|Year : 2018 | Volume
| Issue : 9 | Page : 463-467
Association of CYP3A5*3 polymorphisms and prostate cancer risk: A meta-analysis
Ying Liang1, Wen Han2, Hongwei Yan3, Qiqi Mao1
1 Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
2 Institute of Information and Management, Guangxi Medical University, Nanning, Guangxi, China
3 Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
|Date of Web Publication||29-Jun-2018|
Department of Clinical Laboratory, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi
Source of Support: None, Conflict of Interest: None
Aim of Study: The CYP3A5*3 allele (A6986G transition in intron 3) is the major member of cytochrome P450 subfamily, which plays a pivotal role in exogenous carcinogens of liver. Variation of the CYP3A5*3 (rs776746 A > G) can lead to oxidation and inactivation of testosterone, which may result in individual susceptibility to prostate cancer.
Methods: All eligible published studies about association between CYP3A5*3 polymorphisms and prostate cancer risk were searched in PubMed, Embase, Web of Science, and Cochrane Library, for the period up to August 2015. Odds ratios (ORs) together with 95% confidence intervals (95% CIs) were used to access the strength of the association.
Results: Six case–control studies including 2522 cancer patients and 2444 healthy controls were finally included. The meta-analysis results suggested that CYP3A5*3 polymorphisms were significantly associated with an increased risk of prostate cancer under two genetic models (GG + AG vs. AA: OR = 1.53, 95% CI = 1.23–1.90, P = 0.000; GG vs. AA: OR = 1.46, 95% CI = 1.14–1.87, P = 0.000). Further subgroup analysis according to ethnicity indicated that CYP3A5*3 polymorphism may increase the risks of prostate cancer among African (G allele vs. A allele: OR = 1.34, 95% CI = 1.14–1.57, P = 0.000; GG + AG vs. AA: OR = 1.606, 95% CI = 1.27–2.04, P = 0.000). Sensitivity analysis indicated a reliable result and publication bias suggested no strong publication bias under the genetic models.
Conclusion: Our data support that the CYP3A5*3 polymorphism may be associated with increased risk of prostate cancer, particularly in African populations. Large and well-designed studies are needed to validate this association.
Keywords: CYP3A5*3, meta-analysis, prostate cancer, single nucleotide polymorphism
|How to cite this article:|
Liang Y, Han W, Yan H, Mao Q. Association of CYP3A5*3 polymorphisms and prostate cancer risk: A meta-analysis. J Can Res Ther 2018;14, Suppl S2:463-7
| > Introduction|| |
Prostate cancer is one of the most common malignancy in male worldwide and the second most common cause of death in male., Due to the high occurrence and high mortality, it attracts substantial research efforts. The pathogenesis of prostate cancer is not clear; it seems to result from interactions between environmental and genetic factors. Recent research demonstrates that host genetic mutations play significant role to influence susceptibility of prostate cancer, but the exact mechanism has not been examined extensively.
Testosterone is the major hormone product by the testicles, which is also the main factor responsible for male sexual characteristics. It may play an important role in the growth and differentiation of prostate cancer.CYP3A5*3 is the major member of cytochrome P450 subfamily constitutively expressed in liver; it is located on human chromosome 7q22.1 and contains 13 exons. It has been confirmed that CYP3A5*3 plays an important role in exogenous carcinogens and drug metabolism, and it also involved in the oxidation and inactivation of testosterone., Single nucleotide polymorphisms (SNPs) in the intron of CYP3A5*3 may influence the protein production and enzyme activity. Among them, the A to G transition in intron 3 at position 6986 (CYP3A5*3, rs776746 A > G) is the most frequent and functional polymorphism, which results in the inactivation of CYP3A5*3 and affects metabolism of testosterone. Hence, it was hypothesized that CYP3A5*3 polymorphism was involved in prostate cancer risk.
