TPMT) and catechol O-methyltransferase (COMT) can predict the development of cisplatin-induced ototoxicity and may explain interindividual variability in sensitivity to cisplatin-induced hearing loss. Two recently published studies however, sought to validate these findings and showed inconsistent results. The aim of this study was to evaluate the role of polymorphisms in the TPMT and COMT genes in cisplatin-induced ototoxicity. Therefore we investigated two independent cohorts of 110 Dutch and 38 Spanish patients with osteosarcoma and performed a meta-analysis including all previously published studies resulting in a total population of 664 patients with cancer. With this largest meta-analysis performed to date, we show that the influence of TPMT and COMT on the development of cisplatin-induced hearing loss may be less important than previously suggested.Treatment with cisplatin-containing chemotherapy regimens causes hearing loss in 40–60% of cancer patients. It has been suggested that genetic variants in the genes encoding thiopurine S-methyltransferase ( The aim of the current study is to provide a clearer picture of the genetic impact of TPMT and COMT variants on developing cisplatin-induced ototoxicity. Therefore we investigated two independent cohorts of 110 Dutch and 38 Spanish patients with osteosarcoma and performed a meta-analysis including previously published studies Cisplatin is an effective chemotherapeutic drug for several types of cancer such as ovarian cancer, lung cancer, osteosarcoma and neuroblastoma. Ototoxicity, characterized as a permanent, bilateral sensorineural hearing loss, is one of the most common side effects of cisplatin and occurs in 40–60% of patients 2 (range: 100 to 600 mg/m2). Of patients included audiometric analysis were available at diagnose, during therapy and after completion of therapy. Data concerning administration of other potentially ototoxic medications such as furosemide, vancomycin, gentamicin, tobramycin, amphotericin B, carboplatin and vincristine, were recorded. In patients alive, DNA was extracted from blood using the QIAamp DNA Blood Midi kit  or saliva (2 ml) using the Oragene DNA purification protocol . Of patients that passed away, , DNA of paraffin-embedded samples was extracted as recently described A cohort of 110 Dutch patients with high-grade osteosarcoma treated with cisplatin was recruited from the Radboud University Medical Centre, the University Medical Centre of Groningen and Leiden University Medical Center. All patients were treated with cisplatin with a median cumulative dose of 500 mg/mTo enlarge sample size for meta-analyses, we additionally included an independent Spanish cohort of osteosarcoma patients who were treated with cisplatin-containing regimens. To prevent population bias, this cohort was analyzed separately. In total, 38 patients with osteosarcoma were included on the basis of availability of germline DNA and audiologic assessment at least one month after initial treatment. Data regarding ototoxic medication were available. The study was approved by the local ethics committee from the University of Navarra and University Clinic in Pamplona. Written informed consent was obtained from parents and/or patients.http://ctep.cancer.gov/forms/CTCAEv3.pdf) and the new SIOP Boston ototoxicity scale which classifies hearing loss on the basis of absolute hearing levels in 4 grades In both cohorts audiologic evaluations were prospectively performed at diagnosis, during therapy and after completion of therapy. First audiological follow-up was performed 1–3 months after completion of therapy and thereafter annually. All audiometric assessments were age appropriate performed by conventional or play audiometry under standardized conditions as part of routine clinical monitoring for cisplatin-related hearing loss. Hearing loss was retrospectively classified according to two grading systems: the National Cancer Institute CTCAE version 3.0  and COMT  were genotyped using Taqman allelic discrimination assays according to the protocol of the manufacturer . After amplification, the fluorescent signal for allelic discrimination was determined using the 7500 Fast Real-time System (Invitrogen). Automated allele calling was performed by allelic discrimination plots using SDS 1.4 software (Invitrogen).Previously associated variants in In both cohorts, statistical differences regarding demographic data between patients who developed hearing loss  and patients without hearing loss  were assessed by the Fischer exact test. Reported p-values are two-sided and are considered statistically significant if <0.05. Associations between ototoxicity and potential confounders, such as age, gender, cumulative dosage of cisplatin and concomitant drugs were evaluated using a 2×2 table (in case of dichotomized variables) or linear regression (in case of linear variables) in SPSS version 20 . To assess the effect of the genetic variants on ototoxicity data were dichotomized in grade 0 vs. grade 2–4. Multivariate logistic regression analyses included vincristine exposure as confounder in PLINK COMT and TPMT variants in cancer patients. Meta-analysis was performed on these three previously published studies and the two cohorts presented in this study were included. Of each of the five studies the CTCAE hearing loss criteria were used, excluding patients with grade 1 ototoxicity to better differentiate between cisplatin-induced ototoxicity and normal hearing. The studies were weighed using the inverse variance method, where larger studies with smaller standard errors have more weight than smaller studies with larger errors . Heterogeneity among studies was examined with I2 statistics that can be interpreted as the proportion of total variation contributed by between-study variation. Allelic odds ratio (OR) were recalculated dependent on the number of cases and controls in each cohort and 95% confidence interval (CI) were estimated using a fixed effects model or random effects models in case large heterogeneity I2>50% was observed.We searched PubMed for papers using the keywords: ‘ototoxicity’, ‘TPMT’ and ‘COMT’. Since the publication of Ross and colleagues A total of 110 patients with Dutch ancestry and newly diagnosed osteosarcoma were included of whom 42 (38.2%) developed>20 dB hearing loss above 4 kHz. Characteristics of patients divided in patients with hearing loss  and patients without hearing loss  are depicted in To enlarge sample size for the meta-analyses we included another cohort of 38 Spanish patients of European ancestry with osteosarcoma Table 1.TPMT gene  and two in the COMT gene . No deviation from Hardy–Weinberg equilibrium was observed. Irrespective of the grading system used (CTCAE or SIOP), association analysis using an additive genetic model correcting for usage of vincristine, showed no association between genetic variants in TPMT or COMT with an increased risk of ototoxicity in the Dutch cohort  COMT gene encodes for the COMT enzyme which is involved in the inactivation of catecholamine neurotransmitters. Although, it has been shown that it is also highly expressed in sensory hair cells of the inner ear, its role regarding auditory function remains unclear After meta-analyses of the genetic variants in TPMT variants and cisplatin ototoxicity was unexpected TPMT might have an influence on cisplatin metabolism by increasing levels of S-adenosylmethionine (SAM) TPMT variants were associated with progression-free survival in cisplatin-based chemotherapy outcomes in ovarian cancer TPMT genotypes showed no differences in hearing damage between TPMT wild-type and knockout mice Generally, the association between TPMT and COMT on the development of cisplatin-induced hearing loss may be less pronounced than previously suggested. This lack of association observed might be attributable to heterogeneity between the different studies as shown in 2 in the different studies. However, neither in the study cohort of medulloblastomas with a relatively low cumulative dose of cisplatin With the largest meta-analysis performed to date we show that the influence of It is clear that all studies included in this meta-analysis have confounding variables which could potentially influence the development of ototoxicity. This is important given the inverse method of weighing studies which has been used in this meta-analysis. The studies of Pussegoda et al and Yang et al were consistently attributed the highest weighting. Pussegoda et al included a diverse population of different cancers with different treatment protocols, the youngest population in this meta-analysis with different follow-up time between cases (5 years follow-up) and controls (2 years follow-up). The radiation cohort of Yang et al patients received highly ototoxic cranial irradiation, but 90% also received an otoprotectant, and overall these patients received a significantly lower cumulative dose of cisplatin. Thus, the weight attributed to a study may affect the results of the meta-analysis, however this is something that cannot be circumvented in this type of analysis.Nevertheless, younger age and higher cumulative doses of cisplatin appear to be the most consistent risk factors for ototoxicity. However, an upfront risk stratification based on these two factors is unreliable as these factors seem to be protocol specific and dose adjustments may jeopardize treatment efficacy of cisplatin. The addition of otoprotective agents in combination with cisplatin might be an alternative treatment strategy to prevent hearing loss. Although, the mechanism of cisplatin-induced hearing loss is not fully understood, several preclinical studies have shown that in the cochlear cells cisplatin induces the production of toxic levels of reactive oxygen species (ROS) which can initiate cochlear cell death leading to hearing loss TPMT and COMT play only a minor role in cisplatin-induced ototoxicity and should therefore not guide clinical decision making for cisplatin dosing.It remains challenging to find the right balance to maintain antitumor effect of cisplatin and on the other hand to prevent unwanted adverse effects. Innovative studies translating basic science into clinical practice are needed to unravel both, the mechanism of cisplatin-induced hearing loss and identification of patients at risk to develop ototoxicity. Pharmacogenetics may help to find new target genes, unfortunately it seems that the genes S1 TableMinor allele frequency of Dutch cohort.(DOCX)Click here for additional data file.S2 TableAssociation analyses of Dutch cohort.(DOCX)Click here for additional data file.S3 TableCall rates of the Dutch and Spanish cohort for each variant according to the CTCAE ototoxicity criteria.(DOCX)Click here for additional data file.S1 Checklist(DOC)Click here for additional data file.


