposure has been primarily established at high PhIP doses using animal models, mostly due to limitations in assay sensitivity and the difficulties associated with human in vivo studies. In the present study, these limitations have been overcome by using accelerator mass spectrometry (AMS), which is capable of accurately measuring attomole (1018) quantities of radiolabeled compound (24, 25). The goal of the current study is to determine the relationship between PhIP metabolism, DNA adduct levels, and enzyme phenotype in humans at a dietary relevant dose of PhIP and to determine if metabolite levels and/or enzyme phenotype can predict interindividual susceptibility to DNA adduct formation.
AMS was used to measure colon DNA adducts in a human population exposed to a dietary equivalent dose of PhIP, labeled with a very low level of 14-carbon. The 0.011 mSv radioactive dose each subject received is equivalent to 1/29 of the energy received from an average chest X-ray. Urinary PhIP metabolite levels and selected enzyme phenotypes were also assessed in an effort to establish a link between metabolite levels, enzyme phenotype, and DNA adducts. Data are presented that suggest that urinary PhIP metabolite profiles can serve as a biomarker to predict interindividual differences in DNA adduct levels at dose levels that are typical of human exposure conditions. This pilot study should provide a better understanding of the critical role each metabolic step has in the bioactivation and detoxification of this carcinogen. Ultimately, an assessment of individual susceptibility to the potential cancer risks from PhIP exposure should be possible.
| Materials and Methods |
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Human study. The human study protocol was independently reviewed and approved by the Institutional Review Boards for Human Subjects at the Lawrence Livermore National Laboratory (Livermore, CA), the University of Arkansas Medical School Hospital (Little Rock, AR), and the John L. McClellan Memorial Veterans Administration Medical Center (Little Rock, AR). Details of the study protocol are reported elsewhere (26). Briefly, 10 human volunteers were recruited for the study. All volunteers were cancer patients undergoing surgery to remove colon carcinoma(s) and gave informed consent before enrollment. The study population consisted of nine Caucasian males and one Caucasian female ranging in age from 44 to 82 years. [14C]PhIP was administered orally in a gelatin capsule before surgery. Subjects 1 and 2 received a dose of 70 µg [14C]PhIP per person (specific activity, 56 mCi/mmol), and subjects 3 to 10 received a dose of 84 µg [14C]PhIP (specific activity, 41.8 mCi/mmol). The differences in the amounts and the specific activity of [14C]PhIP were a result of preparing the PhIP capsules on two different occasions from two batches of [14C]PhIP.
Urinary metabolite characterization. Urine was collected at various time points up to 24 hours after [14C]PhIP exposure and then frozen at 20°C until processing for metabolite analysis. Details of the urinary metabolite analysis have been previously reported (17). Briefly, an aliquot of each urine sample containing approximately 6,000 to 8,000 dpm was analyzed by high-performance liquid chromatography (HPLC) for PhIP and PhIP metabolites. Each sample was directly injected into a Rainin HPLC system (Varian, Walnut Creek, CA) equipped with a 5-µm, 4.6 x 220mm TSK-GEL ODS-80 TM column (TosoHaas, Montgomeryville, PA) and monitored at 315 nm. The column eluate was collected at 1-minute intervals, and radioactivity was quantified by scintillation counting (Wallac, Gaithersburg, MD). Metabolites were identified by coelution with authentic PhIP metabolite standards and by mass spectral characterization (17). For mass spectral analysis, each isolated metabolite was directly injected into a Michrom µLC system (Michrom Bioresources, Inc., Auburn, CA) equipped with a Zorbax C18 SB column (0.2 x 150 mm; Michrom Bioresources) and coupled to a Finnigan MAT TSQ-700 triple quadrupole mass spectrometer through a Finnigan electrospray interface (Finnigan MAT, San Jose, CA). Full scan and collision-induced dissociation mass spectra were obtained for each metabolite using previously described variables (17).
Tissue collection and DNA extraction. Forty-eight to 72 hours after dosing, the volunteers underwent surgery for a partial colonectomy. Colon tissue not required for diagnosis or staging was collected and frozen at 80°C until analysis. DNA and protein were extracted from the colon tissue and analyzed by AMS for PhIP-DNA adduct formation using previously reported methods (26, 27).
Enzyme phenotyping. Blood was collected before [14C]PhIP dosing for phenotyping sulfotransferase 1A1 (SULT1A1) activity. Separation of platelets and preparation of cytosol for SULT1A1 phenotyping have been described previously (28). Phenotyping for CYP1A2 and NAT2 was done preoperatively or postoperatively using the caffeine phenotyping assay (29, 30).
Statistical analysis. Two statistical approaches were used to analyze the data. The first used univariate linear modeling and stepwise variable selection using the Akaike Information Criterion method. These parametric methods were used because of the small number of degrees of freedom (df, 9) available in this study. There were 26 variables but only 10 observations in the study. Because the degrees of freedom in a linear model are df = n p, where n is the number of observations and p is the number of variables, a model, including all 26 variables, could not be fitted.
