Int J Clin Exp Med 2016;9(2):1558-1566 www.ijcem.com /ISSN:1940-5901/IJCEM0012820 Original Article Association between ERCC2 rs13181 and XRCC2 rs3218536 polymorphisms and the risk of ovarian cancer: a meta-analysis Xiaowei Yu 1*, Zhentong Wei 2*, Yiyang Li 3, Bin Wang 1, Chen Mi 4, Aiyun Xing 4, Cong Hu 1 1 Center for Reproductive Medicine, Center for Prenatal Diagnosis, Departments of 2 Oncological Gynecology, 3 Gynaecology, The First Hospital of Jilin University, Changchun, Jilin 130021, China; 4 Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, China. * Equal contributors. Received July 13, 2015; Accepted December 8, 2015; Epub February 15, 2016; Published February 29, 2016 Abstract: This study is to evaluate the association between ERCC2 rs13181 and XRCC2 rs3218536 polymorphisms and ovarian cancer risk in diverse populations. We performed a meta-analysis of 14 case-control studies that included 3796 ovarian cancer cases and 7675 case-free controls. For the ERCC2 rs13181 polymorphism, no obvious associations were was observed in the overall comparison (KQ vs. KK: OR = 1.35, 95% CI 0.92-1.98, I 2 = 63.5%, P heterogeneity = 0.018; QQ vs. KK:OR = 1.92, 95% CI 1.00-3.68, I2 = 64.7%, P heterogeneity = 0.015; dominant model: OR = 1.40, 95% CI 0.97-2.01, I 2 = 63.3%, P heterogeneity = 0.018; and recessive model: OR = 1.32, 95% CI 0.79-2.20, I 2 = 65.9%, P heterogeneity = 0.012). When stratifying by ethnicity and source of control, still no obvious associations were found. For the XRCC2 rs3218536 polymorphism, however, when all studies were pooled into the meta-analysis, a significant association was found in heterozygous model (RH vs. RR: OR = 0.86, 95% CI 0.76-0.99, I 2 = 38.6%, P heterogeneity = 0.122), no obvious associations was observed in other model. When stratifying by source of control, a significantly reduced risk was found in population-based control (RH vs. RR: OR = 0.82, 95% CI 0.71-0.96, I 2 = 22.9%, P heterogeneity = 0.269; dominant model: OR = 0.81, 95% CI 0.69-0.96, I 2 = 11.1%, P heterogeneity = 0.343). In conclusion, the XRCC2 rs3218536 polymorphism could be an important risk factor for ovarian cancer. Keywords: Ovarian cancer, ERCC2, XRCC2, polymorphism, meta-analysis Introduction Ovarian cancer (OC) is the second most common group of gynaecologic cancers, and account for about 5% of all women s cancers. It accounts for an estimated 21,980 new cases and approximately 14,270 deaths in the United States alone in 2014 [1]. Because of poor early detection, the death rate for ovarian cancer is higher than for that of any other cancer among women. Only 35% to 38% of the women who are diagnosed with ovarian cancer will survive five years after the initial diagnosis [2, 3]. Ovarian cancer is a multifactorial disease, and hormonal factors, environment and genetic factors all play significant roles in its development [4]. The genetic basis of ovarian cancers has been investigated in many studies. DNA repair genes polymorphism may alter the protein function and cause reduction in DNA repair capacity that may lead to genetic instability and carcinogenesis [5, 6]. Excision repair cross complementing group 2 (ERCC2) gene is one of seven nucleotide excision repair enzymes that cause Xeroderma Pigmentosum when mutated in germ line. Several polymorphisms have been identified in this gene and particularly the K751Q ERCC2 polymorphism (rs13181) which consists of the substitution of an A to C resulting in an amino acid change in the coding region [7]. A change of amino acid is able to modify the effect of protein more or less, which can translate by an effect on the systems of repair and consequently on the carcinogenesis. Conflicting data on the roles of the polymorphism on cancer risk including breast and ovarian cancers have been described [8-10]. The X-ray cross-complementing (XRCC) genes are DNA repair genes and they have an important role in protecting mammalian cells from