Two renalase single nucleotide polymorphisms (SNPs) rs2296545 and rs2576178 have been reported to be associated with the susceptibility to hypertension (HT). Given the inconsistent results, we conducted a meta-analysis to assess the association between these two SNPs and the risk of HT.Electronic databases were systematically searched to find relevant studies. Subgroup analysis was conducted according to the different concomitant diseases and ethnicities in the study population. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated using fixed-effect or random-effect models.A total of six case–control studies on rs2296545 and six studies on rs2576178 were included. In the combined analysis, results showed a significant association between SNP rs2296545 and risk of HT in all genetic models . In subgroup analysis, we observed a significant association between rs2296545 and risk of essential HT. Although we did not observe an association between rs2576178 polymorphism and HT in the combined analysis, an increased risk was observed in the essential HT patients versus healthy controls (subgroup 1) analysis under the dominant, recessive, and codominant genetic models.Renalase gene rs2296545 polymorphism is significantly associated with increased risk of HT, whereas rs2576178 polymorphism may not be associated with the susceptibility to HT. Hypertension (HT) is not only a common chronic disease but also a major risk factor for cardiac–cerebral vascular disease and chronic kidney disease (CKD) . The numRNLS), a 342-amino-acid flavoprotein with monoamine oxidase activity discovered in 2005, is highly expressed in the kidney and heart, circulates in the blood and urine, metabolizes circulating catecholamines, and regulates blood pressure (BP) and cardiovascular function [Renalase , which lead to functional enzymatic changes [RNLS polymorphism is not associated with the risk of HT [Currently, studies revealed that renalase gene variation, particularly single nucleotide polymorphisms (SNPs) rs2296545 and rs2576178, may contribute to HT in humans –22. Rs25 changes , 18. Zha changes  first re changes  reportedsk of HT . TherefoS1 File). An unpublished protocol was prepared for internal comment.This review conformed to the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines  (S1 FileA systematic literature search was conducted independently by two investigators (Yong-Bo Lv and Yang Wang) in PubMed, Embase, Chinese National Knowledge Infrastructure (CNKI), Chinese Biomedical Literature Database, VIP (Chinese), and WanFang (Chinese) Database, with the last search update on January 1, 2016. Only studies in English and Chinese were selected. The terms “ and (polymorphism OR variation) and (hypertension OR high blood pressure)” or equivalent Chinese terms were used to search the databases. The reference lists of the included studies and recent reviews were also manually searched for further relevant studies.RNLS SNP rs2296545/rs2576178 and risk of HT; (2) case–control studies or nested case–control studies; (3) HT was defined as systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg or treatment with antihypertensive medication; and (4) detailed genotype data could be acquired to calculate the odds ratios (OR) and 95% confidence intervals (CI). The exclusion criteria are as follows: (1) case report, review, comments, and editorial and (2) studies with no detailed genotype data. Study selection was achieved by two investigators independently (Yong-Bo Lv and Yang Wang) according to the inclusion and exclusion criteria by screening the title, abstract, and full text.Eligible studies in this meta-analysis must meet the following inclusion criteria: (1) evaluation of the association between The following information were collected from the included studies: name of first author, year of publication, country of origin, ethnicity, characteristics of the cases and controls, genotype frequency in the cases and controls for rs2296545 and rs2576178, and evidence of Hardy–Weinberg equilibrium (HWE) in the controls. Any dispute was solved by discussion.S2 File). A “star system” is utilized for the assessment of study quality, such that a study can be awarded a maximum of one star for each numbered item within the selection and exposure categories, whereas a maximum of two stars can be assigned for the comparability category. Only studies in which most of the nine items on the modified NOS were deemed satisfactory (score of 5 or higher) were considered of high quality.The quality of the included studies was assessed by a modified version of the Newcastle–Ottawa scale (NOS) for genetic association studies , 26 (S2 2 statistic (greater than 50% as evidence of significant inconsistency). In the present study, I2 statistic is been used as major indicator for heterogeneity, due to the fewer number of included studies. When heterogeneity exists (I2 > 50%), we used the random-effects (RE) model; Otherwise, we used the fixed-effects (FE) model. Subgroup analysis was conducted according to the different concomitant diseases and ethnicities in the study population. The present meta-analysis contains the following subgroups: by concomitant diseases: ① essential hypertension (EH) patients versus healthy controls, ② T2DM patients with HT versus T2DM patients without HT, ③ CKD patients with HT versus CKD patients without HT, and ④ stroke patients with HT versus stroke patients without HT; by ethnicities: Asians and Caucasians. Potential publication bias was detected by funnel plot. Asymmetry of the funnel plot indicated the possible publication bias. All statistical analyses were conducted using the RevMan 5.3 software.The HWE was evaluated for each study by chi-square test in the control groups, and p < 0.05 was considered a significant departure from HWE. The OR and 95% CI were calculated to evaluate the strength of the association between rs2296545/rs2576178 polymorphisms and susceptibility to HT. A Z-test p value of less than 0.05 was considered statistically significant for the corresponding summary OR. Pooled ORs were calculated for the dominant model , recessive model , codominant model , and allelic comparison . Heterogeneity was evaluated by Q statistic (significance level of p < 0.1) and IS3 File. Among eight included studies, six studies were written in English [Table 1. In four studies [).A total of 37 article records were searched from the electronic databases . The details of the selection process are presented in the flowchart shown in  English –19 and t English . The bas studies , 18, 19,Table 2; Figs 2and 3). The C allele of rs2296545 was significantly associated with HT, conferring a pooled ORRE of 1.29 (95% CI = 1.10–1.51), and CC genotype have an approximately 1.63-fold increased risk of HT compared with the rs2296545 GG genotype.In this study, for the combined analysis, we observed a statistically significant relationship between SNP rs2296545 and risk of HT in all genetic models (Table 2). This indicates that the C allele of rs2296545 was significantly associated with EH, conferring a pooled ORRE of 1.33 (95% CI = 1.21–1.46). In ethnicity-specific subgroup analysis, we also observed a statistical correlation between rs2296545 and risk of HT in several genetic models (Table 2). The C allele in rs2296545 may separately confer 1.26 and 1.34-fold increased risk to HT in Asians and Caucasians.In concomitant-disease-specific subgroup analysis, we observed a statistical association between rs2296545 and risk of EH in subgroup 1 with negligible heterogeneity : dominant model: ORRE = 1.22, 95% CI = 0.91–1.64; recessive model: ORFE = 1.09, 95% CI = 0.95–1.26; codominant model (GG/AA): ORRE = 1.14, 95% CI = 0.78–1.66; codominant model (AG/AA): ORRE = 1.25, 95% CI = 0.95–1.63; allelic model: ORRE = 1.08, 95% CI = 0.90–1.30.We did not observe an association between rs2576178 and risk of HT in the combined analysis (Table 2): dominant model: ORFE = 1.44, 95% CI = 1.21–1.72, I2 = 31%; recessive model: ORFE = 1.20, 95% CI = 1.02–1.41, I2 = 47%; codominant model (AG/AA): ORFE = 1.41, 95% CI = 1.17–1.69, I2 = 0%. In ethnicity-specific subgroup analysis, no correlation between SNP rs2576178 and HT can be observed.However, in subgroup 1 analysis , we noted an association between rs2576178 and risk of HT in the dominant, recessive, and codominant genetic models with negligible heterogeneity .Funnel plots were employed to assess the publication bias of the included studies. The shape of the funnel plots showed no evident publication bias -binding domain, and an amine oxidase domain [RNLS polymorphisms and cardiovascular diseases has also been investigated in humans. Zhao et al. [RNLS gene variation and BP responses to dietary salt intervention in a previous study [RNLS polymorphism is not associated with HT and cardiovascular disease in Caucasians. Rezk et al. [e domain . Many ste domain . Similare domain . The relo et al.  first sho et al.  determinus study . Howeverus study  revealedk et al.  showed t2 = 31%; recessive model: OR = 1.20, 95% CI = 1.02–1.41, I2 = 47%; codominant model: OR = 1.41, 95% CI = 1.17–1.69, I2 = 0%). This result further supports the conclusion that an association between rs2576178 and risk of HT exists. However, as the studies were limited and heterogeneity does exist, the association should be interpreted with caution.In the present meta-analysis, 6 eligible case–control studies involving 2,890 cases and 2,279 controls for SNP rs2296545 and 6 studies involving 2,871 cases and 2,121 controls for SNP rs2576178 were analyzed. By contrast to a previous meta-analysis focusing on the association between rs2296545 and HT , we obseRNLS contribute to increased susceptibility to HT is unclear. However, the SNP rs2296545 CC genotype results in a conserved amino acid change at amino acid 37 (glutamic to aspartic acid) within the FAD-binding domain. Compared with Glu37, Asp37 has a significantly lower affinity for NADH, whereas NADH is essential for renalase to perform its enzymatic activity fully [The underlying mechanism on how the genetic variants in ty fully . Therefoty fully , who repty fully  and Moraty fully  failed tRNLS SNP rs2576178 was also analyzed. The quality of the included studies was assessed by using the modified NOS, and all control groups in this meta-analysis achieved the HWE.Recently, Shi et al.  reportedRNLS polymorphisms are correlated with HT, not EH.Despite the aforementioned strengths of the present study, several limitations must be acknowledged. Firstly, in