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. 2017 Jul 27;10:3773–3780. doi: 10.2147/OTT.S140424

MDM2 promoter del1518 polymorphism and cancer risk: evidence from 22,931 subjects

Wenfeng Hua 1,*,✉, Anqi Zhang 2,*, Ping Duan 2,*, Jinhong Zhu 3, Yuan Zhao 2, Jing He 4, Zhi Zhang 1,✉
PMCID: PMC5538693  PMID: 28794641

Abstract

Studies have shown that single-nucleotide polymorphisms in MDM2 gene may play important roles in the development of malignant tumor. The association of del1518 polymorphism (rs3730485) in the MDM2 promoter with cancer susceptibility has been extensively studied; however, the results are contradictory. To quantify the association between this polymorphism and overall cancer risk, we conducted a meta-analysis with 12,905 cases and 10,026 controls from 16 eligible studies retrieved from PubMed, Embase, and Chinese Biomedical (CBM) databases. We assessed the strength of the connection using odds ratios (ORs) and 95% confidence intervals (CIs). In summary, no significant associations were discovered between the del1518 polymorphism and overall cancer risk (Del/Del vs Ins/Ins: OR =1.01, 95% CI =0.90–1.14; Ins/Del vs Ins/Ins: OR =1.03, 95% CI =0.96–1.12; recessive model: OR =0.98, 95% CI =0.90–1.07; dominant model: OR =1.03, 95% CI =0.94–1.12; and Del vs Ins: OR =1.01, 95% CI =0.94–1.07). In the stratified analysis by source of control, quality score, cancer type, and ethnicity, no significant associations were found. Despite some limitations, the current meta-analysis provides solid statistical evidence of lacking association between the MDM2 del1518 polymorphism and cancer risk.

Keywords: MDM2, del1518, polymorphism, cancer susceptibility, meta-analysis

Introduction

Worldwide cancer incidence and mortality continues to increase greatly. More than 14.1 million cancer cases and 8.2 million cancer-associated deaths were reported by the latest GLOBOCAN estimates. The burden of cancer has become a serious global problem, particularly in economically developing countries, on account of aging society, smoking, nutritional status, obesity, and physical inactivity. Despite restriction on tobacco use, advocation on vaccination, early diagnosis, and treatment that can prevent cancer mortality effectively, the causes of cancer are still far from clear.1 According to molecular epidemiological researches, genetic polymorphisms have been implicated in diverse carcinogenesis mechanisms.2,3

p53, a tumor suppressor protein, is implicated in almost half of all human cancer. In response of genotoxic stress and oncogenic signals, p53 actives a transcriptional program to induce several cellular damage responses, including apoptosis, cell cycle halt, and autophagy.4,5 In certain cases, p53 activity is depressed by the overexpression of MDM2, a cellular antagonist. MDM2 acts as a major node in the P53 pathway. The MDM2 is an ubiquitin ligase E3 for p53, which promotes the degradation of P53 by the proteasome. There is a negative feedback loop between P53 and MDM2, in which activating p53 protein increases MDM2 transcription, and the resulting MDM2 protein interacts with p53, thereby causing p53 degradation.6 Previous reports have clearly shown that polymorphisms associate with diseases susceptibility by altering affected proteins structurally and functionally. Human MDM2 gene is located on chromosome 12q14.3–q15.1, which contains two promoters, an upstream constitutive promoter (P1) and an internal promoter (P2).7,8 The genetic variations within either of promoters may alter the expression of MDM2. For instance, MDM2 SNP309 (rs2279744, T>G) within promoter P2 enhances the affinity of promoter with the transcriptional activator SP1 to increase MDM2 transcription, thereby promoting tumor development in the different tissues.9 In addition, a del1518 polymorphism (rs3730485), a 40 bp insertion/deletion in the MDM2 promoter P1 region, could also affect promoter activity.10 Recently, several lines of evidence have indicated that the del1518 del-allele contributes to an increase in cancer risk;11–13 however, opposite results were also reported.14,15 To explore the precise correlation between del1518 polymorphism and cancer risk, we performed this meta-analysis with all eligible publications.