Figure 1. Flow chart of selection of studies and specific reasons for exclusion from the meta-analysis. damage caused by ionizing radiations. In addition, they participate in DNA damage processing and genetic stability. XRCC2 is one of XRCC group which participate in homologous recombination of DNA [11]. Recent studies showed that the XRCC2 R188H polymorphism (rs3218536) is associated with a modest reduction in ovarian cancer risk [12]. In recent years, the ERCC2 rs13181 and XRCC2 rs3218536 polymorphisms have been studied as potential candidate genes for ovarian cancer risk, but direct evidence from genetic association studies [13-21] remains controversial. We performed a meta-analysis pooling data from all relevant studies in order to determine the effects of the ERCC2 rs13181 and XRCC2 rs3218536 polymorphisms on ovarian cancer. Materials and methods Publication search We searched for relevant studies up to March 2015 through the Pubmed, EMBASE and China National Knowledge Infrastructure (CNKI) database with the following key words: ovarian cancer/carcinoma, polymorphism/variant, ERCC2/ XPD and XRCC2. All eligible studies were retrieved and their references were checked for other relevant studies. Then we downloaded the relevant papers and further screened to identify potentially eligible studies. Studies included in the current meta-analysis should meet the following requests: (A) only the casecontrol studies were considered; (B) evaluated the ERCC2 rs13181 or XRCC2 rs3218536 1559 Int J Clin Exp Med 2016;9(2):1558-1566
Table 1. Characteristics of the ERCC2 rs13181 polymorphism studies included in this meta-analysis First author Year Country Ethnicity Source of control Sample size (case/control) Case (genotype) Control (genotype) KK KQ QQ KK KQ QQ Costa 2007 Portugal Caucasian HB 126/202 55 49 22 95 95 12 0.061 Xing 2007 China Asian PB 235/246 183 49 3 200 45 1 0.358 Bernard-Gallon 2008 France Caucasian HB 51/995 1 31 19 119 446 430 0.839 Jakubowska 2010 Poland Caucasian HB 145/280 58 65 22 100 123 57 0.094 Khokhrin 2012 Russia Caucasian HB 104/298 28 54 22 109 143 46 0.936 Mohamed 2013 Egypt Caucasian HB 100/100 32 54 14 55 35 10 0.221 PB: population-based; HB: hospital-based; HWE: Hardy-Weinberg Equilibrium. P HWE Table 2. Characteristics of the XRCC2 rs3218536 polymorphism studies included in this meta-analysis First author Year Country Ethnicity Source of control Sample size (case/control) Case (genotype) Control (genotype) RR RH HH RR RH HH Auranen-a 2005 UK Caucasian PB 729/842 629 98 2 704 129 9 0.264 Auranen-b 2005 Denmark Caucasian PB 315/404 260 54 1 331 68 5 0.481 Auranen-c 2005 USA Caucasian PB 269/561 238 31 0 484 75 2 0.614 Auranen-d 2005 UK Caucasian PB 275/1811 251 23 1 1538 267 6 0.117 Webb-a 2005 Australia Caucasian HB 430/950 364 63 3 802 140 8 0.492 Webb-b 2005 Australia Mixed HB 94/168 87 5 2 150 16 2 0.053 Beesley 2007 Australia Caucasian PB 923/818 799 117 7 696 115 7 0.357 Mohamed 2013 Egypt Caucasian HB 100/100 6 58 36 16 60 24 0.038 PB: population-based; HB: hospital-based; HWE: Hardy-Weinberg Equilibrium. P HWE polymorphism and ovarian cancer risk; and (C) had usable reported data on the genotypes among cases and controls. In addition, caseonly studies, case reports, conference abstract, reviews, meta-analyses and studies without detailed data were excluded. Data extraction Two of the authors extracted all data independently, complied with the selection criteria, and reached a consensus on all items. In case of disagreement, a third author assessed the articles. The following data were extracted: first author s name, year of publication, country of origin, ethnicity, source of control, total number of cases and controls, and genotype distributions in cases and controls. Statistical analysis All the data management and analysis for this meta-analysis were performed with STATA 12.0 software (Stata Corporation, College Station, TX). The strength of association between ERCC2 rs13181 and XRCC2 rs3218536 polymorphisms and ovarian cancer susceptibility was estimated by calculating OR with the corresponding 95% CI. In order to calculate heterogeneity of studies, the Chi-Square test was used and significance was set at P value less than 0.05 level. When P > 0.10, the pooled OR of each study was calculated by using the fixedeffects model (the Mantel-Haenszel method); otherwise, the random-effects model (the DerSimonian and Laird method) was used. Relative influence of each study on the pooled estimate was assessed by omitting one study at a time for sensitivity analysis. Publication bias was evaluated by visual inspection of symmetry of Begg s funnel plot and assessment of Egger s test (P < 0.05 was regarded as representative of statistical significance). Results Characteristics of the studies A total of 120 papers were identified from the databases as we described above. After delet- 1560 Int J Clin Exp Med 2016;9(2):1558-1566
