Literature DB >> 26471763

MDM4 SNP34091 (rs4245739) and its effect on breast-, colon-, lung-, and prostate cancer risk.

Liv B Gansmo1,2, Pål Romundstad3, Einar Birkeland1,2, Kristian Hveem3, Lars Vatten3, Stian Knappskog1,2, Per Eystein Lønning1,2.   

Abstract

The MDM4 protein plays an important part in the negative regulation of the tumor suppressor p53 through its interaction with MDM2. In line with this, MDM4 amplification has been observed in several tumor forms. A polymorphism (rs4245739 A>C; SNP34091) in the MDM4 3' untranslated region has been reported to create a target site for hsa-miR-191, resulting in decreased MDM4 mRNA levels. In this population-based case-control study, we examined the potential association between MDM4 SNP34091, alone and in combination with the MDM2 SNP309T>G (rs2279744), and the risk of breast-, colon-, lung-, and prostate cancer in Norway. SNP34091 was genotyped in 7,079 cancer patients as well as in 3,747 gender- and age-matched healthy controls. MDM4 SNP34091C was not associated with risk for any of the tumor forms examined, except for a marginally significant association with reduced risk for breast cancer in a recessive model (OR = 0.77: 95% CI = 0.59-0.99). Stratifying according to MDM2 SNP309 status, we observed a reduced risk for breast cancer related to MDM4 SNP34091CC among individuals harboring the MDM2 SNP309GG genotype (OR = 0.41; 95% CI = 0.21-0.82). We conclude, MDM4 SNP34091 status to be associated with reduced risk of breast cancer, in particular in individuals carrying the MDM2 SNP309GG genotype, but not to be associated with either lung-, colon- or prostate cancer.
© 2015 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

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Keywords:  Cancer risk; MDM4; SNP309; SNP34091; population based

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Year:  2015        PMID: 26471763      PMCID: PMC5123711          DOI: 10.1002/cam4.555

Source DB:  PubMed          Journal:  Cancer Med        ISSN: 2045-7634            Impact factor:   4.452


Introduction

The tumor suppressor p53 plays a pivotal role in many physiological processes, including metabolism and maintenance of genomic stability. In order to allow normal cell proliferation and to maintain cell viability during absence of stress signals, the activity of p53 is kept under strict control, predominantly by the protein product of the murine double minute 2 gene, MDM2, and its homolog MDM4, acting in concert 1. It is well established that MDM2 and p53 are linked in an autoregulatory negative feedback loop, where p53 transcriptionally induces MDM2 and MDM2 downregulates p53 2, mainly by direct inhibition and/or proteolytic degradation 3, 4, 5. Although MDM4 alone is unable to target p53 for ubiquitin‐proteasome‐dependent degradation 6, the MDM2/MDM4 heterodimer has been shown more potent degrading the p53 protein as compared to the MDM2 homodimer 7, 8. Additionally, using Mdm2/Mdm4/p53 triple knockout MEFs, Yuan and colleagues showed that an Mdm2/Mdm4 heterodimer is required for the E3 ligase activity of Mdm2 9. These data suggest that elevated levels of MDM4 may contribute to reduced p53 activity and tumor development. In line with this, the MDM4 gene has been found amplified in malignant gliomas with no TP53 mutations or MDM2 amplifications 10, 11 as well as in breast cancer 12, and acute lymphoblastic leukemia 13. Furthermore, studies in transgenic mice show that overexpression of Mdm4 induced spontaneous tumor formation and accelerated tumorigenesis 14. Single‐nucleotide polymorphisms (SNP) affecting the levels of both MDM2 and MDM4 have been reported 15, 16, 17, 18. While MDM2 SNP309T>G (rs2279744) and SNP285G>C (rs117039649) both affect MDM2 transcription, MDM4 SNP34091A>C (rs4245739) has been found to affect MDM4 mRNA stability and protein levels 17, 18. SNP34091 is located in the 3′ untranslated region of MDM4, and was found to create a functional target site for hsa‐miR‐191 and hsa‐miR‐887. Both miRs bind to the MDM4 SNP34091 C‐allele with higher affinity than to the MDM4 SNP34091 A‐allele, leading to miR‐mediated decrease in MDM4 protein levels in cells carrying the MDM4 SNP34091C variant 17, 18. Genotype AA was recorded to be more frequent in patients with high‐grade than low‐grade ovarian carcinoma 18. Furthermore, previous studies have indicated the SNP34091C allele to be associated with a reduced risk for non‐Hodgkin lymphoma 19, breast cancer 20, esophageal squamous cell carcinoma 21, and prostate cancer 22. Contrasting these results, genome wide association studies (GWAS) reported the C allele to be associated with an increased risk for estrogen receptor negative, and in particular, triple negative breast cancer 23, 24, 25. In this study, we assessed the impact of MDM4 SNP34091 status on the risk of cancer of the breast, lung, prostate, and colon in a large population‐based cohort of Caucasian descent.

