Clinics and Research in Hepatology and Gastroenterology (2014) 38, 226—234
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ORIGINAL ARTICLE
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis Xian-Peng Qin , Yong Zhou , Yi Chen , Ning-Ning Li , Xiao-Ting Wu ∗ Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, 37, Guo Xue Road, Chengdu 610041, Sichuan Province, China Available online 4 December 2013
Summary Background and objective: X-ray repair cross-complementing group 3 (XRCC3) is responsible for maintaining the integrity of the genome, playing a critical role in protecting it against mutations which lead to cancer. Polymorphisms at exons 7 of the XRCC3 gene may alter the XRCC3 repair efficiency. The aim of this study is to derive a precise estimation of the relationship between XRCC3 Thr241Met polymorphism and gastric cancer (GC) risk. Methods: Two investigators independently searched the databases of Pubmed, EMBASE and China National Knowledge Infrastructure (CNKI) up to May 15, 2013. Odds ratio (OR) and 95% confidence intervals (CI) for XRCC3 Thr241Met polymorphism and GC were calculated in a fixedor random- effects model depending on statistical heterogeneity. Results: This meta-analysis included 9 case-control studies, which included 2209 cases and 3269 controls. Overall, the combined results based on all studies indicated that there was no association between XRCC3 Thr241Met polymorphism and GC susceptibility for all genetic models. When stratifying for race, we found the 241Met/Met genotype carriers might be at high risk of GC among Asians, but not among Caucasians. When stratifying by the location of gastric cancer, the combined results showed that Met/Met genotype carriers might have an increased risk of GC in non-cardiac gastric cancer, but not in cardiac cancer. Conclusion: This meta-analysis confirmed that the XRCC3 Thr241Met gene polymorphism might be a risk factor for GC among Asians, and that differences in genotype distribution may be related to the location of gastric cancer. More well-designed studies based on larger population are needed to confirm our results. © 2013 Elsevier Masson SAS. All rights reserved.
Introduction ∗ Corresponding author. Tel.: +86 28 85422870; fax: +86 28 85424110. E-mail address: [email protected] (X.-T. Wu).
Gastric cancer (GC), one of the most common cancers and a leading cause of cancer-related death throughout the world, is an important health problem. A recent analysis of the
2210-7401/$ – see front matter © 2013 Elsevier Masson SAS. All rights reserved. http://dx.doi.org/10.1016/j.clinre.2013.10.011
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis global incidence and cancer-related mortality revealed that over 989,600 new stomach cancer cases were diagnosed and 738,000 patients died from this health problem in 2008 [1]. Overall survival at 5 years is estimated at between 5—15% [2,3] and median survival for advanced gastric cancer is reported around 9—10 months [2]. It is widely accepted that gastric carcinogenesis is a multi-step process and multiple factors are involved. To date, the etiology of GC is still not fully understood, cumulative evidence suggests that environment triggers and genetic susceptibility may contribute to GC development, the environment factors including diet [4,5], lifestyle [6,7], infectious agents such as Helicobacter pylori (H. pylori) [8]. Although about twothirds of GC can be prevented by changes in lifestyle and diet habits [9], the fact that some individuals develop GC while others do not under similar exposure which indicates that host susceptibility is also involved in GC development. DNA repair system is responsible for maintaining the integrity of the genome, playing a critical role in protecting it against mutations that lead to cancer [10]. Therefore, polymorphisms of DNA repair enzymes, which may alter the function or repair efficiency, may result in carcinogenesis [11]. The XRCC3 gene is located in the 14q32.3 region, one of the DNA repair gene, codes for a protein participating in DNA double-strand break/recombination repair pathway. The protein is a member of emerging family of Rad-51-related proteins that may take part in homologous recombination to maintain chromosome stability and repair DNA damage [12]. It has been reported that a single nucleotide polymorphism (C18067T, rs861539) at the 18,067th nucleotide in exon 7 of the XRCC3 gene, with a C-to-T change, and this change leads a Thr-to-Met amino acid change at codon 241 [13]. The XRCC3 Thr241Met polymorphism may affect the enzyme’s function and/or its interaction with other protein involved in DNA damage and repair, may be associated with the risk of tumors [14]. So we think the XRCC3 Thr241Met genetic polymorphism could be a biomarker and this biomarker could be greatly useful in clinical practice, that is understanding the role of the genetic polymorphism and host susceptibility would help us with screening, treatment, surveillance, and prevention of GC. Over the last decade, a number of studies have been conducted to investigate the association between XRCC3 Thr241Met polymorphism and GC risk in humans. However, these studies reported conflicting results. The reason may be the possible small effect of the polymorphism on GC risk and the relatively small sample size in each of the studies. We feel it is necessary to quantitatively summarize the evidence using the gradually accumulated data. In this study, compared with the prior meta-analysis [15], we include several additional studies, which allowed for a larger number of subjects and more precise risk estimation.
Materials and methods This meta-analysis was conducted followed by modified PRISMA guidelines [16], which were more suitable for a genetic meta-analysis.
227
Literature searching strategy We searched the databases of Pubmed, EMBASE, and China National Knowledge Infrastructure (CNKI) up to May 15, 2013. The following keywords were used: (‘‘XRCC3’’ or ‘‘X-ray repair cross-complementation’’) and (gastric or stomach) and (adenocarcinoma* or carcinoma* or cancer* or neoplasm* or tumor* or tumour*). The search was conducted on human subjects, without restriction on language. Abstracts and unpublished reports were not considered. Additional articles were ascertained through checking references cited in reviews and retrieved articles. If more than one article was published using the same case series, we selected the research with the largest sample size or that provided more detailed information.