Though a number of studies have been conducted to investigate the association between CYP3A5*3 polymorphisms and prostate cancer risk, the results remain mixed owning to the obvious inconsistence.,,,,, Up to now, no meta-analysis investigating the association between CYP3A5*3 polymorphisms and prostate cancer risk has been reported. Therefore, we performed a meta-analysis to evaluate the association between CYP3A5*3 polymorphism and prostate cancer risk.
| > Methods|| |
A comprehensive literature search was performed in PubMed, Embase, Web of Science, and Cochrane Library with the following medical subject heading terms: “Genetic polymorphism,” “polymorphism,” “SNP” or “single nucleotide polymorphism;” and “prostate cancer;” and “CYP3A5*3,” “Cytochrome P450 CYP3A,” or “Cytochrome P450 3A.” The relevant reports were all published before July 2015. Reference lists from retrieved articles were also reviewed for more potential studies. In addition, the “Related Articles” function of PubMed was introduced to the search process. When disagreements occurred, we resolved it through discussions.
All included articles had to meet the eligibility criteria: (1) case–control or cohort studies evaluated the association between CYP3A5*3 (rs776746 A > G) polymorphism and prostate cancer risk, (2) prostate cancer confirmed by pathological or histological examinations and genotypes identified by DNA analysis, and (3) the distribution and the frequencies of alleles or genotypes of alleles must be offered. Studies were excluded from the meta-analysis when they met following one: (1) data obtained from the overview or summary, (2) without sufficient data, (3) a lack of control population, and (4) duplicate publications.
The data from the studies included were extracted by two investigators independently. For each eligible study, the following contents were collected: The first author, publication date, country, ethnicity, number of cases and controls, gender ratio, genotyping method, allele and genotype frequencies, and Hardy–Weinberg equilibrium (HWE) in controls. All the extracted data were checked by two authors. In cases of conflicting evaluations, they would have a discussion to reach consensus.
Quality score assessment
The quality of papers was independently assessed by two investigators according to the modified predetermined criteria. The quality scores ranged from 0 to 40, and studies with scores of ≥30 or <20 were considered high quality and low quality, respectively.
We evaluated HWE in control groups of each study by Chi-square test, and P < 0.05 was considered a statistically significant departure. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were performed to estimate the relationship between CYP3A5*3 polymorphism and prostate cancer risk. Pooled ORs were calculated in five genetic models: The allele model (G vs. A), dominant model (GG + AG vs. AA), recessive model (GG vs. AA + AG), homozygous/additive model (GG vs. AA), and heterozygous model (GG vs. AG). To access the heterogeneity among studies, the Q-test (significance level of P < 0.1) and I2 statistic (I2 ≥ 50% indicating the presence of heterogeneity) were used. When the result of the Q-test was Ph < 0.05 or I2 ≥ 50%, the random effects model (DerSimonian and Laird method) was conducted for the meta-analysis. Otherwise, the fixed-effects model (Mantel–Haenszel method) was used. Subgroup analyses were stratified by ethnicity to explore sources of heterogeneity. Sensitivity analysis was performed by sequential omission of individual studies to access the consistency of the results. Begger's funnel plot and Egger's linear regression were performed to evaluate the publication bias. All P values were two-sided. Statistical analyses were performed using Stata software, version 12.0 (Stata Corp., College Station, TX, USA).
| > Results|| |
Characteristics of included studies
A total of 53 studies were initially identified from the PubMed and other databases. After the first screening on the titles and keywords, 21 articles had no relation to the topic and were excluded. Remaining 32 studies were abstract and/or full-text reviewed, and a further 26 studies were excluded, among which 14 were review articles, 6 was not a case–control study, and 6 had insufficient data for calculating OR and 95% CI. At last, 6 case–control studies including 2522 cancer patients and 2444 healthy controls were finally included in the meta-analysis. In these studies, 3 were conducted on Caucasian,,, 3 were on African,,, and 2 were on Asian populations , for the CYP3A5*3 polymorphisms. Polymerase chain reaction-restriction fragment length polymorphism method was mentioned in four studies; direct DNA sequencing method was utilized in the other two studies. The genotype distribution of the control group was consistent with HWE except for one study. The details of each study were presented in [Table 1].