Materials and Methods

Study population

From the population‐based Cohort of Norway (CONOR) study 26, we genotyped 7079 incident cancer cases and 3747 healthy controls, described in detail previously 27. Thus, we examined the potential effect of MDM4 SNP34091A>C by analyzing the four major cancer forms; breast (n = 1,717), lung (n = 1,331), colon (n = 1,531), and prostate (n = 2,500). On the basis of previously published allele frequencies in healthy controls and breast cancer cases 23, we found our study design to provide adequate statistical power (β‐values ranging from 0.83 to 0.95 for the four cancer sample sets, given an α‐value of 0.05).

MDM4 SNP34091 genotyping

All samples were genotyped for MDM4 SNP34091 status using a custom LightSNiP assay (TIB MOLBIOL Syntheselabor GmbH, Berlin, Germany) on a LightCycler 480 II instrument (Roche, Basel, Switzerland). The reactions were performed in a final reaction volume of 10 μL, containing 1 μL LightCycler®FastStart DNA Master HybProbe mix (Roche Diagnostics), 0.5 μL LightSNiP mix (TIB MOLBIOL), 3 mmol/L MgCl2 and 10–50 ng DNA. The thermocycling and melting curve conditions were as follows: 10 min initial denaturation/activation at 95°C, followed by 45 cycles of denaturation at 95°C for 10 sec, annealing for 10 sec at 60°C and elongation at 72°C for 15 sec. Subsequent to the thermocycling amplification the high‐resolution melting (HRM) step was initiated with a denaturation step at 95°C for 30 sec, followed by melting from 40°C to 75°C with a ramp rate of 0.19°C/sec and finally a cooling step at 40°C for 30 sec. The HRM curve profiles were analyzed by the Melt Curve Genotyping software (version 1.5) on the LightCycler® 480 II instrument (Roche Diagnostics).

Statistical analysis

Potential deviations from Hardy–Weinberg equilibrium were assessed by calculating the expected genotype distribution based on the observed allele frequencies and comparing the output with the observed genotype distribution using Chi‐square tests. Potential associations between MDM4 SNP34091 and the risk of any of the cancer types tested as well as cancer risk within different subgroups were estimated by calculating Odds Ratios (OR) with 95% confidence intervals (CI) and logistic regression adjusting for sex and age. In addition, for colon‐ and lung cancer, overall calculations were performed including both genders using the Mantel–Haenszel test (sex adjusted). All statistical analyses were performed using the IBM SPSS 22 software package (IBM Corp, Armonk, NY, USA) and Stata 13.0 for Windows (Stata Corp, College Station, TX, USA). All P‐values are given as two‐sided.