Inclusion and exclusion criteria The following criteria were used to select studies for this meta-analysis: (1) only case-control or cohort studies for human were considered; (2) evaluating the association between XRCC3 Thr241Met polymorphism and GC; (3) sufficient genotype data were presented to calculate the odds ratio (OR) and confidence interval (CI). The major exclusion criteria were as follows: (1) duplicated publications; (2) no controls; (3) no sufficient data reported.
Data extraction Data were extracted independently by two investigators (Xian-Peng Qin and Yi Chen) from the studies selected according to the inclusion criteria listed above. Disagreements were resolved by discussion with other co-authors. The following characteristics were collected from each study: the first author’s name, publication year, ethnicity, country, source of controls [hospital-based case-control study (HCC) was defined as controls from hospitalized patients, and population-based case-control study (PCC) were from healthy people], tumor location, the number of GC cases and controls with different genotype and evidence of Hardy-Weinberg equilibrium (HWE) (Table 1).
Statistical analysis The statistical analysis was conducted using STATA 11.0 (Stata-Corp LP, College Station, TX, USA), P < 0.05 was considered statistically significant, all the P values were two-sided. The goodness-of-fit test (Chi-square or Fisher’s exact test) was used to assess HWE in the controls for each study. Odds ratio (OR) and 95% confidence interval (CI) were used to test the strength of association between XRCC3 Thr241Met polymorphism and the risk of GC. The crude ORs and 95% CIs were calculated by several comparisons: homozygote model (Met/Met vs. Thr/Thr), heterozygote (Thr/Met vs. Thr/Thr), dominant model (Met/Met + Thr/Met vs. Thr/Thr) and recessive model (Met/Met vs. Thr/Met + Thr/Thr) respectively, specifically dominant model if one copy of that allele is sufficient to manifest its effect and recessive model if two copies of that allele are necessary to manifest its effect [17].
228 Table 1
X.-P. Qin et al. Characteristics of studies included in the meta-analysis.
Study (author year)
Ethnicity (country)
Source of controls
Total cases
Total Con.
Thr/Thr Cases
Con.
Cases
Con.
Cases
Con.
Shen H, 2004 Duarte MC, 2005 Huang WY, 2005 Huang GP, 2006 Ye W, 2006 Ruzzo A, 2007 Palli D, 2010 Canbay E, 2010 Zhao L, 2011
Asians (China) Unknown (Brazil) Caucasians (Poland) Asians (China) Caucasians (Sweden) Caucasians (Italy) Caucasians (Italy) Caucasians (Turkey) Asians (China)
PCC PCC PCC HCC PCC PCC PCC HCC HCC
188 160 281 309 126 90 294 40 721
166 150 390 188 472 121 546 247 989
169 84 128 149 52 35 95 16 257
150 67 174 112 203 36 189 74 635
18 53 128 135 63 44 148 19 321
16 60 163 66 218 66 268 146 274
1 23 25 25 11 11 51 5 143
0 23 53 10 51 19 89 27 80
Thr/Met
Met/Met
HWE
0.51 0.13 0.14 0.95 0.51 0.21 0.71 < 0.001 < 0.001
HCC: hospital-based case-control; PCC: population-based case-control; HWE: Hardy-Weinberg equilibrium.
Statistical heterogeneity was measured using the Cochran’s Q statistic (P < 0.10 was considered statistically significant heterogeneity) [18] and the I2 statistic (I2 value more than 50% indicated significant heterogeneity across studies) [19]. The OR was pooled using the fixed-effects model (the Mantel—Haenszel method) when there was no heterogeneity among the included studies [20]. Otherwise, we considered the random-effects model (the DerSimonian and Laird method) [21]. To establish the effect of clinical heterogeneity between researches on meta-analysis conclusions, subgroup analyses were conducted on the basis of ethnicity, source of controls, tumor location and HWE in controls (Yes/No) [16]. To assess the stability of the results, a sensitivity analysis was performed by repeating the meta-analysis when a single case-control study was omitting each time. Additionally, several methods were used to assess the potential publication bias. Visual inspection of funnel plots asymmetry was conducted. The Begg’s rank correlation method [22] and the Egger’s weighted regression method [23] were used to statistically assess publication bias (P < 0.05 was considered statistically significant).
Results Characteristics of studies The search terms resulted in 335 papers (Fig. 1). Through screening the title, scanning the abstract and reading the entire article, 9 eligible case-control studies were included in this meta-analysis [24—32] (8 in English and 1 in Chinese), including totally 2209 GC patients and 3269 controls. Among those studies, 3 studies were performed in Asian population [24,27,32], 5 studies were performed in Caucasians [26,28—31] and 1 study of mixed ethnicity [25]. Studies had been carried out in China, Brazil, Italy, Poland, Sweden, and Turkey. The cases used in the individual studies were pathologically diagnosed GC. Controls were mainly from the age and/or gender matched with the healthy populations, of which 6 were population-based (PCC) and 3 were hospitalbased studies (HCC). The genotype distributions among the controls did not deviate from HWE except for 2 studies [31,32]. Characteristics of selected studies are presented in Table 1.