Methods

Publication search

All possible publications related the association between MDM2 del1518 polymorphism and cancer risk were searched for from PubMed and Embase (up to March 29, 2017). The following items were used: “MDM2 or mouse double minute 2 homolog or human homolog of mouse double minute 2”, “del1518 or rs3730485”, “polymorphism or single-nucleotide polymorphism (SNP) or variant”, and “tumor or cancer or carcinoma or neoplasm”. The reference lists of all eligible studies in the initial search were searched manually to retrieve potentially relevant studies. To broaden our search to find the most relevant research, we also retrieved publications from Chinese Biomedical (CBM) database with items of “MDM2” and “cancer” in Chinese.

Inclusion/exclusion criteria

Studies selected had to meet the following inclusion criteria: 1) evaluating the association between MDM2 del1518 polymorphism and cancer risk, 2) case–control studies, 3) supplying detailed genotype distribution data to estimate the odds ratio (OR) with 95% confidence interval (CI), and 4) published in English or Chinese. Only the latest study was selected from duplicate publications. In addition, studies with genotype frequency distribution of controls departed from Hardy–Weinberg equilibrium (HWE) were excluded from the final analysis.

Data extraction

Information was extracted from studies by two authors (WH and AZ) independently. If two authors had disagreement, a third author would join in the discussion. A final decision would be made by voting. The following information was collected from each study: first author’s surname, year of publication, country of origin, ethnicity, cancer type, control source, total number of cases and controls, genotype methods, percent of males, and numbers of cases and controls with the Ins/Ins, Ins/Del, and Del/Del genotypes for del1518 polymorphism. The subgroup analysis was carried out by ethnicity (Asians and Caucasians), source of control (hospital based [HB] and population based [PB]), and cancer type. Cancer type investigated in only one study was classified into the “others” group.

Statistical methods

Consistency with HWE in the control group was evaluated by Pearson’s goodness-of-fit χ2 test for each study (P<0.05 was considered as statistically significant deviation from HWE). OR and 95% CI were used to assess the strength of the association between the del1518 polymorphism and cancer risk. Pooled risk estimates were calculated under the alleles contrast (Del vs Ins), homozygous (Del/Del vs Ins/Ins), heterozygous (Ins/Del vs Ins/Ins), dominant (Ins/Del and Del/Del vs Ins/Ins), and recessive (Del/Del vs Ins/Del and Ins/Ins) model. We used the chi square-based Q-test to determine the heterogeneity among studies. A P-value of <0.1 means significant heterogeneity. Under such circumstances, the random-effects model would be taken to assess the pooled ORs; otherwise, the fixed-effects would be adopted.16–18 The quality assessment was also performed using the quality assessment criteria (Table S1) as described previously.19 All studies were scored from 0 to 15, and only studies with a score of ≥12 were regarded as high quality. Subgroup analysis was conducted by cancer type, source of control, quality score, and race. Begg’s funnel plots and Egger’s test were used to assess publication bias. The accuracy and reliability of results were verified by sensitivity analysis by sequentially removing one single study at a time to check the influence of deleted study on pooled ORs. All the statistical tests were conducted by STATA Version 11.0 (StataCorp LP, College Station, TX, USA). P<0.05 indicated statistical significance.

Results

Study characteristics

As shown in Figure 1, a total of 14 articles were retrieved from the initial literature search. After careful examination and assessment, three publications were excluded for the following reasons: one had duplicate data with the previous research20 and other two were irrelevant with cancer risk.21,22 All studies were in agreement with HWE, except for an article by Jin et al.11 We included this article for the further study because genotype distribution of the TP53 Arg72 Pro polymorphism was in accordance with HWE in the same study.11 Of these 11 publications, two publications involved two cancer types14,23 and one publication involved four cancer types.24 We divided these articles into different independent studies based on cancer type. And, the controls of these three publications were included into meta-analysis only once. Main characteristics of each study are summarized in Table 1. Totally, there were 12,905 cases ranging from 132 to 2,501 and 10,026 controls ranging from 132 to 3,749 included in the present meta-analysis. Three studies were conducted on esophageal squamous cell carcinoma,14,15,25 two studies were conducted on breast,24,26 colorectal,11,24 ovarian cancer,23,27 and lung,24,28 and five studies were conducted on “others”, such as gastric cardiac adenocarcinoma,14 hepatocellular carcinoma,12 uterine leiomyoma,13 prostate cancer,24 and endometrial cancer.23 Twelve studies were PB,11–14,24–26,28 and four studies were HB.15,23,27 Moreover, there were seven studies performed among Caucasians13,23,24 and nine studies among Asians.11,12,14,15,25–28 In addition, quality scores of seven studies were <12 and scores of the remaining studies were ≥12.

