Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2009 Sep 15.
Published in final edited form as: Int J Cancer. 2008 Sep 15;123(6):1385–1389. doi: 10.1002/ijc.23687

Joint effects of inflammation and androgen metabolism on prostate cancer severity

Timothy R Rebbeck 1,2,*, Hanna Rennert 3, Amy H Walker 1, Saarene Panossian 1, Teo Tran 1, Kyle Walker 1, Elaine Spangler 1, Margerie Patacsil-Coomes 1, Rajeev Sachdeva 4, Alan J Wein 2,5, S Bruce Malkowicz 2,4,5, Charnita Zeigler-Johnson 1
PMCID: PMC2700293  NIHMSID: NIHMS58389  PMID: 18566991

Abstract

Multiple pathways of prostate carcinogenesis have been proposed, including those involving androgen metabolism and inflammation. These pathways are not independent, and may act together in prostate cancer etiology: androgens promote both inflammatory processes and serve as mitogens in prostate tumor growth. To explore the possible joint effects of these pathways in prostate cancer severity, we studied 1,090 Caucasian prostate cancer cases to evaluate whether tumor severity is influenced by a history of benign prostatic hyperplasia (BPH) interacting with genotypes involved in inflammation or androgen metabolism including MSR1, RNASEL, AR, CYP3A4, CYP3A43, CYP3A5 and SRD5A2. We observed a statistically significant interaction between a number of genotypes and BPH. After considering the potential for false positive associations, the only remaining significant associations involved CYP3A43 P340A genotypes and history of BPH on both Gleason grade (interaction p-value = 0.026) and tumor stage (interaction p-value = 0.017). These results suggest that androgen metabolism may act in concert with inflammatory phenotypes such as BPH in determining prostate cancer severity.

Keywords: prostate cancer, gene interactions, hormone metabolism, inflammation

The relationship between prostate cancer and physiological states with inflammatory components, including chronic prostatitis, proliferative inflammatory atrophy (PIA) and benign prostatic hypertrophy (BPH), is not well understood. BPH has been widely studied, but it is not understood whether BPH is a prostate cancer precursor lesion, or whether BPH simply shares similar risk factors and histological proximity with prostate cancer.1 In epidemiologic studies, measurement error and bias probably have limited the ability to tease apart the relationship between BPH and prostate cancer risk.2

Despite the limitations of epidemiological data in establishing the relationship of prostate cancer with states that have an inflammatory component, including BPH, there is growing evidence that chronic inflammation plays an important role in prostate carcinogenesis. PIA are highly proliferating cells that sometimes lead to high-grade prostatic intraepithelial neoplasia (PIN), and have been linked with prostate cancer risk.1,3,4 Atrophy in and around BPH nodules in the transition zone of the prostate may be PIA.3 As a result, some have proposed that BPH may be a form of PIA that occurs in the transitional zone.3 Prostate inflammation can arise from a number of sources3 including infection, hormonal exposures and injury that lead to exposure to reactive oxygen species and DNA damage. In addition, a number of genes have been identified that are associated with prostate cancer risk or severity and are also involved in immune/inflammatory processes. These include MSR1, RNASEL, toll-like receptors, MUC1 and a number of genes that encode the interleukins and their receptors.3,5

Steroid hormones and the genes that regulate them may also influence prostate carcinogenesis by at least 2 mechanisms. First, androgens are known to influence the immune and inflammatory responses.6,7 In the prostate, androgen withdrawal induces expression of genes involved in the immune/inflammatory response including members of the interleukin and interferon families.8–10 Chronic administration of exogenous androgens (sometimes in the presence of exogenous estrogens) induces or suppresses a number of genes in the interferon and interleukin families,8,9 some of which genes have androgen response promoter elements. There is also evidence for crosstalk between the androgen and interferon signaling pathways that involve both the androgen receptor (AR) and RNASEL that may contribute to cell survival and suppression of apoptosis in prostate carcinogenesis.10 An inverse relationship is thought to exist between declining androgen levels and age in older men.11 Therefore, it has been hypothesized that early inflammatory events stimulated by steroid hormone exposures may be required for prostate carcinogenesis.12 Second, androgens regulate the growth and differentiation of the prostate as well as of BPH and prostate tumors.13 It is well established that androgens serve as signaling growth factors in prostate tissue, through binding with AR to cause cellular proliferation to promote prostate carcinogenesis.14,15

