| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece [C. N., A. P., J. P. A. I.]; Biomedical Research Institute, Foundation for Research and Technology–Hellas, Ioannina 45110, Greece [J. P. A. I.]; and Division of Clinical Care Research, Department of Medicine, Tufts-New England Medical Center, Tufts University School of Medicine, Boston, Massachusetts 02111 [J. P. A. I.]
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
has been implicated as a risk factor for prostate cancer, but individual studies have been inconclusive or controversial. Therefore we performed a meta-analysis of 10 studies (12 comparisons) with CYP17 genotyping on 2404 patients with prostate cancer and 2755 controls. Overall, the random effects odds ratio (OR) for the A2 (C) versus A1 (T) allele was 1.08 [95% confidence interval (CI), 0.95–1.22], with some between-study heterogeneity (P = 0.04). There was no suggestion of an overall effect either in recessive or dominant modeling of A2 effects, and the comparison of A2/A2 versus A1/A1 also showed no differential susceptibility to prostate cancer (OR, 1.15; 95% CI, 0.91–1.46). No effect of A2 was seen in subjects of European descent (7 comparisons, OR, 1.04; 95% CI, 0.92–1.18, no significant between-study heterogeneity) or Asian descent (2 comparisons, OR, 1.06; 95% CI, 0.66–1.71; P = 0.02 for heterogeneity), whereas A2 increased susceptibility to prostate cancer in subjects of African descent (3 comparisons, OR, 1.56; 95% CI, 1.07–2.28; no between-study heterogeneity). Smaller studies unilaterally showed more prominent genetic effects for A2 than larger studies (P = 0.038). The meta-analysis suggests that the CYP17 polymorphism is unlikely to increase considerably the risk of sporadic prostate cancer on a wide population basis, especially in subjects of European descent. Previously reported associations may reflect publication bias, although it is also possible that the polymorphism may be important in subjects of African descent. |
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
enzyme (3)
. This cytochrome mediates both 17-hydroxylase and 17,20-lyase activities at key points in the testosterone biosynthesis in gonads and adrenals (3)
. The 5'-untranslated promoter region of the CYP17 gene contains a polymorphic T-to-C substitution that gives rise to A1 (T) and A2 (C) alleles (4)
. There is controversy on whether the A2 allele may change the binding characteristics of the promoter region and lead to increased transcription of CYP17 mRNA (4
, 5)
. Molecular epidemiological studies have also presented seemingly contradictory results concerning a potential role of CYP17 in prostate cancer. Some studies have indicated that the A2 allele may be associated with an increased risk of prostate cancer (6, 7, 8, 9, 10, 11)
. However, other investigations have been apparently inconclusive (12
, 13)
or have even reported that the A1 allele may increase the risk of prostate cancer (14
, 15)
. Single studies may have been underpowered to detect dose-response relationships or even overall effects. Given the amount of accumulated data, a quantitative synthesis of the evidence using rigorous methods was deemed important to perform. To address these issues, we conducted a comprehensive meta-analysis of all available studies relating the CYP17 polymorphism to the risk of prostate cancer. We aimed to obtain summary estimates for the strength of the postulated genetic association, estimate the between-study heterogeneity, and find possible explanations for the presence of heterogeneity between studies. |
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
Case-control studies were eligible if they had determined the distribution of CYP17 genotypes in prostate cancer cases and in a concurrent control group of prostate cancer-free subjects using a molecular method for genotyping. We excluded studies or subgroups thereof with familial linkage designs. We accepted disease-free controls regardless of whether they had BPH2 or not. Cases with prostate cancer were eligible regardless of whether they had a first-degree relative with prostate cancer or not. However, we excluded family-based studies of pedigrees with several affected cases per family because their analysis is based on linkage considerations.
Data Extraction.
Two investigators independently extracted the data and reached consensus on all items. The following information was sought from each study: authors; journal and year of publication; country of origin; selection and characteristics of prostate cancer cases and controls; demographics; racial descent of the study population (categorized as European, African, and Asian descent); eligible and genotyped cases and controls; and number of cases and controls for each CYP17 genotype. For studies where subjects of different racial descent were included, data were extracted separately for each race. Furthermore, we examined whether matching had been used, whether there was specific mention of blinding of the personnel who performed the genotyping to the clinical status of the subjects, and whether the genotyping method had been validated. Whenever complete information on distribution of genotypes in cases and controls was missing in a published report, we obtained the pertinent data directly from primary study investigators.
