Introduction

Breast cancer (BC) is widely recognized as the predominant malignancy affecting women, with the highest incidence rate among all cancers diagnosed. Additionally, it stands as the second primary contributor to cancer-related deaths in women, after lung cancer.[1, 2]. With regard to statistical findings, BC has a high incidence rate worldwide, and 2 million new cases are recognized yearly, accounting for 23% of all cancer cases.

The past three decades witnessed a 128% increase in the total number of incident cases worldwide [3]. In 2020, female breast cancer became the most commonly diagnosed cancer globally for the first time, with an estimated 2.26 million new cases reported [4]. The most recent prediction suggests that by 2040, the global burden of breast cancer is expected to increase to over 3 million new cases annually [5, 6]. From epidemiological perspective, BC is growing strongly in South America, Africa, and Asia. Investigation highlight that early detection of BC has an indispensable role in diminishing the mortality rate and ameliorating its prognosis [7]. BC is a heterogeneous disease influenced by both genetic and environmental factors, including hormonal alteration, unhealthy life style, and a family history of BC [8, 9]. In addition to the mentioned factors, genetic polymorphisms have become a remarkable factor in recent years. Polymorphisms occurred in the oncogenes, tumor suppressors, and the controlling elements may even modulate the BC onset and outcome. Accordingly, p53 as a tumor suppressor gene and MDM2 as an oncogene play a pivotal role in the pathophysiology of BC [10,11,12].

MDM2 gene is located on chromosome 12 ql3-14 and encodes a negative regulator of p53 facilitating its degradation through proteasomal pathways. Furthermore, MDM2 functions as a nuclear phosphoprotein and can directly inhibit the transcriptional activity of p53 by forming a direct interaction with it [13,14,15]. Any genetic polymorphism in sensitive sites can alter the expression of MDM2 and may lead to inactivation of p53, allowing damaged cells to evade cell-cycle checkpoints and progress toward a cancerous state [16,17,18].

A functional single-nucleotide polymorphism (SNP) known as MDM2 SNP309 (rs2279744) occurs in the promoter region of the human MDM2 gene. As the result of this trans version, G nucleotide is substituted by T (T > G). Subsequently, the affinity of the MDM2 promoter is augmented for transcription factor SP1, leading to upregulation of MDM2 expression. Since overexpression of MDM2 gene attenuates the function of p53, which is involved in the etiopathogenesis of various cancers, therefore MDM2 gene rs2279744 SNP can be a predisposing factor in different malignancies, such as cervical, prostate, lung, and oral carcinomas [19,20,21,22,23,24].

A growing body of studies has evaluated the potential association between the MDM2 gene polymorphism and susceptibility to BC, but the results have been contradictory. Two potential reasons can be considered for such findings; first, each published study has had small sample size, resulting in relatively weak statistical power to find the overall effects. Second, it is suggested that the allele frequency of MDM2 gene rs2279744 polymorphism is altered by ethnicity, raising the hypothesis that ethnic differences may influence the impact of this polymorphism. Considering the mentioned points, we performed a thorough and most update meta-analysis to examine the correlation between the rs2279744 polymorphism of the MDM2 gene and the risk of breast cancer. Our analysis encompassed a total of 39 studies, comprising 22,764 cases of breast cancer and 22,444 healthy controls. The aim was to establish a more accurate and dependable conclusion regarding this association.

Methods

This project was carried out in accordance with the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement [25]. Furthermore, it should be noted that the present research project does not involve any studies involving human participants or animals conducted by any of the authors.

Search Strategy

The major databases (PubMed/MEDLINE, ISI Web of Science, and Scopus) were systematically searched up to March 2023 to identify potential publications considering the association between MDM2 gene polymorphism (rs2279744 or SNP309) and susceptibility to BC. The main key words were: (“murine double minute 2” OR “mouse double minute 2” OR “MDM2”) AND (“breast cancer” OR “breast tumor” OR “breast carcinoma” OR “breast neoplasm*”) AND (“polymorphism*” OR “variant*” OR “mutation” OR “genotype” OR “SNP” OR “allele” OR “single nucleotide polymorphism” OR “SNP309” OR “rs2279744”). Additionally, comprehensive cross-referencing was conducted within both eligible and reviewed articles to identify any potential additional publications. Original studies conducted in the English language were gathered with a focus on human populations.

Study Selection

The initial search strategy resulted in a total of 1191 publications, which were subsequently imported into the Endnote X9 software. Duplicate entries were eliminated. Two investigators then proceeded to review the titles and abstracts of the remaining studies, excluding those that were deemed irrelevant. A thorough assessment of the full text was conducted if we could not stratify studies based on the title & abstract. Any discrepancies or disagreements between the investigators were thoroughly discussed and resolved through consensus.

