Genetic polymorphisms in genes whose products regulate the immune and antitumor responses in malignancies are good candidates for investigation. Many candidate genes were reported to be associated to cancerrisk, such as TLRs, CD14. TLRs are pattern recognition receptors (PRR) of the innate immune system that recognise a wide variety of molecules. With respect to CD14, it is a pattern-recognition receptor that plays a central role in innate immunity and directs the adaptive immune responses . As a co-receptor of TLRs, CD14 acts primarily by transferring LPS and other bacterial ligands from circulating LPS-binding protein to the TLR4/MD-2 signaling complex. Two common promoter polymorphisms have been identified in the CD14gene at positions -260 and -651 from the AUG start codon, which correspond to -159 and -550 designated according to the transcription start site, respectively [35,36]. With regard to - 260C/T polymorphism, LeVan et al.  showed that the T allele has a decreased affinity for DNA/protein interactions at a GC box containing a binding site for SP1, SP2, and SP3 transcription factors and leads to an increased transcriptional activity. Consis- tently, Hartel et al.  reported that after in vitro stimulation of cord blood cultures with LPS, carriers of the -159T allele have higher levels of sCD14 compared with carriers of the -159C allele. Recently, the -260C/T polymorphism in CD14gene has been investigated the association with many diseases, such as inflam- matory bowel disease , alcoholic liver disease , tuberculosis , sepsis , coronary heart disease , asthma  and allergic rhinitis . As for cancer, a previous meta-analysis conducted by Zhou et al. , evaluated the associationbetweenCD14 -260C/T polymorphism andrisk of cancer based on 12 studies including 2498 cases and 2696 controls and reported that the CD14 -159C/T gene polymorphism is not a genetic risk factor for cancer.
To the best of our knowledge, the present study is the most comprehensive meta-analysis to date to have assessed the relationship between the miRNA polymorphismsandcancerrisk. Nevertheless, our meta-analysis had some limitations common to these types of studies. First, the present meta-analysis only included case-control studies, most of which were hospital based and excluded 12 cohort studies to avoid potential heterogeneity in comparing results. Thus, the controls may not reflect the representative element of the source population. Second, the difference in the geographic areas (environmental factors) and genetic backgrounds of the study cohort in each article could influence the results. Third, the low sample size in some of the included studies might influence the statistical power to better evaluate the associationbetween miRNA polymorphismsand overall cancer, especially in subgroup analysis. Fourth, gene-geneandgene-environment interactions were not analyzed which might alter the associations between miRNA genepolymorphismsandcancer. Also, a more precise analysis stratified by variables such as age, sex etc. could not be performed due to limitations of the data which also restricted our ability to detect possible sources of heterogeneity.
IL-1B is a pluripotential proinflammatory cytokine that primarily produced by B lymphocytes, monocytes and fibroblasts. It is an important mediator for the inflammatory responses and play key roles in the triggering of immune functions, effecting nearly every cell type. IL-1B influenced thyroid cells via a number of underlying mechanisms, including down-regulation of thyroid peroxidase gene expression , induction of dissociation of the junctional complex , and inhibition of cyclic adenosine monophosphate (cAMP) and thyroglobulin production . In the development of GD, infiltration of the thyroid by activated immune cells results in local release of IL-1B. It has been observed that IL-1B induces the production of IL-6, IL-8, intercellular adhesion molecule-1 (ICAM-1), and other inflammatory mediators [34–36]. IL-1B also enhances T cell-dependent antibody produc- tion by augmenting CD40 ligand and OX40 expression on T cells . IL-1B was shown to promote differentiation of T-helper 17 (Th17) cell, the proportion of which was reported to be higher in intractable GD than that of GD in remission . Therefore, IL1B may play a role in the pathogenesis of thyroid autoimmunity. In this meta-analysis, we observed that the IL1B (-511) TT genotypes were protective against GD in Asians. This SNP may affect protein expression and function [27,39], resulting in down-regulation of inflammatory responses and resistance to develop GD. Several reasons may account for the discrepancy of results between Asians and Caucasians. First, distinct genetic background may play a role. Second, GD is a complex disease which is also related to environmental factors. Genetic susceptibility to GD may be modified by a variety of environmental exposures, leading to differences in genetic associations. Between-study heterogeneity was identified in several pooled analyses. However, when we undertook subgroup analyses according to ethnicity, heterogeneity was greatly reduced, suggesting that ethnicity was the main source of heterogeneity. Other potential factors, such as study design, sample size and genotyping methods, might also contribute to heterogeneity.