Figure 1.

Figure 1

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Flowchart of selection of studies included in the current meta-analysis for the correlation between MDM2 del1518 polymorphism and overall cancer susceptibility.

Abbreviation: CBM, Chinese Biomedical.

Table 1.

Characteristics of studies included in the current meta-analysis

Surname Year Cancer type Country Ethnicity Design Genotype method Males (%), case/control Case
Control
MAF HWE Score
II ID DD All II ID DD All
Hu 2006 Lung China Asian PB PCR 73.5/72.7 349 317 51 717 523 464 96 1,083 0.30 0.631 13
Ma 2006 Breast China Asian PB PCR 0.0/0.0 179 157 30 366 305 241 59 605 0.30 0.263 9
Cao 2007 ESCC China Asian PB PCR 67.2/64.6 181 146 24 351 310 285 47 642 0.30 0.090 11
Cao 2007 Gastric China Asian PB PCR 63.2/64.6 132 72 8 212 310 285 47 642 0.30 0.090 11
Jin 2008 Colorectal China Asian PB PCR NA/NA 25 80 95 200 182 319 339 840 0.59 <0.001 12
Kang 2009 Ovarian China Asian HB PCR 0.0/0.0 132 106 19 257 122 115 20 257 0.30 0.318 9
Dong 2012 HCC China Asian PB PCR 65.7/65.0 169 199 52 420 206 178 39 423 0.30 0.951 12
Ma 2012 ESCC China Asian PB PCR 55.8/55.8 120 91 15 226 118 92 16 226 0.27 0.736 10
Salimi 2015 UL Iran Caucasian PB PCR 0.0/0.0 71 60 23 154 119 64 14 197 0.23 0.195 9
Zhang 2015 ESCC China Asian HB PCR 50.8/56.1 17 59 56 132 13 48 71 132 0.72 0.257 9
Gansmo 2016 Colorectal Norway Caucasian PB PCR 49.2/50.1 478 775 279 1,532 1,285 1,777 687 3,749 0.42 0.095 12
Gansmo 2016 Lung Norway Caucasian PB PCR 62.7/50.1 447 624 260 1,331 1,285 1,777 687 3,749 0.42 0.095 12
Gansmo 2016 Breast Norway Caucasian PB PCR 0.0/0.0 581 809 327 1,717 1,285 1,777 687 3,749 0.42 0.095 12
Gansmo 2016 Prostate Norway Caucasian PB PCR 100.0/100.0 836 1,240 425 2,501 1,285 1,777 687 3,749 0.42 0.095 12
Gansmo 2017 Ovarian Norway Caucasian HB PCR 0.0/0.0 484 655 246 1,385 636 877 359 1,872 0.43 0.069 12
Gansmo 2017 Endometrial Norway Caucasian HB PCR 0.0/0.0 492 664 248 1,404 636 877 359 1,872 0.43 0.069 12
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Abbreviations: HB, hospital based; HCC, hepatocellular carcinoma; HWE, Hardy–Weinberg equilibrium; ESCC, esophageal squamous cell carcinoma; MAF, minor allele frequency; NA, not available; PB, population based; PCR, polymerase chain reaction; UL, uterine leiomyoma; II, Ins/Ins; DD, Del/Del; ID, Ins/Del.

