Association between ESRα and ESRβ polymorphisms and prostate cancer risk: meta-analysis

Background: Gene polymorphisms of ESRα Pvull(rs2234693), Xbal(rs9340799), and ESRβ Alul(rs4986938) and RsaI (rs1256049), have been investigated for their associations with prostate cancer risk. However, the nature of these relationships remains ambiguous. Therefore, the present study aimed to further clarify the association between ESR gene polymorphisms and prostate cancer.

Objective: To investigate the association between ESRα Pvull(rs2234693), Xbal(rs9340799), and ESRβ Alul(rs4986938), Rsal(rs1256049) polymorphisms and prostate cancer risk.

Materials and methods: PubMed, Medline, and CNKI were searched. Associations were assessed using odds ratios (ORs) with 95% confidence intervals (CIs). The false-positive report probability (FPRP), Bayesian false discovery probability (BFDP), and Venetian criteria were used to evaluate the credibility of statistically significant findings.

Results: We found for the first time that, overall, the ESRα PvuII polymorphism was significantly associated with a reduced risk of prostate cancer (pp vs. Pp + PP: OR = 0.83, 95% CI = 0.71–0.97; pp vs. PP: OR = 0.75, 95% CI = 0.57–0.99; p vs. P: OR = 0.88, 95% CI = 0.78–0.99). A similarly reduced risk was observed in Caucasians (pp + Pp vs. PP: OR = 0.01, 95% CI = 0.01–0.04). By contrast, the ESRα PvuII polymorphism increased prostate cancer risk among Africans (pp + Pp vs. PP: OR = 2.38, 95% CI = 1.61–3.51). For ESRβ RsaI, we observed a reduced risk of prostate cancer in Asians (r vs. R: OR = 0.87, 95% CI = 0.77–0.98). However, no significant associations were identified for ESRα XbaI or ESRβ AluI. When evaluating credibility using the FPRP, BFDP, and Venetian criteria, no statistically robust associations were confirmed.

Conclusions: Overall, the results suggest a potential association between the ESRα PvuII and ESRβ RsaI polymorphisms and prostate cancer risk, although the credibility assessments did not support statistically robust relationships.

Introduction

Prostate cancer (PCa) is a highly prevalent malignancy among men worldwide, particularly in Western countries, where it remains a leading cause of cancer-related mortality and a major public health concern (1). Although the incidence of PCa in Asian populations has historically been lower than in Western nations, epidemiological trends indicate a steady rise in cases, attributed to factors such as socioeconomic development, demographic aging, adoption of Westernized dietary habits, and lifestyle changes (2). Despite advances in early detection and therapeutic interventions, the precise etiology and molecular mechanisms underlying PCa pathogenesis remain incompletely understood. Current evidence suggests that both genetic susceptibility and environmental influences contribute to PCa development, with gene polymorphisms serving as an important biological determinant of inherited risk (3).

Estrogen receptors (ESRs) are nuclear macromolecules that mediate the biological effects of estrogen (4). Two isoforms exist—ESRα and ESRβ—which differ in the C-terminal ligand-binding region and the N-terminal activation domain (5). The ESRα gene consists of eight exons spanning approximately 140 kb on chromosome 6q25.1, whereas the ESRβ gene consists of eight exons spanning approximately 40 kb on chromosome 14q23–24.1 (6). Studies have shown that ESRα may act as an oncogenic factor that promotes tumor cell proliferation, while ESRβ is considered protective, exhibiting anti-cancer and pro-apoptotic effects. Genetic polymorphisms in the ESRα and ESRβ genes may lead to altered transcription or affect transcript stability (7). Therefore, polymorphisms in ESRα and ESRβ may represent potential risk factors for prostate cancer.

To date, numerous studies have examined the associations between ESRα and ESRβ gene polymorphisms and prostate cancer risk (8–15, 18–41). However, the evidence remains inconsistent, with some reports identifying significant associations while others report null findings. Eight meta-analyses have evaluated these associations, yet their conclusions remain conflicting (8–15). In addition, no previous meta-analysis performed a credibility assessment of statistically significant findings. Therefore, the present study further investigated the association between ESRα and ESRβ gene polymorphisms and prostate cancer risk.

Materials and methods

PRISMA guidelines were followed in this meta-analysis (42).

