This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Rebbeck, T. R. Articles by Malkowicz, S. B. Search for Related Content PubMed PubMed Citation Articles by Rebbeck, T. R. Articles by Malkowicz, S. B.

Glutathione S-Transferase-µ (GSTM1) and - (GSTT1) Genotypes in the Etiology of Prostate Cancer¹

Departments of Biostatistics and Epidemiology [T. R. R., A. H. W., J. M. J., D. L. W.] and Urology [A. J. W., S. B. M.], University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104

	Abstract

Top Abstract Introduction Materials and Methods Results Discussion References

 
The glutathione S-transferases (GSTs) are involved in the metabolism of numerous potential prostate carcinogens. Common homozygous germ-line deletions exist in the genes that encode GST-|gm (GSTM1) and GST- (GSTT1) and preclude enzyme expression. To evaluate whether GSTM1 and/or GSTT1 contribute to prostate cancer (CaP) etiology, we studied 237 incident CaP cases and 239 age- and race-matched controls. The probability of having CaP was increased in men who had nondeleted (functional) genotypes at GSTT1 (odds ratio, 1.83; 95% confidence interval, 1.19–2.80) but not GSTM1 (odds ratio, 1.07; 95% confidence interval, 0.74–1.55). No interaction of these genes in CaP etiology was observed. GST- is highly expressed in the prostate and can produce genotoxic effects upon exposure to specific carcinogens. These results suggest that GSTT1 is associated with CaP risk.

	Introduction

Top Abstract Introduction Materials and Methods Results Discussion References

 
The GSTs³ µ (GSTM1; chromosome 1p13.3) and (GSTT1; chromosome 22q11.2) catalyze the conjugation of glutathione to numerous potentially genotoxic compounds, including aliphatic aromatic heterocyclic radicals, epoxides, or arene oxides. Glutathione S conjugates, particularly those formed by the activity of GST-, may also produce genotoxic intermediates (1, 2, 3) . GSTM1 and GSTT1 have distinct structures, kinetic properties, and substrate specificities (4 , 5) . Common homozygous deletions exist at GSTM1 in 40–60% of the United States Caucasian population (6) and at GSTT1 in 20–30% of the United States Caucasian population (6) . Absent GST enzyme in individuals who have these deletions may result in poorer elimination of electrophilic carcinogens, which may result in increased risk of somatic mutation leading to tumor formation. Alternatively, GSTT1 is expressed at high levels in the prostate (3) , suggesting that the activation of compounds to genotoxic intermediates by GSTT1 could increase CaP risk. We hypothesize that CaP risk may be modified by GSTM1 and/or GSTT1. To evaluate this hypothesis, we undertook a case-control study to evaluate the role of GSTM1 and GSTT1 in CaP etiology.

	Materials and Methods

Top Abstract Introduction Materials and Methods Results Discussion References

 
Study Subjects and Data Collection.
A sample of 237 incident CaP cases was identified through Urological Oncology Clinics at the HUP between September 1994 and April 1998. Case status was confirmed by medical records review using a standardized abstraction form. Men were excluded from this study if they reported having exposure to finasteride (Proscar) at the time of their CaP diagnosis. Patients who were nonincident cases (i.e., those diagnosed more than 12 months before the date of study ascertainment) or had a prior diagnosis of cancer at any site were also excluded. The mean age of diagnosis was 60.0 years (SD, 6.0 years) with a range of 42–82 years.

The 239 controls studied here were men attending HUP general medicine clinics. These clinics see a patient population that is demographically similar to those seen in the Urological Oncology clinics at HUP. These men were ascertained concurrently with the CaP cases (i.e., between September 1994 and April 1998). Controls were excluded from this study if they ever had an abnormal PSA test (i.e., 4 ng/dl), if they had ever had an abnormal digital rectal examination, if they had a previous cancer diagnosis, or if they reported having had exposure to finasteride (Proscar) at the time of study ascertainment. Controls were frequency matched to cases on age and race. However, because the frequency matching was approximate, analyses adjusted for age and race were also undertaken to account for residual variation due to these factors. The mean age of these men at the time of their clinic visit was 61.0 years (SD, 8.4 years), with a range of 40–91 years.