It is not uncommon to encounter genetic heterogeneity in pooled association studies. Although the overall association of HHEX gene with type 2 diabetes reached significance, there was moderate to strong evidence of heterogeneity attributable to genuine changes in gene effect size. In this meta-analysis, source of controls was identified as a potential source of between-study heterogeneity by subgroup analyses for three examined polymor- phisms. Notably, the results from studies with hospital-based controls deviated greatly from that of our main analysis. For example, the summary estimate of rs7923837-G allele was at 1.37- fold increased risk for type 2 diabetes in studies with hospital-based controls, a doubling of risk in studies with population-based controls (OR = 1.16) and in all included studies (OR = 1.18). It is widely believed that controls drawn from the general population might be representative of the true population of those without the disease, albeit running the risk of misclassification of study participants. However, studies drawing controls from hospitals had bigger problems in terms of population admixture and stratification, as well as the poor comparability between cases and controls due to their differential hospitalization rates. Another major threat to studies with hospital-based controls was a latent narrow socioeconomic profile, especially drawing controls from only one hospital. Once again, the consistency of our findings between main analysisandanalysis of only studies with population-based controls was strong support for the robustness of our observations.
Triple-negative breast cancer (TNBC) is defined by the lack of the expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). It is characterized by aggressive behavior, poor prognosis and lack of targeted therapies. MicroRNA (miRNA) as a novel modulator of gene expression has played an important regulatory role in the malignancy. Dysregulation and/or mutation of the miRNAs may also contribute to the TNBC susceptibility since it is associated with the expression of ER, PR and HER2. Single nucleotide polymorphisms (SNPs) in miRNAs may be extremely relevant for TNBC. We tried to validate the hypothesis that genetic variations in miRNA are associated with TNBC development, and identify candidate biomarkers for TNBC susceptibility and clinical treatment. We screened the genetic variants in all miRNA genes listed in the public database miRBase and NCBI. A total of 23 common SNPs in 22 miRNAs, which tagged the known common variants in the Chinese Han people with a minor allele frequency greater than 0.05, were genotyped. This case-control study involved 191 patients with TNBC and 192 healthy female controls. Frequencies of SNPs were compared between cases and controls to identify the SNPs associated with TNBC susceptibility. No significant association was found between TNBC riskand the SNPs in the miRNA genes in the Chinese Han people (P.0.05), but this warrants further studies.
Several limitations in this meta-analysis should be pointed out when explaining our results. First, though there might be some confounding factors that affect the results of this meta-analysis, we did not perform subgroup analysis because of insufﬁcient data. Second, only studies selected from databases were included, and thus pub- lication bias might exist. We did not perform the publica- tion bias analysis because eligible studies were less than 10. Third, the control group of some included studies were not ideal since a slight deviation from HWE was found. Therefore, more keywords should be used to retrieve more studies for further evaluate the relationship between ADAM33 polymorphism and childhood asthma.
The Cochrane Library, Medline-PubMed, ISI Web of Knowledge, EMBASE, VHL (Virtual Health Library), and gray literature (SIGLE) databases were searched for articles published in English. The main meSH headings and keywords used were: ‘periodontitis’ or ‘periodontal disease’ or ‘aggressive periodontitis’ or ‘chronic periodon- titis’ combined with ‘SNP’ or ‘interleukin-6’ or ‘genotype’ or ‘cytokines’. Suitable modiications in the keywords were done to follow the syntax rules of each database. If the abstract contained insuficient information to allow decision making with regard to inclusion or exclusion, the full article was obtained and reviewed before deciding. Any disagreement regarding article selection was solved by discussion. The selected articles were then carefully read for quality assessment and control of bias and for data extraction. In addiction, the reference lists of the included articles, recent reviews andmeta-analyses were manually searched.