While there is ample evidence for a role of inflammation as well as androgen metabolism in prostate carcinogenesis, interactions between these pathways in prostate cancer etiology is not well understood. We propose a model based on the schema of Palapattu et al.16 and Ho et al.12 that hypothesizes immune/inflammatory events causing chronic inflammation and PIA, PIN and/or BPH are associated with predisposition to prostate cancer, and that these events are regulated by genes that control androgen exposure as well as the immune/inflammatory response (Fig. 1). To address this hypothesis, we undertook a study of 1,090 Caucasian prostate cancer cases to evaluate whether interactions between BPH and genes involved in either inflammatory/immune and androgen metabolism pathways are associated with prostate cancer severity.

Figure 1.

Figure 1

Open in a new tab

Model of inflammatory and androgenic influences on prostate cancer etiology and outcome.

Methods

Study participants and data collection

A sample of 1,090 Caucasian incident prostate cancer cases was identified through Urologic Oncology Clinics at multiple hospitals of the University of Pennsylvania Health System (UPHS) and the adjacent Philadelphia Veteran's Administration Hospital between 1995 and 2006. Case status was confirmed by medical records review using a standardized abstraction form. Cases were excluded from our study if they reported having exposure to finasteride (Proscar) at the time of their prostate cancer diagnosis. Patients who were nonincident cases (i.e., those diagnosed more than 12 months prior to the date of study ascertainment), or had a prior diagnosis of cancer at any site except nonmelanoma skin cancer, were also excluded.

Risk factor, medical history, prostate cancer screening history and prostate cancer diagnostic information was obtained using a standardized questionnaire and review of medical records. Information collected included personal history of BPH and vasectomy, previous cancer diagnoses and demographic information and prostate cancer screening history. Our definition of BPH was based around clinically evident or symptomatic BPH based on evidence from patient or clinician reports as confirmed in medical records. Therefore, this research reflects the association of clinically apparent BPH rather than a broader definition of BPH that may also include screened-detected BPH, although the latter may be under-ascertained in our sample. All study participants provided written informed consent for participation in this research under a protocol approved by the Committee for Studies Involving Human Subjects at the University of Pennsylvania and the Philadelphia Veteran's Administration Hospital.

Biosample collection and genotype analysis

Genomic DNA for the present study was self-collected by each study participant using sterile cheek swabs (Cyto-Pak Cytosoft Brush, Medical Packaging Corporation, Camarillo, CA), and processed using either a protocol modified from Richards et al. (43) as described previously (44) or using a modified protocol on the Qiagen 9604B robot with the QIAamp 96 DNA Buccal Swab Biorobot Kit (Valencia, CA). Genotypes were determined for putatively functional variants in a series of candidate androgen metabolism genes.

We chose candidate prostate cancer genotypes hypothesized to be involved in prostate carcinogenesis that may predict disease severity in 2 pathways: androgen metabolism and hereditary prostate cancer genes thought to be involved in inflammation. In each of these genes, we selected a variant that was most likely to be causally relevant based on prior associations or functional data. To ensure sufficient power for our interaction analyses, we only considered SNPs with a frequency of 5% or greater in every stratum defined by tumor characteristics (Gleason grade or tumor stage) and history of BPH. The variants selected for analysis were ARCAG repeat, SRD5A2 A49T (rs9282858), CYP3A4*1B (rs2740574), CYP3A5*3 (rs776746) and CYP3A43*3 (P340A;rs680055),17 MSR1 TTAdel and RNASEL Arg462Gln (rs486907). Genotypes were determined as previously described.17–19 For AR genotype determination, we used forward primer sequence 5′-TCC AGA ATC TGT TCC AGA GCG TG-3′ and reverse sequence 5′-GCT GTG AAG GTT GCT GTT CCT CAT-3′. Using the GC-Rich Kit (Roche), the 25 μl PCR reaction mixture included 6.5 μl double-distilled H2O, 5 μl reaction buffer, 5 μl resolution solution, 0.5 μl enzyme mix, 2.5 μM of each primer (2×) and 2 μl template DNA. The temperature profile for the PCR reaction was 1 cycle of 95°C for 3 min; 10 cycles of 95°C for 30 sec, 57°C for 30 sec, 62°C for 45 sec; 30 cycles of 95°C for 30 sec, 57°C for 30 sec, 62°C for 45 sec plus 5 sec per cycle; 1 cycle of 72°C for 7 min; and a final hold at 10°C. Sequencing was completed using the reverse PCR primer.