We first investigated the association between CYP3A5*3 polymorphisms and prostate cancer risk by meta-analysis. Since no significant heterogeneity was observed by Q-test and I2 statistician in four genetic models (GG + AG vs. AA: PQ= 0.262; GG vs. AA + AG: PQ= 0.083; GG vs. AA: PQ= 0.228; GG vs. AG: PQ= 0.246), fixed-effects model was used. The random effects model was used to pool the analysis of the other genetic models (G allele vs. A allele: PQ= 0.005). The meta-analysis results suggested that CYP3A5*3 polymorphisms were significantly associated with an increased risk of prostate cancer under two genetic models (GG + AG vs. AA: OR = 1.53, 95% CI = 1.23–1.90, P = 0.000 [Figure 1]; GG vs. AA: OR = 1.46, 95% CI = 1.14–1.87, P = 0.000 [Figure 2]). Next, further subgroup analysis according to ethnicity indicated that CYP3A5*3 polymorphism may increase the risks of prostate cancer among African (G allele vs. A allele: OR = 1.34, 95%
|Figure 1: Forest plots showed significant association between CYP3A5*3 polymorphisms and prostate cancer risk in the dominant model (GG + AG vs. AA)|
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|Figure 2: Forest plots showed significant association between CYP3A5*3 polymorphisms and prostate cancer risk in the homozygous model (GG vs. AA)|
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CI = 1.14–1.57, P = 0.000 [Figure 3]; GG + AG vs. AA: OR = 1.606, 95% CI = 1.27–2.04, P = 0.000 [Figure 4]). However, no significant association was found in Caucasian and Asian groups [Table 2].
|Figure 3: Subgroup analysis by ethnicity for the association between CYP3A5*3 polymorphism and prostate cancer risk in the dominant model (GG + AG vs. AA)|
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|Figure 4: Subgroup analysis by ethnicity for the association between CYP3A5*3 polymorphism and prostate cancer risk in the homozygous model (GG vs. AA)|
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Sensitivity analysis in each comparison model was conducted to assess the influence of individual study by omitting each study sequentially. The results suggested that no individual study greatly influenced the pooled OR of overall results, indicating a reliable result.
The funnel plots and Egger's test were performed to assess the publication bias of the included literature among all comparison models. The shape of the funnel plot of the association between CYP3A5*3 polymorphism and prostate cancer risk did not reveal any evidence of obvious asymmetry [Figure 5]. The Egger's tests suggested no strong publication bias under the dominant model (P = 0.148).
|Figure 5: Begger's funnel plot for publication bias analysis for CYP3A5*3 polymorphism under the dominant model (GG + AG vs. AA)|
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| > Discussion|| |
CYP3A5*3 is belong to cytochrome P450 superfamily which participates in transfer of diverse xenobiotic, such as hormones testosterone., SNPs of CYP3A5*3 may influence the protein production and enzyme activity, which involved in the oxidation and inactivation of testosterone. Testosterone can deeply change growth and function of prostate cell, so the level of androgen produced by the prostate cell is corresponding lower, which contributes to occur of prostate cancer mediated by androgen. This hypothesis has been particularly confirmed in several studies.,,,
This is the first meta-analysis to investigate the relationship between CYP3A5*3 polymorphisms and prostate cancer risk. For CYP3A5*3 polymorphisms, there exists literature studied the relationship between CYP3A5*3 polymorphisms and cancer risk, and the author found no evidence of association between CYP3A5*3 polymorphisms and prostate cancer risk. However, in our study, we include more literature and find a significantly increased risk of CYP3A5*3 polymorphisms in prostate cancer, which we think is a novel discovery. In the present study, six studies with 2522 cancer patients and 2444 healthy control were analyzed. The results showed that a significantly increased risk of prostate cancer in the dominant genetic model (GG + AG vs. AA) and the genetic homozygous model (GG vs. AA) in overall population.