Meta-Analysis.
The primary analysis compared prostate cancer patients against controls for the contrast of A2 versus A1 alleles. This analysis aims to detect overall differences. We also examined the contrast of extremes (homozygotes) A2/A2 versus A1/A1. Finally, we examined the contrast of A2/A2 versus (A1/A2+A1/A1) and (A1/A2+A2/A2) versus A1/A1. These contrasts correspond to recessive and dominant effects, respectively, of the A2 allele.
Because case-control studies were involved, the OR was used as the metric of choice. Studies with subjects of different races were split into separate race-specific comparisons. For each genetic contrast, we estimated the between-study heterogeneity across all eligible comparisons using the 
2
-based Q statistic (16)
. Heterogeneity was considered significant for P < 0.10. Data were combined using both fixed effects (Mantel-Haenszel) and random effects (DerSimonian and Laird) models (17)
. Random effects incorporate an estimate of the between-study variance and tend to provide wider CIs when the results of the constituent studies differ among themselves. In the absence of between-study heterogeneity, the two methods provide identical results. Random effects are more appropriate when heterogeneity is present (17)
.
Subgroup analyses estimated race-specific ORs for the A2 versus A1 contrast. Beyond race, studies were not consistent about adjusting for other parameters such as age, smoking, or family history and presented different genetic contrasts for the adjusted analyses. Therefore, we examined whether the unadjusted analyses yielded similar OR estimates as the adjusted/stratified analyses whenever reported.
We also performed cumulative meta-analysis (18)
and recursive cumulative meta-analysis (19
, 20)
to evaluate whether the summary OR for the A2 versus A1 contrast changed over time as more data accumulated. Inverted funnel plots and the Begg-Mazumdar publication bias diagnostic (nonparametric 
correlation coefficient; Ref. 21
) evaluated whether the magnitude of the observed association was related to the variance of each study.
Analyses were conducted in SPSS 10.0 (SPSS, Inc., Chicago, IL), StatXact (Cytel, Inc., Boston, MA), and Meta-Analyst (Joseph Lau, Boston, MA). All P values are two-tailed.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
. There was a considerable diversity of ethnic groups. Six studies (6, 7, 8
, 11
, 13
, 15)
selected prostate cancer patients based on a histological diagnosis from biopsy and/or prostatectomy, whereas the other four (9
, 10
, 12
, 14)
did not clarify the exact criteria used for the diagnosis of prostate cancer. Two studies (11
, 14)
mentioned that they included a small proportion of patients with a first-degree relative with prostate cancer, one study (13)
specifically excluded such patients, whereas the remaining did not clarify the background of family history. Controls did not have a clinical diagnosis of prostate cancer, but the amount of additional screening [with digital rectal examination, prostate-specific antigen (<4 ng/ml), needle biopsy or prostate resection] to exclude prostate cancer differed substantially across studies (Table 1)
.
|
Meta-Analysis Database.
The eligible studies included a total of 2442 patients with prostate cancer and 2816 controls of whom 2404 and 2755, respectively, had genotype data. Allele and genotype frequencies per group are shown in Table 2
. The A2 allele was more highly represented among controls of Asian descent [44% (95% CI, 41–47)] than in controls of European descent [39% (95% CI, 37–40)] or African descent [31% (95% CI, 25–37)]. Overall, the prevalence of A2/A2 homozygosity was 18, 15, and 10% in control subjects of Asian, European, and African descent, respectively. The respective prevalence rates of A1/A2 heterozygosity were 52, 48, and 42%, and the respective rates for A1/A1 homozygosity were 30, 37, and 48%. The distribution of genotypes in control groups was consistent with Hardy-Weinberg equilibrium in all studies, with the exception of Yamada et al. (8)
, where there was a significant deficit of both homozygote genotypes (P = 0.01). A sensitivity analysis was thus performed excluding this study.