Statistical methods

For genotype associations, we considered univariate and joint effects of each candidate gene with ever/never history of BPH. For all genes, we combined putative risk alleles based on functional information into binary genotype classes. For genotypes at each locus, we combined hypothesized risk alleles based on functional information into binary genotype classes coded 0 to represent the baseline risk genotype, and 1 to represent the “variant” genotype. Genotype associations were undertaken using unconditional logistic regression adjusted for age and educational attainment. Other confounders were explored, but only age and education changed the genotype point estimate by 10% or more, or were associated with a significance level of p < 0.10. We further evaluated whether there were differences in the association of genotypes by tumor characteristics, including organ-confined tumors (i.e., stages T1 and T2) and tumors diagnosed with extracapsular extension or metastasis (i.e., stages T3 and T4) as well as Gleason grade (i.e., Gleason sum < 7 and Gleason sum > 7).

A 2-sided p-value of 0.05 or less was considered statistically significant. However, because we have performed multiple hypothesis tests, we also considered the potential for false-positive findings. Accordingly, we applied the false-positive report probability approach20 that allows the investigator to interpret the results of hypothesis testing to ensure against making false-positive inferences. Our primary hypotheses involved tests for interaction among genotypes and BPH. We considered 14 a priori hypotheses involving interaction and 58 main effects corresponding to a total of 72 hypothesis tests. All analyses were performed in STATA (version 9.0, STATA Corporation, College Station, TX).

Results

Table I presents characteristics of the 1,090 Caucasian prostate cancer cases and genotype frequencies. The mean age of diagnosis for the sample as a whole was 60.9 years (SD = 7.3 years). Overall, 23% of men in our study sample had a history of BPH. This proportion was similar across stage and grade groups. Genotype frequencies at all loci were consistent with previously reported distributions in Caucasian men.17,19

Table I.

Descriptive Characteristics of the Prostate Cancer Case Sample

Variable Total (N = 1,090) Gleason < 7 (N = 619) Gleason ≥ 7 (N = 417) TNM stage 1–2 (N = 802) TNM stage 3–4 (N = 260)
Mean age at diagnosis in years (SD) 60.9 (7.3) 60.4 (7.5) 61.0 (6.8) 61.2 (7.2) 59.1 (6.7)
BPH Never 720 (77%) 336 (66%) 291 (76%) 440 (72%) 170 (78%)
Ever 221 (23%) 130 (28%) 90 (24%) 171 (28%) 48 (22%)
AR-CAG ≥20 Repeats 404 (69%) 212 (66%) 163 (72%) 260 (69%) 101 (69%)
<20 Repeats 184 (31%) 108 (34%) 62 (28%) 118 (31%) 46 (31%)
CYP3A4 Any *1B 59 (7%) 30 (7%) 23 (6%) 41 (7%) 12 (6%)
*1A/*1A 788 (93%) 408 (93%) 338 (94%) 535 (93%) 194 (94%)
CYP3A5 *3/*3 681 (85%) 350 (85%) 299 (87%) 466 (86%) 176 (24%)
Any *1 121 (15%) 61 (15%) 46 (13%) 78 (14%) 24 (12%)
CYP3A43 340PP 514 (76%) 273 (77%) 226 (82%) 365 (80%) 126 (79%)
Any 340A 159 (24%) 83 (23%) 50 (18%) 92 (20%) 34 (21%)
MSR1 No TTA/del 43 (10%) 18 (8%) 23 (12%) 26 (9%) 15 (13%)
Any TTA/del 387 (90%) 198 (82%) 175 (88%) 274 (91%) 97 (87%)
RNASEL 462RR 203 (42%) 107 (45%) 85 (43%) 146 (43%) 45 (36%)
Any 462Q 283 (58%) 129 (55%) 146 (63%) 196 (57%) 78 (63%)
SRD5A2 49AA 697 (94%) 351 (94%) 301 (94%) 479 (94%) 159 (92%)
Any 49T 46 (6%) 23 (6%) 20 (6%) 28 (6%) 13 (8%)
Open in a new tab