Results

Distribution of MDM4 SNP34091

In this study, 7,079 cancer cases and 3,747 healthy controls were analyzed for MDM4 SNP34091 status. Among the healthy individuals, the percentages harboring the three different genotypes (MDM4 SNP34091AA, AC, and CC) were recorded to be 54.5%, 38.4%, and 7.1%, respectively. The genotype frequencies were found to be in Hardy–Weinberg equilibrium (P > 0.9). A comprehensive overview of the MDM4 SNP34091 distribution in the healthy controls as well as the four cancer types analyzed is given in Table 1. Among the healthy controls, no substantial gender difference with respect to genotype distribution was observed (P = 0.193).
Table 1

MDM4 SNP34091 distribution and cancer risk

Cases/controlsGenotypeOR (95% CI) P‐valueOR (95% CI) P‐value
SNP34091 n (%)SNP34091SNP34091
AAACCCCC versus AA+ACCC+AC versus AA
Controls2042 (54.5)1439 (38.4)266 (7.1)1.001.00
Women1021 (54.6)703 (37.6)146 (7.8)1.001.00
Men1021 (54.4)736 (39.2)120 (6.4)1.001.00
Colon cancera 823 (53.8)600 (39.2)108 (7.1)1.04 (0.82–1.32)0.7371.04 (0.93–1.18)0.484
Womenb 429 (55.1)293 (37.7)56 (7.2)1.02 (0.73–1.41)0.9191.01 (0.85–1.20)0.941
Menc 394 (52.3)307 (40.8)52 (6.9)1.09 (0.78–1.54)0.6011.10 (0.92–1.30)0.295
Lung cancera 715 (53.7)515 (38.7)101 (7.6)1.11 (0.87–1.41)0.3961.03 (0.91–1.17)0.662
Womenb 264 (53.1)194 (39.0)39 (7.9)1.05 (0.73–1.53)0.7811.07 (0.87–1.30)0.535
Menc 451 (54.1)321 (38.5)62 (7.4)1.19 (0.86–1.64)0.2881.01 (0.86–1.19)0.912
Prostate cancerc 1412 (56.5)927 (37.1)161 (6.4)1.01 (0.79–1.29)0.9460.92 (0.82–1.04)0.182
Breast cancerb 966 (56.3)643 (37.5)108 (6.3)0.77 (0.59–0.99)0.0450.93 (0.82–1.07)0.317

Sex and age adjusted (logistic regression).

Calculations with female controls only, age adjusted.

Calculations with male controls only, age adjusted.

MDM4 SNP34091 distribution and cancer risk Sex and age adjusted (logistic regression). Calculations with female controls only, age adjusted. Calculations with male controls only, age adjusted.

MDM4 SNP34091 status and cancer risk in four major cancer forms

In order to assess the potential impact of MDM4 SNP34091 status on cancer risk, we compared the frequency of the MDM4 SNP34091 genotypes among breast‐ (n = 1,717), lung‐ (n = 1,331), colon‐ (n = 1,531), and prostate cancer (n = 2,500) patients to healthy controls (n = 3,747). We observed no significant correlation between MDM4 SNP34091 status and the risk of either cancer in the colon, lung, or prostate, either in a dominant or a recessive model (SNP34091 CC+AC vs. AA, or CC vs. AA+AC, respectively). Furthermore, analyzing tumors of the right or the left side of the colon separately, revealed no significant effect of MDM4 SNP34091 status and cancer risk in either of the two groups (Table S1). We observed, however, a marginally significant association with reduced risk for breast cancer among individuals harboring the SNP34091CC genotype (recessive model; OR = 0.77; 95% CI = 0.59–0.99; Table 1, Fig. 1A).
Figure 1

Impact of MDM4 SNP34091 on cancer risk. Forest plots showing the effect of SNP34091 on cancer of the colon, lung, prostate, and breast, as compared to healthy controls, among the total study population (A) and among individuals harboring the MDM2 SNP309GG genotype (B).

Impact of MDM4 SNP34091 on cancer risk. Forest plots showing the effect of SNP34091 on cancer of the colon, lung, prostate, and breast, as compared to healthy controls, among the total study population (A) and among individuals harboring the MDM2 SNP309GG genotype (B). Since 92.6% of the lung cancer patients (from whom we had data) were smokers, excluding nonsmokers from the analysis had no impact on the estimates (Table S2).