Search strategy

Articles were retrieved from PubMed, Medline, and CNKI. The search strategy was as follows: (“estrogen receptors” OR “ESR” OR “estrogen receptor alpha” OR “estrogen receptor beta” OR “ER alpha” OR “ER beta” OR “estrogen receptor 1” OR “estrogen receptor 2” OR “ESR1” OR “ESR2”) AND (“polymorphism” OR “gene” OR “SNP”) AND (“prostate cancer” OR “PCa). Searches were conducted up until September 15, 2024. In addition, reference lists of previously published meta-analyses were carefully reviewed to identify all eligible studies (8–15).

Selection criteria

Inclusion criteria were as follows: (i) case–control studies; (ii) studies that assessed associations between ESRα PvuII and XbaI, and ESRβ AluI and RsaI polymorphisms and prostate cancer risk; (iii) prostate cancer cases confirmed by histopathology. Exclusion criteria were as follows: (i) cross-sectional studies; (ii) case reports, reviews, letters, and meta-analyses; (iii) animal studies.

Data extraction and quality assessment

The literature was screened by two independent reviewers, with disagreements resolved through discussion or by consultation with a third researcher. Extracted data included the first author, publication year, country, ethnicity, sample sizes of cases and controls, and genotype frequencies (Supplementary Tables 2–5). Study quality was independently evaluated by two authors using criteria reported in previous studies (16, 17), as presented in Supplementary Table 1. The quality assessment was based on a 15-point scale, and a score greater than 8 indicated a high-quality study.

Statistical analysis

All statistical analyses were performed using STATA version 12.0. Five genetic models were evaluated (dominant, recessive, additive, over-dominant, and allele models). Hardy–Weinberg equilibrium (HWE) in the control group was assessed using the chi-square test (P < 0.05 was considered indicative of Hardy–Weinberg disequilibrium [HWD]) (43).

Heterogeneity among studies was assessed using the Q test and the I² statistic. Significant heterogeneity was defined as P < 0.10 and/or I² > 50% (44), in which case pooled ORs were calculated using a random-effects model; otherwise, a fixed-effects model was applied. Potential sources of heterogeneity were explored using meta-regression analysis (45). Subgroup analyses were conducted by ethnicity and by source of the control group. Sensitivity analyses were performed by including only studies of high quality and studies in HWE.

Egger’s test (46) and Begg’s test (47) were used to evaluate publication bias. The false-positive report probability (FPRP) (48), Bayesian false discovery probability (BFDP) (49), and Venetian criteria (50) were used to assess the credibility of statistically significant associations (I² < 50%; FPRP < 0.2 and BFDP <0.8).

Results

Overall, 756 articles were retrieved (Figure 1). After screening titles and full texts, 24 articles comprising 51 studies were included (Supplementary Tables 2–5, Figure 1). A total of 26,454 cases and 33,941 controls were analyzed. As shown in Supplementary Tables 2–5, ESRα Pvull was reported in 18 studies (4,623 cases and 9,850 controls), ESRα Xbal in 14 studies (3,716 cases and 4,536 controls), ESRβ Alul in eight studies (8,674 cases and 9,498 controls), and ESRβ Rsal in 11 studies (9,390 cases and 10,057 controls). As detailed in Supplementary Table 6, the number of high-quality articles for each polymorphism was as follows: ESRα Pvull (n=10; with 8 low-quality), ESRα Xbal (n=5; with 9 low-quality), ESRβ Alul (n=3; with 5 low-quality), and ESRβ Rsal (n=7; with 4 low-quality).

Figure 1

Figure 1. Flow diagram of the literature search.

Quantitative synthesis

ESRα Pvull polymorphism

Overall analyses showed that the ESRα PvuII polymorphism was associated with a reduced risk of prostate cancer (pp vs. Pp + PP: OR = 0.83, 95% CI = 0.71–0.97; pp vs. PP: OR = 0.75, 95% CI = 0.57–0.99; p vs. P: OR = 0.88, 95% CI = 0.78–0.99; Table 1 and Figure 2). A similarly reduced risk was observed in Caucasians (pp + Pp vs. PP: OR = 0.01, 95% CI = 0.01–0.04). However, the ESRα PvuII polymorphism was associated with an increased risk of prostate cancer in Africans (pp + Pp vs. PP: OR = 2.38, 95% CI = 1.61–3.51; Table 1). A reduced risk was also observed in hospital-based controls (pp vs. Pp + PP: OR = 0.80, 95% CI = 0.66–0.98; Table 1). Sensitivity analyses further confirmed the robustness of these findings.