Table II presents the results of the main effects, stratum-specific effects and interactions of genotypes and BPH on Gleason grade and tumor stage. The left-most column of results in Table II presents the main effect of genotype disregarding BPH status. The top row of results in Table II presents the main effect of BPH disregarding genotype. We observed no significant association between history of BPH and tumor severity for either Gleason grade or tumor stage. We also identified no statistically significant main effects of any genotype with tumor grade or stage.

Table II.

Odds Ratios1 and 95% Confidence Intervals for Main Effects and Interactions of Candidate Genotypes and History of BPH on Tumor Severity

Gleason grade (<7 vs. ≥7) TNM stage (<TNM 1,2 vs. >TNM 3,4)
Genotype main effect No prior BPH Prior BPH Interaction p-value Genotype main effect No prior BPH Prior BPH Interaction p-value
BPH main effect – (1) 0.82 (0.59–1.13) – – (1) 0.85 (0.59–1.25) –
Gene Variant class
AR-CAG ≤ 20 Repeats (1) (Ref) 0.77 (0.47–1.26) 0.994 (1) (Ref) 0.96 (0.55–1.68) 0.556
>20 Repeats 0.79 (0.54–1.16) 0.79 (0.51–1.21) 0.78 (0.36–1.68) 1.03 (0.67–1.57) 0.96 (0.59–1.57) 1.25 (0.56–2.78)
CYP3A4 Any *1B (1) (Ref) 0.37 (0.09–1.55) 0.282 (1) (Ref) 1.11 (0.23–5.26) 0.778
*1A/*1A 1.14 (0.64–2.01) 0.93 (0.48–1.80) 0.88 (0.62–1.23) 1.25 (0.64–2.45) 1.34 (0.62–2.93) 0.82 (0.55–1.23)
CYP3A5 *3/*3 (1) (Ref) 0.90 (0.63–1.29) 0.483 (1) (Ref) 0.83 (0.55–1.26) 0.687
Any *1 0.81 (0.53–1.25) 0.89 (0.54–1.47) 0.62 (0.24–1.57) 0.79 (0.48–1.32) 0.74 (0.41–1.35) 1.06 (0.36–3.10)
CYP3A43 340PP (1) (Ref) 2.08 (0.80–5.44) 0.026 (1) (Ref) 3.50 (1.21–10.17) 0.017
Any 340A 1.41 (0.94–2.12) 1.82 (1.15–2.87) 0.66 (0.44–0.99) 0.96 (0.61–1.52) 1.27 (.75–2.15) 0.78 (0.48–1.26)
MSR1 No TTA/del (1) (Ref) 0.25 (0.06–1.06) 0.116 (1) (Ref) 0.78 (0.35–1.76) 0.800
Any TTA/del 0.69 (0.36–1.33) 0.49 (0.22–1.10) 0.89 (0.56–1.42) 0.59 (0.30–1.17) 0.56 (0.25–1.25) 1.23 (0.68–2.23)
RNASEL 462RR (1) (Ref) 0.48 (0.24–0.95) 0.042 (1) (Ref) 0.77 (0.18–3.23) 0.336
Any 462Q 1.39 (0.95–2.02) 1.09 (0.70–1.68) 1.23 (0.72–2.11) 1.26 (0.82–1.95) 1.11 (0.67–1.84) 0.96 (0.56–1.64)
SRD5A2 49AA (1) (Ref) 0.77 (0.54–1.10) 0.018 (1) (Ref) 0.90 (0.59–1.37) 0.169
Any 49T 1.01 (0.53–1.90) 0.62 (0.30–1.30) 11.35 (1.24–104.33) 1.26 (0.62–2.58) 0.97 (0.42–2.24) 2.89 (0.57–14.73)
Open in a new tab
1

Odds ratios adjusted for age and educational attainment.