Potential interactions between MDM4 SNP34091 status and MDM2 promoter SNPs

Previously, we assessed SNP status of the MDM4 partner MDM2 across the same population of cancer patients and healthy controls 27. While the MDM2 SNP309GG genotype has been associated with a nonsignificantly increased risk for breast cancer, breast cancer patients carrying the SNP309GG genotype have been found particularly sensitive to cancer risk reduction by a second MDM2 SNP (SNP285G>C) 27. This observation has also been recorded in another separate sample set of breast cancer patients 16. Since MDM4 forms a heterodimer with MDM2 and promotes MDM2‐mediated polyubiquitination and subsequent degradation of p53, we investigated potential interactions/synergistic effects between MDM4 SNP34091 and MDM2 SNPs with respect to cancer risk. Stratifying according to MDM2 SNP309 status (SNP309TT, SNP309TG, and SNP309GG) we found the MDM4 SNP34091CC genotype (recessive model) to be significantly associated with reduced risk of breast cancer among patients carrying the SNP309GG genotype (OR = 0.41; 95% CI = 0.21–0.82; Table 2, Fig. 1B). Notably, when refining the OR estimates by removing individuals harboring the less frequent MDM2 SNP285C allele, which antagonizes SNP309G‐induced transcriptional enhancement 16, this negative association became slightly stronger (gender adjusted OR = 0.40; 95% CI = 0.19–0.85; Table S3).
Table 2

MDM4 SNP34091 among MDM2 SNP309GG

Cases/controlsGenotypeOR (95% CI) P‐valueOR (95% CI) P‐value
SNP34091 n (%)SNP34091SNP34091
AAACCCCC versus AA+ACCC+AC versus AA
Controls294 (58.6)167 (33.3)41 (8.2)1.001.00
Women149 (58.7)77 (30.3)28 (11.0)1.001.00
Men145 (58.5)90 (36.3)13 (5.2)1.001.00
Colon cancera 111 (59.7)60 (32.3)15 (8.1)1.02 (0.54–1.93)0.9470.98 (0.69–1.39)0.903
Womenb 56 (59.6)30 (31.9)8 (8.5)0.82 (0.33–1.99)0.6531.09 (0.65–1.83)0.745
Menc 55 (59.8)30 (32.6)7 (7.6)1.60 (0.59–4.34)0.3561.03 (0.63–1.70)0.898
Lung cancera 100 (54.6)73 (39.9)10 (5.5)0.73 (0.35–1.54)0.4131.18 (0.83–1.68)0.357
Womenb 38 (57.6)25 (37.9)3 (4.6)0.43 (0.12–1.52)0.1901.17 (0.66–2.10)0.588
Menc 62 (53.0)48 (41.0)7 (6.0)1.13 (0.43–3.00)0.7991.30 (0.82–2.05)0.264
Prostate cancerc 184 (53.5)143 (41.6)17 (4.9)0.99 (0.46–2.11)0.9741.26 (0.90–1.77)0.176
Breast cancerb 160 (63.8)77 (30.7)14 (5.6)0.41 (0.21–0.82)0.0120.75 (0.52–1.10)0.139

Sex and age adjusted (logistic regression).

Calculations with female controls only, age adjusted.

Calculations with male controls only, age adjusted.

MDM4 SNP34091 among MDM2 SNP309GG Sex and age adjusted (logistic regression). Calculations with female controls only, age adjusted. Calculations with male controls only, age adjusted. In addition to assessing the effect of MDM4 SNP34091 within subgroups of MDM2 SNP309 genotypes, we also explored differences between all possible combinations of MDM4 SNP34091/MDM2 SNP309 genotypes. By doing so, we confirmed the MDM4 SNP34091CC/MDM2 SNP309 GG genotype to associated with reduced risk of breast cancer (OR = 0.47; 95% CI = 0.24–0.92, when compared with the highest risk genotype (MDM4 SNP34091AA/MDM2 SNP309GG), data not shown). No effect on the risk of any of the other cancer forms with respect to MDM4 SNP34091 status within the different MDM2 genotypes, either when stratifying cancer of the colon according to tumors of the right or left side, or when excluding the nonsmokers in lung cancer, was recorded.