|
. The summary OR was 1.08 by random effects (P = 0.24) and 1.04 by fixed effects (P = 0.29). However, there was significant heterogeneity between the 12 study comparisons (P = 0.04). Excluding the one study where Hardy-Weinberg equilibrium was violated in the controls (8)
brought the results even closer to the null (OR, 1.05; 95% CI, 0.93–1.19; P = 0.43 by random effects and OR, 1.03; 95% CI, 0.95–1.11; P = 0.53 by fixed effects), but there was still some between-study heterogeneity (P = 0.053).
|
. On the contrary, no differences were observed in allele distribution between prostate cancer patients and controls in European and Asian descent subgroups (Table 3)
. There was no significant between-study heterogeneity in comparisons of subjects of European descent (P = 0.15), whereas there was significant heterogeneity (P = 0.02) between the two studies performed in subjects of Asian descent, with a trend for an association between A2 and prostate cancer seen only in the study without Hardy-Weinberg equilibrium in the control group.
|
. No evidence for an association with prostate cancer was discerned also when recessive and dominant models were examined for the effect of A2. There was no between-study heterogeneity in the recessive model contrast, whereas significant heterogeneity (P = 0.003) was seen for the dominant model contrast (Table 3)
.
Adjusted/stratified Analyses for Age and Other Factors.
Three studies (10
, 13
, 14)
provided only unadjusted analyses. The other studies provided some estimates taking also age into account [either by stratification (6, 7, 8)
or as a continuous adjusting variable (9
, 11
, 12
, 15)
]. Smoking status was also considered in one study (9)
and having a relative with prostate cancer in another (11)
. In four studies (8
, 9
, 11
, 12) , the adjusted and unadjusted estimates practically coincided (difference in ORs < 0.03). In the other three studies (6
, 7 , 15)
, the adjusted OR was slightly smaller than the unadjusted OR for the effects of either A2/A2 or A1/A2+A2/A2 versus A1/A1. In Gsur et al. (7)
, adjusted and unadjusted OR for the contrast A2/A2 versus A1/A1 were 2.65 and 2.80, respectively. In the comparison of prostate cancer versus non-BPH controls in Habuchi et al. (15)
, the adjusted and unadjusted OR for the contrast of A2/A2 versus A1/A1 were 0.39 and 0.44, respectively. Finally, in Lunn et al. (6)
, adjusted and unadjusted OR for the contrast A1/A2+A2/A2 versus A1/A1 were 1.66 versus 1.75, respectively. Therefore, the adjusted analyses would probably bring the summary OR for the comparison of A2 versus A1 alleles (1.08 based on unadjusted data) closer toward the null.
In two stratified analyses (6
, 8)
, A2/A2 and A1/A2 seemed to confer a significant susceptibility to prostate cancer in younger subjects (subgroups 
64 and <72 years old, respectively). Conversely, in another stratified analysis (7)
, A2/A2 and A1/A2 conferred susceptibility to prostate cancer in older patients (subgroup >66 years old), whereas a protective trend was seen in the younger group. Thus, there was no consistent evidence for a greater susceptibility in younger or older patients.
Other Bias Diagnostics.
In cumulative meta-analysis and recursive cumulative meta-analysis, the magnitude of the summary OR had been stable and not changing in the same direction over time (by random effects, summary OR for A2 versus A1: 1.10 at the end of 1999, 1.07 at the end of 2000, 1.12 at the end of 2001, and 1.08 in 2002). However, the inverted funnel plot was potentially asymmetric. There was a significant correlation between the variance of each study and the magnitude of the OR ( = 0.52, P = 0.038 considering the 10 studies; = 0.44, P = 0.046 considering the 12 comparisons with racial subgroups considered separately), suggesting that a relationship between A2 and prostate cancer was seen unilaterally in the smaller studies.