Risk factor, medical history, and CaP diagnostic information was obtained by using a standardized questionnaire and review of medical records. Information collected included CaP occurrences in first- and second-degree relatives, personal history of benign prostatic hyperplasia and vasectomy, previous cancer diagnoses, demographic information such as race, educational level, and occupation, and CaP screening history. All study subjects provided informed consent for participation in this research under a protocol approved by the Committee for Studies Involving Human Subjects at the University of Pennsylvania.

GSTM1 and GSTT1 Genotype Analysis.
Genomic DNA for the present study was self-collected by each study subject using sterile cheek swabs (Cyto-Pak Cytosoft Brush; Medical Packaging Corp., Camarillo, CA) and processed using a protocol modified from Richards et al. (7) . Briefly, the swab brush was placed inside a 1.5-ml microcentrifuge tube, and 600 µl of 50 mM NaOH was added. The closed tube was vortexed for 10 min and then heated at 95°C for 10 min. Finally, 120 µl of 1 M Tris (pH 8.0) were added, after which the brush was removed and discarded. The resulting biosample was used for PCR-based genotype analyses.

The complete gene deletion at GSTM1 was determined by using a PCR-based assay that modified the protocol of Davies et al. (8) . Four primer sequences were used to amplify GSTM1. The ß-globin gene was amplified to serve as a positive internal control. These primers were GME4, 5'-CTG CCC TAC TTG ATT GAT GGG; GMN5, 5'-CTG GAT TGT AGC AGA TCA TGC; Beta-Globin 1, 5'-CAA CTT CAT CCA CGT TCA CC; and Beta-Globin 3, 5'-CAT GGT GCA TCT GAC TCC T. The PCR reaction mix consisted of 5 µl of 10x buffer [100 mM Tris-HCl (pH 9), 500 mM KCl, 1% (v/v) Triton, and 15 mM MgCl₂), 1 µl of 10 mM deoxynucleotide triphosphates, 5 µl each of the four primers at 5 µM concentration, 10 µl of template DNA, and 0.3 µl of Taq polymerase in 13.7 µl of double-distilled H₂O, for a reaction volume of 50 µl. The PCR temperature profile consisted of 1 cycle of 94°C for 3 min and 1 cycle of 82°C for 1 min, at which time the Taq polymerase was added to the reaction mixture. This was followed by 30 cycles of 94° for 1 min, 55°C for 1 min, and 72°C for 2 min, ending with an elongation step at 72°C for 10 min. Visualization of the amplification products was accomplished on a 2% agarose gel after staining with ethidium bromide.

GSTT1 genotypes were generated using a modification of the protocol of Pemble et al. (9) . Four primers were used to amplify GSTT1 and a ß-globin positive internal control. These primers were: GSTT1–1, 5'-TTC CTT ACT GGT CCT CAC ATC TC-3'; GSTT1–2, 5'-TCA CCG GAT CAT GGC CAG CA-3'; ß-globin-1, 5'-CAA CTT CAT CCA CGT TCA CC-3'; and ß-globin-2, 5'-GAA GAG CCA AGG ACA GTT AC-3'. The reaction mixture included 2.5 µl of 10x PE Buffer II (Perkin-Elmer), 0.25 µl of 100x BSA, 1.0 µl of 25 mM Mg²⁺, 0.5 µl of 10 mM deoxynucleotide triphosphates, 2.5 µl each of the four 5 µM primers, 6.0 µl of template DNA, and 0.3 µl of Taq polymerase in 4.45 µl double-distilled H₂O, for a total reaction volume of 25 µl. The PCR temperature cycling profile consisted of 1 cycle of 93°C for 2 min 20 s and 1 cycle of 82°C for 1 min, at which time the Taq polymerase was added to the reaction mixture. This was followed by 20 cycles of 93°C for 1 min, 60°C with a decrease of 0.5°C per cycle for 1 min, and 72°C for 1 min, 15 cycles of 93°C for 1 min, 50°C for 1 min, 72°C for 1 min, and a final extension step of 72°C for 7.5 min. Visualization of the amplification products was accomplished on a 4% agarose gel after staining with ethidium bromide.