Table 1

Table 1. Meta-analysis of the association of ESRα Pvull polymorphism with risk of prostate cancer risk.

Figure 2

Figure 2. Overall analysis of the correlation between ESRα Pvull polymorphism and the risk of prostate cancer in the analysis forest map.

ESRβ Rsal polymorphism

An increased risk of prostate cancer was found in Caucasians (rr + Rr vs. RR: OR = 1.17, 95% CI = 1.03–1.32; r vs. R: OR = 1.18, 95% CI = 1.05–1.33; Table 2, Figure 3). In contrast, a reduced risk was observed in Asians (r vs. R: OR = 0.87, 95% CI = 0.77–0.98; Table 2, Figure 3). However, sensitivity analyses did not confirm these associations (Table 2).

Table 2

Table 2. Meta-analysis of the association of ESRβ Rsal polymorphism with risk of prostate cancer risk.

Figure 3

Figure 3. Forest map of the correlation of between ESRβ Rsal polymorphism and prostate cancer in the ethnicity group analysis (r vs. R).

ESRα Xbal and ESRβ Alul polymorphism

The overall and subgroup analyses showed no association between ESRα XbaI or ESRβ AluI polymorphisms and prostate cancer risk. Sensitivity analyses showed no significant changes in these results (Tables 3, 4).

Table 3

Table 3. Meta-analysis of the association of ESRα Xbal polymorphism with risk of prostate cancer risk.

Table 4

Table 4. Meta-analysis of the association of ESRβ Aull polymorphism with risk of prostate cancer risk.

Heterogeneity and sensitivity analysis

During the statistical process, we identified several possible sources of heterogeneity were examined, including ethnicity, sample size, country, source of study population, quality score, and HWE status. Meta-regression analyses were performed, but no clear source of heterogeneity was identified. Two approaches were used for sensitivity analyses: (i) sequential removal of each study, and (ii) restricting the analysis to studies with both high quality and HWE compliance. Both approaches showed that the associations between ESRα and ESRβ polymorphisms and prostate cancer risk remained unchanged (Tables 1, 2).

Publication bias

Begg’s and Egger’s tests showed no publication bias between ESRα Pvull, ESRα Xbal, ESRβ Alul, and ESRβ Rsal polymorphisms and prostate cancer (Figure 4).

Figure 4

Figure 4. Publication bias of the combined effect of Begg funnel plot assessment of ESRα Pvull polymorphism anf prostate cancer (pp + Pp vs. PP).

Credibility analysis

The credibility of this meta-analysis was assessed using the FPRP, BFDP, and Venice criteria. In this study, we observed a reduction in the strength of all statistically significant associations (Table 5).

Table 5

Table 5. Credibility of the current meta-analysis.

Discussion

Interestingly, the effect of ESR on the risk of prostate cancer differed significantly across ethnic groups. We found that ESRβ Rsal was associated with a significantly increased risk of prostate cancer in Caucasians. However, ESRβ Rsal appears to be a protective gene against prostate cancer in Asians. Meanwhile, Pvull may also be a risk gene locus for prostate cancer in Africans. However, ESRα Pvull gene polymorphism showed a significantly reduced association with prostate cancer risk in the general population. However, no significant results were found in the final sensitivity analyses. Although we attempted to include all relevant studies, the inclusion of low-quality studies may have affected the true associations. Unfortunately, we did not find an association between ESRα Xbal and ESRβ Alul and the risk of prostate cancer.

We used subgroups of race and mode of recruitment, as well as five genetic models, which necessarily led to multiple comparisons; therefore, adjustment for pooled p-values was necessary. The confidence of the associations between ESRα Pvull, Xbal, and ESRβ Alul, Rsal polymorphisms and prostate cancer risk was low according to the FPRP, BFDP, and Venice criteria. This seemingly contradictory outcome primarily stems from the following aspects. First, the calculation of FPRP and BFDP depends not only on the P-value but, more critically, on statistical power and the pre-specified prior probability. In this study, the statistical power for this specific variant was at a moderate level, which increases the relative risk of the result being a false positive. Second, adhering to a principle of caution, we employed a relatively conservative prior probability (0.001) in our calculations. This reflects a more prudent stance toward this finding, given the current lack of strong biological or genetic evidence. Therefore, the “low confidence” rating does not negate the association but emphasizes that our findings should be considered preliminary and suggestive evidence, whose ultimate confirmation will require replication in larger, independent cohorts or prospective studies. Future research should aim to validate the association observed here in samples with sufficient statistical power, complemented by functional experimental evidence.