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
For subjects of European descent, the meta-analysis excludes any clinically meaningful overall effect of this polymorphism on prostate cancer risk. No overall effect is seen among Asian descent subjects, but data seem heterogeneous and one study lacks Hardy-Weinberg equilibrium in the control group. Conversely, the polymorphism may play a role in susceptibility to prostate cancer among subjects of African descent. If the association between this polymorphism and prostate cancer holds true, especially in subjects of African descent, this may be because of gene by gene or gene by environment interactions or may be a reflection of a pattern of linkage disequilibrium with other more important polymorphisms, which is unique to men of African descent. However, the currently available data on men of African descent are still very limited and thus should be interpreted with caution. A few more studies may be required in African Americans or other African-derived groups. African Americans have a higher incidence of prostate cancer, present with more advanced disease and at younger ages, and have a worse prognosis than subjects of other ethnicities (24, 25, 26, 27) . This differential profile is not entirely explained by lifestyle, dietary, socioeconomic, or clinical factors (25, 26, 27) , thus genetic parameters may be important. In the meta-analysis database, the A2 allele was slightly less frequent in subjects of African versus European descent, whereas an opposite trend has been observed in a different study (28) . Overall, these two racial groups may exhibit little difference in A2 frequency.
The meta-analysis findings may be interpreted against the postulated biological context of the CYP17 polymorphism. One study has shown that white men with the A2/A2 genotype have 0.5 SDs higher bioavailable testosterone than men with the A1/A1 genotype, and A1/A2 heterozygotes have intermediate values (29) . However, other studies have found no differences in the levels of testosterone or other androgens and metabolites thereof (dehydrotestosterone, androstanediol glucuronide) according to CYP17 genotypes in men (9 , 30) . Most studies in women also do not suggest major influences on hormonal levels (31, 32, 33) . An early study suggested that the A2 allele creates an additional Sp1-binding site in the CYP17 promoter region (4) . Subsequently, Nedelcheva Kristensen et al. (5) did not document Sp1 binding at this polymorphic site or within the promoter region of CYP17 in general, whereas Lin et al. (34) found that Sp1 is an essential factor for CYP17 transcription in human adrenal NCI-H295A cells. Overall, evidence that the A2 allele increases androgen levels is weak and inconsistent. The exact role of androgens in prostate cancer is a contentious issue (1 , 35 , 36) . If androgens participate in the causal pathway of prostate cancer (1 , 35 , 36) , a null effect of the CYP17 polymorphism on androgen levels would be consistent with the results of the meta-analysis.
The CYP17 polymorphism may not be an important population-wide risk factor for prostate cancer. Genome scans have typically not identified significant linkage in the 10q24.32 chromosomal region where the CYP17 gene is located (37 , 38) . A recent meta-analysis of 15 comparisons (39) also concluded that this polymorphism does not seem to play a significant role in susceptibility to breast cancer in women, another type of cancer where hormonal influences are considered to be important. Data on other conditions potentially affected by endogenous sex hormone levels such as endometrial cancer (32 , 40) , ovarian cancer (41 , 42) , hepatocellular carcinoma (43) , and polycystic ovaries (44) are more limited and don’t always show consistent associations. A larger number of studies and many more genotyped subjects are required to clarify these postulated associations.
The meta-analysis was consistently based on unadjusted estimates, but we took care to account for racial effects. Moreover, the reported adjusted estimates taking age into consideration suggest that the overall results would probably shift even closer to the null, if age-adjusted analyses were consistently available. We should acknowledge that the meta-analysis could not address conclusively familial prostate cancer. One study with pedigrees of 
3 prostate cancer cases/family (mean, 5.08; Ref. 12
) has suggested a possible link of prostate cancer with the CYP17 gene region, but the LOD score was only 1.3. However, hereditary forms of prostate cancer with many members affected per family are not very common (38)
. Associations limited to strictly hereditary forms are unlikely to have a substantial population attributable fraction for prostate cancer. Conversely, it is common to encounter families where two first-degree relatives or one first-degree relative and at least two second-degree relatives are affected. This pattern may account for 10–20% of all cases of the disease (38)
. Future studies should explore specifically whether the CYP17 polymorphism may have any effect on the risk of prostate cancer specifically in this setting.
