Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2022 Mar 29:28:e935671.
doi: 10.12659/MSM.935671.

The Correlation of Mouse Double Minute 4 (MDM4) Polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with Cancer Susceptibility: A Meta-Analysis

Affiliations
Meta-Analysis

The Correlation of Mouse Double Minute 4 (MDM4) Polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with Cancer Susceptibility: A Meta-Analysis

Jian Chen et al. Med Sci Monit. .

Abstract

BACKGROUND Mouse double minute 4 (MDM4) has been extensively investigated as a negative regulator of P53, its negative feedback loop, and the effect of its genetic polymorphisms on cancers. However, many studies showed varying and even conflicting results. Therefore, we employed meta-analysis to further assess the intensity of the connection between MDM4 polymorphisms and malignancies. MATERIAL AND METHODS We searched eligible articles in 5 databases (Cochrane Library, PubMed, Web of Science, Wan Fang Database, and China National Knowledge Infrastructure) up to August 2021. Odds ratios (ORs) and 95% confidence intervals (CIs) were utilized to probe the correlation of 5 MDM4 polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with carcinomas. We employed meta-regression and subgroup analysis to probe for sources of heterogeneity; Funnel plots, Begg's test, and Egger's test were used to evaluate publication bias. Sensitivity analysis was applied to assess the stability of the study. RESULTS Twenty-two studies, comprising 77 reports with 29 853 cases and 72 045 controls, were included in our meta-analysis. We found that rs4245739 polymorphism was a factor in reducing overall cancer susceptibility (dominant model, OR=0.85, 95% CI=0.76-0.95; heterozygous model, OR=0.86, 95% CI=0.78-0.96; additive model, OR=0.87, 95% CI=0.79-0.95), especially in Asian populations, and it also reduces the risk for esophageal squamous cell carcinoma (ESCC). The remaining 4 SNPs were not associated with cancers. CONCLUSIONS The rs4245739 polymorphism might reduce the risk of malignancies, especially in Asian populations, and it is a risk-reducing factor for ESCC incidence. However, rs1563828, rs11801299, rs10900598, and rs1380576 are not relevant to cancer susceptibility.

PubMed Disclaimer

Conflict of interest statement

Conflict of interest: None declared

Figures

Figure 1
Figure 1
Flow diagram of the search and selection of literature. (This figure was created and processed using Photoshop, CS6, Adobe Systems Software Ireland, Ltd.)
Figure 2
Figure 2
(A) Forest plot related to rs4245739 polymorphism and cancer in dominant model (CC+AC vs AA). (B) Forest plot related to rs4245739 polymorphism and cancer in the heterozygous model (AC vs AA). (C) Forest plot related to rs4245739 polymorphism and cancer in the additive model (C vs A). CI – Confidence interval; OR – odds ratio. (Figures were created using Stata.16.0 and processed with Photoshop. Stata, 16.0, StataCorp. Photoshop, CS6, Adobe Systems Software Ireland, Ltd.)
Figure 3
Figure 3
(A) Contour-enhanced funnel plot on the dominant model (CC+AC vs AA) of the relationship between rs4245739 and cancer susceptibility. (B) Contour-enhanced funnel plot on the heterozygous model (AC vs AA) of the relationship between rs4245739 and cancer susceptibility. (C) Contour-enhanced funnel plot on the additive model (C vs A) of the relationship between rs4245739 and cancer susceptibility. (Figures were created using Stata.16.0 and processed with Photoshop. Stata, 16.0, StataCorp. Photoshop, CS6, Adobe Systems Software Ireland, Ltd.)

Similar articles

Cited by

References

    1. Mattiuzzi C, Lippi G. Current cancer epidemiology. J Epidemiol Glob Health. 2019;9(4):217–22. - PMC - PubMed
    1. Ou WB. Correlations between MDM2 gene SNP309 polymorphism and susceptibility to leukemia. Med Sci Monit. 2015;21:213–18. - PMC - PubMed
    1. Zhang H, Mao JS, Hu WF. Functional genetic single-nucleotide polymorphisms (SNPs) in cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) locus are associated with risk and prognosis of osteosarcoma in Chinese populations. Med Sci Monit. 2019;25:1307–13. - PMC - PubMed
    1. Rivlin N, Brosh R, Oren M, Rotter V. Mutations in the p53 tumor suppressor gene: Important milestones at the various steps of tumorigenesis. Genes Cancer. 2011;2(4):466–74. - PMC - PubMed
    1. Muller PA, Vousden KH. Mutant p53 in cancer: New functions and therapeutic opportunities. Cancer Cell. 2014;25(3):304–17. - PMC - PubMed

Publication types