Meta-analysis results

The results for the association between del1518 del/ins polymorphism and cancer risk are shown in Table 2 and Figure 2. Overall, the pooled risk estimates suggested that no statistically significant association was found between the polymorphism and cancer risk (Del/Del vs Ins/Ins: OR =1.01, 95% CI =0.90–1.14; Ins/Del vs Ins/Ins: OR =1.03, 95% CI =0.96–1.12; Del/Del vs Ins/Del + Ins/Ins: OR =0.98, 95% CI =0.90–1.07; Ins/Del + Del/Del vs Ins/Ins: OR =1.03, 95% CI =0.94–1.12; Del vs Ins: OR =1.01, 95% CI =0.94–1.07). Moreover, the stratified analysis by source of control, quality score, cancer type, and ethnicity showed no evidence of the association between del1518 polymorphism and overall cancer risk.

Table 2.

Meta-analysis of the association between MDM2 del1518 (rs3730485) polymorphism and overall cancer risk

Variables Number of studies Homozygous
Heterozygous
Recessive
Dominant
Allele
DD vs II
ID vs II
DD vs ID + II
ID + DD vs II
D vs I
OR (95% CI) Phet OR (95% CI) Phet OR (95% CI) Phet OR (95% CI) Phet OR (95% CI) Phet
All 16 1.01 (0.90–1.14) 0.003 1.03 (0.96–1.12) 0.009 0.98 (0.90–1.07) 0.049 1.03 (0.94–1.12) <0.001 1.01 (0.94–1.07) <0.001
Cancer type
 Lung 2 0.97 (0.72–1.30) 0.133 1.01 (0.90–1.14) 0.909 0.96 (0.71–1.30) 0.108 1.02 (0.91–1.13) 0.694 1.01 (0.94–1.10) 0.303
 Breast 2 1.03 (0.88–1.20) 0.449 1.03 (0.91–1.15) 0.526 1.03 (0.89–1.18) 0.333 1.03 (0.92–1.15) 0.780 1.02 (0.95–1.10) 0.822
 ESCC 3 0.82 (0.56–1.19) 0.700 0.91 (0.74–1.13) 0.909 0.79 (0.58–1.08) 0.500 0.89 (0.73–1.10) 0.809 0.89 (0.76–1.04) 0.428
 Others 5 1.07 (0.78–1.48) 0.001 1.04 (0.84–1.29) 0.001 1.01 (0.79–1.29) 0.015 1.05 (0.83–1.33) <0.001 1.03 (0.86–1.24) <0.001
 Colorectal 2 1.43 (0.78–2.63) 0.016 1.37 (0.91–2.08) 0.084 1.12 (0.84–1.49) 0.091 1.42 (0.86–2.36) 0.029 1.20 (0.91–1.60) 0.020
 Ovarian 2 0.90 (0.74–1.09) 0.944 0.96 (0.83–1.11) 0.480 0.91 (0.77–1.09) 0.911 0.94 (0.82–1.08) 0.556 0.95 (0.86–1.04) 0.708
Ethnicity
 Asians 9 0.95 (0.70–1.29) 0.005 1.01 (0.84–1.21) 0.004 0.92 (0.74–1.15) 0.071 0.99 (0.81–1.21) <0.001 0.96 (0.83–1.12) <0.001
 Caucasians 7 1.02 (0.91–1.13) 0.055 1.05 (0.98–1.12) 0.246 0.99 (0.90–1.08) 0.104 1.04 (0.97–1.12) 0.082 1.02 (0.96–1.08) 0.020
Source of control
 PB 12 1.07 (0.92–1.24) 0.002 1.06 (0.96–1.17) 0.003 1.02 (0.92–1.14) 0.048 1.06 (0.95–1.18) <0.001 1.04 (0.96–1.12) <0.001
 HB 4 0.89 (0.77–1.02) 0.822 0.97 (0.87–1.07) 0.911 0.89 (0.79–1.00) 0.570 0.94 (0.86–1.04) 0.859 0.94 (0.88–1.00) 0.517
Quality score
 ≥12 9 1.04 (0.92–1.16) 0.015 1.06 (0.99–1.14) 0.108 0.99 (0.92–1.08) 0.127 1.06 (0.98–1.14) 0.025 1.03 (0.97–1.09) 0.010
 <12 7 0.89 (0.61–1.30) 0.026 0.94 (0.75–1.16) 0.027 0.89 (0.65–1.21) 0.080 0.93 (0.73–1.18) 0.003 0.93 (0.76–1.14) <0.001
Bias 0.919 0.921 0.920 0.921 0.990
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Abbreviations: CI, confidence interval; DD, Del/Del; ESCC, esophageal squamous cell carcinoma; HB, hospital based; het, heterogeneity; ID, Ins/Del; II, Ins/Ins; OR, odds ratio; PB, population based.