Attention should also be given to the design of individual studies. The results of meta-analyses may be affected by methodological problems and potential biases in the designs of the constituent studies. Quality deficiencies may sometimes affect the magnitude of the observed association. Nondifferential misclassification errors may dilute the strength of an observed association. In the CYP17 studies, genotyping was performed with appropriate methods, thus genotype errors are unlikely to have influenced the results substantially. However, controls were not screened consistently across studies to exclude subclinical, latent prostate cancer. Control groups of the different studies were also not equally well characterized as to the extent of inclusion of subjects with BPH. The inclusion or not of subjects with BPH in the control group may affect the results if the CYP17 polymorphism affects BPH. One study found a difference between controls with versus without BPH in the frequency of the A2 allele (15) , but another study has shown no effect of this polymorphism on prostate volume (45) . Moreover, some young control subjects may have developed prostate cancer at older ages. The lifetime risk of prostate cancer in American men is estimated at 16% (46) , therefore the dilution of the OR would not be very large. The choice of an appropriate age-window for assessing a postulated genetic risk factor for prostate cancer is difficult. Studies of younger subjects may be more suitable for identifying risk factors that result in early carcinogenesis. Conversely, selection of younger subjects may be less appropriate, if hormonal or other influences regulated by the postulated risk factor are more important in later ages (35) .
Cases of prostate cancer included in most of these studies are those brought to therapeutic attention, and this may differ from cases diagnosed from population screening. However, there is no reason why the CYP17 genotype distribution would be affected by this selection. Moreover, cases and controls may have been recruited through different sources, but they were ethnically matched and with one exception, they were also well matched for age. Finally, even among cases with prostate cancer, some misclassification might be unavoidable, if cases were unconfirmed by histology. However, this potential misclassification should not have affected a considerable proportion of the cancer cases.
Notwithstanding these considerations, one should not overemphasize subgroup analyses of age or other factors. For CYP17, age subgroup analyses in different studies have reached opposite conclusions, perhaps as a result of chance and multiple comparisons. The summary results do not support a strong overall effect. A very large number of subjects are needed to establish or refute a genetic association of modest magnitude (47) and even larger numbers are needed to validate subgroup differences, let alone more subtle associations such as gene-gene and gene-environment interactions. Given the large number of potential genetic risk factors that may be probed, several initial observations may not be validated by subsequent evidence (47) .
|
Acknowledgments |
|---|
|
Footnotes |
|---|
1 To whom requests for reprints should be addressed, at Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece. Phone: 011-3026510-97807; Fax: 011-3026510-97867; E-mail: jioannid{at}cc.uoi.gr 
2 The abbreviations used are: BPH, benign prostatic hyperplasia; OR, odds ratio; CI, confidence interval.
Received 6/27/02; revised 11/ 8/02; accepted 11/16/02.
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
-hydroxylase/17,20 lyase): similarity with the gene for P450c21. DNA (N. Y.), 6: 439-448, 1987.[Medline]
-reductase type II (SRD5A2) genes on prostate-cancer risk among the Japanese population. Int. J. Cancer, 92: 683-686, 2001.[Medline]
gene (CYP17) polymorphism predicts use of hormone replacement therapy. Cancer Res., 59: 3908-3910, 1999. (CYP17) gene is associated with bioavailability testosterone levels and bone size in men. J. Bone Miner. Res., 16: 911-917, 2001.[Medline]
-reductase (SRD5A2) genes and serum androgen concentrations in men. Cancer Epidemiol. Biomark. Prev., 10: 185-189, 2001.-hydroxylase/17,20 lyase) in human adrenal NCI-H295A cells. Mol. Endocrinol., 15: 1277-1293, 2001.This article has been cited by other articles:
|
|
 |
|