Heterogeneity between studies usually contributes to misleading results, so it is important to identify the sources of heterogeneity in a meta-analysis. In the present study, significant heterogeneity was observed among the allele model (G allele vs. A allele); however, when we stratified analysis to different ethnicity group, there was no statistical evidence of heterogeneity among studies, indicating that ethnic diversity, to some extent, has played a role in the heterogeneity.
Then, we performed subgroup analysis according to the source of control. The results suggested that CYP3A5*3 polymorphisms presented a risk factor for prostate cancer in African while similar associations were not found in Caucasians and Asian. The inconsistent results in Asians and Caucasians demonstrated CYP3A5*3 polymorphisms might play different roles under different ethnic genetic backgrounds. There are several possible reasons for the diverse results such as different genetic backgrounds, lifestyles, environmental conditions, and matching criteria. Generally speaking, compared to overall populations, the ORs in the subgroup analyses were not materially changed, suggesting the high reliabilities of our studies. As for publication bias of CYP3A5*3 polymorphisms, no evidence of publication bias was noted in Begger's funnel plot and Egger's linear regression test.
Despite considerable efforts to investigate the potential relationship between the CYP3A5*3 polymorphisms and prostate cancer, it should be noted that this study also has some limitations. First, due to shortage of original studies, the number of studies included in this analysis was relatively small, which may affect statistical power and generate a fluctuate estimation. Second, further evaluation should be based on adjustments by other covariates such as sex, age, and environmental factors to explore potential interactions. Third, owing to the lack of sufficient data in the included studies, we did not explore the gene–gene interactions in the association between CYP3A5*3 polymorphisms and prostate cancer. However, this is the first meta-analysis focused on the association between CYP3A5*3 polymorphism and prostate cancer risk. We make efficient searching strategy and no limitation in the literature search, so we controlled the selection bias was well. In addition, there was no publication bias in this meta-analysis, which indicated that the results are statistically robust.
| > Conclusion|| |
Our results suggested that CYP3A5*3 polymorphism is significantly associated with increased risk of prostate cancer, especially in African. However, it is necessary to conduct large-sample epidemiological case–control studies to validate this association. Further studies about CYP3A5*3 genetic polymorphisms in prostate cancer are also essential.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| > References|| |
Rubin MA, Maher CA, Chinnaiyan AM. Common gene rearrangements in prostate cancer. J Clin Oncol 2011;29:3659-68.
Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin 2011;61:69-90.
Thompson I, Thrasher JB, Aus G, Burnett AL, Canby-Hagino ED, Cookson MS, et al.
Guideline for the management of clinically localized prostate cancer: 2007 update. J Urol 2007;177:2106-31.
Nelson WG, De Marzo AM, DeWeese TL. The molecular pathogenesis of prostate cancer: Implications for prostate cancer prevention. Urology 2001;57 4 Suppl 1:39-45.
Barbieri CE, Baca SC, Lawrence MS, Demichelis F, Blattner M, Theurillat JP, et al.
Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer. Nat Genet 2012;44:685-9.
Amory JK, Bremner W. Endocrine regulation of testicular function in men: Implications for contraceptive development. Mol Cell Endocrinol 2001;182:175-9.
Tymchuk CN, Barnard RJ, Ngo TH, Aronson WJ. Role of testosterone, estradiol, and insulin in diet- and exercise-induced reductions in serum-stimulated prostate cancer cell growth in vitro
. Nutr Cancer 2002;42:112-6.
Hustert E, Haberl M, Burk O, Wolbold R, He YQ, Klein K, et al.
The genetic determinants of the CYP3A5 polymorphism. Pharmacogenetics 2001;11:773-9.
