Literature DB >> 28794641

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

Wenfeng Hua1, Anqi Zhang2, Ping Duan2, Jinhong Zhu3, Yuan Zhao2, Jing He4, Zhi Zhang1.   

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.

Entities:  

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

Year:  2017        PMID: 28794641      PMCID: PMC5538693          DOI: 10.2147/OTT.S140424

Source DB:  PubMed          Journal:  Onco Targets Ther        ISSN: 1178-6930            Impact factor:   4.147


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

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

SurnameYearCancer typeCountryEthnicityDesignGenotype methodMales (%), case/controlCase
Control
MAFHWEScore
IIIDDDAllIIIDDDAll
Hu2006LungChinaAsianPBPCR73.5/72.734931751717523464961,0830.300.63113
Ma2006BreastChinaAsianPBPCR0.0/0.017915730366305241596050.300.2639
Cao2007ESCCChinaAsianPBPCR67.2/64.618114624351310285476420.300.09011
Cao2007GastricChinaAsianPBPCR63.2/64.6132728212310285476420.300.09011
Jin2008ColorectalChinaAsianPBPCRNA/NA2580952001823193398400.59<0.00112
Kang2009OvarianChinaAsianHBPCR0.0/0.013210619257122115202570.300.3189
Dong2012HCCChinaAsianPBPCR65.7/65.016919952420206178394230.300.95112
Ma2012ESCCChinaAsianPBPCR55.8/55.8120911522611892162260.270.73610
Salimi2015ULIranCaucasianPBPCR0.0/0.071602315411964141970.230.1959
Zhang2015ESCCChinaAsianHBPCR50.8/56.11759561321348711320.720.2579
Gansmo2016ColorectalNorwayCaucasianPBPCR49.2/50.14787752791,5321,2851,7776873,7490.420.09512
Gansmo2016LungNorwayCaucasianPBPCR62.7/50.14476242601,3311,2851,7776873,7490.420.09512
Gansmo2016BreastNorwayCaucasianPBPCR0.0/0.05818093271,7171,2851,7776873,7490.420.09512
Gansmo2016ProstateNorwayCaucasianPBPCR100.0/100.08361,2404252,5011,2851,7776873,7490.420.09512
Gansmo2017OvarianNorwayCaucasianHBPCR0.0/0.04846552461,3856368773591,8720.430.06912
Gansmo2017EndometrialNorwayCaucasianHBPCR0.0/0.04926642481,4046368773591,8720.430.06912

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

VariablesNumber of studiesHomozygous
Heterozygous
Recessive
Dominant
Allele
DD vs II
ID vs II
DD vs ID + II
ID + DD vs II
D vs I
OR (95% CI)PhetOR (95% CI)PhetOR (95% CI)PhetOR (95% CI)PhetOR (95% CI)Phet
All161.01 (0.90–1.14)0.0031.03 (0.96–1.12)0.0090.98 (0.90–1.07)0.0491.03 (0.94–1.12)<0.0011.01 (0.94–1.07)<0.001
Cancer type
 Lung20.97 (0.72–1.30)0.1331.01 (0.90–1.14)0.9090.96 (0.71–1.30)0.1081.02 (0.91–1.13)0.6941.01 (0.94–1.10)0.303
 Breast21.03 (0.88–1.20)0.4491.03 (0.91–1.15)0.5261.03 (0.89–1.18)0.3331.03 (0.92–1.15)0.7801.02 (0.95–1.10)0.822
 ESCC30.82 (0.56–1.19)0.7000.91 (0.74–1.13)0.9090.79 (0.58–1.08)0.5000.89 (0.73–1.10)0.8090.89 (0.76–1.04)0.428
 Others51.07 (0.78–1.48)0.0011.04 (0.84–1.29)0.0011.01 (0.79–1.29)0.0151.05 (0.83–1.33)<0.0011.03 (0.86–1.24)<0.001
 Colorectal21.43 (0.78–2.63)0.0161.37 (0.91–2.08)0.0841.12 (0.84–1.49)0.0911.42 (0.86–2.36)0.0291.20 (0.91–1.60)0.020
 Ovarian20.90 (0.74–1.09)0.9440.96 (0.83–1.11)0.4800.91 (0.77–1.09)0.9110.94 (0.82–1.08)0.5560.95 (0.86–1.04)0.708
Ethnicity
 Asians90.95 (0.70–1.29)0.0051.01 (0.84–1.21)0.0040.92 (0.74–1.15)0.0710.99 (0.81–1.21)<0.0010.96 (0.83–1.12)<0.001
 Caucasians71.02 (0.91–1.13)0.0551.05 (0.98–1.12)0.2460.99 (0.90–1.08)0.1041.04 (0.97–1.12)0.0821.02 (0.96–1.08)0.020
Source of control
 PB121.07 (0.92–1.24)0.0021.06 (0.96–1.17)0.0031.02 (0.92–1.14)0.0481.06 (0.95–1.18)<0.0011.04 (0.96–1.12)<0.001
 HB40.89 (0.77–1.02)0.8220.97 (0.87–1.07)0.9110.89 (0.79–1.00)0.5700.94 (0.86–1.04)0.8590.94 (0.88–1.00)0.517
Quality score
 ≥1291.04 (0.92–1.16)0.0151.06 (0.99–1.14)0.1080.99 (0.92–1.08)0.1271.06 (0.98–1.14)0.0251.03 (0.97–1.09)0.010
 <1270.89 (0.61–1.30)0.0260.94 (0.75–1.16)0.0270.89 (0.65–1.21)0.0800.93 (0.73–1.18)0.0030.93 (0.76–1.14)<0.001
Bias0.9190.9210.9200.9210.990