Eligibility Criteria

Studies considered eligible if they met the following criteria: (i) all case–control or cohort studies considering MDM2 gene polymorphism and BC as the major outcome; (ii) studies containing allele frequency and genotype distribution for case and control groups; (iii) studies including sufficient data to extract or calculate odds ratios (ORs) and 95% confidence intervals (CIs). Only studies with female BC cases were included in the final meta-analysis. Duplicates, animal study, book chapters, review articles, letters to editor, case reports, and studies with repetitive subjects all were excluded. The application of these criteria identified 39 eligible studies for quantitative analysis.

Data Extraction and Quality Assessment

Two investigators independently collected the required information by following a standardized extraction checklist. The data included the name of the first author, age, country of origin, ethnicity, and journal and publication year, number of subjects in the case and control groups, genotyping method, and genotype, and allele counts in the case and control groups. Methodological quality of qualified publication was scored by Newcastle–Ottawa scale (NOS), a validated scale for non-randomized studies in meta-analysis [26]. Based on the NOS score, studies were stratified to high-quality (7–9), intermediate-quality (4–6), and low-quality (1–3).

Statistical Analysis

Deviation from Hardy–Weinberg equilibrium (HWE) for genotype frequency was evaluated by Pearson’s chi-square test in the control group (P < 0.05 was considered as significant). The five comparison models were as follow: dominant model (GG + GT vs. TT), recessive model (GG vs. GT + TT), allelic model (G vs. T), homozygote (GG vs. TT), and heterozygote (GT vs. TT). The strength of association between rs2279744 polymorphism and BC risk was evaluated via pooled ORs and their 95% CIs. Cochrane’s Q test and the I2 test were explored to measure potential between study heterogeneity. In this regard, the fixed-effected model (FEM) was used if PQ-statistic > 0.10 or I2 was < 50%; otherwise, the random-effected model (REM) was applied [27, 28]. In order to assess sources of heterogeneity among included studies, subgroup analysis, and meta-regression analysis based on year of population, the continent of the study population, and the genotyping method were performed. The influence of individual study on the overall effect size was estimated by sensitivity analysis. Begg’s test, Egger’s regression test, and visual examination of the funnel plot were applied to measure publication bias [29, 30]. All statistical analyses were conducted using Stata statistical software (version 14.0; Stata Corporation, College Station, TX, USA) and SPSS (version 23.0; SPSS, Inc. Chicago, IL, USA).

Trial Sequential Analysis

The poor effect of systematic or random errors may stem from sparse data and mislead results in meta-analyses. To attenuated their effects and get more reliable results, the trial sequential analysis (TSA) was used (Copenhagen Trial Unit, Denmark, 2011; https://ctu.dk/tsa/). In this study, we set up TSA with type-I error of 5%, a statistical test power of 80%, and a − 50% relative risk reduction.

Results

Study Characteristics

The study selection process, in accordance with the PRISMA statement, is depicted in Fig. 1, illustrating four distinct phases. Initially, after eliminating duplicate publications (331 in total), 860 publications remained. Subsequently, 631 publications were excluded based on title and abstract screening, followed by the exclusion of 190 publications through full-text evaluation. Ultimately, a total of 39 eligible studies were included for the final analysis. All references from these selected publications were cross-checked, and no additional relevant studies were identified. These studies were published between 2006 and 2022 and were deemed to possess good methodological quality overall, as determined by NOS scores ranging from five to eight. The majority of the included studies employed polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) or PCR methods for genotyping. The sample size in case and control groups varied, ranging from. 39 to 2811 and 45 to 3749 individuals, respectively. The mean ages of participants in both the case and control groups ranged from 23 to 82, indicating that the studies were conducted among adult populations. Detailed characteristics and genotype frequencies of the included studies can be found in Tables 1 and 2.

Fig. 1
figure 1

Flow diagram of study selection process

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Table 1 Characteristics of studies included in meta-analysis
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Table 2 Distribution of genotype and allele among BC patients and controls
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Quantitative Synthesis

In the current meta-analysis, the major TT genotype of the MDM2 gene rs2279744 SNP was used as the reference category for the statistical comparisons.