Discussion

In this study, we observed no association between MDM4 SNP34091 status and the risk for colon‐, prostate‐, or lung cancer, while a marginally significant association with reduced risk of breast cancer was observed. Our observation in breast cancer is similar to, but weaker than the observations of Liu and colleagues, who found the SNP34091 AC and CC genotypes to be significantly associated with reduced breast cancer risk compared with the AA genotype in two different Chinese populations 20. In contrast, GWAS have found an elevated OR for ER negative breast cancer related to the SNP34091C allele in Caucasians but not among Asians 23, 24, 25. Regrettably, information on receptor status was not available for the breast cancer patients examined in this study; thus, a potential effect of SNP43091 status in the minor group of patients harboring ER negative tumors may have been overlooked. Regarding prostate cancer risk, we observed a weak, non‐significant association between MDM4 SNP34091C and reduced risk in the dominant model. This is in line with data from the majority of individual datasets from European populations, included in a recent large GWAS 22, and mirrors our previous findings related to MDM2 polymorphisms [27, 28, 29]. This study is, to our knowledge, the first population‐based case–control study assessing the impact of MDM4 SNP34091 on cancer risk in lung‐ and colon cancer. Previous case–control studies assessing this variant in other cancer forms (esophageal squamous cell carcinoma and non‐Hodgkin lymphoma), including breast cancer, have found the SNP34091C allele to be associated with reduced risk, but have all been performed in Chinese populations 19, 20, 21. Regarding the variations in the results between studies of different ethnic groups, notably, there is a large difference in the distribution of MDM4 SNP34091 between Europeans and Asians with a MAF of 0.26 and 0.05, respectively [30], possibly affecting the power of studies in Asian populations even though the numbers of patients included are large. Also, a possible explanation for the discrepancy may be yet unknown functional SNP(s) that are in linkage disequilibrium (LD) with SNP34091: There are examples of functional SNPs in LD where the SNPs have different geographical distributions and thus confer diverging risk estimates between Europeans and Asians, for example, the two MDM2 SNPs; SNP309 and SNP285 [30, 31, 32, 33]. On the other hand, the possibility of publication bias, where case–control studies reporting positive results are favored cannot be excluded. After stratifying according to MDM2 SNP309 status, we found a reduced risk for breast cancer among individuals harboring the MDM4 SNP34091CC/MDM2 SNP309GG genotype, and this association was stronger after removing individuals harboring the MDM2 SNP285C allele, previously shown to antagonize SNP309G‐induced transcription elevation 16. Interestingly, the MDM4 SNP34091C allele, similar to SNP285G>C seems to execute their effects on breast cancer risk among individuals carrying the SNP309GG genotype only 16, 27. In conclusion, we found no association between the MDM4 SNP34091 status and risk for lung‐, prostate‐, or colon cancer, and a weak association with breast cancer, applying the candidate gene approach. The latter finding was substantiated by the observation of a seemingly synergistic effect between the MDM2 SNP309GG and MDM4 SNP34091AA genotypes on increased risk for breast cancer.

Conflict of Interest

None declared. Table S1. MDM4 SNP34091 distribution and left versus right colon cancer risk. Table S2. MDM4 SNP34091 distribution and lung cancer risk in smokers. Table S3. MDM4 SNP34091 among MDM2 SNP309GG without MDM2 SNP285C. Click here for additional data file.
  34 in total

1.  Differential effects of MDM2 SNP309 polymorphism on breast cancer risk along with race: a meta-analysis.

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Journal:  Breast Cancer Res Treat       Date:  2009-07-10       Impact factor: 4.872

Review 2.  Mdmx as an essential regulator of p53 activity.

Authors:  Jean-Christophe Marine; Aart G Jochemsen
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3.  Influence of MDM2 SNP309 and SNP285 status on the risk of cancer in the breast, prostate, lung and colon.

Authors:  Liv B Gansmo; Stian Knappskog; Pål Romundstad; Kristian Hveem; Lars Vatten; Per E Lønning
Journal:  Int J Cancer       Date:  2014-12-10       Impact factor: 7.396

4.  A genetic variant of MDM4 influences regulation by multiple microRNAs in prostate cancer.

Authors:  Shane Stegeman; Leire Moya; Luke A Selth; Amanda B Spurdle; Judith A Clements; Jyotsna Batra
Journal:  Endocr Relat Cancer       Date:  2015-02-10       Impact factor: 5.678

5.  Refined mapping of 1q32 amplicons in malignant gliomas confirms MDM4 as the main amplification target.

Authors:  Markus J Riemenschneider; Christiane B Knobbe; Guido Reifenberger
Journal:  Int J Cancer       Date:  2003-05-10       Impact factor: 7.396

Review 6.  Genetic susceptibility to triple-negative breast cancer.