Burk O, Koch I, Raucy J, Hustert E, Eichelbaum M, Brockmöller J, et al.
The induction of cytochrome P450 3A5 (CYP3A5) in the human liver and intestine is mediated by the xenobiotic sensors pregnane X receptor (PXR) and constitutively activated receptor (CAR). J Biol Chem 2004;279:38379-85.
Nebert DW, Dalton TP. The role of cytochrome P450 enzymes in endogenous signalling pathways and environmental carcinogenesis. Nat Rev Cancer 2006;6:947-60.
Agundez JA. Cytochrome P450 gene polymorphism and cancer. Curr Drug Metab 2004;5:211-24.
Plummer SJ, Conti DV, Paris PL, Curran AP, Casey G, Witte JS. CYP3A4 and CYP3A5 genotypes, haplotypes, and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 2003;12:928-32.
Zeigler-Johnson C, Friebel T, Walker AH, Wang Y, Spangler E, Panossian S, et al.
CYP3A4, CYP3A5, and CYP3A43 genotypes and haplotypes in the etiology and severity of prostate cancer. Cancer Res 2004;64:8461-7.
Zhenhua L, Tsuchiya N, Narita S, Inoue T, Horikawa Y, Kakinuma H, et al.
CYP3A5 gene polymorphism and risk of prostate cancer in a Japanese population. Cancer Lett 2005;225:237-43.
Vaarala MH, Mattila H, Ohtonen P, Tammela TL, Paavonen TK, Schleutker J. The interaction of CYP3A5 polymorphisms along the androgen metabolism pathway in prostate cancer. Int J Cancer 2008;122:2511-6.
Chew SC, Singh O, Chen X, Ramasamy RD, Kulkarni T, Lee EJ, et al.
The effects of CYP3A4, CYP3A5, ABCB1, ABCC2, ABCG2 and SLCO1B3 single nucleotide polymorphisms on the pharmacokinetics and pharmacodynamics of docetaxel in nasopharyngeal carcinoma patients. Cancer Chemother Pharmacol 2011;67:1471-8.
Fernandez P, Zeigler-Johnson CM, Spangler E, van der Merwe A, Jalloh M, Gueye SM, et al.
Androgen metabolism gene polymorphisms, associations with prostate cancer risk and pathological characteristics: A comparative analysis between South African and Senegalese men. Prostate Cancer 2012;2012:798634.
Gallo V, Egger M, McCormack V, Farmer PB, Ioannidis JP, Kirsch-Volders M, et al.
STrengthening the Reporting of OBservational studies in Epidemiology – Molecular Epidemiology (STROBE-ME): An extension of the STROBE statement. Prev Med 2011;53:377-87.
Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21:1539-58.
DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177-88.
Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 1959;22:719-48.
Duval S, Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000;56:455-63.
Willrich MA, Hirata MH, Hirata RD. Statin regulation of CYP3A4 and CYP3A5 expression. Pharmacogenomics 2009;10:1017-24.
Lamba JK, Lin YS, Schuetz EG, Thummel KE. Genetic contribution to variable human CYP3A-mediated metabolism. Adv Drug Deliv Rev 2002;54:1271-94.
Walsky RL, Obach RS, Hyland R, Kang P, Zhou S, West M, et al.
Selective mechanism-based inactivation of CYP3A4 by CYP3cide (PF-04981517) and its utility as an in vitro
tool for delineating the relative roles of CYP3A4 versus CYP3A5 in the metabolism of drugs. Drug Metab Dispos 2012;40:1686-97.
Lin YS, Dowling AL, Quigley SD, Farin FM, Zhang J, Lamba J, et al.
Co-regulation of CYP3A4 and CYP3A5 and contribution to hepatic and intestinal midazolam metabolism. Mol Pharmacol 2002;62:162-72.
Kuehl P, Zhang J, Lin Y, Lamba J, Assem M, Schuetz J, et al.
Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat Genet 2001;27:383-91.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2]