Table 3. Quantitative analyses of the ERCC2 rs13181 polymorphism on ovarian cancer risk Variables N a KQ versus KK QQ versus KK QQ/KQ versus KK (dominant) QQ versus KQ/KK (recessive) OR (95% CI) P b OR (95% CI) P b OR (95% CI) P b OR (95% CI) P b Total 6 1.35 (0.92-1.98) 0.018 1.92 (1.00-3.6) 0.015 1.40 (0.97-2.01) 0.018 1.32 (0.79-2.20) 0.012 Ethnicities Caucasian 5 1.43 (0.87-2.37) 0.008 1.86 (0.93-3.74) 0.024 1.48 (0.92-2.37) 0.009 1.27 (0.74-2.17) 0.007 Asian 1 1.19 (0.76-1.87) -- 3.28 (0.34-31.8) -- 1.24 (0.79-1.93) -- 3.17 (0.33-30.67) -- Source of control PB 1 1.19 (0.76-1.87) -- 3.28 (0.34-31.8) -- 1.24 (0.79-1.93) -- 3.17 (0.33-30.67) -- HB 5 1.43 (0.87-2.37) 0.008 1.86 (0.93-3.74) 0.024 1.48 (0.92-2.37) 0.009 1.27 (0.74-2.17) 0.007 The numbers in bold indicated statistically significant values. a Number of comparisons. b P value of Q-test for heterogeneity test. Table 4. Quantitative analyses of the XRCC2 rs3218536 polymorphism on ovarian cancer risk Variables N a RH versus RR HH versus RR HH/RH versus RR (dominant) HH versus RH/RR (recessive) OR (95% CI) P b OR (95% CI) P b OR (95% CI) P b OR (95% CI) P b Total 8 0.86 (0.76-0.99) 0.122 0.98 (0.60-1.58) 0.102 0.86 (0.71-1.04) 0.098 1.03 (0.68-1.55) 0.274 Ethnicities Caucasian 7 0.87 (0.76-1.00) 0.103 0.94 (0.57-1.55) 0.070 0.87 (0.71-1.07) 0.067 1.00 (0.66-1.52) 0.207 Mixed 1 0.54 (0.19-1.52) -- 1.72 (0.24-12.46) -- 0.67 (0.27-1.67) -- 1.80 (0.25-13.02) -- Source of control PB 5 0.82 (0.71-0.96) 0.269 0.51 (0.25-1.04) 0.616 0.81 (0.69-0.96) 0.343 0.52 (0.26-1.06) 0.604 HB 3 1.03 (0.77-1.37) 0.093 2.08 (1.02-4.26) 0.191 1.17 (0.59-2.33) 0.066 1.57 (0.92-2.65) 0.585 HWE in controls Yes 7 0.85 (0.74-0.97) 0.335 0.62 (0.35-1.12) 0.690 0.84 (0.73-0.96) 0.443 0.63 (0.35-1.14) 0.677 No 1 2.58 (0.94-7.04) -- 4.00 (1.37-11.67) -- 2.98 (1.12-7.98) -- 1.78 (0.96-3.29) -- The numbers in bold indicated statistically significant values. a Number of comparisons. b P value of Q-test for heterogeneity test. HWE: Hardy-Weinberg Equilibrium. ing the duplications, 103 papers were left. The flow chart of selection of studies and reasons for exclusion is presented in Figure 1. Overall, 9 publications with 14 case-control studies including 3796 cases and 7675 controls were available for this analysis. Study characteristics are summarized in Tables 1 and 2. Among those 14 studies, there were 12 Caucasian, 1 Asian and 1 Mixed studies, respectively. The genotype distributions among the controls of all studies were consistent with HWE except for one study [18]. Quantitative synthesis Two common SNPs occurred in ERCC2 and XRCC2 gene sequences were included in quantitative synthesis, and detail results were shown in Tables 3 and 4. For the ERCC2 rs13181 polymorphism, no obvious associations were was observed in the overall comparison (KQ vs. KK: OR = 1.35, 95% CI 0.92-1.98, I 2 = 63.5%, P heterogeneity = 0.018; QQ vs. KK:OR = 1.92, 95% CI 1.00-3.68, I 2 = 64.7%, P heterogeneity = 0.015; dominant model: OR = 1.40, 95% CI 0.97-2.01, I 2 = 63.3%, P heterogeneity = 0.018; and recessive model: OR = 1.32, 95% CI 0.79-2.20, I 2 = 65.9%, P heterogeneity = 0.012) (Figure 2; Table 3). When stratifying by ethnicity and source of control, still no obvious associations were found (Table 3). For the XRCC2 rs3218536 polymorphism, when all studies were pooled into the meta-analysis, a significant association was found in heterozygous model (RH vs. RR: OR = 0.86, 95% CI 0.76-0.99, I 2 = 38.6%, P heterogeneity = 0.122), no obvious associations were was observed in other model (HH vs. RR:OR = 0.98, 95% CI 0.60-1.58, I 2 = 41.4%, P heterogeneity = 0.102; dominant model: OR = 0.86, 95% CI 0.71-1.04, I 2 = 42.0%, P heterogeneity = 0.098; and recessive model: OR = 1.03, 95% CI 0.68-1.55, I 2 = 19.6%, P heterogeneity = 0.274) (Table 4). In the subgroup analysis by ethnicity, no obvious associations were found. However, when stratifying by source of control, a significantly reduced risk was found in populationbased control (RH vs. RR: OR = 0.82, 95% CI 0.71-0.96, I 2 = 22.9%, P heterogeneity =0.269; dominant model: OR = 0.81, 95% CI 0.69-0.96, I 2 = 11.1%, P heterogeneity = 0.343) (Figure 3); when stratifying by HWE in controls, a significantly 1561 Int J Clin Exp Med 2016;9(2):1558-1566