Figure 2.

Figure 2

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Forest plots of effect estimates for MDM2 del1518 polymorphism and overall cancer susceptibility under dominant model (ID + DD vs II).

Notes: For each study, the estimation of OR and its 95% CI is plotted with a box and a horizontal line. The diamonds represent the pooled ORs and 95% CIs. Weights are from random effects analysis.

Abbreviations: CIs, confidence intervals; ORs, odds ratios; ID, Ins/Del; II, Ins/Ins; DD, Del/Del.

Heterogeneity and sensitivity analysis

As shown in Table 1, significant between-study heterogeneity was observed under the different models (homozygous model: P=0.003; heterozygous model: P=0.009; recessive model: P=0.049; dominant model: P<0.001; and allele comparing: P<0.001); therefore we adopted the random-effects model to generate wider CIs. Sensitivity analysis suggested that ORs were not significantly altered by any single study, indicating that this meta-analysis result was stable and reliable.

Publication bias

The publication bias was performed by Begg’s funnel plot and Egger’s test. We found no asymmetry of funnel plot (Figure 3). In addition, the results of Egger’s test did not suggest any evidence of publications bias (homozygous: P=0.919; heterozygous: P=0.921; recessive model: P=0.920; dominant model: P=0.921; and allele comparing model: P=0.990).

Figure 3.

Figure 3

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Funnel plot to detect publication bias for MDM2 del1518 polymorphism and overall cancer susceptibility under dominant model.

Note: Each point represents a separate study for the indicated association.

Abbreviation: ES, effect size.

Discussion

The tumor suppressor p53, a transcriptional factor, essentially controls the growth and development of normal cells. p53 instability may lead to cell cycle disorder and aberrant cellular apoptosis, thereby strongly contributing to malignant transformation and progression.29,30 The MDM2 gene, a genomic size of 34 kb, contains two promoters, such as a p53-responsive promoter and a p53-independent promoter.8 MDM2, as a major mechanism of genetic toxicity and carcinogenesis, is a principle regulator of the stabilization of p53 in the no-stress condition.31 MDM2, functioning as an E3 ligase, specifically complexes with p53 by the N-terminus domain and induces its degradation through proteasomal pathway.32,33 The expression of MDM2 is elevated by p53-positive regulation. Given a negative autoregulatory loop between MDM2 and p53, the importance of MDM2 has been proved in the central part of p53-assosiated signal pathway.34,35 Genetic variations, including SNPs and other types of polymorphisms, may modify genetic predisposition to diseases.36 Some genetic alterations located in the MDM2 gene, such as SN309,37 have been proved to be associated with cancer risk.16,38,39 As far as we know, there are at least 4,765 polymorphisms found in the MDM2 gene (http://www.ncbi.nlm.nih.gov/projects/SNP). One of the frequently investigated polymorphisms is MDM2 del1518, a common 40 bp Ins/Del polymorphism, located in constitutive promoter with a putative TATA motif.10,26

Due to the special location of del1518 polymorphism, its association with cancer risk has been a hot spot. Salimi et al suggested that women carrying del allele had an increased risk of uterine leiomyoma compared with the women carrying MDM2 40 bp insert allele.13 Jin et al reported that the 40 bp deletion allele had an important role in the oncogenesis of colorectal cancer, specially for rectal cancer.11 In addition, a genetic association study by Dong et al have found that the del1518 was significantly associated with an increased risk of hepatocellular carcinoma.12 While some studies have considered del1518 del-allele as susceptibility loci for the risk of various cancer types,14,15 other studies failed to confirm its contribution to cancer risk.23–28 The discrepant results might be caused by small sample size, and variations among different study populations. Moreover, it is widely believed that malignancies arising from different tissue had completely distinct molecular mechanisms, and even the same cancer type could display significant heterogeneity among different individuals.