Meta-Analysis of MDM2 Gene rs2279744 Polymorphism and BC Risk

Overall Analysis

In this study, a comprehensive search yielded 42 studies (derived from 39 publications) that presented relevant data on the association between the MDM2 gene rs2279744 polymorphism and breast cancer (BC) risk. The quantitative analysis encompassed a total of 22,764 BC cases and 22,444 controls. Of them, 17 studies were performed among countries with Caucasian ethnicity [31,32,33,34,35,36,37,38,39,40,41,42,43,44], 16 studies were in Asians [2, 45,46,47,48,49,50,51,52,53], 5 studies were in countries with mix ethnicity (American, African-America, Latin) [54,55,56,57,58], and one study in Oceania [8]. The pooled OR divulged a positive association between rs2279744 and risk of BC and demonstrated this SNP as a predisposing factor for BC, according to dominant model (odds ratio = 1.04, 95% CI = 1–1.09, P = 0.03), recessive model (odds ratio = 1.13, 95% CI = from 1.01 to 1.26, P = 0.02), allelic model (odds ratio = 1.07, 95% CI = from 1.02 to 1.12, P = 0.009), and GG versus. TT model (odds ratio = 1.18, 95% CI = from 1.04 to 1.34, P 0.008) (Fig. 2). REM was employed to assess recessive, allelic, and GG versus TT models, whereas FEM was utilized to analyze dominant and GT versus TT models. Table 3 displays the outcomes of heterogeneity tests, pooled odds ratios (ORs), and publication bias assessments across various analytic models.

Fig. 2
figure 2

Pooled OR and 95% CI of individual studies and pooled data for the association between MDM2 gene rs2279744 and BC risk in: A; recessive model and B; allelic model

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Table 3 Main results of pooled ORs in meta-analysis of MDM2 gene polymorphism
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Subgroup Analysis by Ethnicity

We stratified eligible articles into three groups, including Caucasians (17 articles), Asians (16 articles), and mixed population (five articles). The results of quantitative analysis demonstrated rs2279744 as a potential risk factor for Asians under some genotype models. In details, dominant model (odds ratio = 1.13, 95% CI = from 1.01 to 1.27, P = 0.02), allelic model (odds ratio = 1.13, 95% CI = from 1 to 1.28, P = 0.05), and GT versus TT model (odds ratio = 1.17, 95% CI = from 1.04 to 1.32, P = 0.01) for Asian indicated significant association with increased risk of BC (Fig. 3). No significant association was detected for population with Caucasians and mixed ethnicity (Table 3).

Fig. 3
figure 3

Pooled OR and 95% CI of individual studies and pooled data for the association between MDM2 gene rs2279744 and BC risk in different ethnicity subgroups for: A; allelic model and B; TG versus TT model

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Meta-Regression Analyses

To explore the potential factors contributing to the observed heterogeneity among the included studies, logistic meta-regression analyses were conducted (Table 4). The results revealed that none of the examined parameters, including publication year, continent, and genotyping method were the source of heterogeneity (Fig. 4).

Table 4 Meta-regression analyses of potential source of heterogeneity
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Fig. 4
figure 4

Meta-regression plots for the meta-analysis of the association between MDM2 gene rs2279744 and risk of BC based on; A: Publication year, B: continent (Asian = 1, Europa = 2, America = 3), C: genotyping methods (RFLP-PCR = 1, PCR = 2, Taqman-PCR = 3, RT-PCR = 4, ARMS-PCR = 5, others = 6)

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Evaluation of Publication Bias and Heterogeneity

For all five genetic models, the level of heterogeneity was assessed. Overall, significant heterogeneity was detected in certain models, leading to the adoption of a random effect model (Table 3). The application of Egger’s regression, Begg’s rank correlation analysis, and quantitative analysis-based funnel plot revealed no statistically significant findings, indicating the absence of publication bias (Table 3 and Fig. 5).

Fig. 5
figure 5

Begg’s funnel plot for publication bias test. Each point represents a separate study for the association between MDM2 gene rs2279744 and risk of BC (dominant model)

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Sensitivity Analysis

The influence of each study on the combined odds ratio (OR) was assessed through a systematic removal of each study in a sequential manner. The results confirmed that none of the individual studies had a substantial impact on the combined ORs across all genotype models of the MDM2 gene rs2279744 polymorphism (Fig. 6).

Fig. 6
figure 6

Sensitivity analysis for the meta-analysis of MDM2 gene rs2279744 in association with the risk of BC (dominant model)

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Trial Sequential Analysis

The results of TSA analysis for dominant model revealed that Z curve crosse both conventional statistical significance boundary corresponding to two-sided P-value of 0.05 (− 2, 2) and TSA monitoring boundary. These evidences indicated that the current meta-analysis is conclusive at this level and further relevant studies are unnecessary (Fig. 7).

Fig. 7
figure 7

TSA of the association between MDM2 gene rs2279744 (dominant model) and risk of BC

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Discussion

Up to now, a bulk of individual case–control replication studies have tried to decipher the correlation between MDM2 gene rs2279744 polymorphism and risk of BC. However, these replication investigations have produced conflicting results due to certain disparities. Factors such as differences in the racial composition of the study population, differences in the diagnostic criteria used for identifying cases, and low sample sizes may underlie these discrepancies [59]. Nevertheless, meta-analysis studies offer an approach to address this issue by mitigating the limitations inherent in individual replication studies, including inadequate statistical power. Consequently, in order to overcome the above-mentioned limiting factors with respect to the association of MDM2 gene rs2279744 polymorphism and risk of BC, here we performed the most update and comprehensive systematic review and meta-analysis through including 39 studies (containing 22,764 cases and 22,444 healthy controls).