Authors:  Kristen N Stevens; Celine M Vachon; Fergus J Couch
Journal:  Cancer Res       Date:  2013-03-27       Impact factor: 12.701

7.  MDM2 promoter polymorphism SNP309 contributes to tumor susceptibility: evidence from 21 case-control studies.

Authors:  Zhibin Hu; Guangfu Jin; Lu Wang; Feng Chen; Xinru Wang; Hongbing Shen
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2007-12       Impact factor: 4.254

8.  MDM2 promoter SNP344T>A (rs1196333) status does not affect cancer risk.

Authors:  Stian Knappskog; Liv B Gansmo; Pål Romundstad; Merete Bjørnslett; Jone Trovik; Jan Sommerfelt-Pettersen; Erik Løkkevik; Rob A E M Tollenaar; Caroline Seynaeve; Peter Devilee; Helga B Salvesen; Anne Dørum; Kristian Hveem; Lars Vatten; Per E Lønning
Journal:  PLoS One       Date:  2012-04-30       Impact factor: 3.240

9.  MDM4 SNP34091 (rs4245739) and its effect on breast-, colon-, lung-, and prostate cancer risk.

Authors:  Liv B Gansmo; Pål Romundstad; Einar Birkeland; Kristian Hveem; Lars Vatten; Stian Knappskog; Per Eystein Lønning
Journal:  Cancer Med       Date:  2015-10-16       Impact factor: 4.452