  J. Beuten, J. A.L. Gelfond, J. L. Franke, K. S. Weldon, A. C. Crandall, T. L. Johnson-Pais, I. M. Thompson, and R. J. Leach Single and Multigenic Analysis of the Association between Variants in 12 Steroid Hormone Metabolism Genes and Risk of Prostate Cancer Cancer Epidemiol. Biomarkers Prev., June 1, 2009; 18(6): 1869 - 1880. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. L. Banez, M. K. Terris, W. J. Aronson, J. C. Presti Jr., C. J. Kane, C. L. Amling, and S. J. Freedland Race and Time from Diagnosis to Radical Prostatectomy: Does Equal Access Mean Equal Timely Access to the Operating Room?--Results from the SEARCH Database Cancer Epidemiol. Biomarkers Prev., April 1, 2009; 18(4): 1208 - 1212. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Hamada, T. Sissung, D. K. Price, R. Danesi, C. H. Chau, N. Sharifi, D. Venzon, K. Maeda, K. Nagao, A. Sparreboom, et al. Effect of SLCO1B3 Haplotype on Testosterone Transport and Clinical Outcome in Caucasian Patients with Androgen-Independent Prostatic Cancer Clin. Cancer Res., June 1, 2008; 14(11): 3312 - 3318. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
V. W. Setiawan, F. R. Schumacher, C. A. Haiman, D. O. Stram, D. Albanes, D. Altshuler, G. Berglund, J. Buring, E. E. Calle, F. Clavel-Chapelon, et al. CYP17 Genetic Variation and Risk of Breast and Prostate Cancer from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) Cancer Epidemiol. Biomarkers Prev., November 1, 2007; 16(11): 2237 - 2246. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 O. Cussenot, A. R. Azzouzi, N. Nicolaiew, G. Fromont, P. Mangin, L. Cormier, G. Fournier, A. Valeri, S. Larre, F. Thibault, et al. Combination of Polymorphisms From Genes Related to Estrogen Metabolism and Risk of Prostate Cancers: The Hidden Face of Estrogens J. Clin. Oncol., August 20, 2007; 25(24): 3596 - 3602. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Park, L. Chen, L. Ratnashinge, T. A. Sellers, J.-P. Tanner, J.-H. Lee, N. Dossett, N. Lang, F. F. Kadlubar, C. B. Ambrosone, et al. Deletion Polymorphism of UDP-Glucuronosyltransferase 2B17 and Risk of Prostate Cancer in African American and Caucasian Men. Cancer Epidemiol. Biomarkers Prev., August 1, 2006; 15(8): 1473 - 1478. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. A. Trikalinos, G. Salanti, M. J. Khoury, and J. P. A. Ioannidis Impact of Violations and Deviations in Hardy-Weinberg Equilibrium on Postulated Gene-Disease Associations Am. J. Epidemiol., February 15, 2006; 163(4): 300 - 309. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. Mononen, E. H. Seppala, P. Duggal, V. Autio, T. Ikonen, P. Ellonen, J. Saharinen, J. Saarela, M. Vihinen, T. L.J. Tammela, et al. Profiling Genetic Variation along the Androgen Biosynthesis and Metabolism Pathways Implicates Several Single Nucleotide Polymorphisms and Their Combinations as Prostate Cancer Risk Factors Cancer Res., January 15, 2006; 66(2): 743 - 747. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. F. Skibola, P. M. Bracci, R. A. Paynter, M. S. Forrest, L. Agana, T. Woodage, K. Guegler, M. T. Smith, and E. A. Holly Polymorphisms and Haplotypes in the Cytochrome P450 17A1, Prolactin, and Catechol-O-Methyltransferase Genes and Non-Hodgkin Lymphoma Risk Cancer Epidemiol. Biomarkers Prev., October 1, 2005; 14(10): 2391 - 2401. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. L. Parnes, I. M. Thompson, and L. G. Ford Prevention of Hormone-Related Cancers: Prostate Cancer J. Clin. Oncol., January 10, 2005; 23(2): 368 - 377. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Ntais, A. Polycarpou, and J. P.A. Ioannidis Association of GSTM1, GSTT1, and GSTP1 Gene Polymorphisms with the Risk of Prostate Cancer: A Meta-analysis Cancer Epidemiol. Biomarkers Prev., January 1, 2005; 14(1): 176 - 181. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Spinola, P. Pedotti, T. A. Dragani, and E. Taioli Meta-Analysis Suggests Association of L-myc EcoRI Polymorphism with Cancer Prognosis Clin. Cancer Res., July 15, 2004; 10(14): 4769 - 4775. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. J. Schaid The complex genetic epidemiology of prostate cancer Hum. Mol. Genet., April 1, 2004; 13(90001): R103 - 121. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Ntais, A. Polycarpou, and J. P. A. Ioannidis Vitamin D Receptor Gene Polymorphisms and Risk of Prostate Cancer: A Meta-analysis Cancer Epidemiol. Biomarkers Prev., December 1, 2003; 12(12): 1395 - 1402. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Ntais, A. Polycarpou, and J. P. A. Ioannidis SRD5A2 Gene Polymorphisms and the Risk of Prostate Cancer: A Meta-Analysis Cancer Epidemiol. Biomarkers Prev., July 1, 2003; 12(7): 618 - 624. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Meeting Abstracts Online |