concomitant-disease-specific subgroup analysis, particularly the last two subgroups, the number of included studies is relatively few to analyze the association between SNPs and risk of HT in CKD and stroke patients fully. Secondly, we failed to obtain complete original data from the studies included, so it was hard to make adjustments for gender, or some other factors. Finally, although we found an association between both SNPs and the risk of EH in subgroup 1 analysis, we cannot be sure that the remaining hypertensive patients (subgroup 2–4) are EH patients as the comorbid conditions of diabetes and CKD, which can cause secondary HT, were present in them or not. Thus, we can conclude that RNLS is associated with the increased risk of HT, whereas the SNP rs2576178 may not be associated with HT. These findings should be interpreted with caution because of the existing heterogeneity and limited studies. Well-designed studies with a larger sample size and more ethnic groups are required to validate the risk identified in the current meta-analysis.In conclusion, the present study revealed that the SNP rs2296545 in S1 File(ZIP)Click here for additional data file.S2 File(DOCX)Click here for additional data file.S3 File(ZIP)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Background. In order to clarify previous ambiguous research conclusions, a meta-analysis was made to investigate the relationship between betatrophin levels in blood and type 2 diabetes mellitus (T2DM). Methods. We have searched all the English and Chinese references regarding the relationship between betatrophin and diabetes in database both manually and online. Strict criteria have been established to include and exclude articles, with Mean and Standard Deviation as statistics to evaluate strength of association. We have chosen either fixed- or random effect model according to heterogeneity inspection results and used Begg's test and Egger's test to analyze publication bias. Results. A total of 11 studies were included in this meta-analysis. Meta-analysis indicated a significant association between betatrophin and T2DM . However, in the subgroup analysis, there was no significant statistic between betatrophin concentration and T2DM within Caucasian population . Conclusions. Such relationship may suggest preference for association between betatrophin and T2DM in different population. Diabetes mellitus (DM) is a type of metabolic disease characterized by hyperglycemia. It is caused by either defected insulin secretion or damaged biological function, or both. The statement of a high-level blood glucose that a body is in for a long time will lead to dysfunction of a variety of tissues. Nowadays, such methods as taking antidiabetic medicines or injecting insulin to cope with diabetes are the usual practice, but there is no way of thorough treatment. Recently, researchers  from HarTwo researchers (Yue and Wu) have conducted document retrieval to the relationship between betatrophin and DM independently and elaborately, who have searched such database in the text as PubMed, MEDLINE, Embase, Cochrane Library with “betatrophin and diabetes,” “Angptl8 and diabetes,” “RIFL and diabetes,” and “Lipasin and diabetes” combined and searched others including CNKI, China Wan-Fang database, and Chongqing VIP database with “betatrophin and diabetes.” The latest search date is May 1, 2015. We have studied every article selected as “Related Articles” by PubMed and searched it to get extra potentially related articles. We have also searched the references and contacted the authors to get extra articles. When there was ambiguity about the results or lack of sufficient data, we contacted all authors to make it clear. The searching method has been made beyond linguistic limits, but we only included the articles published in English or Chinese language.The following criteria have to be met for the articles to be included: (1) case-control study; (2) the cases in those studies that were type 2 diabetes; (3) all the case groups which were in accordance with international criteria for diagnosis of type 2 diabetes; (4) articles published as papers until May 2015; (5) articles that provided directly or indirectly the results on relevant research index in case group and control group.Exclusion criteria are defined as follows: (1) articles in which the case group was diagnosed with type 1 diabetes; (2) research with insufficient data; (3) research with data that could not be converted; (4) adopting the best-quality among research papers that were duplicated, repeatedly collected, or with similar data.The two researchers entered into each database, respectively, with standard procedures and extracted research data independently. If there was a discrepancy, the researchers would appraise the data together. The following information was gathered including the first author, publication year, nationality, blood sample, experimental method, sample size of patients and the control group, and Mean and Standard Deviation (SD) (part of the data were converted) of betatrophin levels.The review and analysis were guided to conduct by the PRISMA statement for preferred reporting of meta-analysis .I2 < 50%), the fixed effect model was used to weight and pool the effect size. However, when research results appeared to be heterogeneous (I2 > 50%), the random effect model was adapted to weight and pool the effect size, and meta-analysis forest plot was drawn. We used statistical software named Comprehensive Meta-Analysis  to draw funnel plots, and an asymmetrical one suggested the existence of heterogeneity. Besides, the researchers used Begg's and Egger's test to analyze publication bias, and it is considered that if P < 0.05 in Begg's and Egger's test, publication bias was significant statistically. All P values were two sided.The RevMan5.3 statistical software provided by The Cochrane Collaboration was applied, with Mean and SD as statistics to evaluate strength of association. According to heterogeneity inspection results, corresponding pooled method was chosen: when there was no significant heterogeneity in research results . Therefore, the random effect model was employed to conduct pooled analysis. The outcomes of pooled Mean [95%  CI] at 329.46 , Z = 4.39, showed that the circulating level of betatrophin in T2DM patient blood was higher than that in control groups, in All this meta-analysis outcomes were shown in Figures P < 0.00001, I2 = 99%) existed in the six papers that performed the study on Chinese people and therefore the random effect model was used to do meta-analysis. The results of pooled Mean [95%  CI] at 214.15 , Z = 2.68, revealed in P < 0.00001, I2 = 95%) was more significant in the four papers that studied Western Caucasians and therefore the random effect model was used to do pooled analysis. As the result, pooled Mean [95%  CI] was at 98.40 , Z = 0.11, which showed that the index of betatrophin circulating level in Caucasians' blood had no statistical significance, in (2) A subgroup analysis was carried out based on different group of people. The results showed that heterogeneity , and the fixed effect model was chosen to do pooled analysis. The results of pooled Mean (95%  CI) at 220.47 , Z = 2.28, revealed in (3) Another subgroup analysis was made based on different types of blood samples. The two papers with plasma as research sample did not present a conclusion of heterogeneity  in the nine papers with serum as research sample. The results of pooled Mean (95%  CI) at 358.64 , Z = 4.38, revealed in In addition, the random effect model was carried out to do pooled analysis according to the result of heterogeneity , the funnel plot was not asymmetrical  all the research samples for Chinese people were serum, and the results showed that betatrophin circulating level increased in the serum of Chinese T2DM patients; (2) betatrophin circulating level increased in the plasma of the T2MD patients. Since the study subjects are all Caucasian, we could make a conclusion for the moment: increased plasma betatrophin circulating levels in Caucasian T2DM patients.However, the result showed that circulating levels of betatrophin in Caucasian T2DM patients have no statistical significance. There are differences between the result of this subgroup analyses and the overall result. Nevertheless, the results were consistent with the conclusions by Fenzl et al. . In prevDuring the screening, Ebert et al.  also conIn this meta-analysis, the entire included case group is T2DM patients. Since the pathogenesis of T1DM is different from that of T2DM, we have not included articles on T1DM research. There have been scholars who have explored, among which Espes et. al.  studied I2 = 99%) was observed among the studies. To find the source of heterogeneity, sensitivity analysis was performed. Articles were excluded one by one before reanalyzing statistically. The results showed that there was always substantial heterogeneity. Heterogeneity increases were caused by selection bias existing in case group. The second was the small sample size. Different race and different sample are also the reasons of heterogeneity, because of which we conduct subgroup analyses. Fu et al.'s [P value according to Begg's and Egger's tests .According to the forest plot A, substantial heterogeneity (et al.'s  researchThis is meta-analysis investigating the association between betatrophin and DM, which has significantly increased the statistical power. However, the present results of meta-analysis have some limitations. First, DM is a kind of disease influenced by multiple factors and there are complex interactions between them. In this meta-analysis we have not enough data to evaluate the interaction of betatrophin in diabetes and other factors. Second, we have no access to the data that are not published, so the publication bias cannot be avoided absolutely. Third, our search languages are only English and Chinese and research data of other races may have influence on the results. Fourth, we did not get the original data of the included literature, so we cannot guarantee the accuracy of the data.Despite the limitations above, we believe that based on the positive results of the meta-analysis, it is worth for more scholars making further study in prospective study and follow-up research.In conclusion, the meta-analysis of all published case-control studies on betatrophin and T2DM revealed increased circulating levels of betatrophin in patients with type 2 diabetes.