Figure 2. Meta-analysis for the association between OC risk and the ERCC2 rs13181 polymorphism (KQ vs. KK) is illustrated in overall population. OR: odds ratio; CI: confidence interval; I 2, measure to quantify the degree of heterogeneity in meta-analyses. Figure 3. Meta-analysis for the association between OC risk and the XRCC2 rs3218536 polymorphism (RH vs. RR) is illustrated in subgroup analysis by source of control. OR: odds ratio; CI: confidence interval; I 2, measure to quantify the degree of heterogeneity in meta-analyses. 1562 Int J Clin Exp Med 2016;9(2):1558-1566
Figure 4. Sensitivity analysis of ERCC2 rs13181 polymorphism for a heterogynous model (A: KQ vs. KK) and XRCC2 rs3218536 polymorphism for a heterogynous model (B: RH vs. RR). reduced risk was found in HWE(Yes) (RH vs. RR: OR = 0.85, 95% CI 0.74-0.97, I 2 = 12.5%, P heterogeneity = 0.335; dominant model: OR = 0.84, 95% CI 0.73-0.96, I 2 = 11.4%, P heterogeneity = 0.443; and recessive model: OR = 1.69, 95% CI 1.12-2.55, I 2 = 0.0%, P heterogeneity = 0.154) (Table 4). Sensitivity analysis Sensitivity analyses were performed to assess the influence of individual dataset on the pooled ORs by sequential removing each eligible study. As seen in Figure 4, any single study was omitted, while the overall statistical signifi- 1563 Int J Clin Exp Med 2016;9(2):1558-1566
Figure 5. Funnel plots of ERCC2 rs13181 polymorphism for a heterogynous model (A: KQ vs. KK) and XRCC2 rs3218536 polymorphism for a heterogynous model (B: RH vs. RR). cance does not change, indicating that our results are statistically robust. Publication bias Begg s funnel plot and Egger s test were performed to assess publication bias among the literatures. The funnel plots have been shown that the ERCC2 rs13181 and XRCC2 rs3218536 are no evidence of publication bias. The results of Egger s test also indicated that the ERCC2 rs13181 (Egger s test P = 0.102) (Figure 5A) and the XRCC2 rs3218536 (Egger s test P = 0.849) (Figure 5B) are no evidence of publication bias. Discussion As the core component of cell nucleus, DNA suffers from various damaging agents such as chemicals, radiations and some endogenous elements. Unrepaired or misrepaired DNA results in gene mutations, chromosomal alterations, and genomic instability. Several studies have suggested that genes involved in DNA repair system play a crucial role in protecting against mutations. Patients with certain cancers have reduced DNA repair proficiencies [22]. There are multiple pathways to repair the different types of DNA damage and maintain genomic integrity. Among these pathways is nucleotide excision repair (NER) pathway that repairs a wide variety of DNA damage, including crosslinks, oxidative damage and bulky adducts and the base excision repair (BER) pathway that repair small lesions such as oxidized or reduced bases, fragmented or non bulky adducts, and lesions caused by methylating agents [23]. The important component of NER, xeroderma pigmentosum group D (XPD, or ERCC2), an evolutionarily conserved ATP-dependent helicase, has two functions: nucleotide excision repair and basal transcription as part of the transcription factor complex, TFIIH [24]. Its protein is 761 amino acids in length. Single-nucleotide polymorphisms in the XPD locus that lead to amino acid substitution have been described. An important and frequent one is the XPD Lys751Gln polymorphism in chromosome 19q13.2-13.7. Although the functional significance of XPD polymorphic variants is still unclear, the A to C base substitution at codon 751 leads to a complete change in the charge configuration of the resulting amino acid and reduced DNA repair efficiency [25]. Up to now, several single nucleotide polymor- 1564 Int J Clin Exp Med 2016;9(2):1558-1566