The second approach used the nonparametric random forest regression analysis, which is a test to determine the importance of one variable in relation to another. This method ranks all variables in a study in the order of importance. The importance measure, which is the percentage increase in mean squared error (MSE), is calculated for each variable. Each variable is then randomly shuffled across observations, whereas all other variables are left as is. The new MSE is calculated using the random forest regression algorithm. If the variable in question is an important predictor of the outcome (i.e., DNA adducts), the new calculated MSE will be higher than the original MSE. The larger the percentage increase in MSE, the more important the variable is as a predictor of outcome.
| Results |
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Statistical analysis. Data obtained from the metabolite analysis, enzyme phenotype, and PhIP-DNA adduct data sets were analyzed by various statistical methods to determine if any of the measured variables were correlated to colon DNA adducts. There were 26 variables that were considered for this analysis. Both univariate and nonparametric models were used to evaluate the data. Because there were 26 variables but only 9 degrees of freedom, it was not possible to fit a full univariate linear model to include all the variables. Therefore, a univariate linear analysis was done for each variable and the Ps were compared from each analysis. Table 4 shows the univariate linear model results for all the variables. N-hydroxy-PhIP-N2-glucuronide, unknown metabolite 3, and CYP1A2 activity had the lowest Ps, indicating that these variables are the most significantly (P < 0.05) correlated to colon DNA adducts. However, the low level and the lack of significant variation in unknown metabolite 3 between each subject deemed this metabolite not useful for predicting DNA adducts. N-hydroxy-PhIP-N2-glucuronide was determined to be the best predictor of colon DNA adducts. Because of the low degrees of freedom due to the small sample set, the data were independently reevaluated using the nonparametric random forest analysis. Although this is a less robust test compared with the univariate analysis, the two independent tests provided the same apparent conclusion that N-hydroxy-PhIP-N2-glucuronide was the most important variable in predicting the level of PhIP-DNA adducts in the colon.
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| Discussion |
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Six of the 12 PhIP metabolites were identified as glucuronide conjugates, indicating that glucuronidation plays a significant role in the metabolism of PhIP. The identification of N-hydroxy-PhIP-N2-glucuronide as the major urinary metabolite in all 10 subjects is consistent with earlier studies showing UGT1A1-mediated glucuronidation as being a major pathway in the biotransformation of PhIP (35). The presence of this metabolite also serves as an indirect indicator of PhIP bioactivation because formation of the CYP1A2-mediated reactive intermediate N-hydroxy-PhIP is a prerequisite step to forming N-hydroxy-PhIP-N2-glucuronide (15, 16). These results are contrary to what has been reported for rodents. In both rats and mice, N-hydroxy-PhIP-N2-glucuronide is a minor urinary metabolite. The major metabolite in the rodent is 4'-PhIP-sulfate, indicating that hydroxylation at the 4' position (a detoxification step) is more prevalent in rodents than in humans (36, 37). This could be due to differences in substrate selectivity and oxidation rates of the different CYP450 isozymes between humans and the rodent model. These differences between humans and rodents support the necessity for more human studies to determine if there is an association between specific metabolic pathways, DNA adducts, and carcinogenic outcome.
The finding that glucuronidation is a major detoxification pathway in the biotransformation of PhIP is significant because the capacity to glucuronidate N-hydroxy-PhIP can vary greatly among individuals due to genetic polymorphisms in the UGT1A1 gene. The most notable polymorphisms are variants in the UGT1A1 gene that result in significant down-regulation of UGT1A1 activity. The most prevalent polymorphism is characterized by an allelic variant in the UGT1A1 gene, which contains an additional (TA) dinucleotide repeat in the "A(TA)nTAA" box region of the promoter (38). Wild-type UGT1A1 activity is associated with six repeats, whereas the variant allele contains seven TA repeats (UGT1A1*28). Significant down-regulation of UGT1A1 activity results when this variant is present in both alleles (homozygous). The frequency of occurrence is relatively high at 10% to 12% of the general population. There is evidence to suggest that individuals with the UGT1A1*28 genotype may be at greater risk for cancer from exposure to heterocyclic amines that are conjugated by UGT1A1 because their ability to detoxify these compounds would be diminished (39). For example, a recent study has reported a correlation between the UGT1A1*28 polymorphism and a decreased ability to glucuronidate and detoxify N-hydroxy-PhIP in human liver microsomes (21).
In the current study, seven of the nine individuals that were genotyped for the UGT1A1*28 polymorphism were heterozygous (6 of 7) for the "A(TA)nTAA" repeat. The remaining two subjects were homozygous wild-type (6 of 6). Previous studies have shown that there is no significant difference in UGT1A1 activity between the wild-type and the heterozygous variant (33, 34). Only individuals possessing the homozygous variant (7 of 7) display significant down-regulation of UGT1A1 activity. Therefore, due to the lack of significant UGT1A1 genotype variation and the homogeneity of the study population, UGT1A1 genotype would not be expected to influence the metabolism or the DNA adduct profiles of these individuals. Additional experiments, using a larger study population, are needed to determine the role of UGT1A1 activity on PhIP-DNA adduct formation.