Analytical Methods.
Four genotype classes were considered for analysis: (a) homozygous deletion genotypes at GSTM1 (denoted GSTM1–0 or "functional" GSTM1) were compared with genotypes for which at least one none-deleted allele was present (denoted GSTM1-1or "non-functional" GSTM1); (b) the same definition was used to distinguish GSTT1-0 and GSTT1-1 genotypes. The GSTM1-1 and GSTT1-1 genotypes did not distinguish between those individuals who were homozygous for a nondeleted allele and those who were heterozygous for a nondeleted allele; (c) an interaction genotype was defined in which an individual had both GSTM1-0 and GSTT1-0 (denoted GST-0). Individuals who had at least one nondeleted allele at either GSTM1 or GSTT1 were denoted GST-1; and (d) an interaction genotype was defined in which an individual had either GSTM1-0 or GSTT1-0 (denoted GST1-0). Individuals who had inherited nondeleted alleles at both GSTM1 and GSTT1 were denoted GST1-1.

Descriptive analyses for discrete traits were carried out using contingency table methods and ² or Fisher’s Exact test statistics. Means or medians were used to summarize continuously distributed traits, and nonparametric Kruskal-Wallis statistics were used to compare these values across groups (e.g., between cases and controls). Genotype disease associations were undertaken using unconditional logistic regression. Analyses considered the effect of genotype unadjusted for potential confounders and adjusted for age (at time of diagnosis in cases or time of study ascertainment in controls) and race (coded as a discrete variable with three levels: Caucasian, African American, or other). All P values were based on two-sided hypothesis tests.

	Results

Top Abstract Introduction Materials and Methods Results Discussion References

 
Table 1 presents a description of the sample population. Consistent with most previous reports, mean PSA levels were significantly higher in cases than controls, and cases were significantly more likely to have a family history of CaP than controls.

We also evaluated whether one locus modified the effects of the other locus by fitting models that contained both GSTM1 and GSTT1. The adjusted OR effects at each locus did not change substantially from those estimates obtained from the univariate genotype models. The adjusted OR effect associated with GSTM1 controlling for GSTT1 and other covariates was 1.06 (95% CI, 0.73–1.55), whereas the GSTM1 estimate not controlling for GSTT1 was 1.07 (95% CI, 0.74–1.55; Table 2 ). Similarly, the adjusted OR associated with GSTT1 controlling for GSTM1 and other covariates was 1.84 (95% CI, 1.20–2.83), whereas the GSTT1 estimate not controlling for GSTM1 was 1.83 (95% CI, 1.19–2.83; Table 2 ). To further evaluate the independence of GSTM1 and GSTT1 genotypes, we also compared the distribution of GSTM1 and GSTT1 among cases only. In 95 GSTM1-0 cases, 18 (19%) were GSTT1-0. Among 94 GSTM1-1 cases, 17 (18%) were GSTT1-0 (Fisher’s Exact test, P > 0.99). This implies the effect of each of these genes on CaP is independent (e.g., additive) rather than interactive (e.g., multiplicative).

Compared with GSTM1-1/GSTT1-0 genotypes (the referent class), individuals with GSTM1-0/GSTT1-0 genotypes were not at increased risk (OR, 1.15; 95% CI, 0.55–2.43), whereas individuals with GSTM1-1/GSTT1-1 and GSTM1-0/GSTT1-1 genotypes were at increased risk (OR, 2.04; 95% CI, 1.13–3.68; and OR, 1.89; 95%CI, 1.04–3.42, respectively). These results further indicate that an increase in risk occurred only among those with a GSTT1-1 genotype. Therefore, we conclude that CaP risk may be increased by GSTT1-1 (i.e., the presence of GST- enzyme), and that this effect is largely independent of GSTM1.