P = 0.001; dominant model,OR = 1.24, 95% CI 1.06-1.46,P < 0.008). Besides, significant associationwas found among Asian population , whereas there was non-significantrelationship detected among Caucasian population . The present meta-analysis had suggestedthat Int7G24A polymorphism of gene TGFBR1 involved in the transforming growth factorbeta (TGF-β) signaling pathway had a significantly increased risk forcancer development.Accumulating evidences have suggested the potential association between Int7G24A(rs334354) polymorphism and cancer risk. However, results from epidemiologicalstudies are controversial. We thus conducted this meta-analysis to clarify theassociation. Relevant studies were identified on electronic databases according tothe inclusion criteria. A total of 13 case-control studies containing 4092 cases and5909 controls were included in our meta-analysis. Odds ratios (ORs) with 95%confidence intervals (CIs) were applied to assess the association. The results ofthe overall population had suggested that Int7G24A polymorphism had an increasedrisk for cancer, reaching significant levels in the 2 genetic models (allele model,OR = 1.25, 95% CI 1.09-1.42, Cancer has become the leading cause of death in developed countries and the secondleading cause of death in developing countries, according to the data provided by theInternational Agency for Research on Cancer (IARC)1In the recent years, interest in the genetic susceptibility to cancers has led to agrowing attention to the study of polymorphisms of genes involved in tumourigenesis.TGF-β is one of the most potent inhibitors of proliferation in epithelial,neuronal and hematopoietic cells4467910Among the polymorphism variations of gene TGFBR1, Int7G24A (rs334354), representing a Gto A transversion in the +24 position of the donor splice site in intron 7, had beenfirstly found to be possibly related with cancer risk by Chen in 199913In this meta-analysis, 13 studies121314171819202122232425GA/GG and OR AA/GGwere Ph < 0.001 andPh = 0.168. Thus, therandom-effect model was applied to calculate the summary ORs. Under logisticregression, the ORGA/GG and OR AA/GG were 1.19  and 1.80 . The parametersθ2 and θ3 in thelogistic regression equation were 0.08 (95% CI 0.01-0.14) and 0.26 (95% CI0.11-0.40). In addition, plots of study-specific estimates and 95% CIs of thetwo parameters, θ2 andθ3, had been shown in P value of 0.711 for the nullhypothesis had suggested there was no difference between ORGA/GG andOR AA/GG. Therefore, the best genetic model was indicated to bedominant model according to the above algorithm. Besides, in order to explorewhether A allele could increase the risk for cancer or not, allele model (A vs.G) would also be conducted. Forest plots of meta-analysis on the associationbetween Int7G24A rs334354 polymorphism and cancer risk applying the 2 modelswere displayed in P = 0.008). As for the allelemodel, increased risk was determined with OR of 1.25 (95% CI 1.09-1.42),reaching a significant level (P = 0.001). However,heterogeneity were confirmed in both of the two models.In our meta-analysis, the Q test of ORP < 0.001; mixed population,OR = 2.02, 95% CI 1.52-2.68,P < 0.001) and dominant model , while non-significantrelationship was detected for the Caucasian population . Notably, no heterogeneity wasdetected in this subgroup analysis. When stratified by control source, Int7G24Ars334354 had been found to have an increased risk for cancer risk forpopulation-based (PB) group  and hospital-based (HB)group  in allele model. Heterogeneity wasconfirmed in HB group with P < 0.001.Applying dominant model, we found significant relationship only in PB group but not in HB group, with heterogeneity found in HB group(Ph < 0.001). According tothe type of sample for genotyping, significantly increased relationship wasfound using allele model , while only the tissue sample groupwas detected to increase the risk for cancer . Subgroup analysis wasconducted among 3 methods for genotyping. In the PCR-RFLP group and PCR- SSCPgroup, significantly increased associations between Int7G24A rs334354polymorphism and cancer risk were found in allele model  and dominant model , with no heterogeneityconfirmed. In contrast, no relationship was detected in TaqMan group applyingallele model  and dominant model. In this subgroupanalysis, the studies on cancer type were further studied. However, nosignificant association was found between Int7G24A rs334354 and colorectalcancer in the two models . As for the breast cancer group,significant association was only found in allele model but not dominant model. Among the group of other type cancer,Int7G24A polymorphism was confirmed to increase the risk for cancer . Moreover, in order to explorethe confounding effect of sample size on the studying association, we alsoconducted the subgroup analysis according to sample size. As for the group withsample size larger than 1000, significantly increased association was found inboth allele model  and dominant model. In contrast, no association wasdetected among the group with sample size smaller than 300 . Among the group with sample sizelarger than 300 (including 300) and smaller than 1000 (including 1000),increased relationship was only found in allele model but not dominant model. Detailed results were shown in Results of subgroup analyses had been shown in P = 0.001; fixed-effect model,OR = 1.20, 95% CI = 1.12-1.29,P < 0.001; quality-effect model,OR = 1.57, 95% CI = 1.06-1.46,P < 0.001) and dominant model . Secondly, we appliedleave-one-out method by excluding one study in turn to evaluate the stability ofthe obtained conclusions. The results of the leave-one-out method had been shownin Sensitivity analyses were used to evaluate the sensitivity of this meta-analysis.Firstly, fixed-effect model and quality-effect model were compared withrandom-effect models, and the conclusions remained unchanged in allele model and Begg test did not suggestevidence of publication bias at a significant level ofP = 0.05.Publication bias was assessed through the visual inspection of funnel plots andwith tests of Begg rank correlation and Egger regression asymmetry. The shape offunnel plots did not reveal any evidence of obvious asymmetry in all comparisonsin overall population. In addition, the Egger test(http://www.hapmap.org), G allele distributions of Int7G24Avariant were 78% for Utah residents with ancestry from Northern and WesternEurope (CEU) and 51% for Han Chinese in Beijing (CHB) and A allele distributionswere 22% for CEU and 49% for CHB. In our meta-analysis, the minor allelefrequency (MAF) of Int7G24A variant was set to be 0.22. Power analyses wereperformed on the basis of the least effect size suggested in our meta-analysis under the assumption for thealpha value of 0.01 and the number of case-control pairs of 4092. When theallele frequency of A allele was set to be 0.49, our meta-analysis had a powerof 98.6% to detect an OR of 1.24 for the association between Int7G24Apolymorphism and cancer risk. When the allele frequency of A was set to be 0.22,our meta-analysis had a power of 99.7% to detect an OR of 1.24 for theassociation between Int7G24A polymorphism and cancer risk.Based on the data in HapMap database  and dominant model(Ph < 0.001). To explore thepotential heterogeneity among studies, subgroup analyses were conducted in ourmeta-analysis. In the subgroup analysis by ethnicity, the heterogeneity waseffectively removed, suggesting that the present heterogeneity was partly derivedfrom ethnicity. It is well known that genotype distributions vary betweenpopulations, and genetic studies on the genotype-disease association are generallyperformed on specific population. With respect to Int7G24A rs334354, the genotypefrequencies also differ between ethnicities . Thus, conclusions of genetic studies performed invarious countries might be different. In our work, significant association was foundamong Asian population , whereas there was non-significantrelationship was detected in the two genetic models among Caucasian population. This result had indicated that thecarcinogenesis of Int7G24A polymorphism might be effective only among Asianpopulation but not Caucasian population. Interestingly, it was noted that whenstratified by control population, heterogeneity appeared only in the hospital-based(HB) group but not the population-based (PB) group. Besides, in HB group , there was a great risk to develop cancercompared with PB group . Selection bias might be the reason ofthis result. On one side, since the HB group were hospital patients, they could notvalidly represent the exposure situation of the overall population. On the otherside, mostly, the HB controls were not randomly selected from the whole patientpopulation. Thus, results from the population-based controls were thought to be morereliable.Heterogeneity between studies is common in the meta-analysis of genetic associationstudies. In the present meta-analysis, heterogeneity was determined by Q-test andstatistically significant heterogeneity was confirmed within allele model,compared with the previous meta-analysis including 3 studies by Zhang in 2012Some limitations should be considered for our meta-analysis. Firstly, potentialbiases were hardly inevitable in our analysis. Our restriction on searching studiespublished in indexed journals could bring in biases such as time-lag bias andpublication bias, though the publication bias was not found in the presentmeta-analysis. Besides, non-differential misclassification bias was possible becausethe included controls were not uniform. These controls were likely to develop cancerin subsequent years though no clinical symptoms was observed at the time ofinvestigation. Moreover, lack of information for the adjustments of majorconfounders including age, smoking status, drinking status and environmental factorsmight cause confounding bias. Secondly, the number of included studies for Int7G24Ars334354 polymorphism was limited for further analysis due to shortage of originalstudies. More larger and well-designed studies were needed to confirm our results.Thirdly, there are only three ethnicity groups  included inthe present paper. Thus, it was doubtful whether the obtained conclusions weregeneralizable to other population.In conclusion, the present meta-analysis of 13 studies including 4092 cases and 5909controls suggested that Int7G24A rs334354 polymorphism of gene TGFBR1 involved inthe TGF-β signaling pathway had a significantly increased risk on therisk for cancer in both of the two genetic models. Additionally, compared withCaucasian population, Asian population with Int7G24A polymorphism had been found tohave a greater risk for the development of cancer. However, well-designed studieswith larger sample size and more ethnic groups are required to validate the riskidentified in the current meta-analysis.In this paper, we conducted a literature search on PubMed (Medline), Embase, Webof Science and Chinese National Knowledge Infrastructure (CNKI) from January1966 through August 2014 for case-control studies examining the associationbetween Int7G24A (rs334354) polymorphism of TGFBR1 and the risk for cancer,applying the search terms “TGFBR1 or transforming growth factorreceptor 1 or type 1 TGF-beta receptor”, “polymorphismor mutation or variation or genotype or SNP” and “canceror tumor or neoplasm or carcinoma”. Besides, reference lists fromretrieved articles were also reviewed. Only articles published in the Englishand Chinese were considered. We conducted our meta-analysis according to thePRISMA checklists and followed the guidelineStudies meeting the following criteria were included in the meta-analysis: (1)the study design was case-control (2) the outcome of interest was cancer, (3)the study evaluated the association between Int7G24A rs334354 polymorphism andthe risk for cancer, (4) the study reported sufficient data to calculate oddsratios (ORs) and their 95% confidence intervals (CI), (5) the study should behuman research. Additionally, we excluded reviews, editorials, non-humanstudies, and letters without sufficient data. When multiple reports based on thesame study were published, only the most recent or complete report could beused.Eligibility evaluation and data extraction were carried out independently by tworeviewers (W. W. and Y.T.). Discrepancies were adjudicated by discussion with athird reviewer (Q.L.). The following information was extracted from all theidentified studies: name of first author, year of publication, country where thestudy was performed, ethnicity, type of control source, type of cancer, methodfor genotyping, total number of cases and controls, and the frequencies of everygenotype.The qualities of the included studies were accessed by two authors respectivelyaccording to a set of predetermined criteria ,which wP ≤ 0.10. Fisher’s exacttest was used to check for deviations from Hardy–Weinbergequilibrium (HWE) among the controls in each studyet al.θ2 andθ3 are log ORGA/GG and log ORAA/GG, respectively, as defined by the following logisticregression model:The heterogeneity among studies was estimated by the Cochran Q test, whichconfirmed the heterogeneity at a significance level ofπij is the disease risk for thejth genotype in the ith study, and zi2 andzi3 are dummy variables indicating genotypes GA andAA, respectively. If there was heterogeneity on at least one of these oddsratios (ORGA/GG and OR AA/GG), random-effect modelθ2 and θ3, asfollow:θ2 = θ3 = 0(ORGA/GG = ORAA/GG = 1);No association:θ2 = 0(ORGA/GG = 1) andθ3 ≠ 0(ORAA/GG ≠ 1);Recessive model:θ2 ≠ 0,θ3 ≠ 0andθ2 = θ3(ORGA/GG = ORAA/GG ≠ 1);Dominant model:θ2 ≠ 0,θ3 ≠ 0and2θ2 = θ3(OR2GA/GG = ORAA/GG).Multiplicative codominant model:where Once the best genetic model was identified, the three genotypes were collapsedinto two groups to obtain the pooled results. Notably, Among the 13 studies,there were 2 studies13P < 0.05 was considered to berepresentative of a significant statistical publication bias. Forest plots wereapplied to assess the association between Int7G24A rs334354 polymorphism andcancer risk. Power analysis was performed to calculate the power for ourmeta-analysis to detect the estimated risk of the association between Int7G24Apolymorphism and cancer risk. In addition to the power calculation (using Quantoversion 1.2.4) and quality-effect modeling (applying MetaXL version 2.2software), all the other statistical analyses were performed with STATA version12.0 software . Allreported probabilities  were two-sided.To explore the potential heterogeneity among studies, subgroup analyses wereconducted according to ethnicity, control source, genotyping method, type ofsample, type of cancer and sample size. In addition, sensitivity analyses wereemployed to find potential origins of heterogeneity and to examine the influenceof various exclusions on the combined OR. Besides, the results fromquality-effect model was introduced to be compared with those from random-effectmodel and fixed-effect modelHow to cite this article: Wu, W. et al. Association between Int7G24Ars334354 polymorphism and cancer risk: a meta-analysis of case-control studies.Sci. Rep. 5, 11350; doi: 10.1038/srep11350 (2015).