The joint effect of genotype and BPH is presented as 3 odds ratios, all referent to the control stratum, which was defined as the group of individuals who did not carry the risk genotype and did not have prior BPH (denoted “(Ref)” in Table II): first, the effect of genotype among those with no prior BPH; second, the effect of BPH among those without the putative risk genotype; and finally the multiplicative interaction of BPH and genotype on the log odds scale. We observed a number of statistically significant interactions involving CYP3A43, RNASEL and SRD5A2 (Table II).

First, we observed a statistically significant interaction between CYP3A43 genotypes and history of BPH with both tumor stage (pinteraction = 0.017) and Gleason grade (pinteraction = 0.026). Individuals who carry any 340A genotype at CYP3A43 had a higher probability of having an unfavorable Gleason grade tumor if they also had no prior BPH (OR = 1.82, 95% CI: 1.15–2.87). In contrast, those homozygous for the 340P allele are protected from having an unfavorable Gleason grade if they had a prior history of BPH (OR = 0.66, 95% CI: 0.44–0.99). A nonstatistically significant increased probability of having a higher grade tumor was also observed in men with both prior BPH and who were homozygous for the 340P allele. We also observed a significantly increased probability of having a high stage tumor among men who had both prior BPH and carried any Ala allele at CYP3A43 (OR = 3.50, 95% CI: 1.21–10.17). The direction of the other odds ratios involved in this interaction was similar to that seen for Gleason grade.

Second, we observed a statistically significant interaction of RNASEL R462Q genotypes with BPH (pinteraction = 0.042). Men who are homozygous for the 462R allele and who have a prior BPH are less likely to have a high-grade tumor than men who had no prior BPH and this same genotype (OR = 0.48, 95% CI: 0.24–0.95).

Third, we observed a statistically significant interaction of SRD5A2 A49T (pinteraction = 0.018) genotypes with BPH on Gleason grade. Men who have any 49T allele and who have a prior BPH are more likely to have a high-grade tumor than men who had no prior BPH and did not carry a 49T allele (OR = 11.35, 95% CI: 1.24–104.33).

To evaluate whether the statistically significant associations reported in Table II represent false-positive findings, we calculated the false-positive report probability20 for associations in which statistically significant interactions were observed by assuming prior probabilities of association to be 0.05, 0.1 and 0.2. For 2 main effect odds ratios that we reported as statistically significantly different from an odds ratio of 1.0, the false-positive report probability was less than 0.2 even for a low prior probability of association. The 2 associations that appeared to be the least likely to be false positive effects based on these criteria both involved CYP3A43 and BPH. In the first situation, an OR = 1.82 (95% CI: 1.15–2.87) was observed for the relationship of these factors with Gleason grade (Table II). In the second situation, an OR = 3.5 (95% CI: 1.21–10.17) was observed for the relationship of these factors with tumor stage. A false-positive report probability of 0.2 or less was observed when the prior probability of these associations was assumed to be 0.05 or more. That is, these estimated odds ratios can be considered likely to be true-positive associations only when the prior probability for this association is assumed to be 0.05 or more. This prior probability may be reasonable given the biologic plausibility that the androgenic activity of CYP3A43 could be involved in mediating the biologic effect of prostate inflammation. For the remaining statistically significant interactions and the associated stratum-specific OR's, FPRP probabilities were not lower than 0.3 and the best of these FPRP probabilities were only seen for very high prior probabilities of >0.1. Therefore, we cannot exclude the possibility that these associations represent false positive reports, and we conclude that only those that involve CYP3A43 (Table II) represent noteworthy findings.

Discussion

Prostate carcinogenesis has been hypothesized to involve both inflammation and androgen exposure. To date, neither epidemiological studies nor molecular approaches have resolved whether BPH is a direct precursor of prostate cancer or whether it is not a precursor but shares similar risk factors and histological proximity to prostate cancer.1 In part, the difficulty in resolving the BPH-prostate cancer relationship may be confounded by the use of prostate cancer screening, where the presence of BPH may directly influence prostate cancer detection and diagnosis.