	Discussion

Top Abstract Introduction Materials and Methods Results Discussion References

 
We report that men who do not have homozygous deletions at GSTT1 (i.e., whose GST- protein is presumably expressed and functional) are at increased CaP risk. Although our results are largely hypothesis generating, these findings are consistent with knowledge that GST- produces genotoxic metabolites in response to specific exposures (1, 2, 3) . There is substantial evidence that glutathione S conjugates derived from halogenated alkanes, halogenated alkenes, hydroquinones, quinones, aminophenols, and other compounds can cause cellular and DNA damage (reviewed in Ref. 10 ). Many of these compounds are commonly found as occupational exposures, and some are known carcinogens. Glutathione metabolic intermediates from ethylene dibromide, 1,2,3,4-diepoxybutane, methyl bromide, epibromohydrin, 1,3-dichloroacetone, and methylene chloride are mutagenic (1 , 2) . Epidemiological evidence has provided further support that these compounds may be involved in prostate carcinogenesis. For example, cellulose triacetate-fiber workers exposed to methylene chloride may have a significantly elevated CaP mortality (11) . Other occupations with increased CaP risk include those that may involve exposure to halogenated alkanes or alkenes, such as the rubber industry (12) . However, there has been little consistency in these reports (13) , and these potentially carcinogenic exposures may be found in a wide range of exposures. GSTT1 is expressed at high levels in the prostate (3) , suggesting that the activation of specific carcinogenic compounds to genotoxic intermediates by GSTT1 may occur in the prostate itself. Thus, our results support the inference that carcinogen activation by GSTT1 may play a role in prostate carcinogenesis.

Information about biological differences in the activity of GSTT1 relative to GSTM1 may further help to identify pathways involved in prostate carcinogenesis. There does not appear to be a single class of chemical compounds that is associated with GSTM1 or GSTT1 metabolism. Despite functional similarity, the two loci also have different substrate specificities. These include metabolism of benzo(a)pyrene, styrene-7,8-oxide, and trans-stilbene oxide by GSTM1, and of epoxybutanes, ethylene oxide, halomethanes, and methyl bromide by GSTT1. Therefore, it is plausible that GSTT1 metabolizes a compound or set of compounds distinct from those metabolized by GSTM1, which could elucidate specific pathways of prostate carcinogenesis.

Although GSTT1 is the most recently identified and one of the lesser studied of the GST multigene family (14) , a great deal is known about the activity of the GSTs in general. In addition to metabolism of chemical carcinogens, described above, the GSTs metabolize steroid hormones, compounds found in the diet, and other agents potentially involved in CaP etiology. The GSTs are thought to be involved in the intracellular transport of steroid hormones (15) and are involved in the isomerization of androst-5-ene-3,17-dione to androst-4-ene-3,17-dione, the immediate precursor of testosterone (16) . The hypothesis that presence of GST- may be involved in hormone-mediated prostate carcinogenesis requires additional investigation. The GSTs are also involved in the metabolism of numerous dietary compounds. For example, dietary fat consumption can result in an increase in GST activity (17) , and dietary lipids are substrates for GST metabolism (16) . Somatic hypermethylation of deoxycytidine residues in CpG islands in the 5' regulatory region of GSTP1 eliminates GST- expression in the majority of prostate tumors (18) and prostatic intraepithelial neoplasia (19) . Harries et al. (20) have reported case-control study results that suggest germ-line variability at GSTP1 is associated with CaP risk. These results provide additional support for the hypothesis that the GST family may be acting on multiple levels of prostate carcinogenesis. Therefore, the GSTs may play a role in prostate carcinogenesis by modulating the metabolism of androgens or other exposures.

We have reported OR effects associated with GSTT1 that are relatively small (<2), as may be expected for genes involved in the metabolism of a myriad of carcinogenic compounds. However, because a large proportion of the population has a functional allele GSTT1, the population-attributable risk associated with GSTT1-1 genotypes may be large. For example, we can assume a GSTT1-1 frequency in the United States population to be P = 0.76–0.85 (Ref. 6 ), and an adjusted OR effect of the functional state of 1.83 (Table 2) . We can then estimate the percent attributable risk of CaP due to GSTT1-1 using the formula 100% x P (OR - 1)/[P (OR - 1) + 1] (Ref. 21 ). The resulting attributable risk range is 39–41%. Although these estimates are at best rough approximations, they suggest that a sizable proportion of CaP may be explained by the effect of GSTT1-1 genotypes.