Based on subgroup analyses by population, the results across different ethnic subgroups revealed contradictory patterns. Our findings underscore that the effects of genetic variants may be highly population-specific. The underlying factors for these discrepancies may include differences in allele frequencies, variations in linkage disequilibrium patterns across populations, and gene–environment interactions. Extreme caution should be exercised when extrapolating these findings to populations with different genetic backgrounds. Future studies should focus on more refined genetic analyses within individual populations and integrate environmental exposure data to elucidate the precise mechanisms underlying these discordant associations.

Previously, eight interlinked meta-analyses had published results on the association between the ESRα Pvull, Xbal, and ESRβ Alul, Rsal genetic polymorphisms and the risk of prostate cancer. Chang et al, Fu et al, Ma et al, and Liu found that ESRβ Rsal might be correlated with an increased risk of PCa in Caucasians, while less susceptibility was observed in Asians (8, 9, 13, 14). Wang et al. and Li et al. found that the PvuII polymorphism was significantly associated with an increased risk of prostate cancer among Asian populations (11, 15). Gazzaz et al. demonstrated that ESRα Rsal increases the risk of prostate cancer. Gu et al. suggested that ESRα Xbal is a noteworthy gene for prostate cancer risk in Africans (12). Unfortunately, we did not replicate the findings of Gu et al. after including additional data from our study. The conflicting results, particularly in Asian populations, may be due to the insufficient number of included studies. These studies examined only the association between a single SNP and prostate cancer risk. Furthermore, several studies did not conduct a quality assessment of eligible articles. In addition, none evaluated the credibility of statistically significant associations. Compared with previous studies, our study is the first to reveal a significant association between the ESRα Pvull polymorphism and a reduced risk of prostate cancer. By including a larger number of studies, we further clarified the relationship between ESRα, ESRβ, and prostate cancer risk.

In order to further clarify the uncertain results of previous meta-analyses and evaluate current findings, we conducted this meta-analysis. The present study has the following advantages over previous analyses: (i) strict inclusion criteria; (ii) HWE examination of control groups; (iii) assessment of the credibility of statistically significant associations; (iv) inclusion of more studies with larger sample sizes; and (v) more accurate subgroup analyses and more professional modeling approaches. The shortcomings of previous studies were noted and addressed. However, our study has several limitations. First, we included only published articles that could be retrieved through database searches. Second, the included studies did not adjust for confounding factors that may significantly affect the results; therefore, our findings are based on unadjusted OR estimates. Third, although the overall sample size was large, the quality of the included studies varied, which may reduce confidence in the final results. Therefore, additional studies are needed in the future to further verify our findings.

The pathogenesis of prostate cancer involves complex interactions between environmental factors and polygenic influences. While our investigation specifically examined the impact of ESR single-nucleotide polymorphisms on prostate cancer risk, this systematic analysis incorporated the majority of currently available studies on the ESR–prostate cancer association. Our findings further elucidate the relationship between ESR and prostate cancer and provide a meaningful perspective for future prostate cancer research and the identification of potential therapeutic targets.

Conclusion

In summary, ESRα Pvull and ESRβ Rsal polymorphisms are associated with the risk of prostate cancer. However, the observed effects were inconsistent or weak across studies. To resolve this uncertainty and confirm any potential link, large studies with sufficient methodological quality are needed in the future.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.

Author contributions

XB: Writing – original draft, Methodology, Conceptualization, Software, Investigation. LG: Writing – original draft, Data curation, Conceptualization. JZ: Writing – original draft, Methodology, Data curation. WL: Data curation, Writing – original draft. YC: Writing – original draft, Data curation. XG: Writing – original draft, Data curation. JJ: Writing – review & editing. BG: Writing – review & editing.

Funding

The author(s) declared financial support was received for this work and/or its publication. The study was supported by Natural Science Foundation of Guangxi Province (grant no. [2023GXNSFAA026061]; [Li Gao]), National Natural Science Foundation of China (grant no. [32360170], [Li Gao]; [82460158].

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2025.1630363/full#supplementary-material

Abbreviations

BFDP, Bayesian false discovery probability; CI, confidence interval; FPRP, false-positive report probabilities; HWE, Hardy–Weinberg equilibrium; OR, odds ratio; PRISMA, Preferred Reporting Items for Systematic Review and Meta-Analyses; ESR, estrogen receptor.

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