PIA, sometimes leading to high grade PIN, has been linked with prostate cancer risk.1,3 BPH can be considered a form of PIA.3 cDNA microarray analysis of BPH and prostate cancer revealed that patients with the severe form of BPH and patients with prostate cancer exhibit similar genetic alterations involving primarily growth regulating and signaling genes, stroma-associated genes and immunological genes.21 Thus, it is likely that chronic inflammation, including PIA/BPH, plays a role in prostate carcinogenesis. Furthermore, androgens are involved both in the generation of chronic inflammation and as growth factors that promote the proliferation and growth of prostate tumors. Therefore, it is reasonable to hypothesize that prostate tumors initiated under conditions of chronic inflammation are fed by androgen exposures to lead to clinically more severe tumor phenotypes (Fig. 1).

The data presented here support this hypothesis. We observed interactions of BPH with a number of candidate genes, including RNASEL, CYP3A43 and SRD5A2. After considering the potential that these interactions and stratum-specific odds ratios represented false positive findings, only the associations involving CYP3A43 remained noteworthy. CYP3A43 may catalyze the oxidative metabolism of testosterone into less active metabolites including 2β-, 6β- and 15β-hydroxytestosterone.22 The function of the CYP3A43 P340A variant is not known, but it has been previously reported in 2 independent studies17,23 to be associated with increased prostate cancer risk. In the present study, we report that the increased risk of high Gleason grade or high stage prostate cancer appears in men homozygous for the 340P allele who have had prior BPH, as well as in those that have both the 340A allele and no history of BPH. Men with any 340A allele and prior BPH are protected from high-grade tumors. These results suggest that the CYP3A4 P340A variant may modulate the effect of BPH on prostate cancer severity. While our stated hypothesis is that androgen metabolism may drive prostate cancer etiology, there is also a relationship between inflammation and estrogen metabolism.24 Since CYP3A43 may act in the metabolism of both androgens and estrogens, the present results do not clarify whether the effect of CYP3A43 is through androgen metabolism pathways, through the related estrogen metabolism pathways, or both. Additional studies are required to further inform the specific hormonal effects that explain our observations.

There are a number of limitations to the analyses presented here. We have attempted to assess first-order interactions between a selected set of candidate genotypes and BPH. The power to address these interactions is limited, so we have not considered some rare variants in the present analyses. In addition, the variants studied here may not be causative of the effects we report, particularly if they are in linkage disequilibrium with other variants in these genes. We assessed BPH by using self report and medical records that were available from patients in our study. No systematic assessment of BPH was used on all patients in our study. Therefore, it is possible that we have misclassified the true prevalence of BPH in the men studied here. This misclassification would tend to bias the association of BPH with prostate cancer toward the null hypothesis. However, because men with symptoms of BPH may be more likely to be screened for prostate cancer, it is not clear how this misclassification may affect the association with disease severity as reported here. Furthermore, it is difficult to assess the direction or magnitude of bias that may be acting to influence genotype-BPH interactions in disease severity. A related concern of our approach is that the anatomical location of BPH or prostate tumors was not available. Therefore, our analyses are unable to asses whether the inflammation that is relevant to prostate carcinogenesis may be localized to the transitional zone or other areas of the prostate, and may not reflect a prostate-wide phenomenon. Finally, we specified a large number of a priori hypothesis tests, and it was therefore important to determine if we detected false-positive associations. We have computed the false-positive report probability of Wacholder et al.20 to aid in interpreting our findings. In situations which we have observed statistically significant associations (Table II), the false-positive report probability results led us to conclude that some of the associations identified here were not noteworthy. Thus, we have been conservative in our interpretation of our results, despite statistically significant p-values for some associations. Although we have limited our analyses to evaluate first-order interactions between genotypes and BPH, the sample sizes for the joint effects of these factors sometimes were very small. Therefore, we may not have the power to detect some important effects in groups for which the joint genotype-BPH interaction effects were small. Despite these limitations, the present results suggest that further exploration of the relationship between chronic inflammation and genes involved in inflammation or androgen-mediated growth may be of interest.

Acknowledgments

This study was supported by grants from the Public Health Service (R29-ES08031, R01-CA85074 and P50-CA105641 to T.R.R. The authors wish to thank Drs. D. Goldmann, W. Greer, G.W. Crooks, D.A. Horowitz, D. Farhadi, M.D. Cirigliano, M. Rusk, V. Weil, S.J. Gluckman, C. Bridges, M.L. Walker and C. Guerra for their invaluable assistance in ascertaining study participants.