We also considered a number of potential study limitations. The observed GSTT1-0 frequency in controls (0.31; Table 2 ) was somewhat higher than that reported in other U.S. populations (0.15–0.24; Ref. 6 ). This higher estimate may be explained by the fact that our sample included Asian and African Americans, who have higher rates of GSTT1-0 than United States Caucasians (6) . Among Caucasian controls, the GSTT1-0 frequency was 0.24. This value is within the range reported previously and suggests that the present results cannot be explained by an elevated GSTT1-0 frequency in controls. Our correction for race as a confounder in multiple logistic regression models (Table 2) also minimizes the potential for population stratification as an explanation for the present findings. It is unlikely that genotyping errors could account for an elevated proportion of GSTT1-0 in controls but not cases. Positive internal and external controls were used in all assays to limit the possibility of PCR failures being typed as a homozygous deletion genotype. All genotype readings were done blinded to case status. Therefore, it is unlikely that genotype errors induced significant bias in the OR estimates reported in Table 2 . The analyses were not adjusted for multiple comparisons, because only eight hypothesis tests were undertaken. However, a simple Bonferroni correction of our significance levels can be applied, P* = p/n, where p is the standard P cutpoint of 0.05, n is the total number of tests conducted, and P* is the adjusted P level for assessing statistical significance given the multiple tests. The corrected P required to conclude statistical significance using this correction would be 0.006. The P associated with the GSTT1 association in Table 2 was 0.005. Therefore, even with a very stringent correction for multiple hypothesis tests, we can conclude that there is a significant association between GSTT1 and prostate cancer.

Misclassification of case or control status could also have influenced the inferences of this study. Cases were all confirmed to have disease by medical records review, and it is highly unlikely that cases were misclassified. No control reported ever being told they had a diagnosis of CaP, nor were controls who had any history of elevated PSA or abnormal digital rectal exam included in this study. Medical records review confirmed that no control was diagnosed with CaP. Controls could have had latent disease that was not detectable by either PSA and/or digital rectal exam, or the disease may have arisen between the time these tests had been done and time of ascertainment, but without the patient’s knowledge. This misclassification might bias the OR toward the null hypothesis. If that were the case, the true OR effects might be higher those reported here. If we assume that 10% of controls had a latent (undetected) CaP at the time of their participation in this study, then the unadjusted OR associated with GSTM1 would be essentially the same (1.04) as that estimated using the available data (Table 2) , and the GSTT1 OR estimate would be 1.73 (compared with 1.83; Table 2 ). Although it is highly unlikely that as many as 10% of controls were misclassified, the OR estimates assuming this misclassification rate are not substantially different than those reported in Table 2 .

As described above, GST- is highly expressed in the prostate and can produce genotoxic effects upon exposure to specific carcinogens. The GSTs role in steroid hormone metabolism may be an additional pathway through which GSTT1 may be acting in prostate carcinogenesis. Although not providing any information about the mechanism of action, our results do indicate that men who have a nondeleted (presumably functional) GSTT1 genotype, and can therefore express prostate-specific GST-, may be at increased risk of CaP. By identifying specific compounds that may be metabolized by GSTT1, novel pathways of prostate carcinogenesis may be identified.

	Acknowledgments

 
We thank Peter Shields for his extremely helpful discussion of this paper. We thank Drs. D. Goldmann, W. Greer, G. W. Crooks, D. A. Horowitz, D. Farhadi, M. D. Cirigliano, M. Rusk, V. Weil, S. J. Gluckman, and C. Guerra for their valuable assistance in ascertaining study subjects.

	Footnotes

 
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.

¹ This study was supported by USPHS Grant ES08031 (to T. R. R.) and a grant from the University of Pennsylvania Cancer Center.

² To whom requests for reprints should be addressed, at Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, 904 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021. Phone: (215) 898-1793; Fax: (215) 573-2265; E-mail: rebbeck{at}cceb.med.upenn.edu

³ The abbreviations used are: GST, glutathione S-transferase; CaP, prostate cancer; HUP, Hospital of the University of Pennsylvania; PSA, prostate-specific antigen; OR, odds ratio; CI, confidence interval.