10.  Genome-wide association studies identify four ER negative-specific breast cancer risk loci.

Authors:  Montserrat Garcia-Closas; Fergus J Couch; Sara Lindstrom; Kyriaki Michailidou; Marjanka K Schmidt; Mark N Brook; Nick Orr; Suhn Kyong Rhie; Elio Riboli; Heather S Feigelson; Loic Le Marchand; Julie E Buring; Diana Eccles; Penelope Miron; Peter A Fasching; Hiltrud Brauch; Jenny Chang-Claude; Jane Carpenter; Andrew K Godwin; Heli Nevanlinna; Graham G Giles; Angela Cox; John L Hopper; Manjeet K Bolla; Qin Wang; Joe Dennis; Ed Dicks; Will J Howat; Nils Schoof; Stig E Bojesen; Diether Lambrechts; Annegien Broeks; Irene L Andrulis; Pascal Guénel; Barbara Burwinkel; Elinor J Sawyer; Antoinette Hollestelle; Olivia Fletcher; Robert Winqvist; Hermann Brenner; Arto Mannermaa; Ute Hamann; Alfons Meindl; Annika Lindblom; Wei Zheng; Peter Devillee; Mark S Goldberg; Jan Lubinski; Vessela Kristensen; Anthony Swerdlow; Hoda Anton-Culver; Thilo Dörk; Kenneth Muir; Keitaro Matsuo; Anna H Wu; Paolo Radice; Soo Hwang Teo; Xiao-Ou Shu; William Blot; Daehee Kang; Mikael Hartman; Suleeporn Sangrajrang; Chen-Yang Shen; Melissa C Southey; Daniel J Park; Fleur Hammet; Jennifer Stone; Laura J Van't Veer; Emiel J Rutgers; Artitaya Lophatananon; Sarah Stewart-Brown; Pornthep Siriwanarangsan; Julian Peto; Michael G Schrauder; Arif B Ekici; Matthias W Beckmann; Isabel Dos Santos Silva; Nichola Johnson; Helen Warren; Ian Tomlinson; Michael J Kerin; Nicola Miller; Federick Marme; Andreas Schneeweiss; Christof Sohn; Therese Truong; Pierre Laurent-Puig; Pierre Kerbrat; Børge G Nordestgaard; Sune F Nielsen; Henrik Flyger; Roger L Milne; Jose Ignacio Arias Perez; Primitiva Menéndez; Heiko Müller; Volker Arndt; Christa Stegmaier; Peter Lichtner; Magdalena Lochmann; Christina Justenhoven; Yon-Dschun Ko; Taru A Muranen; Kristiina Aittomäki; Carl Blomqvist; Dario Greco; Tuomas Heikkinen; Hidemi Ito; Hiroji Iwata; Yasushi Yatabe; Natalia N Antonenkova; Sara Margolin; Vesa Kataja; Veli-Matti Kosma; Jaana M Hartikainen; Rosemary Balleine; Chiu-Chen Tseng; David Van Den Berg; Daniel O Stram; Patrick Neven; Anne-Sophie Dieudonné; Karin Leunen; Anja Rudolph; Stefan Nickels; Dieter Flesch-Janys; Paolo Peterlongo; Bernard Peissel; Loris Bernard; Janet E Olson; Xianshu Wang; Kristen Stevens; Gianluca Severi; Laura Baglietto; Catriona McLean; Gerhard A Coetzee; Ye Feng; Brian E Henderson; Fredrick Schumacher; Natalia V Bogdanova; France Labrèche; Martine Dumont; Cheng Har Yip; Nur Aishah Mohd Taib; Ching-Yu Cheng; Martha Shrubsole; Jirong Long; Katri Pylkäs; Arja Jukkola-Vuorinen; Saila Kauppila; Julia A Knight; Gord Glendon; Anna Marie Mulligan; Robertus A E M Tollenaar; Caroline M Seynaeve; Mieke Kriege; Maartje J Hooning; Ans M W van den Ouweland; Carolien H M van Deurzen; Wei Lu; Yu-Tang Gao; Hui Cai; Sabapathy P Balasubramanian; Simon S Cross; Malcolm W R Reed; Lisa Signorello; Qiuyin Cai; Mitul Shah; Hui Miao; Ching Wan Chan; Kee Seng Chia; Anna Jakubowska; Katarzyna Jaworska; Katarzyna Durda; Chia-Ni Hsiung; Pei-Ei Wu; Jyh-Cherng Yu; Alan Ashworth; Michael Jones; Daniel C Tessier; Anna González-Neira; Guillermo Pita; M Rosario Alonso; Daniel Vincent; Francois Bacot; Christine B Ambrosone; Elisa V Bandera; Esther M John; Gary K Chen; Jennifer J Hu; Jorge L Rodriguez-Gil; Leslie Bernstein; Michael F Press; Regina G Ziegler; Robert M Millikan; Sandra L Deming-Halverson; Sarah Nyante; Sue A Ingles; Quinten Waisfisz; Helen Tsimiklis; Enes Makalic; Daniel Schmidt; Minh Bui; Lorna Gibson; Bertram Müller-Myhsok; Rita K Schmutzler; Rebecca Hein; Norbert Dahmen; Lars Beckmann; Kirsimari Aaltonen; Kamila Czene; Astrid Irwanto; Jianjun Liu; Clare Turnbull; Nazneen Rahman; Hanne Meijers-Heijboer; Andre G Uitterlinden; Fernando Rivadeneira; Curtis Olswold; Susan Slager; Robert Pilarski; Foluso Ademuyiwa; Irene Konstantopoulou; Nicholas G Martin; Grant W Montgomery; Dennis J Slamon; Claudia Rauh; Michael P Lux; Sebastian M Jud; Thomas Bruning; Joellen Weaver; Priyanka Sharma; Harsh Pathak; Will Tapper; Sue Gerty; Lorraine Durcan; Dimitrios Trichopoulos; Rosario Tumino; Petra H Peeters; Rudolf Kaaks; Daniele Campa; Federico Canzian; Elisabete Weiderpass; Mattias Johansson; Kay-Tee Khaw; Ruth Travis; Françoise Clavel-Chapelon; Laurence N Kolonel; Constance Chen; Andy Beck; Susan E Hankinson; Christine D Berg; Robert N Hoover; Jolanta Lissowska; Jonine D Figueroa; Daniel I Chasman; Mia M Gaudet; W Ryan Diver; Walter C Willett; David J Hunter; Jacques Simard; Javier Benitez; Alison M Dunning; Mark E Sherman; Georgia Chenevix-Trench; Stephen J Chanock; Per Hall; Paul D P Pharoah; Celine Vachon; Douglas F Easton; Christopher A Haiman; Peter Kraft
Journal:  Nat Genet       Date:  2013-04       Impact factor: 38.330