Quantitative synthesis Table 2 listed the main results of this pooled analysis, Figs. 2 and 3 showed the association of GC risk with XRCC3 Thr241Met polymorphism in the form of forest plots. Overall, the genotypes comprising at least one variant allele (Met/Met and Thr/Met) of the Thr241Met were not associated with GC risk when compared with the wild-type Thr/Thr homozygote (Met/Met vs. Thr/Thr, OR = 1.16, 95% CI = 0.62—2.17; Thr/Met vs. Thr/Thr, OR = 1.10, 95% CI = 0.75—1.63). Similarly, no associations were observed in the dominant and recessive models (dominant model, OR = 1.10, 95% CI = 0.72—1.71; recessive model, OR = 1.12, 95% CI = 0.71—1.78). Also, no significant associations were found when analyses were limited to studies in which genotype frequencies were in HWE. Taking into account of the potential underestimation of the true effect of the polymorphism on the GC risk, these studies were stratified according to ethnicity, source of controls, tumor location and HWE in controls. Different ethnicities were categorized as Asians and Caucasians, different source of controls were classified as HCC and PCC and different tumor locations were defined as cardiac cancer and non-cardiac gastric cancer. When stratifying by ethnicity, the significantly increased GC risk was observed among Asians (Met/Met vs. Thr/Thr, OR = 3.86, 95% CI = 2.89—5.15; Met/Met vs. Thr/Met + Thr/Thr, OR = 2.60, 95% CI = 1.98—3.41), but not in Caucasians (Met/Met vs. Thr/Thr, OR = 0.86, 95% CI = 0.65—1.13; Met/Met vs. Thr/Met + Thr/Thr, OR = 0.86, 95% CI = 0.67—1.11). Stratifying this meta-analysis by source of controls, the pooled results showed that in both HCC and PCC groups there was no significant association with GC risk in all genetic model except that a significantly increased GC risk was observed among the HCC populations in the Recessive model (OR = 2.46, 95% CI = 1.90—3.20). When stratifying by tumor location, we also detected that Met/Met genotype carriers might have an increased risk of GC in non-cardiac gastric cancer (Met/Met vs. Thr/Thr, OR = 3.11, 95% CI = 1.36—7.09; Met/Met vs. Thr/Met + Thr/Thr, OR = 2.59, 95% CI = 1.97—3.41), but not in cardiac cancer (Met/Met vs. Thr/Thr, OR = 1.23, 95%
Meta-analysis of XRCC3 Thr241Met gene polymorphism and risk of gastric cancer.
Genetic model Variables
Total Ethnicity Asians Caucasians Source of controls HCC PCC Tumor location Cardiac Non-cardiac HWE in controls Yes No
Homozygote
Heterozygote
Dominant model
Recessive model
Sample size
Met/Met vs. Thr/Thr
Thr/Met vs. Thr/Thr
Met/Met + Thr/Met vs. Thr/Thr
Met/Met vs. Thr/Met + Thr/Thr
n
Case/Control
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
9
2209/3269
1.16 (0.62—2.17)
< 0.001
1.10 (0.75—1.63)
< 0.001
1.10 (0.72—1.71)
< 0.001
1.12 (0.71—1.78)
< 0.001
3 5
1218/1343 831/1776
3.86 (2.89—5.15) 0.86 (0.65—1.13)
0.128 0.467
1.76 (0.96—3.21) 1.01 (0.84—1.21)
0.001 0.377
1.86 (0.96—3.59) 0.97 (0.82—1.16)
< 0.001 0.401
2.60 (1.98—3.41) 0.86 (0.67—1.11)
0.369 0.478
3 6
1070/1424 1139/1845
2.15 (0.84—5.52) 0.85 (0.66—1.11)
0.004 0.535
1.49 (0.70—3.17) 0.99 (0.84—1.18)
< 0.001 0.509
1.58 (0.71—3.51) 0.96 (0.82—1.13)
< 0.001 0.515
2.46 (1.90—3.20) 0.87 (0.68—1.10)
0.120 0.595
2 2
435/660 1030/1177
1.23 (0.74—2.04) 3.11 (1.36—7.09)
0.136 0.044
1.33 (1.01—1.77) 2.15 (1.16—4.00)
0.282 0.005
1.33 (1.01—1.74) 2.30 (1.14—4.64)
0.161 0.001
1.08 (0.66—1.75) 2.59 (1.97—3.41)
0.188 0.158
7 2
1448/2033 761/1236
0.93 (0.73—1.19) 2.12 (0.43—10.51)
0.264 0.005
1.07 (0.91—1.25) 1.37 (0.30—6.39)
0.206 < 0.001
1.04 (0.90—1.21) 1.49 (0.31—7.28)
0.117 < 0.001
0.92 (0.73—1.15) 2.63 (1.99—3.48)
0.446 0.103
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis
Table 2
n: number of comparisons; OR: odds ratio; CI: confidence interval; P: value of Q-test for heterogeneity test. Random-effects model was used when P value for heterogeneity test < 0.05; otherwise, fixed-effects model was used.
229
230
X.-P. Qin et al.
Figure 1
Flow chart of selection of studies and specific reasons for exclusion from the meat-analysis.
CI = 0.74—2.04; Met/Met vs. Thr/Met + Thr/Thr, OR = 1.08, 95% CI = 0.66—1.75).
Publication bias Funnel plot was generated to evaluate the potential publication bias (Fig. 4). Begg’s and Egger’s tests were performed to provide statistical evidence of funnel plot asymmetry. No publication bias was detected in Begg’s test: [Met/Met vs. Thr/Thr: P = 0.677; Thr/Met vs. Thr/Thr: P = 0.211; Met/Met + Thr/Met vs. Thr/Thr: P = 0.532; Met/Met vs. Thr/Met + Thr/Thr: P = 0.532]. However, the publication bias was evident when the Egger’s test was used in the heterozygote model and the dominant model (P = 0.009 and 0.015 respectively).