Received 10/13/98; revised 1/29/99; accepted 2/15/99.

	References

Top Abstract Introduction Materials and Methods Results Discussion References

 

1. Thier R., Taylor J. B., Pemble S. E., Humphreys W. G., Persmark M., Ketterer B., Guengerich F. P. Expression of mammalian glutathione S-transferase 5–5 in Salmonella typhimurium TA1535 leads to base-pair mutations upon exposure to dihalomethanes. Proc. Natl. Acad. Sci. USA, 90: 8576-8580, 1993.[Abstract/Free Full Text]
2. Hallier E., Schroeder K. R., Asmuth K., Donnermuth A., Aust B., Goergens H. W. Metabolism of dichloromethanes (methylene chloride) to formaldehyde in human erythrocytes: influences of polymorphism of glutathione S-transferase theta (GST T1-1). Arch. Toxicol., 68: 423-427, 1994.[Medline]
3. Sherrat P. J., Pulford D. J., Harrison D. J., Green T., Hayes J. D. Evidence that human theta class glutathione S-transferase T1-1 can catalyse the activation of dichloromethane, a liver and lung carcinogen. Biochem. J., 326: 837-846, 1997.
4. Armstrong R. N. Glutathione S-transferases: reaction mechanism, structure, and function. Chem. Res. Toxicol., 4: 131-140, 1991.[Medline]
5. Ketterer B., Christodoulides L. G. Enzymology of cytosolic glutathione S-transferases. Adv. Pharmacol., 27: 37-69, 1994.
6. Rebbeck T. R. Molecular epidemiology of the human glutathione S-transferase genotypes GSTM1 and GSTT1 in cancer susceptibility. Cancer Epidemiol. Biomark. Prev., 6: 733-743, 1997.[Abstract]
7. Richards B., Skoletsky J., Shuber A. P., Balfour R., Stern R. C., Dorkin H. L., Parad R. B., Witt D., Klinger K. W. Multiplex PCR amplification from the CFTR gene using DNA prepared from buccal brushes/swabs. Hum. Mol. Genet., 2: 159-163, 1993.[Abstract/Free Full Text]
8. Davies M. H., Elias E., Acharya S., Cotton W., Faulder G. C., Fryer A. A., Strange R. C. GSTM1 null polymorphism at the glutathione S-transferase M1 locus: phenotype and genotype studies in patients with primary biliary cirrhosis. Gut, 34: 549-553, 1993.[Abstract/Free Full Text]
9. Pemble S., Schroeder K. R., Spencer S. R., Meyer D. J., Hallier E., Bolt H. M., Ketterer B., Taylor J. B. Human glutathione S-transferase theta (GSTT1): cDNA cloning and the characterization of genetic polymorphism. Biochem. J., 300: 271-276, 1994.
10. Dekant W., Vamvakas S. Glutathione-dependent bioactivation of xenobiotics. Xenobiotica, 23: 873-887, 1993.[Medline]
11. Gibbs G. W., Amsel J., Soden K. A cohort mortality study of cellulose triacetate-fiber workers exposed to methylene chloride. J. Occup. Env. Med., 38: 693-697, 1996.[Medline]
12. Goldsmith D. F., Smith A. H., McMichael A. J. A case-control study of CaP within a cohort of rubber and tire workers. J. Occup. Med., 22: 533-541, 1980.[Medline]
13. Meyer D. J., Coles B., Pemble S. E., Gilmore K. S., Fraser G. M., Ketterer B. Theta, a new class of glutathione S-transferases purified from rat and man. Biochem. J., 274: 409-414, 1991.
14. Straif K., Weiland S. K., Werner B., Chambless L., Mundt K. A., Keil U. Workplace risk factors for cancer in the German rubber industry. Part 2. Mortality from non-respiratory cancers. Occup. Env. Med., 55: 325-332, 1998.[Abstract]
15. Listowsky I., Abramovitz M., Homma H., Niitsu Y. Intracellular binding and transport of hormones and xenobiotics by glutathione-S-transferases. Drug Metab. Rev., 19: 305-318, 1988.[Medline]
16. Hayes J. D., Pulford D. J. 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, 1995.[Medline]
17. Hietanen E., Ahotupa M., Heikela A., Laitinen M. Dietary cholesterol-induced changes of xenobiotic metabolism in liver. II. Effects of phenobarbitone and carbon tetrachloride on activities of drug-metabolizing enzymes. Drug-Nutrient Interact., 1: 313-327, 1982.
18. Lee W. H., Morton R. A., Epstein J. I., Brooks J. D., Campbell P. A., Bova G. S., Hsieh W. S., Isaacs W. B., Nelson W. G. Cytidine methylation of regulatory sequences near the pi-class glutathione S-transferase gene accompanies human prostatic carcinogenesis. Proc. Natl. Acad. Sci. USA, 91: 11733-11737, 1994.[Abstract/Free Full Text]
19. Brooks J. D., Weinstein M., Lin X. H., Sun Y. H., Pin S. S., Bova G. S., Epstein J. I., Isaacs W. B., Nelson W. G. CG island methylation changes near the GSTP1 gene in prostatic intraepithelial neoplasia. Cancer Epidemiol. Biomark. Prev., 7: 531-536, 1998.[Abstract]
20. Harries L. W., Stubbins M. J., Forman D., Howard G. C., Wolf C. R. Identification of genetic polymorphisms at the glutathione S-transferase Pi locus and association with susceptibility to bladder, testicular and CaP. Carcinogenesis (Lond.), 18: 641-644, 1997.[Abstract/Free Full Text]
21. Ed. 2 Lillienfeld, A. M. Lillienfeld, D. E. eds. . Foundations of Epidemiology, : Oxford University Press New York 1980.