The differences in urinary PhIP metabolite ratios, relative metabolite excretion rates, and DNA and protein adducts between the study subjects suggest that interindividual phenotypic variation of specific enzymes associated with PhIP biotransformation may be contributing to these observed variations. Although it is difficult to make any definite conclusions from the data due to the small sample size, several trends in metabolite excretion rates, DNA adduct levels, and enzyme phenotypes were observed. Subjects 1, 4, and 7, who were categorized as having a rapid CYP1A2 phenotype, had the lowest level of [14C]PhIP bound to colon DNA. These subjects also had the fastest excretion rate and the highest levels of urinary N-hydroxy-PhIP-N2-glucuronide after 24 hours of collection, suggesting that detoxification of N-hydroxy-PhIP predominated over bioactivation. These observations agree with the linear regression analysis that showed that both N-hydroxy-PhIP-N2-glucuronide and CYP1A2 activity were negatively correlated to colon DNA adducts. Furthermore, the univariate analysis showed that N-hydroxy-PhIP-N2-glucuronide levels and CYP1A2 phenotype were also the most important variables in predicting colon DNA adduct levels.
Subjects 8 and 10 also had rapid excretion rates of N-hydroxy-PhIP-N2-glucuronide, although these individuals were categorized as having a slow CYP1A2 phenotype. These two subjects, however, did have a UGT1A3*3 genotype,4 which is associated with increased expression of UGT1A3 (40). The increased expression of UGT1A3 could have contributed to an increase in the formation of N-hydroxy-PhIP-N2-glucuronide (35). In another observation, subject 6 had the highest level of PhIP macromolecular adducts in all three end points (DNA, total protein, and whole tissue) and was the only subject with both NAT2 and SULT1A1 rapid phenotypes. Statistical analysis, however, indicated that there was no correlation (P < 0.05) between the NAT2 or SULT1A1 phenotype and DNA adduct levels. Furthermore, the differences among each individual in the time the colon tissue was harvested after [14C]PhIP exposure and the relative rate of DNA repair could have influenced DNA adduct levels. Further study is needed to determine if these observations are relevant to human cancer risk. Other variables that were excluded from analysis, due to the lack of relevance to PhIP metabolite levels and DNA adducts, were CYP1A1, NAT1, and glutathione S-transferase genotypes (data not shown).
The finding that colon DNA adducts were lower in subjects with a rapid CYP1A2 phenotype and a higher percentage of urinary N-hydroxy-PhIP-N2-glucuronide suggests that detoxification by glucuronidation predominated over bioactivation in these individuals. This was somewhat unexpected because Lang et al. (23) reported a correlation between rapid CYP1A2 and rapid NAT2 activity, with a higher incidence of colon cancer among individuals who consume heterocyclic amines in their diet. The differences between the two studies could be because Lang et al. did not know the precise exposure level of PhIP, whereas in this current study the exact PhIP dose was known. It is also possible that other unknown factors in the diet could have been linked to the carcinogenic outcome in the Lang et al. study. Furthermore, differences in glucuronidation activity among the sample population in the Lang et al. study were not reported. In support of the current study, Sachse et al. (41) reported that CYP1A2 activity was lower in colon cancer patients compared with controls. The low levels of adducts and high percentage of N-hydroxy-PhIP-N2-glucuronide observed in rapid CYP1A2 individuals seen in this present study could partially be explained by the differences in the Km and Vmax values for CYP1A2 and UGT1A1 as well as the phase II activation enzymes (i.e., acetyltransferase and/or sulfotransferase). A high percentage of N-hydroxy-PhIP-N2-glucuronide indicates that the reactive intermediate N-hydroxy-PhIP was detoxified by glucuronidation at a faster rate compared with conjugation by acetyltransferase and/or sulfotransferase, which results in further activation to the DNA-binding species. Therefore, it can be postulated that individuals with compromised UGT activity may be at greater risk from exposure to PhIP than individuals with normal or elevated levels of UGT because their ability to detoxify PhIP will be diminished. These results are consistent with the present understanding of PhIP metabolism (42).
Based on the above observations and from the statistical analysis of the data, it was determined that, out of all the variables investigated, N-hydroxy-PhIP-N2-glucuronide was the best predictor of colon DNA adducts. The subjects with a high percentage of N-hydroxy-PhIP-N2-glucuronide in their urine had the lowest level of PhIP-DNA adducts in their colon. This is the first time a urinary metabolite profile has been linked to a genotoxic end point in humans. These conclusions must be made with caution, however, because they are based on a small study group that may not be representative of the general population. Nevertheless, this pilot study has provided some insight into the disposition of PhIP in a human population at a dietary relevant dose and has served as a basis for continual study to determine if N-hydroxy-N2-glucuronide can serve as a reliable urinary biomarker to predict an individual's propensity to form colon DNA adducts.
| Acknowledgments |
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The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
| Footnotes |
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Received 5/ 1/06. Revised 8/ 3/06. Accepted 8/18/06.
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