phisms within the XRCC2 gene have been identified as potential cancer risk factors, especially for the Arg188His polymorphism [26-28]. The Arg188H is (rs3218536), also known as R188H, has been suggested to be associated with risk of ovarian cancer. However, it is seen that many of these studies have relatively low statistical power and the results remained inconsistent. In the present meta-analysis, we identified 14 eligible studies, including 3796 ovarian cancer cases and 7675 controls, and analyzed the relationship between ERCC2 rs13181 and XRCC2 rs3218536 polymorphisms and susceptibility to ovarian cancer. To the best of our knowledge, this is the first systematic review of the literature by a meta-analysis so far exploring the association between ERCC2 rs13181 and XRCC2 rs3218536 Polymorphisms and ovarian cancer risk. We found that ERCC2 rs13181 polymorphism was not associated with ovarian cancer risk in overall population and subgroup analysis based on ethnicity and source of control. For the XRCC2 rs3218536 polymorphism, when all studies were pooled into the meta-analysis, a significant association was found in heterozygous model. When stratifying by source of control, a significantly reduced risk was found in population-based control. Heterogeneity is a potential problem when interpreting the results of meta-analyses. In this meta-analysis, for ERCC2 rs13181 polymorphism, heterogeneity was found in the overall and subgroup analyses; thus, the random effects model was used. Sensitivity analyses were also conducted by sequential removing each eligible study. With this exclusion, the estimated pooled OR did not change significantly, strengthening our confidence in our results. Furthermore, this study suggests that the ethnicity and source of control were not sources of heterogeneity. Alternatively, lifestyle, environment and other unknown factors may be sources of heterogeneity. In interpreting the current results, some limitations should be considered. First, only published studies were included in this meta-analysis, which may have biased our results. Second, lack of access to original source data limited our further evaluation of potential interactions, because the interactions between genes and between genes and environment may modulate OC risk. Third, there was significant heterogeneity among included studies for ERCC2 rs13181 polymorphism. Even though we used the random-effect model to calculate pool ORs, the precision of outcome would be affected. In summary, this meta-analysis demonstrates that the XRCC2 rs3218536 polymorphism is associated with a significantly reduced risk of ovarian cancer. However, future well designed large studies, particularly stratified by genegene and gene-environment interactions might be necessary to clarify the possible role of the XRCC2 rs3218536 polymorphism in the susceptibility to ovarian cancer. Disclosure of conflict of interest None. Address correspondence to: Dr. Cong Hu, Center for Reproductive Medicine, Center for Prenatal Diagnosis, The First Hospital of Jilin University, No.71, Xinmin Street, Changchun, Jilin 130021, China. Tel: +86-431-88782222; Fax: +86-431- 88782222; E-mail: conghumed@yeah.net References [1] Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin 2014; 64: 9-29. [2] Li Y, Wang Y, Kang S, Wang N, Zhou RM, Duan YN, Sun DL, Qin JJ, Zhao W, Zhao L. Association of vascular endothelial growth factor gene polymorphisms with susceptibility to epithelial ovarian cancer. Int J Gynecol Cancer 2010; 20: 717-723. [3] Hennessy BT, Coleman RL, Markman M. Ovarian cancer. Lancet 2009; 374: 1371-1382. [4] Romero I, Bast RC Jr. Minireview: human ovarian cancer: biology, current management, and paths to personalizing therapy. Endocrinology 2012; 153: 1593-1602. [5] de Boer JG. Polymorphisms in DNA repair and environmental interactions. Mutat Res 2002; 509: 201-210. [6] Berwick M, Vineis P. Markers of DNA repair and susceptibility to cancer in humans: an epidemiologic review. J Natl Cancer Inst 2000; 92: 874-897. [7] Costa S, Pinto D, Pereira D, Vasconcelos A, Afonso-Lopes C, Osorio T, Lopes C, Medeiros R. Importance of xeroderma pigmentosum group D polymorphisms in susceptibility to ovarian cancer. Cancer Lett 2007; 246: 324-330. [8] Lunn RM, Helzlsouer KJ, Parshad R, Umbach DM, Harris EL, Sanford KK, Bell DA. XPD poly- 1565 Int J Clin Exp Med 2016;9(2):1558-1566
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