This article has been cited by other articles:

				J. M. Marzec, J. D. Christie, S. P. Reddy, A. E. Jedlicka, H. Vuong, P. N. Lanken, R. Aplenc, T. Yamamoto, M. Yamamoto, H.-Y. Cho, et al. Functional polymorphisms in the transcription factor NRF2 in humans increase the risk of acute lung injury FASEB J, July 1, 2007; 21(9): 2237 - 2246. [Abstract] [Full Text] [PDF]

				N. L. Nock, D. Tang, A. Rundle, C. Neslund-Dudas, A. T. Savera, C. H. Bock, K. G. Monaghan, A. Koprowski, N. Mitrache, J. J. Yang, et al. Associations between Smoking, Polymorphisms in Polycyclic Aromatic Hydrocarbon (PAH) Metabolism and Conjugation Genes and PAH-DNA Adducts in Prostate Tumors Differ by Race Cancer Epidemiol. Biomarkers Prev., June 1, 2007; 16(6): 1236 - 1245. [Abstract] [Full Text] [PDF]

				N. L. Nock, X. Liu, M. S. Cicek, L. Li, F. Macarie, B. A. Rybicki, S. J. Plummer, G. T. MacLennan, G. Casey, and J. S. Witte Polymorphisms in polycyclic aromatic hydrocarbon metabolism and conjugation genes, interactions with smoking and prostate cancer risk. Cancer Epidemiol. Biomarkers Prev., April 1, 2006; 15(4): 756 - 761. [Abstract] [Full Text] [PDF]

				R. K. Nam, W. W. Zhang, M. A.S. Jewett, J. Trachtenberg, L. H. Klotz, M. Emami, L. Sugar, J. Sweet, A. Toi, and S. A. Narod The Use of Genetic Markers to Determine Risk for Prostate Cancer at Prostate Biopsy Clin. Cancer Res., December 1, 2005; 11(23): 8391 - 8397. [Abstract] [Full Text] [PDF]

				R. K. Nam, W. W. Zhang, J. Trachtenberg, M. A. S. Jewett, M. Emami, D. Vesprini, W. Chu, M. Ho, J. Sweet, A. Evans, et al. Comprehensive Assessment of Candidate Genes and Serological Markers for the Detection of Prostate Cancer Cancer Epidemiol. Biomarkers Prev., December 1, 2003; 12(12): 1429 - 1437. [Abstract] [Full Text] [PDF]