Gout is a common inflammatory disease characterized by acute arthritis and hyperuricemia. A number of epidemiological studies have suggested the critical role of gout in carcinogenesis. The aim of this study was to estimate the association between gout and cancer risk by meta-analysis of all relevant studies published to date. A comprehensive literature search in PubMed and Embase databases from their inception up to July 1, 2014, was performed to identify eligible studies. The strength for relationship between gout and the risk of different cancers was evaluated by calculating pooled relative risks (RRs) with 95% confidence intervals (95% CIs). All analyses were carried out by STATA 12.0 software. Gout patients were at an increased risk of cancer, particularly urological cancers, digestive system cancers, and lung cancer. No such significant association between gout and the risk of breast or brain cancers was observed. Sensitivity analysis did not materially alter the pooled results. Gout is a risk factor of cancer, particularly that of urological cancers, digestive system cancers, and lung cancer. The pooled data further support the hypothesis of a link between gout and carcinogenesis. Gout is a common inflammatory disease characterized by acute arthritis and hyperuricemia due to disorder of purine metabolism . It is cDuring the past few years, the association between cancer and gout as well as hyperuricemia has drawn a lot of attention. High cell turnover can lead to hyperuricemia and tumorigenesis, implicating an underlying link between purine metabolism disorders and cancer . It has Although recent epidemiological studies have sparked interest in the hypothesis, the precise association between gout and cancer risk remains obscure. Our study was firstly aimed to investigate this association by meta-analysis of all currently available data.We performed a comprehensive literature search in PubMed and Embase databases from their inception up to July 1, 2014, for studies on the association between gout and cancer risk. The following search terms were used: gout, or hyperuricemia; cancer, tumor, or carcinoma; risk, or incidence. The references of retrieved studies were also screened for additional publications. No language restriction was imposed.The included studies must meet the inclusion criteria as follows: (1) studies concerning the association between gout and cancer risk; (2) studies in a cohort design; (3) studies with enough information for odds ratio (ORs), relative risks (RRs), or hazard ratios (HRs) with corresponding 95% confidence intervals (95% CIs).Studies were excluded if they were (1) publications not related to the role of gout in cancer risk; (2) case-only study; (3) case report; (4) reviews; (5) animal studies; (6) studies with overlapping data.Two investigators independently extracted available data from all studies as follows: first author's name, year of publication, origins, diagnosis of patients, study design, type of cancers, total sample size, study period, adjusted factors, baseline time, follow-up duration, mean age of gout patients, and RRs or HRs or ORs with corresponding 95% CIs. Disagreements were resolved by consensus.I2 test [P < 0.05 and I2 > 50% implicated potential between-study heterogeneity among studies. The fixed-effects model by Mantel and Haenszel method was used if the between-study heterogeneity was not statistically significant [P values were two-tailed, and P < 0.05 suggested statistical significance.The strength for relationship between gout and cancer risk was estimated by calculating the pooled RRs with 95% CIs. The between-study heterogeneity was evaluated by Cochran's Q-statistic test and I2 test , 15. P <nificant ; otherwinificant . Subgrounificant , 19. TheAfter a comprehensive literature search, three prospective cohort studies with a total of 50, 358 subjects were retrieved for meta-analysis , 13, 20.P = 0.008) . Besides, no significant association between gout and total cancer risk was observed in the male population, suggested by the pooled RR   . However= 0.087) . SensitiP < 0.001; I2 = 90.7%, P < 0.001)  .P < 0.001; I2 = 68.2%, P < 0.001)  .P = 0.039; I2 = 75.5%, P = 0.007)  .No significant relationship between gout and the risk of breast cancer or brain cancer was observed in our study .Begg's funnel plots and Egger's test did not show any evidence for publication bias risk in the present meta-analysis (data not shown).The present meta-analysis based on three prospective cohort studies shows the evidence that gout confers risk effect on carcinogenesis, particularly in urological cancers, digestive system cancers, and lung cancer. Besides, gout did not modify the risk of breast cancer or brain cancer or total cancer risk in males, as suggested by the pooled RRs, respectively. Nevertheless, the findings about breast and brain cancers risk must be interpreted with caution due to limited sample size. Sensitivity analysis did not materially alter the pooled results.Gout is a disorder of purine metabolism, which has been suggested in relation to many kinds of diseases, such as end-stage renal disease, myocardial infarction, obesity, and diabetes, due to increased serum uric acid –24. Kuo Up till now, three prospective cohort studies with a total of 50,358 subjects have been performed to evaluate the association between gout and cancer risk , 13, 20.Some limitations must be seriously considered. Firstly, only three cohort studies were included into our study, but the statistical power was sufficient in estimating the role of gout in carcinogenesis. More relevant studies on the association between gout and individual cancers risk, especially brain and breast cancers, are warranted for further investigation. Secondly, adjusted factors of all included studies were not consistent. Thus, bias might be introduced in our study because of confounding factors such as age, sex, and ethnicity. Future studies based on adjusted analysis are encouraged to investigate the effect of gout disease on cancer risk. Thirdly, the influence of gout disease duration in tumorigenesis was elucidated in a recent study . We failIn summary, our study does show evidence for the hypothesis of a link between gout and carcinogenesis. It suggests that gout is an independent risk factor for the incidence of total cancer, particularly urological cancers, digestive system cancers, and lung cancer. The precise association between gout and individual cancers warrants further investigation by more epidemiological studies with high quality.