Grant sponsor: Public Health Service; Grant numbers: R29-ES08031, R01-CA85074, P50-CA105641.

References

  • 1.De Marzo AM, DeWeese TL, Platz EA, Meeker AK, Nakayama M, Epstein JI, Isaacs WB, Nelson WG. Pathological and molecular mechanisms of prostate carcinogenesis: implications for diagnosis, detection, prevention, and treatment. J Cell Biochem. 2004;91:459–77. doi: 10.1002/jcb.10747. [DOI] [PubMed] [Google Scholar]
  • 2.Guess HA. Benign prostatic hyperplasia and prostate cancer. Epidemiol Rev. 2001;23:152–8. doi: 10.1093/oxfordjournals.epirev.a000782. [DOI] [PubMed] [Google Scholar]
  • 3.De Marzo AM, Platz EA, Sutcliffe S, Xu J, Gronberg H, Drake CG, Nakai Y, Isaacs WB, Nelson WG. Inflammation in prostate carcinogenesis. Nat Rev Cancer. 2007;7:256–69. doi: 10.1038/nrc2090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.van Leenders GJ, Gage WR, Hicks JL, van Balken B, Aalders TW, Schalken JA, De Marzo AM. Intermediate cells in human prostate epithelium are enriched in proliferative inflammatory atrophy. Am J Pathol. 2003;162:1529–37. doi: 10.1016/S0002-9440(10)64286-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Nelson WG, De Marzo AM, Isaacs WB. Prostate cancer. N Engl J Med. 2003;349:366–81. doi: 10.1056/NEJMra021562. [DOI] [PubMed] [Google Scholar]
  • 6.Cutolo M, Sulli A, Capellino S, Villaggio B, Montagna P, Seriolo B, Straub RH. Sex hormones influence on the immune system: basic and clinical aspects in autoimmunity. Lupus. 2004;13:635–8. doi: 10.1191/0961203304lu1094oa. [DOI] [PubMed] [Google Scholar]
  • 7.Sahu A, Lambris JD. Structure and biology of complement protein C3, a connecting link between innate and acquired immunity. Immunol Rev. 2001;180:35–48. doi: 10.1034/j.1600-065x.2001.1800103.x. [DOI] [PubMed] [Google Scholar]
  • 8.Harris MT, Feldberg RS, Lau KM, Lazarus NH, Cochrane DE. Expression of proinflammatory genes during estrogen-induced inflammation of the rat prostate. Prostate. 2000;44:19–25. doi: 10.1002/1097-0045(20000615)44:1<19::aid-pros3>3.0.co;2-s. [DOI] [PubMed] [Google Scholar]
  • 9.Asirvatham AJ, Schmidt M, Gao B, Chaudhary J. Androgens regulate the immune/inflammatory response and cell survival pathways in rat ventral prostate epithelial cells. Endocrinology. 2006;147:257–71. doi: 10.1210/en.2005-0942. [DOI] [PubMed] [Google Scholar]
  • 10.Bettoun D, Scafonas A, Rutledge S, Hodor P, Chen O, Gambone C, Vogel R, McElwee-Witmer S, Bai C, Freedman L, Schmidt A. Interaction between the androgen receptor and RNase L mediates a crosstalk between the interferon and androgen signaling pathways. J Biol Chem. 2005;280:38898–901. doi: 10.1074/jbc.C500324200. [DOI] [PubMed] [Google Scholar]
  • 11.Maggio M, Basaria S, Ceda GP, Ble A, Ling SM, Bandinelli S, Valenti G, Ferrucci L. The relationship between testosterone and molecular markers of inflammation in older men. J Endocrinol Invest. 2005;28:116–9. [PubMed] [Google Scholar]
  • 12.Ho E, Boileau TW, Bray TM. Dietary influences on endocrine-inflammatory interactions in prostate cancer development. Arch Biochem Biophys. 2004;428:109–17. doi: 10.1016/j.abb.2004.01.009. [DOI] [PubMed] [Google Scholar]
  • 13.Heinlein CA, Chang C. Androgen receptor (AR) coregulators: an overview. Endocr Rev. 2002;23:175–200. doi: 10.1210/edrv.23.2.0460. [DOI] [PubMed] [Google Scholar]