In the current meta-analysis, we combined all eligible investigations comprising 12,905 cases and 10,026 controls from 16 studies on MDM2 del1518 polymorphism. We found no significant association between del1518 polymorphism in the overall analysis and stratification analyses by cancer type, ethnicity, source of control, and scores. A latest meta-analysis conducted by Yu et al found that there was no significant difference between del1518 polymorphism and overall squamous cell carcinoma susceptibility with a total of 309 cases and 1,000 controls from three studies, results of which is consistent with the current study.22

To our knowledge, this investigation is the largest and most comprehensive meta-analysis regarding the association between del1518 polymorphism and all cancer type. However, there were still some limitations to be addressed. First, statistical power might be limited to certain degree, especially for stratified analyses, such as cancer type of gastric, hepatocellular, uterine leiomyoma, prostate, and endometrial. Hence, the results of this meta-analysis should be interpreted with caution. Second, because of the stratification analysis of ethnicity included Asians and Caucasians only, we could not take genetic and geographical differences into consideration. Further analysis should contain diverse area and ethnicities. Third, the results of this study were based on unadjusted estimates by the reason of insufficient data of individual such as age, gender, smoking, environment exposure, and lifestyles. Gene–gene and gene–environment interactions could not be explored. Fourth, there was obvious heterogeneity for the meta-analysis, which might owe to differences in cancer types, the populations, geographical area, and study designs. Finally, the included studies were mainly searched for from PubMed, Embase, and CBM; therefore, publication bias might exist in this meta-analysis for the unavailability of the unpublished studies with negative results.

Conclusion

Our present meta-analysis suggested no association between MDM2 gene del1518 polymorphism and overall cancer susceptibility. Further well-designed study with large sample sizes, different ethnicities, cancer types, and gene–environment interactions is needed to confirm our findings.

Supplementary material

Table S1.

Score of quality assessment

Criteria Score
Representativeness of cases
 Selected from population cancer registry 2
 Selected from hospital 1
 No method of selection described 0
Representativeness of controls
 Population based 3
 Blood donors 2
 Hospital based 1
 Not described 0
Ascertainment of cancer cases
 Histopathologic confirmation 2
 Patient medical record 1
 Not described 0
Control selection
 Controls matched with cases by age and sex 2
 Controls matched with cases only by age or by sex 1
 Not matched or not descried 0
Genotyping examination
 Genotyping done blindly and quality control 2
 Only genotyping done blindly or quality control 1
 Unblinded and without quality control 0
Total sample size for both cases and controls
 >1,000 3
 >500 but <1,000 2
 >200 but <500 1
 <200 0
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Acknowledgments

This study was supported by grants from the introduction of talent scientific research start-up fund of Guangdong Second Provincial General Hospital (YY2016-004), Scientific Research Foundation of Wenzhou (Y20100175), Zhejiang Provincial Medical and Health Science and Technology plan (2013RCA035), Project of Science and Technology Department of Zhejiang Province (2014C37003), and Zhejiang Provincial Natural Science Foundation of China (LY16H160054).

Footnotes

Disclosure

The authors report no conflicts of interest in this work.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1.

Score of quality assessment

Criteria Score
Representativeness of cases
 Selected from population cancer registry 2
 Selected from hospital 1
 No method of selection described 0
Representativeness of controls
 Population based 3
 Blood donors 2
 Hospital based 1
 Not described 0
Ascertainment of cancer cases
 Histopathologic confirmation 2
 Patient medical record 1
 Not described 0
Control selection
 Controls matched with cases by age and sex 2
 Controls matched with cases only by age or by sex 1
 Not matched or not descried 0
Genotyping examination
 Genotyping done blindly and quality control 2
 Only genotyping done blindly or quality control 1
 Unblinded and without quality control 0
Total sample size for both cases and controls
 >1,000 3
 >500 but <1,000 2
 >200 but <500 1
 <200 0
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