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

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

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. Score of quality assessment
Table S1

Score of quality assessment

CriteriaScore
Representativeness of cases
 Selected from population cancer registry2
 Selected from hospital1
 No method of selection described0
Representativeness of controls
 Population based3
 Blood donors2
 Hospital based1
 Not described0
Ascertainment of cancer cases
 Histopathologic confirmation2
 Patient medical record1
 Not described0
Control selection
 Controls matched with cases by age and sex2
 Controls matched with cases only by age or by sex1
 Not matched or not descried0
Genotyping examination
 Genotyping done blindly and quality control2
 Only genotyping done blindly or quality control1
 Unblinded and without quality control0
Total sample size for both cases and controls
 >1,0003
 >500 but <1,0002
 >200 but <5001
 <2000
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1.  P53 is a tumor suppressor gene.

Authors:  Arnold J Levine; Cathy A Finlay; Philip W Hinds
Journal:  Cell       Date:  2004-01-23       Impact factor: 41.582

2.  Association between SNP309 and del1518 Polymorphism in MDM2 Homologue and Esophageal Squamous Cell Carcinoma Risk in Chinese Population of Shandong Province.

Authors:  Lin Zhang; Zhendong Zhu; Hongyan Wu; Kejie Wang
Journal:  Ann Clin Lab Sci       Date:  2015       Impact factor: 1.256

3.  Genetic variants in the MDM2 promoter and lung cancer risk in a Chinese population.

Authors:  Zhibin Hu; Hongxia Ma; Daru Lu; Ji Qian; Jiannong Zhou; Yijiang Chen; Lin Xu; Xinru Wang; Qingyi Wei; Hongbing Shen
Journal:  Int J Cancer       Date:  2006-03-01       Impact factor: 7.396

Review 4.  Using high-throughput SNP technologies to study cancer.

Authors:  L J Engle; C L Simpson; J E Landers
Journal:  Oncogene       Date:  2006-03-13       Impact factor: 9.867

5.  No association between MTR rs1805087 A > G polymorphism and non-Hodgkin lymphoma susceptibility: evidence from 11 486 subjects.

Authors:  Jing He; Fang Wang; Jin-Hong Zhu; Wei Chen; Zhuo Cui; Wei-Hua Jia
Journal:  Leuk Lymphoma       Date:  2014-08-13

6.  Polymorphisms in the MDM2 promoter and risk of breast cancer: a case-control analysis in a Chinese population.

Authors:  Hongxia Ma; Zhibin Hu; Xiangjun Zhai; Shui Wang; Xuechen Wang; Jianwei Qin; Guangfu Jin; Jiyong Liu; Xinru Wang; Qingyi Wei; Hongbing Shen
Journal:  Cancer Lett       Date:  2005-11-08       Impact factor: 8.679

Review 7.  Improving cancer therapy by non-genotoxic activation of p53.

Authors:  S Lain; D Lane
Journal:  Eur J Cancer       Date:  2003-05       Impact factor: 9.162

8.  Association of LEP G2548A and LEPR Q223R polymorphisms with cancer susceptibility: evidence from a meta-analysis.

Authors:  Jing He; Bo Xi; Rikje Ruiter; Ting-Yan Shi; Mei-Ling Zhu; Meng-Yun Wang; Qiao-Xin Li; Xiao-Yan Zhou; Li-Xin Qiu; Qing-Yi Wei
Journal:  PLoS One       Date:  2013-10-17       Impact factor: 3.240

9.  Association of IL10 -819C>T and -592C>A Polymorphisms with Non-Hodgkin Lymphoma Susceptibility: Evidence from Published Studies.

Authors:  Ting Zhang; Shang Xie; Jin-Hong Zhu; Qi-Wen Li; Jing He; Ai-Ping Zeng
Journal:  J Cancer       Date:  2015-06-11       Impact factor: 4.207

10.  Influence of MDM2 polymorphisms on squamous cell carcinoma susceptibility: a meta-analysis.

Authors:  Huanxin Yu; Haiyan Li; Jinling Zhang; Gang Liu
Journal:  Onco Targets Ther       Date:  2016-10-11       Impact factor: 4.147

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  1 in total

1.  A case-control study on the SNP309T → G and 40-bp Del1518 of the MDM2 gene and a systematic review for MDM2 polymorphisms in the patients with breast cancer.

Authors:  Amin Jalilvand; Kheirollah Yari; Mozaffar Aznab; Zohreh Rahimi; Iman Salahshouri Far; Pantea Mohammadi
Journal:  J Clin Lab Anal       Date:  2020-09-20       Impact factor: 3.124

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