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Authors:  Nevena Kotarac; Zorana Dobrijevic; Suzana Matijasevic; Dusanka Savic-Pavicevic; Goran Brajuskovic
Journal:  Pathol Oncol Res       Date:  2020-06-17       Impact factor: 3.201

2.  Association between single nucleotide polymorphism in miR-499, miR-196a2, miR-146a and miR-149 and prostate cancer risk in a sample of Iranian population.

Authors:  Mohammad Hashemi; Nazanin Moradi; Seyed Amir Mohsen Ziaee; Behzad Narouie; Mohammad Hosein Soltani; Maryam Rezaei; Ghazaleh Shahkar; Mohsen Taheri
Journal:  J Adv Res       Date:  2016-03-29       Impact factor: 10.479

3.  The MDM4 SNP34091 (rs4245739) C-allele is associated with increased risk of ovarian-but not endometrial cancer.

Authors:  Liv B Gansmo; Merete Bjørnslett; Mari Kyllesø Halle; Helga B Salvesen; Anne Dørum; Einar Birkeland; Kristian Hveem; Pål Romundstad; Lars Vatten; Per Eystein Lønning; Stian Knappskog
Journal:  Tumour Biol       Date:  2016-02-11

4.  MDM4 SNP34091 (rs4245739) and its effect on breast-, colon-, lung-, and prostate cancer risk.

Authors:  Liv B Gansmo; Pål Romundstad; Einar Birkeland; Kristian Hveem; Lars Vatten; Stian Knappskog; Per Eystein Lønning
Journal:  Cancer Med       Date:  2015-10-16       Impact factor: 4.452

5.  Individual and combined effect of TP53, MDM2, MDM4, MTHFR, CCR5, and CASP8 gene polymorphisms in lung cancer.

Authors:  Ausra Stumbryte; Zivile Gudleviciene; Gabrielis Kundrotas; Daiva Dabkeviciene; Agne Kunickaite; Saulius Cicenas
Journal:  Oncotarget       Date:  2017-11-29

Review 6.  The role of MDM2 and MDM4 in breast cancer development and prevention.

Authors:  Sue Haupt; Reshma Vijayakumaran; Panimaya Jeffreena Miranda; Andrew Burgess; Elgene Lim; Ygal Haupt
Journal:  J Mol Cell Biol       Date:  2017-02-01       Impact factor: 6.216

7.  A PRISMA-compliant meta-analysis of MDM4 genetic variants and cancer susceptibility.

Authors:  Yajing Zhai; Zhijun Dai; Hairong He; Fan Gao; Lihong Yang; Yalin Dong; Jun Lu
Journal:  Oncotarget       Date:  2016-11-08

8.  The associations between MDM4 gene polymorphisms and cancer risk.

Authors:  Ming-Jie Wang; Yong-Jun Luo; Zhi-Yong Shi; Xiao-Liang Xu; Guo-Liang Yao; Rui-Ping Liu; Hui Zhao
Journal:  Oncotarget       Date:  2016-08-23

Review 9.  Role of Sex in the Therapeutic Targeting of p53 Circuitry.

Authors:  Francesca Mancini; Ludovica Giorgini; Emanuela Teveroni; Alfredo Pontecorvi; Fabiola Moretti
Journal:  Front Oncol       Date:  2021-07-08       Impact factor: 6.244

10.  Profile of the breast cancer susceptibility marker rs4245739 identifies a role for miRNAs.

Authors:  Sumadi Lukman Anwar; Wahyu Wulaningsih; Johnathan Watkins
Journal:  Cancer Biol Med       Date:  2017-11       Impact factor: 4.248

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