Discussion The exact mechanism of gastric carcinogenesis is not yet entirely clear. It is widely accepted that gastric
carcinogenesis is a multi-step process and multiple factors are involved, and one major possible mechanism is molecular alteration. Genetic predisposition has been suggested to correlate with GC risk by numerous epidemiological studies [33—35]. DNA alterations may be involved in the early stages of environmental carcinogenensis. Most of these alterations, if not repaired, may lead to genetic instability, mutagenesis [11]. DNA repair mechanisms play an important role in maintaining the integrity and stability of the genome and act as a key role in pathogenesis and progression of GC [36]. XRCC3, coding the key protein of DNA double-strand break/recombination repair pathway, is the major gene involved in the homologous recombination repair mechanism. Mutations of this gene may increase the GC risk by exhibiting a hypersensitivity to ionizing radiations, ultraviolet light and mono- or bifunctional alkylating agents [37]. Until recently, many studies have been conducted to investigate the XRCC3 Thr241Met polymorphism on the development of GC. However, most of these researches were based on small sample size and reported inconsistent results. As an effective statistical method, meta-analysis
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis
231
Figure 2 Subgroup meta-analysis for XRCC3 Thr241Met polymorphism (Met/Met vs. Thr/Met + Thr/Thr) and gastric cancer risk. Forest plot showed that individuals carrying the -241Met/Met allele have an increased risk of GC among Asians, but not among Caucasians.
can pool the results of individual studies, and may help estimate population-wide effects of genetic risk factors in GC carcinogenesis and provide more reliable results [38,39]. As for the XRCC3 Thr241Met polymorphism with cancer risk, Li et al. found an increased risk role of XRCC3
241Met/Met genotype in bladder cancer among all subjects [40]. Also, Yin et al. found 241Met allele was a low-penetrant risk factor for developing breast cancer [41]. Yin et al. concluded that XRCC3 241Met allele (Met/Met + Thr/Met) might act as a head and neck cancer risk factor among all subjects
Figure 3 Subgroup meta-analysis for XRCC3 Thr241Met polymorphism (Met/Met vs. Thr/Met + Thr/Thr) and gastric cancer risk. Forest plot showed that use of hospital-based controls resulted in a significant association between XRCC3 241Met/Met genotype and development of GC than did use of population-based controls.
232
Figure 4 Funnel plot of XRCC3 Thr241Met polymorphism and gastric cancer (each point represents a separate study for the indicated association, and Begg’s test for publication bias is nonsignificant: Met/Met vs. Thr/Met + Thr/Thr, P = 0.532).
[42]. However, when the research focused on other cancers, the result was different. Wang et al. found no statistically significant association of XRCC3 Thr241Met polymorphism with colorectal cancer risk in any genetic model [43]. Xu et al. did a meta-analysis, all available data did not support any appreciable association between the XRCC3 Thr241Met polymorphism and lung cancer risk in any population [44]. In 2011, Fang et al. conducted a meta-analysis to investigate the association between gastric cancer risk and XRCC3 Thr241Met polymorphism (1154 cases and 1487 controls from 6 studies) and demonstrated that XRCC3 241Met allele may act as a gastric cancer risk in Asian population. In this meta-analysis, we included several additional case-controls, which allowed for a greater number of subjects (2209 cases of GC and 3269 controls) to explore the association between XRCC3 Thr241Met polymorphism and GC risk. The overall results indicated that XRCC3 Thr241Met polymorphism was not a significant risk factor for developing GC. One possible explanation is that the modulation of GC risk may depend not only on a single gene/single nucleotide polymorphism, but also depend on a combined effect of different genes/multiple polymorphisms, or on intently interplay between polymorphisms and environmental factors [45]. Another major finding of this meta-analysis was the different associations of XRCC3 polymorphisms with the GC risk according to ethnicity. Our study indicated that the Met/Met genotype carriers might be at high risk of developing GC among Asians, but not among Caucasians. The discrepancies might be due to genetic background and/or environmental exposure differences [46]. As it is conceivable that the XRCC3 gene polymorphism may confer susceptibility to non-cancerous diseases, there may be differences in the genotype frequencies between the hospital-based and population-based controls. Hence, the results of meta-analysis often depend on the control selection procedures. In subgroup analysis stratified on the basis of different sources of controls, we found
X.-P. Qin et al. that use of hospital-based controls resulted in a significant association between XRCC3 241Met/Met genotype and development of GC than did use of population-based controls. This may be due to that the investigated genotypes were associated with the disease conditions hospital-based controls might have. But HCC studies have some selection biases because such controls might be ill-related population, and may not be a representative of the general population, so a proper population-based control subject may be better to reduce biases in such genetic association studies. Additionally, in the subgroup meta-analysis based on cancer location, we detected that Met/Met genotype carriers might have an increased risk of GC in non-cardiac gastric cancer, but not in cardiac cancer. Because there were only two studies included in this subgroup meta-analysis, for the limited study sample size, the result should be interpreted with caution. Similar to other meta-analysis and systematic reviews, this study also has some limitations: (1) only published studies were included in the meta-analysis, therefore, publication bias may occur. The Egger weighted regression shows clear evidence. It is known that positive results tend to have a greater probability of being published, even though the unpublished research quality is not as good as published, if they are not included, will make an overestimate of the XRCC3 Thr241Met polymorphism at GC risk; (2) the small sample size in some subgroup analyses; (3) obvious heterogeneity was observed in the included studies; (4) GC is a multifactorial disease affected by many genes, XRCC3 Thr241Met gene polymorphism may have little influence on the risk of individual GC development; (5) meta-analysis is retrospective research that is subject to the methodological limitations. In order to minimize the bias, we developed a detailed scheme before starting the research, performed a meticulous search for published studies and using accurate methods for study selection, data extraction and data analysis. Nevertheless, our results should be considered with care. Additional well-designed, high-quality epidemiological studies with larger participants are needed to further evaluate the association between XRCC3 Thr241Met polymorphism and GC. In conclusion, this meta-analysis confirmed that the XRCC3 Thr241Met gene polymorphism might be a risk factor for GC among Asians, and that differences in genotype distribution may be related to the location of gastric cancer. More well-designed studies based on larger population are needed to confirm our results.
Disclosure of interest The authors declare that they have no conflicts of interest concerning this article.
Acknowledgement Funding/Support: the research of this paper is supported by National Natural Science Foundation of China (No. 30901427).
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis
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ORIGINAL ARTICLE
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis Xian-Peng Qin , Yong Zhou , Yi Chen , Ning-Ning Li , Xiao-Ting Wu ∗ Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, 37, Guo Xue Road, Chengdu 610041, Sichuan Province, China Available online 4 December 2013
Summary Background and objective: X-ray repair cross-complementing group 3 (XRCC3) is responsible for maintaining the integrity of the genome, playing a critical role in protecting it against mutations which lead to cancer. Polymorphisms at exons 7 of the XRCC3 gene may alter the XRCC3 repair efficiency. The aim of this study is to derive a precise estimation of the relationship between XRCC3 Thr241Met polymorphism and gastric cancer (GC) risk. Methods: Two investigators independently searched the databases of Pubmed, EMBASE and China National Knowledge Infrastructure (CNKI) up to May 15, 2013. Odds ratio (OR) and 95% confidence intervals (CI) for XRCC3 Thr241Met polymorphism and GC were calculated in a fixedor random- effects model depending on statistical heterogeneity. Results: This meta-analysis included 9 case-control studies, which included 2209 cases and 3269 controls. Overall, the combined results based on all studies indicated that there was no association between XRCC3 Thr241Met polymorphism and GC susceptibility for all genetic models. When stratifying for race, we found the 241Met/Met genotype carriers might be at high risk of GC among Asians, but not among Caucasians. When stratifying by the location of gastric cancer, the combined results showed that Met/Met genotype carriers might have an increased risk of GC in non-cardiac gastric cancer, but not in cardiac cancer. Conclusion: This meta-analysis confirmed that the XRCC3 Thr241Met gene polymorphism might be a risk factor for GC among Asians, and that differences in genotype distribution may be related to the location of gastric cancer. More well-designed studies based on larger population are needed to confirm our results. © 2013 Elsevier Masson SAS. All rights reserved.
Introduction ∗ Corresponding author. Tel.: +86 28 85422870; fax: +86 28 85424110. E-mail address: [email protected] (X.-T. Wu).
Gastric cancer (GC), one of the most common cancers and a leading cause of cancer-related death throughout the world, is an important health problem. A recent analysis of the
2210-7401/$ – see front matter © 2013 Elsevier Masson SAS. All rights reserved. http://dx.doi.org/10.1016/j.clinre.2013.10.011
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis global incidence and cancer-related mortality revealed that over 989,600 new stomach cancer cases were diagnosed and 738,000 patients died from this health problem in 2008 [1]. Overall survival at 5 years is estimated at between 5—15% [2,3] and median survival for advanced gastric cancer is reported around 9—10 months [2]. It is widely accepted that gastric carcinogenesis is a multi-step process and multiple factors are involved. To date, the etiology of GC is still not fully understood, cumulative evidence suggests that environment triggers and genetic susceptibility may contribute to GC development, the environment factors including diet [4,5], lifestyle [6,7], infectious agents such as Helicobacter pylori (H. pylori) [8]. Although about twothirds of GC can be prevented by changes in lifestyle and diet habits [9], the fact that some individuals develop GC while others do not under similar exposure which indicates that host susceptibility is also involved in GC development. DNA repair system is responsible for maintaining the integrity of the genome, playing a critical role in protecting it against mutations that lead to cancer [10]. Therefore, polymorphisms of DNA repair enzymes, which may alter the function or repair efficiency, may result in carcinogenesis [11]. The XRCC3 gene is located in the 14q32.3 region, one of the DNA repair gene, codes for a protein participating in DNA double-strand break/recombination repair pathway. The protein is a member of emerging family of Rad-51-related proteins that may take part in homologous recombination to maintain chromosome stability and repair DNA damage [12]. It has been reported that a single nucleotide polymorphism (C18067T, rs861539) at the 18,067th nucleotide in exon 7 of the XRCC3 gene, with a C-to-T change, and this change leads a Thr-to-Met amino acid change at codon 241 [13]. The XRCC3 Thr241Met polymorphism may affect the enzyme’s function and/or its interaction with other protein involved in DNA damage and repair, may be associated with the risk of tumors [14]. So we think the XRCC3 Thr241Met genetic polymorphism could be a biomarker and this biomarker could be greatly useful in clinical practice, that is understanding the role of the genetic polymorphism and host susceptibility would help us with screening, treatment, surveillance, and prevention of GC. Over the last decade, a number of studies have been conducted to investigate the association between XRCC3 Thr241Met polymorphism and GC risk in humans. However, these studies reported conflicting results. The reason may be the possible small effect of the polymorphism on GC risk and the relatively small sample size in each of the studies. We feel it is necessary to quantitatively summarize the evidence using the gradually accumulated data. In this study, compared with the prior meta-analysis [15], we include several additional studies, which allowed for a larger number of subjects and more precise risk estimation.
Materials and methods This meta-analysis was conducted followed by modified PRISMA guidelines [16], which were more suitable for a genetic meta-analysis.
227
Literature searching strategy We searched the databases of Pubmed, EMBASE, and China National Knowledge Infrastructure (CNKI) up to May 15, 2013. The following keywords were used: (‘‘XRCC3’’ or ‘‘X-ray repair cross-complementation’’) and (gastric or stomach) and (adenocarcinoma* or carcinoma* or cancer* or neoplasm* or tumor* or tumour*). The search was conducted on human subjects, without restriction on language. Abstracts and unpublished reports were not considered. Additional articles were ascertained through checking references cited in reviews and retrieved articles. If more than one article was published using the same case series, we selected the research with the largest sample size or that provided more detailed information.
Inclusion and exclusion criteria The following criteria were used to select studies for this meta-analysis: (1) only case-control or cohort studies for human were considered; (2) evaluating the association between XRCC3 Thr241Met polymorphism and GC; (3) sufficient genotype data were presented to calculate the odds ratio (OR) and confidence interval (CI). The major exclusion criteria were as follows: (1) duplicated publications; (2) no controls; (3) no sufficient data reported.
Data extraction Data were extracted independently by two investigators (Xian-Peng Qin and Yi Chen) from the studies selected according to the inclusion criteria listed above. Disagreements were resolved by discussion with other co-authors. The following characteristics were collected from each study: the first author’s name, publication year, ethnicity, country, source of controls [hospital-based case-control study (HCC) was defined as controls from hospitalized patients, and population-based case-control study (PCC) were from healthy people], tumor location, the number of GC cases and controls with different genotype and evidence of Hardy-Weinberg equilibrium (HWE) (Table 1).
Statistical analysis The statistical analysis was conducted using STATA 11.0 (Stata-Corp LP, College Station, TX, USA), P < 0.05 was considered statistically significant, all the P values were two-sided. The goodness-of-fit test (Chi-square or Fisher’s exact test) was used to assess HWE in the controls for each study. Odds ratio (OR) and 95% confidence interval (CI) were used to test the strength of association between XRCC3 Thr241Met polymorphism and the risk of GC. The crude ORs and 95% CIs were calculated by several comparisons: homozygote model (Met/Met vs. Thr/Thr), heterozygote (Thr/Met vs. Thr/Thr), dominant model (Met/Met + Thr/Met vs. Thr/Thr) and recessive model (Met/Met vs. Thr/Met + Thr/Thr) respectively, specifically dominant model if one copy of that allele is sufficient to manifest its effect and recessive model if two copies of that allele are necessary to manifest its effect [17].
228 Table 1
X.-P. Qin et al. Characteristics of studies included in the meta-analysis.
Study (author year)
Ethnicity (country)
Source of controls
Total cases
Total Con.
Thr/Thr Cases
Con.
Cases
Con.
Cases
Con.
Shen H, 2004 Duarte MC, 2005 Huang WY, 2005 Huang GP, 2006 Ye W, 2006 Ruzzo A, 2007 Palli D, 2010 Canbay E, 2010 Zhao L, 2011
Asians (China) Unknown (Brazil) Caucasians (Poland) Asians (China) Caucasians (Sweden) Caucasians (Italy) Caucasians (Italy) Caucasians (Turkey) Asians (China)
PCC PCC PCC HCC PCC PCC PCC HCC HCC
188 160 281 309 126 90 294 40 721
166 150 390 188 472 121 546 247 989
169 84 128 149 52 35 95 16 257
150 67 174 112 203 36 189 74 635
18 53 128 135 63 44 148 19 321
16 60 163 66 218 66 268 146 274
1 23 25 25 11 11 51 5 143
0 23 53 10 51 19 89 27 80
Thr/Met
Met/Met
HWE
0.51 0.13 0.14 0.95 0.51 0.21 0.71 < 0.001 < 0.001
HCC: hospital-based case-control; PCC: population-based case-control; HWE: Hardy-Weinberg equilibrium.
Statistical heterogeneity was measured using the Cochran’s Q statistic (P < 0.10 was considered statistically significant heterogeneity) [18] and the I2 statistic (I2 value more than 50% indicated significant heterogeneity across studies) [19]. The OR was pooled using the fixed-effects model (the Mantel—Haenszel method) when there was no heterogeneity among the included studies [20]. Otherwise, we considered the random-effects model (the DerSimonian and Laird method) [21]. To establish the effect of clinical heterogeneity between researches on meta-analysis conclusions, subgroup analyses were conducted on the basis of ethnicity, source of controls, tumor location and HWE in controls (Yes/No) [16]. To assess the stability of the results, a sensitivity analysis was performed by repeating the meta-analysis when a single case-control study was omitting each time. Additionally, several methods were used to assess the potential publication bias. Visual inspection of funnel plots asymmetry was conducted. The Begg’s rank correlation method [22] and the Egger’s weighted regression method [23] were used to statistically assess publication bias (P < 0.05 was considered statistically significant).
Results Characteristics of studies The search terms resulted in 335 papers (Fig. 1). Through screening the title, scanning the abstract and reading the entire article, 9 eligible case-control studies were included in this meta-analysis [24—32] (8 in English and 1 in Chinese), including totally 2209 GC patients and 3269 controls. Among those studies, 3 studies were performed in Asian population [24,27,32], 5 studies were performed in Caucasians [26,28—31] and 1 study of mixed ethnicity [25]. Studies had been carried out in China, Brazil, Italy, Poland, Sweden, and Turkey. The cases used in the individual studies were pathologically diagnosed GC. Controls were mainly from the age and/or gender matched with the healthy populations, of which 6 were population-based (PCC) and 3 were hospitalbased studies (HCC). The genotype distributions among the controls did not deviate from HWE except for 2 studies [31,32]. Characteristics of selected studies are presented in Table 1.
Quantitative synthesis Table 2 listed the main results of this pooled analysis, Figs. 2 and 3 showed the association of GC risk with XRCC3 Thr241Met polymorphism in the form of forest plots. Overall, the genotypes comprising at least one variant allele (Met/Met and Thr/Met) of the Thr241Met were not associated with GC risk when compared with the wild-type Thr/Thr homozygote (Met/Met vs. Thr/Thr, OR = 1.16, 95% CI = 0.62—2.17; Thr/Met vs. Thr/Thr, OR = 1.10, 95% CI = 0.75—1.63). Similarly, no associations were observed in the dominant and recessive models (dominant model, OR = 1.10, 95% CI = 0.72—1.71; recessive model, OR = 1.12, 95% CI = 0.71—1.78). Also, no significant associations were found when analyses were limited to studies in which genotype frequencies were in HWE. Taking into account of the potential underestimation of the true effect of the polymorphism on the GC risk, these studies were stratified according to ethnicity, source of controls, tumor location and HWE in controls. Different ethnicities were categorized as Asians and Caucasians, different source of controls were classified as HCC and PCC and different tumor locations were defined as cardiac cancer and non-cardiac gastric cancer. When stratifying by ethnicity, the significantly increased GC risk was observed among Asians (Met/Met vs. Thr/Thr, OR = 3.86, 95% CI = 2.89—5.15; Met/Met vs. Thr/Met + Thr/Thr, OR = 2.60, 95% CI = 1.98—3.41), but not in Caucasians (Met/Met vs. Thr/Thr, OR = 0.86, 95% CI = 0.65—1.13; Met/Met vs. Thr/Met + Thr/Thr, OR = 0.86, 95% CI = 0.67—1.11). Stratifying this meta-analysis by source of controls, the pooled results showed that in both HCC and PCC groups there was no significant association with GC risk in all genetic model except that a significantly increased GC risk was observed among the HCC populations in the Recessive model (OR = 2.46, 95% CI = 1.90—3.20). When stratifying by tumor location, we also detected that Met/Met genotype carriers might have an increased risk of GC in non-cardiac gastric cancer (Met/Met vs. Thr/Thr, OR = 3.11, 95% CI = 1.36—7.09; Met/Met vs. Thr/Met + Thr/Thr, OR = 2.59, 95% CI = 1.97—3.41), but not in cardiac cancer (Met/Met vs. Thr/Thr, OR = 1.23, 95%
Meta-analysis of XRCC3 Thr241Met gene polymorphism and risk of gastric cancer.
Genetic model Variables
Total Ethnicity Asians Caucasians Source of controls HCC PCC Tumor location Cardiac Non-cardiac HWE in controls Yes No
Homozygote
Heterozygote
Dominant model
Recessive model
Sample size
Met/Met vs. Thr/Thr
Thr/Met vs. Thr/Thr
Met/Met + Thr/Met vs. Thr/Thr
Met/Met vs. Thr/Met + Thr/Thr
n
Case/Control
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
9
2209/3269
1.16 (0.62—2.17)
< 0.001
1.10 (0.75—1.63)
< 0.001
1.10 (0.72—1.71)
< 0.001
1.12 (0.71—1.78)
< 0.001
3 5
1218/1343 831/1776
3.86 (2.89—5.15) 0.86 (0.65—1.13)
0.128 0.467
1.76 (0.96—3.21) 1.01 (0.84—1.21)
0.001 0.377
1.86 (0.96—3.59) 0.97 (0.82—1.16)
< 0.001 0.401
2.60 (1.98—3.41) 0.86 (0.67—1.11)
0.369 0.478
3 6
1070/1424 1139/1845
2.15 (0.84—5.52) 0.85 (0.66—1.11)
0.004 0.535
1.49 (0.70—3.17) 0.99 (0.84—1.18)
< 0.001 0.509
1.58 (0.71—3.51) 0.96 (0.82—1.13)
< 0.001 0.515
2.46 (1.90—3.20) 0.87 (0.68—1.10)
0.120 0.595
2 2
435/660 1030/1177
1.23 (0.74—2.04) 3.11 (1.36—7.09)
0.136 0.044
1.33 (1.01—1.77) 2.15 (1.16—4.00)
0.282 0.005
1.33 (1.01—1.74) 2.30 (1.14—4.64)
0.161 0.001
1.08 (0.66—1.75) 2.59 (1.97—3.41)
0.188 0.158
7 2
1448/2033 761/1236
0.93 (0.73—1.19) 2.12 (0.43—10.51)
0.264 0.005
1.07 (0.91—1.25) 1.37 (0.30—6.39)
0.206 < 0.001
1.04 (0.90—1.21) 1.49 (0.31—7.28)
0.117 < 0.001
0.92 (0.73—1.15) 2.63 (1.99—3.48)
0.446 0.103
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis
Table 2
n: number of comparisons; OR: odds ratio; CI: confidence interval; P: value of Q-test for heterogeneity test. Random-effects model was used when P value for heterogeneity test < 0.05; otherwise, fixed-effects model was used.
229
230
X.-P. Qin et al.
Figure 1
Flow chart of selection of studies and specific reasons for exclusion from the meat-analysis.
CI = 0.74—2.04; Met/Met vs. Thr/Met + Thr/Thr, OR = 1.08, 95% CI = 0.66—1.75).
Publication bias Funnel plot was generated to evaluate the potential publication bias (Fig. 4). Begg’s and Egger’s tests were performed to provide statistical evidence of funnel plot asymmetry. No publication bias was detected in Begg’s test: [Met/Met vs. Thr/Thr: P = 0.677; Thr/Met vs. Thr/Thr: P = 0.211; Met/Met + Thr/Met vs. Thr/Thr: P = 0.532; Met/Met vs. Thr/Met + Thr/Thr: P = 0.532]. However, the publication bias was evident when the Egger’s test was used in the heterozygote model and the dominant model (P = 0.009 and 0.015 respectively).