RASSF1A), a tumor suppressor gene at 3p21.3, plays a very important role in various cancers, including the head and neck squamous cell carcinoma (HNSCC). Hypermethylation of CpG islands in the RASSF1A promoter region contribute to epigenetic inactivation. However, the association between RASSF1A promoter methylation and HNSCC remains unclear and controversial. Therefore, a meta-analysis was performed in the study to identify the association. We identified the eligible studies through searching PubMed, EMBASE, Web of Science, and China National Knowledge Infrastructure (CNKI) databases with a systematic searching strategy. The information on characteristics of each study and prevalence of RASSF1A methylation were collected. Pooled odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated. Meta-regression was performed to analyze heterogeneity and funnel plots were applied to evaluate publication bias. A total of 550 HNSCC patients and 404 controls from twelve eligible studies were included in the meta-analysis. Overall, a significant association was observed between RASSF1A methylation status and HNSCC risk under a random-effects model . There was no significant publication bias observed. The meta-analysis suggested that there was a significant association between aberrant RASSF1A methylation and HNSCC.The RAS association domain family protein 1a ( Head and neck cancer is the sixth most common cancer worldwide accounting for approximately 6% of all newly diagnosed malignancies. HNSCC makes up over 90% of head and neck cancer, and commonly arises from the mucosal lining in this regionRASSF1A, a kind of tumor suppressor gene, is one of eight isoforms of RASSF1 which is involved in cell cycle control, microtubule stabilization, cellular adhesion and motility as well as apoptosisRASSF1A by hypermethylation is originally described in lung and breast cancerRASSF1A is one of the most frequently hypermethylated genes so far described and was reported as a prognostic indicator in renal cell carcinoma, non-small cell lung cancer, neuroblastoma, endometrial cancer and breast cancer151617181920RASSF1A within promoter CpG islands is frequently observed in the HNSCC cell linesRASSF1A might play an important role in the development of HNSCC.DNA methylation of cytosine-guanosine dinucleotides (CpG) islands within the promoter region of genes is an alternative mechanism of gene inactivation to gene deletion or mutation. Teschendorff7891011RASSF1A and HNSCC through a comparison of the methylation prevalence of RASSF1A between cancerous tissues and controls. However, the obtained results of these studies are inconclusive and inconsistent23To date, a number of studies have investigated the association between aberrant methylation of RASSF1A and one without full text) were excluded. The remaining 17 citations were retrieved for full-text assessment. Upon the assessment, two articles which were not case-control studies and three articles with inadequate RASSF1A methylation data were excluded. In total, the electronic search strategy initially identified 112 potentially relevant studies. Firstly, these potentially relevant studies were screened for inclusion based on their titles and abstracts. As a result, 19 duplications and 76 studies . In the overall meta-analysis, the RASSF1A promoter methylation was significantly associated with HNSCC, with a combined OR of 2.93 (95% CI: 1.58–5.46) under the random-effects model.The pooled ORs and corresponding ORs 95% CIs for the association between RASSF1A methylation detection methods, case sample size, HPV infection status, gender proportion smoking status and histology types. However, only the data about ethnicity, control types, methods of RASSF1A methylation detection and case sample size were collected completely. Then, we conducted a multiple regression model with following four variables: races (Asians and Caucasians), control types (autologous control heterogeneous control), methods used to RASSF1A methylation detection  and case sample size (≥40 and <40). According to the result of the meta-regression analysis result, all 95% confidence intervals included 0 for the coefficients which indicated that none of the variables can explain the heterogeneity between-studies in A significant heterogeneity was found among the studies. Therefore we conducted a meta-regression to explore the source of heterogeneity with restricted maximum likelihood method  to 3.42 (95% CI: 1.79–6.52). This demonstrated that none of the studies dramatically influenced the pooled ORs in P = 0.73) and Begg’s rank correlation testP = 0.87), respectively. Furthermore, the fail-safe numberZ = 21.60, Nfs0.05 = 161.47, Nfs0.01 = 73.94) indicated that the pooled ORs were stable in our meta-analysis.We performed a Begg’s funnel plotRASSF1A in various cancers, including HNSCCPrevious studies have demonstrated that epigenetic alteration is an important event in the carcinogenic progression. Particularly, increased methylation in the promoter region of tumor suppressor gene can account for a progressive reduction of its expression, silencing and selective proliferative advantage in certain cells, which plays a vital role in the development of human cancerRASSF1A methylation in cancer tissues and controls under the random-effects model was 2.93 (95% CI: 1.58–5.46), which suggested a significant association of the methylation of RASSF1A promoter with HNSCC. The overall heterogeneity between included studies was interpreted by the χ2-based Cochran Q statistic test and I2 statistics and meta-regression was used to explore the sources of the heterogeneity. When I2 > 50% and P < 0.1 for the Q statistic, the between-study heterogeneity was considered significant and the pooled ORs was calculated using a random-effects model (the DerSimonian-Laird estimate)RASSF1A had a stronger association with increased risk of HNSCC in Caucasians. Similarly, the methylation rates of the MGMT gene and GSTP1 gene in non-small cell lung cancer were also significantly higher in Caucasians than in AsiansRASSF1A methylation in heterogeneous controls compared to autologous controls. The reason for this might be because the benign lesions had a higher probability of RASSF1A methylation as an early stage of carcinoma. In the method subgroup, the ORs were 10.76 (95% CI: 0.56–211.78) in the BSP group, 1.06 (95% CI: 0.38–2.94) in the Q-MSP group, and 3.30 (95%CI: 2.17–5.01) in the MSP group under the fixed-effects model. The differences of ORs in these subgroups were potentially caused by the different sensitivities and specificities of the method used to the detection of gene methylation. Q-MSP is a sensitive quantitative assay with normalization of the amplifiable DNA content of samples. The cut-off point of Q-MSP was derived from the best distinguish point. However, the cut-off point of MSP is defined by visual detection of the presence or absence of PCR product compared to the intensity of controlsOur meta-analysis included 550 HNSCC tissues and 404 controls from 12 published studies. Overall, the pooled OR of Some potential limitations of the study should be taken into consideration when interpreting the results of meta-analysis. Firstly, due to the 12 included studies were retrospective, there might be a potential unidentified confounding bias, information bias and selection bias. Secondly, although we explored and evaluated the source of heterogeneity in four variables, we could not explore heterogeneity from other aspects because of the insufficient demographic and clinical data. Thirdly, previous studies demonstrated that time of samplingRASSF1A promoter with HNSCC, which indicated that hypermethylation of RASSF1A promoter might be a potential biomarker in the process of HNSCC. Prospective studies with larger sample size are needed to confirm these results in the future.Our meta-analysis identified an association between aberrant rmethylation of The meta-analysis was performed according to the latest meta-analysis guidelines (PRISMA).RASSF1A’, ‘methylation’ and ‘hypermethylation’. Articles were searched in the databases form Jan 1, 2000 to May 8, 2015 without language limitation. Two independent reviewers screened the titles and abstracts identified by the electronic search to identify relevant studies. The inclusion criteria of the meta-analysis were as follows: (1) case-control study design; (2) presentation of data necessary for calculating odds ratios (ORs); (3) studies primarily evaluating the incidence of RASSF1A methylation in HNSCCs and corresponding autologous/heterogeneous control, including non-tumor tissue, plasma and sputum of HNSCC patients. The excluded studies were as follows: duplication, review, animal study, experimental study and adequate specific data.Studies were identified via an electronic search of a range of computerized databases, including PubMed, Embase, Web of Science and CNKI using the following key words: ‘squamous cell carcinoma or cancer’, ‘oropharyngeal or oropharynx or head and neck or tonsil’, ‘RAS association domain family protein 1A’, ‘RASSF1A promoter in extracted cancer tissues and controls. Data extraction was conducted by two reviewers independently using a standard data extraction form. If there were disagreement between them, a third reviewer was used to reach a consensus.Data retrieved from the eligible studies including first author’s name, year of publication, published journal and country, patient ethnicity, population size, methods used to determine methylation status, histology, control type, and methylation status of http://www.r-project.org/). The pooled odds ratios (ORs) of different studies and corresponding 95% confidence intervals (CIs) were calculated to evaluate the strength of the association between RASSF1A methylation and HNSCC risk. In order to assess the percentage of variability across studies attributable to heterogeneity beyond by sampling error, the χ2-based Cochran Q statistic test and I2 statistics were employed. When I2 > 50% and P < 0.1 for the Q statistic, the between-study heterogeneity was considered significant and the pooled ORs was calculated using a random-effects model (the DerSimonian-Laird estimate)P value of 0.05 in our study.All statistical analyses were conducted by using the Meta package (version 2.2-1) in R .


A linear dose-response relationship was found, with the risk of endometrial cancer decreased by 2% for every one-month increase in the duration of breastfeeding . Our analysis suggested that breastfeeding, particularly a longer duration of breastfeeding, was inversely associated with the risk of endometrial cancer, especially in North America, but not in Europe and Asia, probably due to the small number of cases included. Due to this limitation, further studies originating in other countries are required to assess the association between breastfeeding and endometrial cancer risk.Quantification of the association between breastfeeding and risk of endometrial cancer is still conflicting. We therefore conducted a meta-analysis to assess the association between breastfeeding and endometrial cancer risk. Pertinent studies were identified by a search of PubMed and Web of Knowledge through April 2015. A random effect model was used to combine the data for analysis. Sensitivity analysis and publication bias were conducted. Dose-response relationships were assessed by restricted cubic spline and variance-weighted least squares regression analysis. Fourteen articles involving 5158 endometrial cancer cases and 706,946 participants were included in this meta-analysis. Pooled results suggested that breastfeeding significantly reduced the risk of endometrial cancer (summary relative risk (RR): 0.77, 95% CI: 0.62–0.96, I Incidence of endometrial cancer has been increasing worldwide . EndometWe performed a literature search up to April 2015 using the databases of PubMed  and Web vs. never breastfeeding or the total duration of breastfeeding; (3) the outcome of interest was endometrial cancer; (4) relative risk (RR) or odds ratio (OR) with a 95% confidence interval (CI) was provided ; and (5) for dose-response analysis, the duration of breastfeeding for each category must also be provided.For inclusion, studies should fulfill the following criteria: (1) have a prospective or retrospective design; (2) the exposure of interest were the association between ever breastfeeding (the women with a history of breastfeeding) Data extraction was carried out by two reviewers. Disagreements were discussed and resolved by a third reviewer. Data abstracted from each study were as follows: the first author’s last name, year of publication, study region and design, study sample size (number of