From genetic and functional perspective, T to G substitution in rs2279744 SNP at nucleotide 309 in the first intron of MDM2 gene causes a promoted affinity of the promoter to the transcription activator SP1, resulting in upregulation of mRNA and protein expression of MDM2. This issue, in turn, interferes with the function of tumor suppressing p53 pathway [24]. Several studies have revealed that MDM2 gene rs2279744 polymorphism could increase the susceptibility of individuals to develop several types of cancers, such as breast, gastric, bladder, endometrial, ovary.

Zhang et al. [60] performed a systematic review and meta-analysis of MDM2 gene rs2279744 and rs117039649 polymorphisms and risk of gynecological cancers, encompassing cervical, breast, ovarian, and endometrial cancer. They included 24 articles for rs2279744 polymorphism, involving 6808 controls and 6094 cases. This meta-analysis revealed that the TT and T (compared to those with GG, G) genotype exhibited a reduced risk of gynecological cancer. Conversely, the GG genotype, (in comparison to the combined TG + TT genotype) was associated with an increased risk of gynecological cancer. This meta-analysis indicated no significant association of MDM2 gene rs2279744 and risk of BC. Additionally, Gao et al. [61] in 2014 performed a meta-analysis of association between MDM2 gene rs2279744 SNP and risk of BC by including 19 studies, involving 7815 BC cases and 8677 controls. The overall analysis revealed that GT (OR = 1.10) and GG (OR = 1.09) genotypes were associated with increased risk of BC. Our meta-analysis, on the other hand, specifically considered the BC patients in the meta-analysis and included a large number of subjects in the analysis (39 studies containing 22,764 cases and 22,444 healthy controls), which is considered a remarkable improvement with respect to sample size, conferring robust statistical power and reliable results. Based on the analysis performed in the current meta-analysis, the dominant model (OR = 1.04), recessive model (OR = 1.13), allelic model (OR = 1.07), GG genotype (OR = 1.18) indicated a statistically significant increased risk of BC.

We conducted a subgroup analysis by categorizing the patients according to their ethnic backgrounds. The populations were stratified into three groups, including Caucasians, Asians, and mixed populations. The results indicated that the dominant model (OR = 1.13), allelic model (OR = 1.13), and GT genotype (OR = 1.17), of the MDM2 gene rs2279744 SNP was associated with increased risk of BC in Asians. The previous meta-analysis by Zhang et al. [60], on the other hand, revealed that TT or T allele was associated with a lower risk of gynecological cancer in the dominant, heterozygote, and allele models in Caucasian. However, the GG genotype exhibited a significantly elevated susceptibility to gynecological cancer among individuals of Asian descent. Furthermore, their subgroup analysis, according to the type of cancer, did not indicate significant association of MDM2 gene rs2279744 SNP with risk of BC. Furthermore, Gao et al. [61] meta-analysis indicated significant association of GT in Caucasians, GT in Africans, and allelic, GG genotype, GT genotype, and dominant models in Asians.

In our meta-analysis, meta-regression analyses were conducted to look for potential sources of heterogeneity, suggesting that none of the potential heterogeneity sources, including publication year, continent, and genotyping method were conferring heterogeneity to the results. Interestingly, the TSA analysis revealed that the present meta-analysis provided sufficient evidence to draw a conclusive understanding of the association between rs2279744 polymorphism of the MDM2 gene and risk of BC.

This meta-analysis holds a number of caveats and limitations. Initially, the analysis was bases on the crude estimation of MDM2 gene rs2279744 polymorphism association with risk of BC. This assessment did not take into account the influence of confounding factors or the involvement of other genes linked to the MDM2 gene. Second, potential bias raised through population stratification and false positive, which are very common in candidate approach studies, could be a source of heterogeneity that was unable to be abrogated in the analysis. Third, our analysis did not encompass an examination of additional genes that may play a role in elucidating the relationship between tumor suppressor genes/oncogenes in the susceptibility to BC.

Conclusion

Taking into account all the relevant information, this study represents the most recent and comprehensive systematic review and meta-analysis examining the correlation between the MDM2 gene rs2279744 polymorphism and risk of BC. The analysis consisted of a comprehensive evaluation of 39 studies comprising a total of 22,764 BC cases and 22,444 healthy controls. Our analysis indicated increased risk of BC in the overall pooled analysis. Furthermore, this polymorphism was a genetic risk variation in the Asians. This study suggests that further studies should consider other genetic variations of the MDM2 gene in an interaction with rs2279744 polymorphism as well as other tumor suppressor genes/oncogenes in BC patients.