  • 14.Davies P, Eaton CL. Regulation of prostate growth. J Endocrinol. 1991;131:5–17. doi: 10.1677/joe.0.1310005. [DOI] [PubMed] [Google Scholar]
  • 15.McCormick DL, Rao KV, Dooley L, Steele VE, Lubet RA, Kelloff GJ, Bosland MC. Influence of N-methyl-N-nitrosourea, testosterone, and N-(4-hydroxyphenyl)-all-trans-retinamide on prostate cancer induction in Wistar-Unilever rats. Cancer Res. 1998;58:3282–8. [PubMed] [Google Scholar]
  • 16.Palapattu GS, Sutcliffe S, Bastian PJ, Platz EA, De Marzo AM, Isaacs WB, Nelson WG. Prostate carcinogenesis and inflammation: emerging insights. Carcinogenesis. 2005;26:1170–81. doi: 10.1093/carcin/bgh317. [DOI] [PubMed] [Google Scholar]
  • 17.Zeigler-Johnson C, Friebel T, Walker AH, Wang Y, Spangler E, Panossian S, Patacsil M, Aplenc R, Wein AJ, Malkowicz SB, Rebbeck TR. CYP3A4. CYP3A5, and CYP3A43 genotypes and haplotypes in the etiology and severity of prostate cancer. Cancer Res. 2004;64:8461–7. doi: 10.1158/0008-5472.CAN-04-1651. [DOI] [PubMed] [Google Scholar]
  • 18.Zeigler-Johnson CM, Walker AH, Mancke B, Spangler E, Jalloh M, McBride S, Deitz A, Malkowicz SB, Ofori-Adjei D, Gueye SM, Rebbeck TR. Ethnic differences in the frequency of prostate cancer susceptibility alleles at SRD5A2 and CYP3A4. Hum Hered. 2002;54:13–21. doi: 10.1159/000066695. [DOI] [PubMed] [Google Scholar]
  • 19.Rennert H, Zeigler-Johnson CM, Addya K, Finley MJ, Walker AH, Spangler E, Leonard DG, Wein A, Malkowicz SB, Rebbeck TR. Association of susceptibility alleles in ELAC2/HPC2. RNASEL/HPC1, and MSR1 with prostate cancer severity in. European American and African American men. Cancer Epidemiol Biomarkers Prev. 2005;14:949–57. doi: 10.1158/1055-9965.EPI-04-0637. [DOI] [PubMed] [Google Scholar]
  • 20.Wacholder S, Chanock S, Garcia-Closas M, El Ghormli L, Rothman N. Assessing the probability that a positive report is false: an approach for molecular epidemiology studies. J Natl Cancer Inst. 2004;96:434–42. doi: 10.1093/jnci/djh075. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Shah U, Getzenberg R. Fingerprinting the diseased prostate: associations between BPH and prostate cancer. J Cell Biochem. 2004;91:161–9. doi: 10.1002/jcb.10739. [DOI] [PubMed] [Google Scholar]
  • 22.Cauffiez C, Lo-Guidice J, Chevalier D, Allorque D, Hamdan R, Lhermitte M, Lafitte J, Colombel J, Libersa C, Broly F. First report of a genetic polymorphims of the cytochrome P450 3A43 (CYP3A43) gene: identification of a loss-of-function variant. Hum Mutat. 2004;23:101. doi: 10.1002/humu.9211. [DOI] [PubMed] [Google Scholar]
  • 23.Stone A, Ratnasinghe LD, Emerson GL, Modali R, Lehman T, Runnells G, Carroll A, Carter W, Barnhart S, Rasheed AA, Greene G, Johnson DE, et al. CYP3A43 Pro(340)Ala polymorphism and prostate cancer risk in African Americans and Caucasians. Cancer Epidemiol Biomarkers Prev. 2005;14:1257–61. doi: 10.1158/1055-9965.EPI-04-0534. [DOI] [PubMed] [Google Scholar]
  • 24.Prins GS, Birch L, Tang WY, Ho SM. Developmental estrogen exposures predispose to prostate carcinogenesis with aging. Reprod Toxicol. 2007;23:374–82. doi: 10.1016/j.reprotox.2006.10.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES