Association of Genetic Variants in and Promoter Hypermethylation of CDH1 With Gastric Cancer A Meta-Analysis Huiquan Jing, PhD, Fei Dai, MD, PhD, Chuntao Zhao, PhD, Juan Yang, MD, Lizhuo Li, MD, Pravina Kota, MS, Lijuan Mao, MD, Kaimin Xiang, MS, Changqing Zheng, MD, and Jingyun Yang, PhD Abstract: Gastric cancer (GC) is a common cause of cancer-related death. The etiology and pathogenesis of GC remain unclear, with genetic and epigenetic factors playing an important role. Previous studies investigated the association of GC with many genetic variants in and promoter hypermethylation of E-cadherin gene (CDH1), with conflicting results reported. To clarify this inconsistency, we conducted updated metaanalyses to assess the association of genetic variants in and the promoter hypermethylation of CDH1 with GC, including C-160A (rs16260) and other less-studied genetic variants, Data sources were PubMed, Cochrane Library, Google Scholar, Web of Knowledge, and HuGE, a navigator for human genome epidemiology. Study eligibility criteria and participant details are as follows: studies were conducted on human subjects; outcomes of interest include GC; report of genotype data of individual genetic variants in (or methylation status of) CDH1 in participants with and without GC (or providing odds ratios [OR] and their variances). Study appraisal and synthesis methods included the use of OR as a measure of the association, calculated from random effects models Editor: Lu Wang. Received: May 3, 2014; revised: July 18, 2014; accepted: August 10, 2014. From the Institute of Social Science Survey (HJ), Peking University, Beijing; Department of Social Science (HJ), Shenyang Medical College; Emergency Department (LL); Department of Gastroenterology (CZ), Shengjing Hospital, China Medical University, Shenyang, Liaoning; Division of Gastroenterology (FD, JY, LM), Second Affiliated Hospital, Medical College of Xi’an Jiaotong University, Xi’an, Shaanxi; Department of General Surgery (KX), Third Xiangya Hospital, Central South University, Changsha, Hunan, China; Brain Tumor Center (CZ), Cancer and Blood Diseases Institute, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH; Department of Biostatistics and Epidemiology (PK), University of Oklahoma Health Sciences Center, Oklahoma City, OK; Rush Alzheimer’s Disease Center (JYY); and Department of Neurological Sciences (JYY), Rush University Medical Center, Chicago, IL. Correspondence: Huiquan Jing, Department of Social Science, Shenyang Medical College, 146 Huanghe North Street, Shenyang, Liaoning 110034, China (e-mail: hqjing@hotmail.com). Dr JYY’s research was supported by National Institutes of Health/ National Institute on Aging R01AG036042 and the Illinois Department of Public Health. The authors have no conflicts of interest to disclose. Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (www.mdjournal.com). Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. This is an open access article distributed under the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ISSN: 0025-7974 DOI: 10.1097/MD.0000000000000107 Medicine • Volume 93, Number 19, October 2014 in meta-analyses. We used I2 for the assessment of between-study heterogeneity, and publication bias was assessed using funnel plot and Egger test. A total of 33 studies from 30 published articles met the eligibility criteria and were included in our analyses. We found no association between C-160A and GC (OR ¼ 0.88; 95% confidence interval [CI], 0.71–1.08; P ¼ 0.215), assuming an additive model (reference allele C). C-160A was associated with cardia (OR ¼ 0.21; 95% CI, 0.11–0.41; P ¼ 2.60  10 6), intestinal (OR ¼ 0.66; 95% CI, 0.49– 0.90; P ¼ 0.008), and diffuse GC (OR ¼ 0.57; 95% CI, 0.40–0.82; P ¼ 0.002). The association of C-160A with noncardia GC is of bottom line significance (OR ¼ 0.65; 95% CI, 0.42–1.01; P ¼ 0.054). Multiple other less-studied genetic variants in CDH1 also exhibited association with GC. Gene-based analysis indicated a significant cumulative association of genetic variants in CDH1 with GC (all Ps <10 5). Sensitivity analysis excluding studies not meeting Hardy–Weinberg equilibrium (HWE) yielded similar results. Analysis by ethnic groups revealed significant association of C-160A with cardia GC in both Asian and whites, significant association with noncardia GC only in Asians, and no significant association with intestinal GC in both ethnic groups. There was significant association of C160-A with diffuse GC in Asians (P ¼ 0.011) but not in whites (P ¼ 0.081). However, after excluding studies that violate HWE, this observed association is no longer significant (P ¼ 0.126). We observed strong association of promoter hypermethylation of CDH1 with GC (OR ¼ 12.23; 95% CI, 8.80–17.00; P ¼ 1.42  10 50), suggesting that epigenetic regulation of CDH1 could play a critical role in the etiology of GC. Limitations of this study are as follows: we could not adjust for confounding factors; some meta-analyses were based on a small number of studies; sensitivity analysis was limited due to unavailability of data; we could not test publication bias for some metaanalyses due to small number of included studies. We found no significant association of the widely studied genetic variant C-160A, but identified some other genetic variants showing significant association with GC. Future studies with large sample sizes that control for confounding risk factors and/or intensively interrogate CpG sites in CDH1 are needed to validate the results found in this study and to explore additional epigenetic loci that affect GC risk. (Medicine 93(19):e107) Abbreviations: CDH1 = E-cadherin gene, GC = gastric cancer, HWE = Hardy–Weinberg equilibrium, OR = odds ratio, SNP = single-nucleotide polymorphism. INTRODUCTION G astric cancer (GC) is one of the most common gastrointestinal malignancies throughout the world. Over the past half www.md-journal.com | 1 Medicine Jing et al century, the incidence of GC has gradually decreased. However, GC remains to be the second most common cause of cancerrelated death, with >700,000 deaths/y.1 Lauren2,3 proposed a histological classification of gastric adenocarcinoma into an intestinal type, including papillary adenocarcinomas and welldifferentiated tubular adenocarcinomas, and a diffuse type, including signet ring cell carcinomas and poorly differentiated adenocarcinomas. Based on anatomic conditions, GC can also be divided into 2 subtypes: gastric cardia cancer and noncardia GC, with the former referring to cancers of the top portion of the stomach and the latter referring to cancers in the other areas of the stomach. Noncardia cancer is commonly associated with the Helicobacter pylori infection. There was no overall association between gastric cardia cancer and H pylori infection, whereas a positive association was observed in high-risk populations.4 The etiology and pathophysiology of GC is not fully understood. It is well established that gastric carcinogenesis is a complex multifactorial and multistage process. Previous studies have identified several risk factors that might contribute to gastric carcinogenesis including H pylori infection,5 inadequate vitamin C uptake,6 smoking,7 high salt intake,8 and low vegetable intake.9 Meanwhile, multiple genetic variants and different genetic pathways have been identified to contribute to GC risk,10 suggesting that genetic factors play important roles in GC susceptibility. Many studies have been conducted to search for susceptibility genes for GC, such as Interleukin-1, Interleukin-8, Glutathione S-Transferase, and Cytochrome P450 2E1.11 E-cadherin glycoprotein, encoded by E-cadherin gene (CDH1), is involved in the establishment and maintenance of intercellular adhesion.12 In vitro studies found that the A allele of C-160A could decrease the transcriptional efficiency of CDH1 by approximately 70%, suggesting that the A allele could potentially increase susceptibility to GC.13 Many previous studies investigated the association of the genetic variants, C-160A (rs16260) in CDH1 with GC risk, with conflicting results reported. Several meta-analyses have also been conducted to examine the association of C-160A with GC. Although all of them found no significant association of C-160A with GC, subgroup analysis by ethnic groups reported inconsistent findings (Table 1). In addition to the widely studied genetic variant C-160A, the association between GC and many other less-studied genetic variants in CHD1 has also been explored in many studies, with inconsistent results reported. Meanwhile, promoter hypermethylation of CDH1 has also been studied for its effect on GC susceptibility, with inconsistent results found. Therefore, in this study we performed updated meta-analyses to assess the genetic and epigenetic effect of CDH1 on GC risk. Since GC is a complex disease, a single-nucleotide polymorphism (SNP) may only confer a small or marginal individual effect on GC susceptibility. Studies focused on individual genetic variant may be less powerful in detecting small genetic effect and fail to capture the joint contribution from multiple genetic variants. We therefore conducted a gene-based analysis to examine the cumulative effect of multiple genetic variants in CDH1 on GC risk. METHODS Search Strategy and Study Selection From January to May 2014, we did an extensive literature search in PubMed, Cochrane Library, Google 2 | www.md-journal.com • Volume 93, Number 19, October 2014 Scholar, Web of Knowledge, and HuGE, a navigator for human genome epidemiology, for candidate gene studies on the association of GC with genetic variants in and promoter hypermethylation of CDH1. Details of keywords used in the literature search can be found in the supplementary file (http://links.lww.com/MD/A54, Key words used in the literature search). We used the following inclusion criteria in determining study eligibility: studies on human subjects, outcomes of interest include GC, and report of genotype data of individual genetic variants in (or methylation status of) CDH1 in participants with and without GC (or providing odds ratios [ORs] and their variances). All potentially relevant publications were retrieved and further evaluated for inclusion. We also hand-searched references of all relevant publications for additional studies missed by the database search. Only studies published in the English language were included in our analysis. Two authors (H.J. and J.Y.Y.) performed the search independently. Disagreement over eligibility of a study was resolved by discussion until a consensus was reached. Data Extraction Two reviewers (J.Y. and L.M.) independently extracted the following data according to a prespecified protocol: first author’s name, year of publication, characteristics of the study participants (sample size, number of GC patients, and number of participants in the control group, race/country of participants), genotype or methylation status data for subjects with and without GC (or OR and the corresponding variances), and the genetic model used (additive, allelic, dominant, or recessive). Discrepancies were resolved by discussion, and extracted data were entered into a computerized spreadsheet for analysis. Statistical Analysis We used the OR as a measure of the association between the genetic variants in and methylation status of CDH1 and GC. We used random effects models to calculate ORs and the corresponding 95% confidence intervals (CIs). The inverse of the variance of each study was used as the weight for that study. We used forest plots to graphically represent the calculated pooled ORs and their 95% CIs. Each study was represented by a square in the plot, the area of which is proportional to the weight of the study. The overall effect from the meta-analysis is represented by a diamond, with its width representing the 95% CI for the estimate. We used I2 for assessment of between-study heterogeneity, and publication bias was assessed using funnel plot and Egger test, and a P value <0.20 was considered statistically significant. We performed an updated meta-analysis for the association of C-160A with GC, and also conducted meta-analysis for association of other genetic variants in CDH1 with GC, when there are multiple eligible studies for the genetic variants. Otherwise, we compiled the results of the association with GC for genetic variants that appear in single studies. We also analyzed the association between C-160A and subtypes of GC (cardia and noncardia GCs and intestinal and diffuse GCs). Meta-analyses were conducted when there were multiple studies for the analysis of each subtype. In order to assess the cumulative association of CDH1 with GC, we conducted a gene-based analysis using the P values for the association of individual genetic variants in CDH1 with GC, calculated from our meta-analyses and/or ã 2014 Lippincott Williams & Wilkins Medicine • Volume 93, Number 19, October 2014 Association Between CDH1 and Gastric Cancer TABLE 1. Summary of Previous Meta-Analyses on the Association of CDH1 C-160A Polymorphism With Risk of GC Authors No. of Studies Main Genetic Model Result GC Wang et al14 Li et al15 19* 16† Multiple Multiple Cui et al16 14 Recessive Chen et al17 17 Multiple Loh et al18 14 AA vs AB+BB‡ Gao et al19 Wang et al20 10 11 Dominant Dominant 4 NA Recessive Multiple No significant association observed No significant association observed 3 NA Recessive Multiple No significant association observed No significant association observed 6 NA 4 Recessive Multiple Dominant No significant association observed No significant association observed No significant association in the overall population, Asians or whites 6 NA 4 Recessive Multiple Dominant No significant association observed No significant association observed No significant association in the overall population, Asians or whites Cardia GC Cui et al16 Chen et al17 Noncardia GC Cui et al16 Chen et al17 Intestinal GC Cui et al16 Chen et al17 Gao et al19 Diffuse GC Cui et al16 Chen et al17 Gao et al19 No significant association in the overall population, Asians or whites No significant association in the overall population for all genetic models used In Asians, A-allele conferred a decreased risk In whites, no significant association No significant association in the overall population Significant association found in Asians but not in whites No significant association in the overall population for all genetic models used In whites, A-allele conferred an increased risk In Asians, no significant association No significant association in the overall population Significant association found in Asians but not in whites No significant association in the overall population, Asians or whites No significant association in the overall population Significant associations were found in both Asians and whites, but they are in opposite direction GC ¼ gastric cancer. *One article has 2 studies21 and another article has 3 studies.22 Therefore, the 19 studies are from 16 published articles. One article has 3 studies.22 Therefore, these 16 studies are from 14 published articles. ‡ A is the major allele and B is the minor allele. † from published literature. We used 4 popular P value combination methods to assess this cumulative association: the Fisher method,23 the Simes method,24 the modified inverse normal method,25 and the truncated product method (TPM).26,27 A detailed description of the 4 methods has been reported elsewhere.26,28 We used 100,000 simulations to estimate the combined P value for TPM because the individual P values are most likely to be dependent. Finally, we performed meta-analysis to examine the effect of promoter hypermethylation of CDH1 on susceptibility of GC. Sensitivity Analysis We performed separate meta-analyses by excluding studies in which genotype in the control group did not meet Hardy–Weinberg equilibrium (HWE). We also performed meta-analysis separately for individual ethnic groups/countries of origin (Asian and whites). As a research using systematic review and metaanalysis, ethical approval of this study is not required. This ã 2014 Lippincott Williams & Wilkins work was reported according to the PRISMA guidelines.29 Meta-analysis was performed using Stata 11.2 (StataCorp LP, College Station, TX). All other analyses were performed using SAS version 9.3 (SAS Institute Inc, Cary, NC), R (www.R-project.org), and Matlab 8.1.0.604 (The MathWorks, Inc, Natick, MA). A P value <0.05 was considered statistically significant. RESULTS Literature Search and Eligible Studies Figure 1 is the flow diagram showing the selection of studies to be included in our analysis. Using our predefined search strategy, we identified a total of 311 potential publications through our initial search. After screening the abstracts of these studies, 221 were excluded either because they were irrelevant, not about human subjects, not genetic studies, or not published in English. The remaining 90 studies were retrieved for more detailed evaluations, which excluded an additional 62 studies because they were irrelevant, there were not sufficient data, the www.md-journal.com | 3 Medicine Jing et al outcome of interest was not GC, or they were meta-analyses or review studies. This left 28 potentially relevant publications (with 31 studies) to be included in our analysis. A further review of the references of these studies and review articles identified 3 more studies. Further exploration of the data from these studies excluded 1 more study because of insufficient data. A total of 33 studies from 30 published articles met the eligibility criteria and were included in our analyses.21–57 All qualified publications were published since 2002 and had sample sizes ranging from 14 to 1197 (Table 2). Prevalence of GC ranged from 16% to 88%. Of these 33 studies, 22 studies reported association results for C-160A, 4 studies for rs1801552, rs3743674, and rs5030625, and 3 studies for rs1801026. Two studies investigated the association of GC • Volume 93, Number 19, October 2014 with rs2010724, 2296-616G>C, and rs33964119. The combined study population included 9593 participants in the metaanalysis of C-160A, 1563 of rs1801552, 1993 of rs3743674, 2048 of rs5030625, 1373 of rs1801026, 783 of rs2010724, 771 of 2296-616G>C, and 447 of rs33964119. In addition to the 8 genetic variants included in the respective meta-analyses, the association between GC and 17 additional genetic variants in CDH1 was reported in individual studies (or calculated based on individual studies). These results, together with results obtained from our mea-analyses, were included in our genebased analysis. Moreover, the association of the promoter hypermethylation of CDH1 with GC has been examined in 8 studies, and meta-analysis was performed to explore the effect of promoter hypermethylation on GC risk. DNA methylation PubMed Cochrane Library Google Scholar Web of Science HuGE 219 2 111 30 65 Filtering doubles 311 Screening titles and abstracts Papers retrieved for more detailed evaluation (n = 90) Potential studies to be included (n = 28, studies = 31) Critical appraisal Additional studies included by reviewing of references (3) Papers excluded (n = 221) - Not genetic studies - Not in English - Not human studies - Irrelevant Papers excluded (n = 62) Reasons - Not about GC - Review/meta-analysis - Not on CDH1 - Not relevant data Studies excluded (1) Reasons - No sufficient data Final studies included (n = 30, studies = 33) FIGURE 1. Flow diagram of the selection process of the studies included in the meta-analyses. Please see the Methods section for additional details. CDH1 ¼ E-cadherin gene, GC ¼ gastric cancer. 4 | www.md-journal.com ã 2014 Lippincott Williams & Wilkins Medicine • Volume 93, Number 19, October 2014 Association Between CDH1 and Gastric Cancer was measured similarly across studies (ie, bisulfate treatment followed by methylation-specific polymerase chain reaction). of other SNPs is not meaningful due to the low number of studies included in the corresponding meta-analysis. Assessment of Publication Bias Association of C-160A With GC Both funnel plot and Egger test were used to assess publication bias. There was no evidence of publication bias for the meta-analysis of C-160A (P ¼ 0.380, Figure 2). We found no evidence of publication bias for the meta-analysis of rs1801552, rs3743674, rs5030625, rs1801026 (all Ps >0.38). There was some evidence of publication bias for the metaanalysis for promoter hypermethylation of CDH1 (P ¼ 0.128, Figure 3). Assessment of publication bias for the meta-analysis We calculated the association between the C-160A in CDH1 and GC assuming 4 different genetic models (additive, recessive, dominant, and allelic). Due to space limitations, we only present the results using an additive model. Results obtained using other models can be found in the supplementary materials. Of the 22 studies included in our meta-analysis, 10 showed significant association between C-160A and GC TABLE 2. Characteristics of Studies Included in the Meta-Analyses Study C-160A (rs16260) Humar et al22 Wu et al30 Pharoah et al31 (a) Pharoah et al31 (b) Pharoah et al31 (c) Kuraoka et al32 Park et al33 Shin et al34 Lu et al35 Cattaneo et al36 Medina-Franco et al37 Yamada et al21 Jenab et al38 Zhang et al39 (a) Zhang et al39 (b) Zhang et al40 Corso et al41 Al-Moundhri et al42 Borges et al43 Zhan et al44 Menbari et al45 Chu et al57 Other genetic variants in CDH1 Humar et al22 Shin et al34 Zhang et al56 Yamada et al21 Jenab et al38 Nasri et al46 Zhang et al39 Zhang et al40 Al-Moundhri et al42 Borges et al43 Li et al47 Zhan et al44 Promoter hypermethylation of CDH1 To et al48 Oue et al49 Tan et al50 Zhang et al51 Poplawski et al52 Tahara et al53 Yu et al54 Nomura et al55 ã 2014 Lippincott Williams & Wilkins Ethnicity Total Sample Size No. of Cases No. of Controls Whites Asian Whites Whites Whites Asian Asian Asian Asian Whites Mixed Asian Whites Asian Asian Asian Whites Asian Mixed Asian Whites Asian 123 397 241 174 484 196 438 170 467 353 117 440 1195 489 1197 582 820 362 112 779 306 241 53 201 148 132 153 106 292 28 206 107 39 148 245 96 572 239 412 174 58 354 144 107 70 196 93 42 331 90 146 142 261 246 78 292 949 393 625 343 408 166 51 361 162 134 Asian Asian Asian Asian Whites Whites Asian Asian Asian Mixed Asian Asian 123 170 206 440 1195 234 1197 582 362 112 460 779 53 28 101 148 245 134 572 239 192 58 230 387 70 142 105 292 950 100 625 343 170 54 230 392 Asian Asian Asian Asian Whites Asian Asian Asian 62 85 14 78 52 305 180 527 52 75 4 47 27 125 92 115 10 10 10 31 25 180 88 412 www.md-journal.com | 5 Medicine Jing et al • Volume 93, Number 19, October 2014 Begg funnel plot with pseudo 95% confidence limits 1 Log (OR) 0 –1 –2 0 0.2 0.4 Standard error of log (OR) FIGURE 2. Funnel plot for meta-analysis of C-160A in CDH1. The x-axis is the standard error of the log-transformed OR (log [OR]), and the y-axis is the log (OR). The horizontal line in the figure represents the overall estimated log (OR). The 2 diagonal lines represent the pseudo 95% confidence limits of the effect estimate. CDH1 ¼ E-cadherin gene, log (OR) ¼ log-transformed OR, OR ¼ odds ratio. (Table 3). Specifically, 3 studies31,33 indicated that compared with CC carriers, those carrying each additional copy of the A allele had increased risk of GC, whereas the other 7 studies reported decreased risk. Our meta-analysis indicates no significant association of C-160A with GC (OR ¼ 0.88; 95% CI, 0.71–1.08; P ¼ 0.215; Table 3,Figure 4). We found no significant association using different genetic models (Figures S1–S3 [http://links.lww.com/MD/A44, http://links. lww.com/MD/A45, and http://links.lww.com/MD/A46], Forest plots for meta-analysis of C-160A in CDH1; Tables S1– S3 [http://links.lww.com/MD/A47, http://links.lww.com/MD/ A48, and http://links.lww.com/MD/A49], Meta-analysis of the association of C-160A in CDH1 with GC). Association of C-160A With Subtypes of GC We found significant association of C-160A with cardia (OR ¼ 0.21; 95% CI, 0.11–0.41; 2.60  10 6), intestinal (OR ¼ 0.66; 95% CI, 0.49–0.90; P ¼ 0.008), and diffuse GCs (OR ¼ 0.57; 95% CI, 0.40–0.82; P ¼ 0.002). The association Begg funnel plot with pseudo 95% confidence limits 6 Log (OR) 4 2 0 –2 0 0.5 1 1.5 2 Standard error of log (OR) FIGURE 3. Funnel plot for meta-analysis of promoter hypermethylation of CDH1. The x-axis is the standard error of the logtransformed OR (log [OR]), and the y-axis is the log (OR). The horizontal line in the figure represents the overall estimated log (OR). The 2 diagonal lines represent the pseudo 95% confidence limits of the effect estimate. CDH1 ¼ E-cadherin gene, log (OR) ¼ logtransformed OR, OR ¼ odds ratio. 6 | www.md-journal.com ã 2014 Lippincott Williams & Wilkins Medicine • Volume 93, Number 19, October 2014 Association Between CDH1 and Gastric Cancer TABLE 3. Meta-Analysis of the Association of GC and C-160A in CDH1* Study Case Control Humar et al22 Wu et al30 Pharoah et al31 (a) Pharoah et al31 (b) Pharoah et al31 (c) Kuraoka et al32 Park et al33 Shin et al34 Lu et al35 Cattaneo et al36 Medina-Franco et al37 Yamada et al21 Jenab et al38 Zhang et al39 (a) Zhang et al39 (b) Zhang X et al40 Corso et al41 Al-Moundhri et al42 Borges et al43 Zhan et al44 Menbari et al45 Chu et al57 Total 53 201 148 132 153 106 292 28 206 107 39 148 245 96 572 239 412 174 58 354 144 107 4014 70 196 93 42 331 90 146 142 261 246 78 292 949 393 625 343 408 166 51 361 162 134 5579 OR (95% CI) 0.86 1.29 1.65 2.59 0.57 0.90 1.62 0.26 0.82 0.58 0.88 0.56 0.34 0.36 0.97 0.63 0.97 1.19 1.46 1.05 1.21 1.24 0.88 P (0.68–1.08) (0.87–1.90) (1.23–2.22) (1.72–3.91) (0.46–0.70) (0.66–1.24) (1.23–2.14) (0.12–0.57) (0.65–1.04) (0.44–0.76) (0.59–1.32) (0.42–0.75) (0.28–0.40) (0.26–0.49) (0.83–1.14) (0.49–0.82) (0.83–1.12) (0.92–1.54) (0.96–2.22) (0.87–1.27) (0.85–1.71) (0.91–1.67) (0.71–1.08) 0.196 0.208 0.001 5.50  10 3.00  10 0.519 0.001 0.001 0.100 8.46  10 0.538 8.82  10 1.33  10 6.97  10 0.716 4.34  10 0.645 0.177 0.074 0.602 0.290 0.172 0.215 6 7 5 5 37 11 4 P value in bold indicates statistical significance. CI ¼ confidence interval, GC ¼ gastric cancer, OR ¼ odds ratio. *Assuming an additive model with reference genotype CC. of C-160A with noncardia GC is of bottom line significance (OR ¼ 0.65; 95% CI, 0.42–1.01; P ¼ 0.054; Table 4). individual studies because, due to inadequate number of studies, it is not possible to determine whether there is selective reporting that can lead to inflation of the P values. Association of Other Genetic Variants With GC Our meta-analysis of the less-studied genetic variants in CDH1 found no significant association with GC (Table 5). However, several genetic variants that appeared in single studies showed significant association with GC. Specifically, 7 genetic variants from a single study38 showed strong association with GC, whereas 1 other genetic variant (rs1125557) from another individual study46 also exhibited significant association with GC (P ¼ 7.53  10 5). Gene-Based Analysis To examine the cumulative association of multiple genetic variants in CDH1 with GC, we performed a genebased analysis using all the P values we obtained for each individual genetic variant in CDH1. Additionally, we examined whether the association varies in meta-studies only (including only results for genetic variants covered in metaanalyses) and in individual studies only (including only results for genetic variants that appeared in single studies). Our gene-based analysis indicated a significant association between the genetic variants in CDH1 and GC (all Ps <10 5). The association held when pooling results from only individual-studies, but disappeared when only results from meta-studies were included, indicating that the observed gene-based association was driven mainly by results from the less-studied genetic variants (Table S4 [http://links.lww.com/ MD/A50], Gene-based analysis with GC). We would like to caution against over interpretation of the results from ã 2014 Lippincott Williams & Wilkins Association of Promoter Hypermethylation of CDH1 With GC Our meta-analysis of 8 studies showed very strong and significant association of promoter hypermethylation of CDH1 with GC (OR ¼ 12.23; 95% CI, 8.80–17.00; P ¼ 1.42  10 50; Table 6, Figure 5). More specifically, of the 8 studies, 1 study50 showed no association of promoter hypermethylation of CDH1 with GC, probably due to insufficient statistical power resulting from limited sample size (n ¼ 14), and another study48 showed marginal association (P ¼ 0.080). All the other 6 studies indicated that promoter hypermethylation of CDH1 is significantly associated with increased risk of GC. Sensitivity Analysis There were 4 studies in which the genotype in the control group did not meet HWE.32,40,44,45 After excluding these 4 studies, our meta-analysis again indicated no significant association of C-160A with GC (OR ¼ 0.87; 95% CI, 0.68–1.11; P ¼ 0.261). There were 12 studies from 11 articles and 8 studies from 6 articles examining the association of C-160A with GC in Asian and white participants, respectively. Our meta-analysis based on these studies found no significant association of C-160A with GC in Asian (OR ¼ 0.82; 95% CI, 0.66–1.02; P ¼ 0.075) and white participants (OR ¼ 0.94; 95% CI, 0.60–1.47; P ¼ 0.793; Table S5 [http://links.lww.com/MD/A51], Meta-analysis of www.md-journal.com | 7 Medicine Jing et al Study • Volume 93, Number 19, October 2014 ES (95% CI) Weight, % Humar et al22 1.29 (0.87, 1.90) 4.30 Wu et al30 0.86 (0.68, 1.08) 4.77 Pharoah et al31 (a) 1.65 (1.23, 2.22) 4.60 Pharoah et al31 (b) 2.59 (1.72, 3.91) 4.23 Pharoah et al31 (c) 0.57 (0.46, 0.70) 4.80 Kuraoka et al32 0.90 (0.66, 1.24) 4.53 Park et al33 1.62 (1.23, 2.14) 4.65 Shin et al34 0.26 (0.12, 0.57) 3.01 Lu et al35 0.82 (0.65, 1.04) 4.76 Cattaneo et al36 0.57 (0.44, 0.76) 4.65 Medina-Franco et al37 0.88 (0.59, 1.32) 4.24 Yamada et al21 0.56 (0.41, 0.75) 4.60 Jenab et al38 0.34 (0.28, 0.40) 4.91 Zhang et al39 (a) 0.36 (0.26, 0.49) 4.56 Zhang et al39 (b) 0.97 (0.83, 1.14) 4.93 Zhang et al40 0.63 (0.49, 0.82) 4.71 Corso et al41 0.96 (0.83, 1.12) 4.94 Al-Moundhri et al42 1.19 (0.92, 1.54) 4.71 Borges et al43 1.46 (0.96, 2.22) 4.21 Zhan et al44 1.05 (0.87, 1.27) 4.87 Menbari et al45 1.21 (0.85, 1.71) 4.44 Chu et al57 1.24 (0.91, 1.67) 4.58 Overall (I2) = 93.0%, P = 0.000 0.22 (0.71, 1.08) 100.00 Note: Weights are from random effects analysis 0.2 1 3 FIGURE 4. Forest plot for meta-analysis of C-160A in CDH1. Each study is represented by a square, whose area is proportional to the weight of the study. The overall effect from meta-analysis is represented by a diamond whose width represents the 95% CI for the estimated OR. CDH1 ¼ E-cadherin gene, CI ¼ confidence interval, ES ¼ effect size, OR ¼ odds ratio. C-160A by ethnic groups). These results do not change after excluding studies that did not meet HWE. There were 1 study30 and 2 studies38,41 examining the association of C-160A with cardia GC in Asian and white participants, respectively. A significant association was found between C-160A and GC in both Asian (OR ¼ 0.12; 95% CI, 0.07–0.22; P ¼ 9.71  10 13) and white participants (OR ¼ 0.27; 95% CI, 0.14–0.55; P ¼ 2.50  10 4; Table S6 [http:// links.lww.com/MD/A52], Association with cardia and noncardia GC by ethnic groups). There were 2 studies examining the association of C-160A with noncardia GC in Asian30,35 and white participants.38,42 Our meta-analysis found significant association in Asian (OR ¼ 0.80; 95% CI, 0.68–0.95; P ¼ 0.011) but not in white participants (OR ¼ 0.53; 95% CI, 0.20–1.37; P ¼ 0.190). There were 3 studies30,33,44 and 2 studies38,41 examining the association of C-160A with intestinal GC in Asian and white participants, respectively. Our meta-analysis based on these studies found no significant association in Asian (OR ¼ 0.72; 95% CI, 0.50–1.02; P ¼ 0.066) and white participants (OR ¼ 0.52; 95% CI, 0.23–1.14; P ¼ 0.103; Table S7 [http://links.lww.com/MD/A53], Association with intestinal and diffuse GC by ethnic groups). There were 6 studies and 3 studies examining the association of C-160A with diffuse GC in Asian and white participants, respectively. Our meta-analysis based on these studies indicated significant association of C-160A with diffuse GC in Asian participants (OR ¼ 0.55; 95% CI, 0.35–0.87; P ¼ 0.011) but not in white participants (OR ¼ 0.49; 95% CI, 0.22–1.09; P ¼ 0.081; Table S7 [http://links.lww.com/MD/A53], Association with 8 | www.md-journal.com intestinal and diffuse GC by ethnic groups). However, after excluding the studies in which genotype in the control group did not meet HWE (n ¼ 2), the association in Asian participants is no longer statistically significant (OR ¼ 0.64; 95% CI, 0.36–1.13; P ¼ 0.126). DISCUSSION In this study, we conducted an extensive literature search for publications on the association of GC with genetic variants in and promoter hypermethylation of CDH1. We provided an updated meta-analysis on the widely studied genetic variant C-160A. Our analysis showed that C-160A is not associated with GC, either in the overall population, or in Asian or white participants. However, within a very limited set of articles that evaluated subtypes of GC, we found significant association of C-160A with cardiac, intestinal, and diffuse GC. We found that the promoter hypermethylation of CDH1 is strongly associated with GC, indicating potential epigenetic influences in the carcinogenesis and development of GC. To the best of our knowledge, this is the most comprehensive meta-analysis on the association of GC with a number of genetic variants in CDH1, and with promoter methylation of CDH1. In the meta-analysis of C-160A, we identified significant heterogeneity between the studies included for analysis (I2 ¼ 93.0%; 95% CI, 90.6%–94.7%). Identifying the source of heterogeneity is challenging with limited information provided in many studies. Variation in patient characteristics might be an important source of heterogeneity. Some studies used ã 2014 Lippincott Williams & Wilkins Medicine • Volume 93, Number 19, October 2014 Association Between CDH1 and Gastric Cancer TABLE 4. Association of C-160A With Subtypes of GC Study Cardia GC Wu et al30 Jenab et al38 Corso et al41 Total Noncardia GC Wu et al30 Lu et al35 Jenab et al38 Corso et al41 Total Intestinal GC Wu et al30 Park et al33 Jenab et al38 Corso et al41 Borges et al43 Zhan et al44 Total Diffuse GC Humar et al22 Wu et al30 Park et al33 Shin et al34 Medina-Franco et al37 Jenab et al38 Zhang et al40 Corso et al41 Borges et al43 Zhan et al44 Chu et al57 Total Case Control OR (95% CI) 24 69 62 155 196 257 408 861 0.12 0.39 0.19 0.21 (0.07–0.22) (0.29–0.52) (0.14–0.27) (0.11–0.41) 9.71  10 4.92  10 3.56  10 2.60  10 177 206 128 350 861 196 261 506 408 1371 0.79 0.82 0.32 0.86 0.65 (0.62–1.00) (0.65–1.04) (0.26–0.41) (0.73–1.00) (0.42–1.01) 0.048 0.100 6.58  10 0.054 0.054 99 165 96 285 33 257 935 196 146 372 408 51 361 1534 0.49 0.95 0.34 0.77 0.94 0.79 0.66 (0.37–0.65) (0.70–1.30) (0.26–0.45) (0.65–0.91) (0.59–1.51) (0.64–0.97) (0.49–0.90) 1.42  10 0.751 1.70  10 0.002 0.810 0.024 0.008 53 92 127 28 39 93 239 127 25 52 107 982 70 196 146 142 78 368 343 408 51 361 134 2297 1.29 0.46 0.87 0.26 0.88 0.29 0.63 0.32 0.88 0.26 1.24 0.57 (0.87–1.90) (0.34–0.62) (0.63–1.21) (0.12–0.57) (0.59–1.32) (0.22–0.39) (0.49–0.82) (0.25–0.41) (0.53–1.45) (0.19–0.37) (0.91–1.67) (0.40–0.82) 0.208 3.75  10 0.410 0.0001 0.538 4.49  10 4.43  10 2.13  10 0.614 1.02  10 0.172 0.002 P 13 10 22 6 21 6 15 7 17 4 18 13 CI ¼ confidence interval, GC ¼ gastric cancer, OR ¼ odds ratio. matched controls (eg, age and sex matched),21,22,35,37,38,43,46 whereas most other studies did not perform matching. Other patient characteristics, such as smoking behavior, H pylori infection, and tumor location, can also contribute to the heterogeneity of the included studies in the meta-analyses. Of the 24 less-studied genetic variants in CDH1, our analysis found multiple genetic variants showing significant association with GC. Specifically, 1 study by Jenab et al38 reported findings for 7 less-studied SNPs and all of them showed significant association with GC. Another study46 showed that rs1125557 was significantly associated with GC (Table 5). The gene-based analysis indicated that these lessstudied genetic variants other than C-160A cumulatively confer significant genetic susceptibility of GC (Table S4 [http://links.lww.com/MD/A50], Gene-based analysis with GC). Realizing that the observed gene-based association might be driven by the results reported in the study by Jenab et al,38 in sensitivity analysis we dropped that study from the genebased analysis and still observed significant gene-based association (all Ps <0.003). The SNP rs1125557 is in high linkage disequilibrium (LD) with C-160A (D0 ¼ 1, SNP annotation and proxy search, http://www.broadinstitute.org/ mpg/snap/ldsearchpw.php). Given the high LD, we feel that the significant finding was probably because of the small ã 2014 Lippincott Williams & Wilkins sample size based on which the result was reported.46 Studies on functional outcomes of these less-studied genetic variants in CDH1 are scarce, and further studies are needed to elucidate whether and how they function in influencing disease susceptibility. DNA methylation is the most extensively studied epigenetic modification, and plays an important role in regulating gene expression and cell differentiation. Aberrant DNA methylation leads to silencing of tumor suppressor genes or loss of oncogene repression, and therefore is an important mechanism in the initiation and development of GC.58 The precise molecular mechanism underlying the association of promoter hypermethylation of CDH1 with GC remains to be understood. A key challenge remains whether changes in methylation are a cause or an effect of the pathological process. Although some studies suggest that altered methylation in CDH1 might be involved in carcinogenesis of GC but not development of GC,55 others indicate that accumulation of aberrant methylation might be an important mechanism for GC development.48 There are also studies indicating that the accumulation of DNA methylation might be caused by proliferative changes during tumor progression.49 Moreover, CDH1 methylation seems to be age related,51 making it more complicated to disentangle the exact role of methylation in www.md-journal.com | 9 Medicine Jing et al • Volume 93, Number 19, October 2014 TABLE 5. Association of Other Genetic Variants in CDH1 With GC Genetic Variant Case Control rs5030625* rs3743674* rs2010724* rs1801026* rs1801552* 2296-616G>C* rs33964119* rs1078621 rs2276329 rs2276330 rs3785076 rs4076177 rs7188750 rs7203904 rs10673765 rs1125557 rs9282650 rs9931853 rs9932686 rs28372783 rs3833051 rs13689 rs17690554 1937-13T>C 885 766 325 643 574 320 208 241 245 244 243 244 245 245 134 134 134 134 134 572 572 373 354 107 1163 986 458 730 748 451 239 934 949 940 938 939 950 946 100 100 100 100 100 625 625 371 370 134 OR (95% CI) 0.81 0.73 0.83 1.05 0.78 0.76 1.26 0.39 0.23 0.30 0.14 0.38 0.28 0.32 1.38 1.58 1.25 1.32 1.52 0.90 0.93 1.06 1.02 1.29 (0.62–1.06) (0.52–1.02) (0.50–1.39) (0.97–1.13) (0.59–1.03) (0.42–1.38) (0.52–3.04) (0.35–0.45) (0.15–0.35) (0.23–0.39) (0.07–0.27) (0.33–0.44) (0.22–0.35) (0.26–0.39) (0.54–3.51) (1.26–1.98) (0.90–1.74) (1.03–1.70) (0.51–4.51) (0.74–1.09) (0.81–1.07) (0.85–1.33) (0.82–1.27) (0.64–2.59) P 0.128 0.065 0.484 0.254 0.083 0.368 0.610 9.32  10 7.96  10 1.26  10 5.49  10 1.24  10 4.41  10 1.15  10 0.497 7.53  10 0.184 0.027 0.450 0.283 0.321 0.575 0.868 0.481 46 12 18 9 41 24 29 5 P value in bold indicates statistical significance. CI ¼ confidence interval, GC ¼ gastric cancer, OR ¼ odds ratio. *Indicates results obtained from meta-analysis; other results were from single studies. the initiation and development of GC. More future large-scale studies are needed that examine subjects at risk of developing GC as well as subjects with GC to better elucidate whether and how CDH1 promoter hypermethylation is implicated in GC initiation and development. Our study has some limitations. Since relevant data were not available, our meta-analysis could not adjust for confounding factors such as age, sex, smoking behavior, or H pylori infection. First, future studies are needed to validate our results— especially large consortium studies that provide control for such confounding factors. Second, some meta-analyses were based on few studies, and the gene-based analysis used some results from individual studies. Third, sensitivity analyses by ethnicity are limited because race information was not available in all studies. Fourth, due to the limited number of studies included in some of the meta-analyses, we could not test publication bias for them. This might lead to bias in the resulting data, and subsequently influence the validity of the gene-based analysis. Finally, there are other types of genetic variations that are not included in our study, such as copy number variation that was recently reported to be associated with GC.59,60 In summary, in this study, we performed meta-analyses to analyze the genetic and epigenetic effect of CDH1 on GC risk. We found no significant association of the widely studied genetic variant C-160A with GC. However, a limited number of studies suggest that C-160A may be associated with subtypes of GC in different ethnic groups, and we identified some other genetic variants showing significant association with GC. Gene-based analysis indicated that the previously studied variants cumulatively influence GC susceptibility. Meta-analysis on the promoter hypermethylation of CDH1 TABLE 6. Association of Promoter Hypermethylation of CDH1 With GC Study Case Control To et al48 Oue et al49 Tan et al50 Zhang et al51 Poplawski et al52 Tahara et al53 Yu et al54 Nomura et al55 Total 52 75 4 47 27 125 92 115 412 10 10 10 31 25 180 88 412 586 OR (95% CI) 13.25 25.26 9.00 8.94 7.35 9.29 763.63 8.83 12.23 (0.74–238.44) (1.43–446.75) (0.29–275.56) (2.39–33.51) (2.16–25.04) (5.27–16.37) (45.16–13000.00) (5.19–15.02) (8.80–17.00) P 0.080 0.028 0.208 0.001 0.001 6.40  10 0.004 8.88  10 1.42  10 15 16 50 P value in bold indicates statistical significance. CI ¼ confidence interval, GC ¼ gastric cancer, OR ¼ odds ratio. 10 | www.md-journal.com ã 2014 Lippincott Williams & Wilkins Medicine • Volume 93, Number 19, October 2014 Association Between CDH1 and Gastric Cancer Study OR (95% CI) Weight, % To et al48 13.25 (0.74, 238.44) 2.09 Oue et al49 25.26 (1.43, 446.75) 1.63 Tan et al50 9.00 (0.29, 275.56) 0.90 Zhang et al51 8.94 (2.39, 33.51) 7.60 Poplawski et al52 7.35 (2.16, 25.03) 7.76 Tahara et al53 9.29 (5.27, 16.37) 35.09 Yu et al54 763.63 (45.16, 12912.20) Nomura et al55 Overall (I 2 = 40.3%, P = 0.110) 0.1 1 0.40 8.83 (5.19, 15.02) 44.53 12.23 (8.80, 17.00) 100.00 10 FIGURE 5. Forest plot for meta-analysis of promoter hypermethylation of CDH1. Each study is represented by a square whose area is proportional to the weight of the study. The overall effect from meta-analysis is represented by a diamond whose width represents the 95% CI for the estimated OR. CDH1 ¼ E-cadherin gene, CI ¼ confidence interval, OR ¼ odds ratio. suggests that epigenetics also plays a critical role in the carcinogenesis of GC. Future studies with large sample sizes that control confounding risk factors and/or intensively interrogate CpG sites in CDH1 are needed to validate the results found in this study and explore additional epigenetic loci that affect GC risk. REFERENCES 1. Ferlay J, Shin HR, Bray F, et al. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010;127:2893–2917. 2. Lauren P. Histogenesis of intestinal and diffuse types of gastric carcinoma. Scand J Gastroenterol Suppl. 1991;180:160–164. 3. Lauren P. The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. An attempt at a histoclinical classification. Acta Pathol Microbiol Scand. 1965;64:31–49. 4. Cavaleiro-Pinto M, Peleteiro B, Lunet N, et al. Helicobacter pylori infection and gastric cardia cancer: systematic review and metaanalysis. Cancer Causes Control. 2011;22:375–387. 5. Schistosomes, liver flukes and Helicobacter pylori. IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. Lyon, 7–14 June 1994. IARC Monogr Eval Carcinog Risks Hum. 1994;61:1–241. 10. Hamilton JP, Meltzer SJ. A review of the genomics of gastric cancer. Clin Gastroenterol Hepatol. 2006;4:416–425. 11. Gianfagna F, De Feo E, van Duijn CM, et al. A systematic review of meta-analyses on gene polymorphisms and gastric cancer risk. Curr Genomics. 2008;9:361–374. 12. Graziano F, Humar B, Guilford P. The role of the E-cadherin gene (CDH1) in diffuse gastric cancer susceptibility: from the laboratory to clinical practice. Ann Oncol. 2003;14:1705–1713. 13. Li LC, Chui RM, Sasaki M, et al. A single nucleotide polymorphism in the E-cadherin gene promoter alters transcriptional activities. Cancer Res. 2000;60:873–876. 14. Wang L, Wang G, Lu C, et al. Contribution of the -160C/A polymorphism in the E-cadherin promoter to cancer risk: a metaanalysis of 47 case-control studies. PLoS One. 2012;7:e40219. 15. Li YL, Tian Z, Zhang JB, et al. CDH1 promoter polymorphism and stomach cancer susceptibility. Mol Biol Rep. 2012;39:1283–1286. 16. Cui Y, Xue H, Lin B, et al. A meta-analysis of CDH1 C-160A genetic polymorphism and gastric cancer risk. DNA Cell Biol. 2011;30:937–945. 17. Chen B, Zhou Y, Yang P, et al. CDH1 -160C> a gene polymorphism is an ethnicity-dependent risk factor for gastric cancer. Cytokine. 2011;55:266–273. 6. You WC, Zhang L, Gail MH, et al. Gastric dysplasia and gastric cancer: Helicobacter pylori, serum vitamin C, and other risk factors. J Natl Cancer Inst. 2000;92:1607–1612. 18. Loh M, Koh KX, Yeo BH, et al. Meta-analysis of genetic polymorphisms and gastric cancer risk: variability in associations according to race. Eur J Cancer. 2009;45:2562–2568. 7. Ji BT, Chow WH, Yang G, et al. The influence of cigarette smoking, alcohol, and green tea consumption on the risk of carcinoma of the cardia and distal stomach in Shanghai, China. Cancer. 1996;77:2449–2457. 19. Gao L, Nieters A, Brenner H. Meta-analysis: tumour invasionrelated genetic polymorphisms and gastric cancer susceptibility. Aliment Pharmacol Ther. 2008;28:565–573. 8. Joossens JV, Hill MJ, Elliott P, et al. Dietary salt, nitrate and stomach cancer mortality in 24 countries. European Cancer Prevention (ECP) and the INTERSALT Cooperative Research Group. Int J Epidemiol. 1996;25:494–504. 20. Wang GY, Lu CQ, Zhang RM, et al. The E-cadherin gene polymorphism 160C->A and cancer risk: a HuGE review and meta-analysis of 26 case-control studies. Am J Epidemiol. 2008;167:7–14. 9. Shimazu T, Wakai K, Tamakoshi A, et al. Association of vegetable and fruit intake with gastric cancer risk among Japanese: a pooled analysis of four cohort studies. Ann Oncol. 2014;25:1228–1233. 21. Yamada H, Shinmura K, Ikeda S, et al. Association between CDH1 haplotypes and gastric cancer risk in a Japanese population. Scand J Gastroenterol. 2007;42:1479–1485. ã 2014 Lippincott Williams & Wilkins www.md-journal.com | 11 Jing et al Medicine • Volume 93, Number 19, October 2014 22. Humar B, Graziano F, Cascinu S, et al. Association of CDH1 haplotypes with susceptibility to sporadic diffuse gastric cancer. Oncogene. 2002;21:8192–8195. 42. Al-Moundhri MS, Al-Khanbashi M, Al-Kindi M, et al. Association of E-cadherin (CDH1) gene polymorphisms and gastric cancer risk. World J Gastroenterol. 2010;16:3432–3436. 23. Fisher RA. Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd; 1932. 43. Borges Bdo N, Santos Eda S, Bastos CE, et al. Promoter polymorphisms and methylation of E-cadherin (CDH1) and KIT in gastric cancer patients from northern Brazil. Anticancer Res. 2010;30:2225–2233. 24. Simes RJ. An improved Bonferroni procedure for multiple tests of significance. Biometrika. 1986;73:751–754. 25. Hartung J. A note on combining dependent tests of significance. Biometrical J. 1999;41:849–856. 26. Sheng X, Yang J. Truncated product methods for panel unit root tests. Oxford B Econ Stat. 2013;75:624–636. 27. Zaykin DV, Zhivotovsky LA, Westfall PH, et al. Truncated product method for combining P-values. Genetic Epidemiol. 2002;22: 170–185. 28. Wang H, Dong S, Xu H, et al. Genetic variants in FTO associated with metabolic syndrome: a meta- and gene-based analysis. Mol Biol Rep. 2012;39:5691–5698. 29. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097. 30. Wu MS, Huang SP, Chang YT, et al. Association of the -160C—a promoter polymorphism of E-cadherin gene with gastric carcinoma risk. Cancer. 2002;94:1443–1448. 31. Pharoah PD, Oliveira C, Machado JC, et al. CDH1 c-160a promotor polymorphism is not associated with risk of stomach cancer. Int J Cancer. 2002;101:196–197. 32. Kuraoka K, Oue N, Yokozaki H, et al. Correlation of a single nucleotide polymorphism in the E-cadherin gene promoter with tumorigenesis and progression of gastric carcinoma in Japan. Int J Oncol. 2003;23:421–427. 33. Park WS, Cho YG, Park JY, et al. A single nucleotide polymorphism in the E-cadherin gene promoter-160 is not associated with risk of Korean gastric cancer. J Korean Med Sci. 2003;18:501–504. 34. Shin Y, Kim IJ, Kang HC, et al. The E-cadherin -347G->GA promoter polymorphism and its effect on transcriptional regulation. Carcinogenesis. 2004;25:895–899. 35. Lu Y, Xu YC, Shen J, et al. E-cadherin gene C-160A promoter polymorphism and risk of non-cardia gastric cancer in a Chinese population. World J Gastroenterol. 2005;11:56–60. 36. Cattaneo F, Venesio T, Molatore S, et al. Functional analysis and case–control study of -160C/A polymorphism in the E-cadherin gene promoter: association with cancer risk. Anticancer Res. 2006;26:4627–4632. 37. Medina-Franco H, Ramos-De la Medina A, Vizcaino G, et al. Single nucleotide polymorphisms in the promoter region of the E-cadherin gene in gastric cancer: case–control study in a young Mexican population. Ann Surg Oncol. 2007;14:2246–2249. 38. Jenab M, McKay JD, Ferrari P, et al. CDH1 gene polymorphisms, smoking, Helicobacter pylori infection and the risk of gastric cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC-EURGAST). Eur J Cancer. 2008;44:774–780. 39. Zhang B, Pan K, Liu Z, et al. Genetic polymorphisms of the Ecadherin promoter and risk of sporadic gastric carcinoma in Chinese populations. Cancer Epidemiol Biomarkers Prev. 2008;17: 2402–2408. 40. Zhang XF, Wang YM, Ge H. et al. Association of CDH1 single nucleotide polymorphisms with susceptibility to esophageal squamous cell carcinomas and gastric cardia carcinomas. Dis Esophagus. 2008;21:21–29. 41. Corso G, Berardi A, Marrelli D, et al. CDH1 C-160A promoter polymorphism and gastric cancer risk. Eur J Cancer Prev. 2009;18:46–49. 12 | www.md-journal.com 44. Zhan Z, Wu J, Zhang JF, et al. CDH1 gene polymorphisms, plasma CDH1 levels and risk of gastric cancer in a Chinese population. Mol Biol Rep. 2012;39:8107–8113. 45. Menbari MN, Rahmani SA, Zandi F, et al. Evaluation of E-cadherin (CDH1) gene polymorphism related to gastric cancer in Kurdish population. Life Sci J. 2013;10:212–216. 46. Nasri S, More H, Graziano F, et al. A novel diffuse gastric cancer susceptibility variant in E-cadherin (CDH1) intron 2: a case control study in an Italian population. BMC Cancer. 2008;8:138. 47. Li Y, Tang Y, Zhou R, et al. Genetic polymorphism in the 30 untranslated region of the E-cadherin gene is associated with risk of different cancers. Mol Carcinog. 2011;50:857–862. 48. To KF, Leung WK, Lee TL, et al. Promoter hypermethylation of tumor-related genes in gastric intestinal metaplasia of patients with and without gastric cancer. Int J Cancer. 2002;102:623–628. 49. Oue N, Mitani Y, Motoshita J, et al. Accumulation of DNA methylation is associated with tumor stage in gastric cancer. Cancer. 2006;106:1250–1259. 50. Tan SH, Ida H, Lau QC, et al. Detection of promoter hypermethylation in serum samples of cancer patients by methylation-specific polymerase chain reaction for tumour suppressor genes including RUNX3. Oncol Rep. 2007;18:1225–1230. 51. Zhang KL, Sun Y, Li Y, et al. Increased frequency of CpG island methylator phenotype and CDH1 methylation in a gastric cancer high-risk region of China. Transl Oncol. 2008;1:28–35. 52. Poplawski T, Tomaszewska K, Galicki M, et al. Promoter methylation of cancer-related genes in gastric carcinoma. Exp Oncol. 2008;30:112–116. 53. Tahara T, Shibata T, Nakamura M, et al. Increased number of CpG island hypermethylation in tumor suppressor genes of non-neoplastic gastric mucosa correlates with higher risk of gastric cancer. Digestion. 2010;82:27–36. 54. Yu QM, Wang XB, Luo J, et al. CDH1 methylation in preoperative peritoneal washes is an independent prognostic factor for gastric cancer. J Surg Oncol. 2012;106:765–771. 55. Nomura T, Tahara T, Shiroeda H, et al. Influence of HRH2 promoter polymorphism on aberrant DNA methylation of DAPK and CDH1 in the gastric epithelium. BMC Gastroenterol. 2013;13:1. 56. Zhang Y, Liu X, Fan Y, et al. Germline mutations and polymorphic variants in MMR, E-cadherin and MYH genes associated with familial gastric cancer in Jiangsu of China. Int J Cancer. 2006;119:2592–2596. 57. Chu CM, Chen CJ, Chan DC, et al. CDH1 polymorphisms and haplotypes in sporadic diffuse and intestinal gastric cancer: a case– control study based on direct sequencing analysis. World J Surg Oncol. 2014;12:80. 58. Kim J, Min SY, Lee HE, et al. Aberrant DNA methylation and tumor suppressive activity of the EBF3 gene in gastric carcinoma. Int J Cancer. 2012;130:817–826. 59. Deng N, Goh LK, Wang H, et al. A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets. Gut. 2012;61:673–684. 60. Fan B, Dachrut S, Coral H, et al. Integration of DNA copy number alterations and transcriptional expression analysis in human gastric cancer. PLoS One. 2012;7:e29824. ã 2014 Lippincott Williams & Wilkins