Discussion The exact mechanism of gastric carcinogenesis is not yet entirely clear. It is widely accepted that gastric
carcinogenesis is a multi-step process and multiple factors are involved, and one major possible mechanism is molecular alteration. Genetic predisposition has been suggested to correlate with GC risk by numerous epidemiological studies [33—35]. DNA alterations may be involved in the early stages of environmental carcinogenensis. Most of these alterations, if not repaired, may lead to genetic instability, mutagenesis [11]. DNA repair mechanisms play an important role in maintaining the integrity and stability of the genome and act as a key role in pathogenesis and progression of GC [36]. XRCC3, coding the key protein of DNA double-strand break/recombination repair pathway, is the major gene involved in the homologous recombination repair mechanism. Mutations of this gene may increase the GC risk by exhibiting a hypersensitivity to ionizing radiations, ultraviolet light and mono- or bifunctional alkylating agents [37]. Until recently, many studies have been conducted to investigate the XRCC3 Thr241Met polymorphism on the development of GC. However, most of these researches were based on small sample size and reported inconsistent results. As an effective statistical method, meta-analysis
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis
231
Figure 2 Subgroup meta-analysis for XRCC3 Thr241Met polymorphism (Met/Met vs. Thr/Met + Thr/Thr) and gastric cancer risk. Forest plot showed that individuals carrying the -241Met/Met allele have an increased risk of GC among Asians, but not among Caucasians.
can pool the results of individual studies, and may help estimate population-wide effects of genetic risk factors in GC carcinogenesis and provide more reliable results [38,39]. As for the XRCC3 Thr241Met polymorphism with cancer risk, Li et al. found an increased risk role of XRCC3
241Met/Met genotype in bladder cancer among all subjects [40]. Also, Yin et al. found 241Met allele was a low-penetrant risk factor for developing breast cancer [41]. Yin et al. concluded that XRCC3 241Met allele (Met/Met + Thr/Met) might act as a head and neck cancer risk factor among all subjects
Figure 3 Subgroup meta-analysis for XRCC3 Thr241Met polymorphism (Met/Met vs. Thr/Met + Thr/Thr) and gastric cancer risk. Forest plot showed that use of hospital-based controls resulted in a significant association between XRCC3 241Met/Met genotype and development of GC than did use of population-based controls.
232
Figure 4 Funnel plot of XRCC3 Thr241Met polymorphism and gastric cancer (each point represents a separate study for the indicated association, and Begg’s test for publication bias is nonsignificant: Met/Met vs. Thr/Met + Thr/Thr, P = 0.532).
[42]. However, when the research focused on other cancers, the result was different. Wang et al. found no statistically significant association of XRCC3 Thr241Met polymorphism with colorectal cancer risk in any genetic model [43]. Xu et al. did a meta-analysis, all available data did not support any appreciable association between the XRCC3 Thr241Met polymorphism and lung cancer risk in any population [44]. In 2011, Fang et al. conducted a meta-analysis to investigate the association between gastric cancer risk and XRCC3 Thr241Met polymorphism (1154 cases and 1487 controls from 6 studies) and demonstrated that XRCC3 241Met allele may act as a gastric cancer risk in Asian population. In this meta-analysis, we included several additional case-controls, which allowed for a greater number of subjects (2209 cases of GC and 3269 controls) to explore the association between XRCC3 Thr241Met polymorphism and GC risk. The overall results indicated that XRCC3 Thr241Met polymorphism was not a significant risk factor for developing GC. One possible explanation is that the modulation of GC risk may depend not only on a single gene/single nucleotide polymorphism, but also depend on a combined effect of different genes/multiple polymorphisms, or on intently interplay between polymorphisms and environmental factors [45]. Another major finding of this meta-analysis was the different associations of XRCC3 polymorphisms with the GC risk according to ethnicity. Our study indicated that the Met/Met genotype carriers might be at high risk of developing GC among Asians, but not among Caucasians. The discrepancies might be due to genetic background and/or environmental exposure differences [46]. As it is conceivable that the XRCC3 gene polymorphism may confer susceptibility to non-cancerous diseases, there may be differences in the genotype frequencies between the hospital-based and population-based controls. Hence, the results of meta-analysis often depend on the control selection procedures. In subgroup analysis stratified on the basis of different sources of controls, we found
X.-P. Qin et al. that use of hospital-based controls resulted in a significant association between XRCC3 241Met/Met genotype and development of GC than did use of population-based controls. This may be due to that the investigated genotypes were associated with the disease conditions hospital-based controls might have. But HCC studies have some selection biases because such controls might be ill-related population, and may not be a representative of the general population, so a proper population-based control subject may be better to reduce biases in such genetic association studies. Additionally, in the subgroup meta-analysis based on cancer location, we detected that Met/Met genotype carriers might have an increased risk of GC in non-cardiac gastric cancer, but not in cardiac cancer. Because there were only two studies included in this subgroup meta-analysis, for the limited study sample size, the result should be interpreted with caution. Similar to other meta-analysis and systematic reviews, this study also has some limitations: (1) only published studies were included in the meta-analysis, therefore, publication bias may occur. The Egger weighted regression shows clear evidence. It is known that positive results tend to have a greater probability of being published, even though the unpublished research quality is not as good as published, if they are not included, will make an overestimate of the XRCC3 Thr241Met polymorphism at GC risk; (2) the small sample size in some subgroup analyses; (3) obvious heterogeneity was observed in the included studies; (4) GC is a multifactorial disease affected by many genes, XRCC3 Thr241Met gene polymorphism may have little influence on the risk of individual GC development; (5) meta-analysis is retrospective research that is subject to the methodological limitations. In order to minimize the bias, we developed a detailed scheme before starting the research, performed a meticulous search for published studies and using accurate methods for study selection, data extraction and data analysis. Nevertheless, our results should be considered with care. Additional well-designed, high-quality epidemiological studies with larger participants are needed to further evaluate the association between XRCC3 Thr241Met polymorphism and GC. In conclusion, this meta-analysis confirmed that the XRCC3 Thr241Met gene polymorphism might be a risk factor for GC among Asians, and that differences in genotype distribution may be related to the location of gastric cancer. More well-designed studies based on larger population are needed to confirm our results.
Disclosure of interest The authors declare that they have no conflicts of interest concerning this article.
Acknowledgement Funding/Support: the research of this paper is supported by National Natural Science Foundation of China (No. 30901427).
XRCC3 Thr241Met polymorphism and gastric cancer susceptibility: A meta-analysis
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