				R. K. Nam, W. W. Zhang, J. Trachtenberg, E. Diamandis, A. Toi, M. Emami, M. Ho, J. Sweet, A. Evans, M. A.S. Jewett, et al. Single Nucleotide Polymorphism of the Human Kallikrein-2 Gene Highly Correlates With Serum Human Kallikrein-2 Levels and in Combination Enhances Prostate Cancer Detection J. Clin. Oncol., June 15, 2003; 21(12): 2312 - 2319. [Abstract] [Full Text] [PDF]

				R. Aplenc, H. Zhao, T. R. Rebbeck, and K. J. Propert Group Sequential Methods and Sample Size Savings in Biomarker-Disease Association Studies Genetics, March 1, 2003; 163(3): 1215 - 1219. [Abstract] [Full Text] [PDF]

				C. H. van Gils, R. M. Bostick, M. C. Stern, and J. A. Taylor Differences in Base Excision Repair Capacity May Modulate the Effect of Dietary Antioxidant Intake on Prostate Cancer Risk: An Example of Polymorphisms in the XRCC1 Gene Cancer Epidemiol. Biomarkers Prev., November 1, 2002; 11(11): 1279 - 1284. [Abstract] [Full Text] [PDF]

				E. P. Gelmann, D. J. Steadman, J. Ma, N. Ahronovitz, H. J. Voeller, S. Swope, M. Abbaszadegan, K. M. Brown, K. Strand, R. B. Hayes, et al. Occurrence of NKX3.1 C154T Polymorphism in Men with and without Prostate Cancer and Studies of Its Effect on Protein Function Cancer Res., May 1, 2002; 62(9): 2654 - 2659. [Abstract] [Full Text] [PDF]

				E. L. Goode, J. L. Stanford, M. A. Peters, M. Janer, M. Gibbs, S. Kolb, M. D. Badzioch, L. Hood, E. A. Ostrander, and G. P. Jarvik Clinical Characteristics of Prostate Cancer in an Analysis of Linkage to Four Putative Susceptibility Loci Clin. Cancer Res., September 1, 2001; 7(9): 2739 - 2749. [Abstract] [Full Text] [PDF]

				C.-A. Sun, L.-Y. Wang, C.-J. Chen, S.-N. Lu, S.-L. You, L.-W. Wang, Q. Wang, D.-M. Wu, and R. M. Santella Genetic polymorphisms of glutathione S-transferases M1 and T1 associated with susceptibility to aflatoxin-related hepatocarcinogenesis among chronic hepatitis B carriers: a nested case-control study in Taiwan Carcinogenesis, August 1, 2001; 22(8): 1289 - 1294. [Abstract] [Full Text] [PDF]

				S. A. Geisler and A. F. Olshan GSTM1, GSTT1, and the Risk of Squamous Cell Carcinoma of the Head and Neck: A Mini-HuGE Review Am. J. Epidemiol., July 15, 2001; 154(2): 95 - 105. [Abstract] [Full Text] [PDF]

				P. A. Kanetsky, R. Holmes, A. Walker, D. Najarian, J. Swoyer, D. Guerry, A. Halpern, and T. R. Rebbeck Interaction of Glutathione S-Transferase M1 and T1 Genotypes and Malignant Melanoma Cancer Epidemiol. Biomarkers Prev., May 1, 2001; 10(5): 509 - 513. [Abstract] [Full Text]

				S. N. Kelada, S. L. R. Kardia, A. H. Walker, A. J. Wein, S. B. Malkowicz, and T. R. Rebbeck The Glutathione S-Transferase-{micro} and -{{theta}} Genotypes in the Etiology of Prostate Cancer: Genotype-Environment Interactions with Smoking Cancer Epidemiol. Biomarkers Prev., December 1, 2000; 9(12): 1329 - 1334. [Abstract] [Full Text]

This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Rebbeck, T. R. Articles by Malkowicz, S. B. Search for Related Content PubMed PubMed Citation Articles by Rebbeck, T. R. Articles by Malkowicz, S. B.