cases and controls or cohort size), range of follow-up for prospective studies, exposure and outcome assessment including ever breastfeeding and the total or average breastfeeding duration categories, the RR and 95% CI for ever breastfeeding compared with never breastfeeding and longest category compared with shortest category of breastfeeding, and factors adjusted for in the individual study. If multiple estimates of the association were available, we abstracted the estimate that adjusted for the most covariates.The quality of studies was examined and controlled in accordance with checklists of Preferred Reporting Items for Systematic reviews and Meta-Analyses for randomized trials (PRISMA) . To deteet al. [p-value for nonlinearity was calculated by testing against the null hypothesis that the coefficient of the second spline is equal to 0 [2 statistics [2 values of <30%, 30%–75% and >75% represent low, moderate and high heterogeneity, respectively. Meta-regression was performed to assess the potentially important covariates that might exert substantial impact on between-study heterogeneity [This dose-response meta-analysis was performed using the method proposed by Greenland and Longnecker  and Orsiet al. , which tual to 0 . The metual to 0 ,15. The atistics . An I2 vogeneity . A sensiogeneity . Publicaogeneity .p ≤ 0.05 was accepted as statistically significant.All statistical analyses were conducted with STATA version 10.0 . Two-tailed After the search strategy, 553 articles from PubMed and 664 from the Web of Knowledge were searched, and 79 articles were reviewed in full after reviewing the title/abstract. Sixty-five of these 79 articles were subsequently excluded from the meta-analysis for various reasons. In total, 14 articles ,31,32,332: 63.0%)  .vs. never breastfeeding and endometrial cancer risk. The summary RR of endometrial cancer for the ever breastfeeding compared with never breastfeeding was 0.85 .Six studies ,27,30,332: 60.3%).Eight studies ,29,31,322: 63.0%, Pheterogeneity = 0.001) was found in our pooled analysis. In order to explore the moderate between-study heterogeneity, univariate meta-regression with the covariates of publication year, geographic locations, study type (ever vs. never or longest vs. shortest), study design (retrospective or prospective), number of cases and source of controls were performed. However, no significant findings were found in the above-mentioned analyses.As shown in When we conducted the subgroup analysis by study design, the association was significant in the retrospective studies , but not in the prospective studies. In subgroup analysis for geographic locations, breastfeeding was significantly associated with reduced the risk of endometrial cancer in North America , but not in Europe and Asia. Subgroup analysis by sources of control suggested that there is no significant association in the population-based retrospective studies or hospital-based retrospective studies. Furthermore, there is only one study involving seven cases that reported a breastfeeding duration of more than six years. Considering most studies reported the longest breastfeeding duration is about two years, we conducted a subgroup for those studies duration at two years. The pooled RR was 0.79 (95% CI: 0.59–0.98). The details results are summarized in Pfor nonlinearity = 0.14). Our dose-response results indicated that increasing breastfeeding duration by one month was significantly associated with a 2% decrease in developing endometrial cancer risk   .p = 0.168) showed no evidence of significant publication bias on the association between breastfeeding and endometrial cancer risk.Sensitivity analysis showed that no individual study exerted excessive influence on the association between breastfeeding and endometrial cancer risk . Egger’sThe findings from this meta-analysis of epidemiologic studies indicated that breastfeeding could reduce the risk of endometrial cancer. The inverse association was also found for the longest compared with shortest categories of breastfeeding.Breastfeeding has been suggested to reduce endometrial cancer risk, possibly because estrogen levels are low during lactation . Most of2: 63.0%, Pheterogeneity = 0.001) was found in the pooled results. The between-study heterogeneity might arise from publication year, geographic locations, study design (retrospective or prospective), study type (ever vs. never or longest vs. shortest duration), number of cases and source of controls. Thus, we used meta-regression to explore the causes of heterogeneity for covariates. However, no covariate had a significant impact on between-study heterogeneity for the above-mentioned covariates. Subgroup analyses by the study design (retrospective or prospective), study type (ever vs. never or longest vs. shortest duration), geographic locations and sources of controls were also conducted to explore the source of heterogeneity. However, the between-study heterogeneity persisted in some of the subgroups analyses. Endometrial cancer is a complex etiology and pathophysiology disease generated by the combined effects of genes and environment factors. Thus, other environment variables, as well as their possible interaction, may well be potential contributors to the heterogeneity observed.Previous study had indicated that between-study heterogeneity is common in meta-analyses , and expAs a meta-analysis of published studies, our findings showed some advantages. To our knowledge, this is the first comprehensive dose-response meta-analysis of breastfeeding and endometrial cancer risk. Second, we included large number of cases and participants, allowing a much greater possibility of reaching reasonable conclusions between breastfeeding and endometrial cancer risk. However, some limitations in this meta-analysis should be addressed. First, as a meta-analysis of observational studies, it was prone to recall or selection bias inherent in the original studies, especially in case-control studies. The information on exposures for prospective study is collected before the diagnosis of the disease, so that it is less susceptible to bias than retrospective studies. The results of the meta-regression showed no evidence of significant heterogeneity between subgroups, but the summary RR was different in subgroup analyses by study design. In our meta-analysis, the significant association was only found in retrospective studies, but not in the prospective studies, while only four studies included were prospective design. More original studies with prospective design would be beneficial in the future. Second, some individual studies did not adjust for potential confounders, which may have introduced bias in an unpredictable direction. Ever breastfeeding and the duration of breastfeeding are often associated with lower levels of BMI , a lowerIn summary, results from this meta-analysis suggested that breastfeeding, particularly a longer duration of breastfeeding, was inversely associated with risk of endometrial cancer. Dose-response analysis indicated that the risk reduced in endometrial cancer estimated is 2% for every one month increase in the duration of breastfeeding. In our study, we found a significant association between breastfeeding and endometrial cancer in North America, but not in Europe and Asia, probably due to the small number of cases included. Due to this limitation, further studies originating in other countries are required to assess the association between breastfeeding and endometrial cancer risk.


TCF7L2) rs7903146 polymorphism and risk of GDM in Hispanics/Latinos are recently available. The present meta-analysis was to estimate the impact of allele variants of TCF7L2 rs7903146 polymorphism on GDM susceptibility in overall population and racial/ethnic subgroups.There are racial and ethnic differences in the prevalence of gestational diabetes mellitus (GDM). Prior meta-analyses included small samples and very limited non-Caucasian populations. Studies to determine the relationship between transcription factor 7 like-2  2.0 statistical software. The association between TCF7L2 rs7903146 polymorphism and GDM risk was assessed by pooled odd ratios (ORs) using five gene models . Stratified analysis based on race/ethnicity was also conducted. The between-study heterogeneity and contribution of each single study to the final result was tested by Cochran Q test and sensitivity analyses, respectively. Publication bias was evaluated using Egger’s linear regression test.Literature was searched in multiple databases including PubMed, Web of Science, EMBASE (Ovid SP), Airiti Library, Medline Complete, and ProQuest up to July 2015. Allelic frequency for A total of 16 studies involving 4,853 cases and 10,631 controls were included in this meta-analysis. Significant association between the T-allele of rs7903146 and GDM risk was observed under all genetic models, dominant model , recessive model , heterozygous model , homozygous model , and allele model . Stratified analysis by race/ethnicity showed a statistically significant association between rs7903146 polymorphism and susceptibility to GDM under homozygous genetic model (TT versus CC) among whites, Hispanics/Latinos and Asians. Sensitivity analysis showed that the overall findings were robust to potentially influential decisions of the 16 studies included. No significant evidence for publication bias was observed in this meta-analysis for overall studies and subgroup studies.TCF7L2 rs7903146 polymorphism was associated with susceptibility of GDM in overall population in white, Hispanic/Latino and Asian sub-groups. Asians with homozygous TT allele of rs7903146 polymorphism have highest risk of GDM (OR = 2.08) followed by Hispanics/Latinos (OR = 1.80) and whites (OR = 1.51). The highest and lowest frequency of T allele of rs7903146 was found in Malaysia and South Korea, respectively. Future studies are needed to profile genetic risk for GDM among high risk Asian and Pacific Islander subgroups.This meta-analysis showed that the T allele of  Gestational diabetes mellitus (GDM) is a glucose tolerance disorder leading to hyperglycemia, diagnosed for the first time in pregnancy . GDM is There are racial and ethnic differences in the prevalence of GDM. As reported by some studies , 8, AsiaTCF7L2) gene produces the strongest susceptibility for T2DM   . Such re42–1.51] . The exafunction . The risfunction , 21. In function . In addifunction . The rs7American –29. As r in T2DM , 30. Therecently . UnderstTCF7L2 rs7903146 polymorphism and GDM in PubMed, Web of Science, EMBASE (Ovid SP), Airiti Library, Medline Complete, and ProQuest. The keywords used for searching were “gestational diabetes” in combination with “TCF7L2” and the search was not limited to English language. All articles published up to June of 2015 were included. To further identify eligible studies, reference lists from the retrieved articles were also examined.A broad search was performed for reports on TCF7L2 gene and GDM. If an article did not include information on genotypic frequencies in cases and controls, the researcher contacted the study authors by mail to request specific additional data. Studies were excluded if they met any of the following criteria: (1) overlapping and insufficient data; (2) family-based studies or case only design; (3) review articles; (4) rs7903146 polymorphism was not investigated.Published studies meeting the following criteria were selected: (1) study subjects must be humans; (2) study design conformed to case-control; (3) study was published as an original article or a conference abstract with original data including allelic frequencies and their distributions in cases and controls; and (4) study investigated the relationship between The studies were reviewed by two independent reviewers who extracted the following information: name of the first author, year of publication, country of study setting, race/ethnicity of study subjects, sample size, mean age of cases and controls, allelic frequencies and their distributions in cases and controls, adjusted OR and 95% confidence intervals (CI), and p value for Hardy-Weinberg Equilibrium (HWE) test. Disagreements concerning inclusion/exclusion of studies or risk estimates were resolved by consensus.p values less than 0.05 were considered statistically significant [The meta-analysis was performed using Comprehensive Meta-Analysis (CMA) 2.0 statistical software . The strength of association between rs7903146 polymorphism and GDM risk was assessed by calculating the logarithm of OR with 95% CI. We calculated the OR by genotype and allele model comparisons of rs7903146 polymorphism between cases and controls. Stratified analysis was