MDM2 oncogene, E3 ubiquitin protein ligase T309G polymorphism and risk of oesophageal or gastric cancer: Meta-analysis of 15 studies

Meta-analysis MDM2 oncogene, E3 ubiquitin protein ligase T309G polymorphism and risk of oesophageal or gastric cancer: Meta-analysis of 15 studies Journal of International Medical Research 2014, Vol. 42(5) 1065–1076 ! The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0300060514527910 imr.sagepub.com Wei Shen, Ping Hu, Jia-qing Cao, Xiu-xia Liu and Jiang-hua Shao Abstract Objective: To investigate the association between potentially functional MDM2 oncogene, E3 ubiquitin protein ligase (MDM2) T309G polymorphism and susceptibility to oesophageal or gastric cancer. Methods: Two investigators independently searched the PubMed and Chinese National Knowledge Infrastructure databases for studies published before September 2013. Results: Pooled results showed that the variant homozygous 309GG genotype (versus TT) was significantly associated with increased risk of both oesophageal (odds ratio [OR] 0.77; 95% confidence interval [CI] 0.65, 0.90) and gastric cancer (OR 0.52; 95% CI 0.38, 0.72). Subgroup analysis revealed a 309GG-associated increased risk for both cancer types in Asian populations, particularly among Chinese and Japanese ethnicity. When stratified for Helicobacter pylori infection and histological type of gastric cancer, the 309GG-related risk was higher in H. pylori-positive patients (T versus G: OR 0.37; 95% CI 0.22, 0.63) and the association was stronger with intestinal (TT þ TG versus GG: OR 0.68; 95% CI 0.54, 0.87) rather than diffuse gastric-cancer type. Conclusions: The MDM2 T309G polymorphism may be significantly associated with increased susceptibility to oesophageal or gastric cancer, particularly among Eastern Asian populations. Keywords Oesophageal cancer, gastric cancer, MDM2 oncogene, E3 ubiquitin protein ligase (MDM2) gene, polymorphism, meta-analysis, susceptibility Date received: 23 October 2013; accepted: 19 February 2014 Department of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China Corresponding author: Jiang-hua Shao, Department of General Surgery, The Second Affiliated Hospital of Nanchang University, 1 Minde Road, Nanchang, Jiangxi 330006, China. Email: Creative Commons CC-BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (http://www.uk.sagepub.com/aboutus/openaccess.htm). 1066 Journal of International Medical Research 42(5) Introduction Gastric and oesophageal cancer represent the second and sixth, respectively, most frequent causes of cancer-related deaths worldwide.1 Oesophageal cancer is a relatively common upper digestive tract cancer, with distinct geographical distribution characteristics relating to its development. China is a high-incidence area for oesophageal cancer and contributes more than 50% of the world’s newly diagnosed oesophageal cancer cases.2,3 More than 50% of the world’s new gastric cancer cases occur in Asian countries and China alone contributes 42% of newly diagnosed patients with stomach cancer worldwide.4 It would be beneficial, therefore, to identify risk factors for use in screening high-risk subjects, in order to facilitate prompt detection of these two malignancies. The tumour suppressor gene, tumour protein p53 (P53), which encodes cellular tumour antigen p53, is well known for its activities in cell-cycle regulation, cellular transcription control and apoptosis.5 A central node in the P53 pathway is the E3 ubiquitin-protein ligase Mdm2 protein, which is a key negative regulator of P53. MDM2 and P53 form an oscillating autofeedback loop, which is tightly controlled to allow the appropriate response to environmental stresses in order to suppress cancer growth.6 The Mdm2 protein, an E3 ubiquitin ligase, negatively regulates the stability and activity of p53 protein, by binding to p53, leading to its degradation. It is likely that damaged cells escape from the cell-cycle checkpoint control and become carcinogenic, by the attenuation of p53 function, when MDM2 is overexpressed. A single nucleotide polymorphism (SNP) of the MDM2 gene (T309G) was found in the P53-responsive intronic promoter region, and it was revealed that the G allele could increase the affinity for binding the transcription factor Sp1, subsequently leading to elevated Mdm2 protein levels.6 A number of studies have been conducted to investigate the relationship between MDM2 SNP309 and the risk of developing oesophageal or gastric cancer;7–21 the results of such studies remain inconclusive, however. Thus, the present meta-analysis was conducted to provide a quantitative summary of the association between gastrooesophageal cancer and polymorphism T309G in the MDM2 gene, particularly among patients with Eastern Asian ethnicity. Materials and methods Literature search strategy Relevant published studies were identified by searching electronic databases as follows: PubMed (1950–September 2013) and Chinese National Knowledge Infrastructure (1979–September 2013). The following key words were used: (‘MDM2’ OR ‘murine double minute 2’) AND (‘esophageal’ OR ‘gastric’ OR ‘stomach’ OR ‘gastrointestinal’) AND (‘carcinoma’ OR ‘cancer’ OR ‘tumor’ OR ‘tumour’ OR ‘neoplasm’ OR ‘adenocarcinoma’). The search was performed independently by two investigators (W.S. and P.H.), without any language restrictions. In addition, references cited in the selected articles and published reviews were manually searched, to identify any additional relevant studies. Inclusion and exclusion criteria Human case–control studies that presented original data relating to the MDM2 oncogene T309G polymorphism and risk of oesophageal or gastric cancer were included. The exclusion criteria were as follows: no usable data reported; duplicate data; no controls. Data extraction Two investigators (W.S. and P.H.) independently extracted data from original Shen et al. 1067 publications. Discrepancies were resolved by group discussion (among all five coauthors). The information sought from each included study comprised the following: first author’s name; cancer type; publication year; study design; country of origin; ethnicity of the population; source of controls; total number of cases and controls; genotype frequencies of cases and controls. The quality of all included studies was assessed according to a previously published scale for quality assessment.22 Statistical analyses Meta-analysis was conducted using RevMan software, version 5.2 (Cochrane Collaboration, Oxford, UK) and STATAÕ software, version 12.0 (StataCorp LP, College Station, TX, USA); the results are presented as odds ratios (OR) and 95% confidence intervals (CI). Between-study heterogeneity was evaluated with the 2tes (...truncated)