performed for race/ethnicity. I2 statistical test was performed to calculate the degree of inconsistency. I2 is the ratio of true heterogeneity to total variation in observed effects, representing a signal to noise ratio . I2 valunificant .HWE deviation was assessed in controls of each study by chi-square test. Publication bias was examined in funnel plots and with the Egger’s regression test  and a p TCF7L2 polymorphism and GDM; (3) 13 non case-control studies; (4) 34 studies unrelated to TCF7L2 gene and GDM; (5) five studies not focus on rs7903146 polymorphism; (6) four articles lacking genotype frequency data in the text or from corresponding authors [Our meta-analysis was performed according to the “Preferred Reporting Items for Systematic Reviews and Meta-analyses” (PRISMA)  and the  authors –46; (7)  authors –48 shari authors . Hence,  authors , 49–54 , the recessive model , the heterozygote model , the homozygous model , and the allele model .Association between p = 0.007), Hispanics/Latinos  and Asians   in whites  . Under aAllele frequencies of rs7903146 polymorphism by study countries are showed in To evaluate the robustness of the association results, leave-one-out sensitivity analysis was conducted by removing one study at a time and recalculating the summary ORs. The summary ORs remained stable , indicatPublication bias was determined using Egger’s test. No statistically significant evidence of publication bias was observed for studies included in the overall and subgroup analyses  .TCF7L2 rs7903146 polymorphism was significantly associated with the risk of GDM in overall sample as well as in racial/ethnic subgroups, Whites, Hispanics/Latinos and Asians. The T allele of TCF7L2 rs7903146 polymorphism was associated with a reduced compensation of insulin secretion for insulin resistance induced by 9 days of bed rest [The result of this meta-analysis indicates that the at risk T allele of bed rest .TCF7L2 rs7903146 polymorphism and risk of GDM in the dominant and co-dominant models . Of the 10 studies considered, all included Caucasians except for three studies . Due to small sample sizes with limited racial/ethnic subgroups, evaluating the relationship between TCF7L2 rs7903146 polymorphism and the risk of GDM among racial/ethnic subgroups was limited. Our meta-analysis included an extensive dataset from 16 distinct studies with 4,853 GDM cases and 10,631 controls and showed a significant association between TCF7L2 rs7903146 polymorphism and risk of GDM. The odd ratios in our meta- analysis are similar to the two existing meta-analyses when data are pooled disregard racial/ethnic subgroups. However, studies to determine the relationship between TCF7L2 rs7903146 polymorphism and risk of GDM in Hispanics/Latinos were not available until recently [Mao and colleagues  performerecently , 31, 32.recently  to perfoOf racial/ethnic groups in the United States, Asian and Pacific Islander women were found to have a higher age-adjusted prevalence of GDM than whites, blacks, or Hispanics , 8, 65. TCF7L2 rs7903146 polymorphism and GDM did not reach statistical significance , this level of association is similar to results from our overall pooled data and in Asian subgroup. In our analysis, the association between TCF7L2 rs7903146 polymorphism and GDM in Asians is strongest under homozygous genetic model ; however, only allele model  was used in the genome-wide association study by Kwak et al. [In a genome wide association study conducted in South Korea  includink et al. .Interestingly, we found that the at-risk T allele in Asian population varied greatly, with the most frequent percentage of 89.5% reported by a study from Malaysia  and the TCF7L2 risk haplotype . In addition, the TCF7L2 risk haplotype was also associated with metabolic quantitative traits, including higher levels of fasting glycemia (p = 0.0128), and 60 and 120 minutes of OGTT glycemia . In our meta-analysis, we have included one study from Brazil [Result of this meta-analysis suggests the Hispanic/Latino women with TT genotype of rs7903146 polymorphism are 1.8 times more likely to have GDM than women with CC genotype. Huerta-Chagoya and associates  performem Brazil , 32 in tTCF7L2 rs7903146 polymorphism as a risk factor for GDM.Characteristics of controls varied greatly between studies. For example, Cho and colleagues  recruiteTCF7L2 rs7903146 polymorphism and the risk of GDM. Other factors that can affect risk of GDM, such as obesity, family history of T2DM were not included.Some limitations exist in this meta-analysis. First, we were unable to obtain detailed genotype frequency data from four published studies , 46, 68.Fourth, geographic distribution of risk T or TT alleles of rs7903146 polymorphism can only be stratified when specific genotype data are available by study country. For example, the study by Freathy and colleagues  was exclTCF7L2 rs7903146 polymorphism is associated with GDM risk in whites, Hispanics/Latinos and Asians. Asians with homozygous TT allele of rs7903146 polymorphism have highest risk of GDM (OR = 2.08) followed by Hispanics/Latinos (OR = 1.80) and whites (OR = 1.51). The highest and lowest frequency of T allele of rs7903146 was found in Malaysia and South Korea, respectively. Future studies are needed to profile genetic risk for GDM among high risk Asian and Pacific Islander subgroups.In summary, our meta-analysis provides evidence that the T allele of the S1 Table(DOC)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Glutathione S-transferase (GST) genetic polymorphisms has been reported to be associated with osteosarcoma; however, the results of previous studies are conflicting. Thus, in the present study, a meta-analysis was conducted to investigate the effects of GSTM1 and GSTT1 polymorphisms on osteosarcoma risk. A literature search was performed in the PubMed, Cochrane Library and China National Knowledge Infrastructure databases to identify case-control studies published prior to March 2014. Data were extracted and pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated. In addition, Begg’s test was used to measure publication bias. Sensitivity analysis were performed to ensure the accuracy of the results. The meta-analysis results demonstrated no significant association between the null genotype of GSTM1 and osteosarcoma risk . By contrast, the results revealed a significant association for the comparison of null vs. non-null genotypes of GSTT1 . In conclusion, the GSTT1 null genotype may be associated with an increased risk of developing osteosarcoma. Further studies with larger sample sizes and well-designed methodologies are required to verify these conclusions. Osteosarcoma is a highly malignant and aggressive bone tumor, occurring primarily in individuals between 10 and 30 years old . FurtherGlutathione S-transferases (GSTs) are a family of phase II enzymes . GSTs arIn humans, the GST super family consists of numerous cytosolic, mitochondrial and microsomal proteins. Cytosolic proteins are divided into eight distinct classes, including the α, κ, μ, ω, π, σ, θ and ζ . The θ cA previous study revealed that the null genotypes of GSTT1 and GSTM1 were associated with increased risk of bladder and prostate cancer . In addiwww.ncbi.nlm.nih.gov/pubmed), Cochrane Library (www.thecochranelibrary.com) and China National Knowledge Infrastructure (http://www.cnki.net) databases were examined to identify all the studies investigating the association between GSTM1 and GSTT1 polymorphisms and osteosarcoma risk, which were published prior to March 2014. The following key words were used: ‘glutathione S-transferases’, ‘GST’, ‘osteosarcoma’, ‘polymorphism’, ‘mutation’ and ‘variant’. No publication language restrictions were imposed. The references of all the studies identified through the literature search were investigated for other relevant publications. In the case that sequential or multiple publications using the same data were identified, the publication reporting data from the largest or most recent study was included. The search strategy used in this study is shown in The literature was screened  by two researchers independently, in order to determine which studies were eligible for inclusion in this meta-analysis. The results were compared and disagreements were resolved by consensus. The PubMed (The inclusion criteria for human studies included the following: i) Case-control studies, addressing osteosarcoma cases and healthy controls; ii) studies evaluating the association between GSTM1 and GSTT1 polymorphisms and osteosarcoma risk; and iii) studies that included sufficient genotype data for extraction. The exclusion criteria included the following: i) Non-case-control studies, evaluating the association between GSTM1 and GSTT1 polymorphisms and osteosarcoma risk; ii) case reports, letters, reviews, meta-analyses and editorial articles; iii) studies reporting incomplete or insufficient data; iv) studies containing duplicate data; and v) studies with a family-based design.The data were independently examined and extracted by two researchers, based on the aforementioned inclusion and exclusion criteria. In the case of inconsistency between the studies selected by the two researchers, consensus was reached following discussion. The following information was collected from the eligible studies: First author’s name; year of publication; country and ethnicity of the studied population; number of cases and controls; and number of genotyped cases and controls. The cases and controls were categorized into the Asian or Caucasian ethnic groups. No minimum number of patients was required to include a study in this meta-analysis.I2 test. I2 values of 25, 50 and 75% were defined as low, moderate and high estimates, respectively  with 95% confidence intervals (CIs) were used to determine the strength of association between the GSTM1 and GSTT1 polymorphisms and osteosarcoma risk. Pooled ORs for the risk associated with the GSTM1 and GSTT1 null genotypes vs. the non-null genotypes were calculated. Heterogeneities between the studies were estimated using the ectively . When thfindings . PublicaBased on the search criteria used in the present study, 31 individual manuscripts were identified. Of these, eight full-text publications were preliminarily selected for further detailed evaluation. According to the exclusion criteria, five of these publications were then excluded, including one duplicate study, one meta-analysis and three studies with insufficient data for extraction. Finally, as shown in The combined results of the GSTM1 and GSTT1 null genotypes and osteosarcoma risk are summarized in The funnel plot and Begg’s test were used to assess the publication bias. No evidence of publication bias was detected in the present meta-analysis P>0.05; .Even with identical environmental exposure, different individuals present a varied susceptibility to the same cancer type. A number of factors, including polymorphisms of genes involved in carcinogenesis, may account for this susceptibility variation. Therefore, recent studies have focused on genetic susceptibility to cancer ,5. As imThe association between GSTM1 and GSTT1 null genotypes and osteosarcoma risk has been investigated in several studies ,17,18; hThe underlying mechanism of the association between the GSTT1 null genotype and osteosarcoma risk remains unclear. A recent study demonstrated that GSTT1 is different compared with other phase II enzymes (such as GSTM1), which also exhibit phase I enzyme activity and possess the ability to activate carcinogens . The nulThe limitations of the current meta-analysis should be acknowledged. Firstly, the systematic review was based on unadjusted data, since the genotype information stratified for the main confounding variables was not available in the original studies, while the confounding factors addressed across the different studies were variable. In addition, this meta-analysis was not able to address all the sources of heterogeneity that existed among the previous studies for the majority of polymorphisms, although subgroup stratification analysis may be possible for the limited number of the included published studies. Furthermore, gene-gene and gene-environment interactions were not investigated in the present study, due to the lack of information from the original studies.In conclusion, the present meta-analysis indicated that the GSTT1 null genotype was associated with an increased risk of developing osteosarcoma. Since only a small number of studies are available in this field and the current evidence remains limited, future studies with large sample groups and adequate methodological quality are required to obtain accurate results.