G (rs4553808) polymorphismsandcancer susceptibility. Third, the lack of detailed original data, such as the age and sex of the populations, smoking status, or alcohol consumption in the eligible studies may influence our further analyses. However, our meta- analysis also has many advantages. First, we searched all possible publications, and the total number of eligible studies was much larger than other previously published meta-analyses; therefore, our results are more convincing. Second, no publication bias was detected in our meta-analysis. Finally, the genotype distribution of controls did not agree with the HWE in the studies were excluded by sensitivity analysis, we revealed these studies did not affect the pooled ORs, so, our results were robust and reliable.
Several potential limitations of the present meta-analysis should be taken into consideration. First, although the funnel plot and Egger’s test showed no publication bias and although an exhaustive literature search was done, it is likely that some publications and unpublished data were overlooked. Selection bias for the meta-analysis might have occurred. Secondly, in the subgroup analysis by cancer type, the number of studies and subjects analyzed for rs664677 was small, and the statistical power was so low that caution should be taken in interpreting these results. A further investigation with much larger sample sizes is needed. Thirdly, our results were based on unadjusted estimates due to the absence of available information. A more precise analysis would be detected if more detailed individual data were available, such as age, sex, and exposure. Despite its limitations, our meta-analysis also had some advantages. There was no evidence for heterogeneity in a recessive model among the studies Figure 3. Funnel plot analysis to detect publication bias. Each point represents a separate study for the indicated association (CC VS CT/TT).
GSTs are found in basically all eukaryotic species and are generally distributed in nature. Eight distinct classes of the soluble cytoplasmic mammalian GST have been identified: a (GSTA), m (GSTM), y (GSTT), p (GSTP), s (GSTS), k (GSTK), o (GSTO), and t (GSTZ) . Two loci in particular, GSTM1 and GSTT1, have received the most attention. The most com- mon variant of the GSTM1 and GSTT1 genes is homozygous deletion (null genotype), which has been associated with the loss of enzyme activity and increased vulnerability to cytogenetic damage [11,12]. Okcu and colleagues  found that GSTM1 is one of the genes encoding themu class of enzymes located on chromosome 1p13.3. Daniel  reported that the theta class of GST enzymes is encoded by the GSTT1 gene, which is mapped to chromosome 22q11.23. At the GSTM1 locus, one deletion allele and two others (GSTM1a and GSTM1b) have been identified, which differ by C!G substitution [15,16]. The C!G substitution leads to the substitution at amino acid 172 (Lys! Asn) . And the substitution leads to no func- tional difference between these two alleles. In result, GSTM1a and GSTM1b are regarded as positive conjugator phenotype. At the GSTT1 locus, two alleles (one functional and the other nonfunctional) have been identified . People with homozygous deletion genotype are
this meta-analysis, while our analysis by different tumor sites might minimize the issue of the confounding effect from mixed tumor sites. Although this analysis had such strengths, it also had some limitations. First, the number of eligible studies included in this meta-analysis was limited, and the sample size of each study was relatively small, especially in stratified analyses. For example, there were only two studies examined the associationbetween the MMP3 -1171 5A.6A polymorphism and HNC risk in Europeans. Although significant association was detected, the statistical power could have been limited. Second, if more detailed information about age, sex, alcohol consumption, tobacco smoking and/or HPV status had been available in the original studies, a more accurate OR would have been estimated after further stratifica- tion. Third, evaluating the associationbetween MMP polymorph- isms and HNC risk using linkage disequilibrium (LD) would have been more powerful. However, few studies performed haplotype analysis of these three MMPs. Additionally, publication bias may have occurred because we included only published studies in the meta-analysis, although it was not detected via a statistical test. Despite these limitations, however, the statistical power of the analysis could have been significantly increased as the cases and controls were pooled from different studies. Therefore, our results from this meta-analysis might be more reliable than those of individual studies.
the authors also suggested that higher serum EGF expression could be biologically explained by the proximity of the +61G locus to a region involved in EGF gene regulation. In September 2011, at the European Multidisciplinary Cancer Congress, in Stockholm, the associationbetween EGF+61A/G polymorphismsand the risk of non-small-cell lung cancer (NSCLC) was shown for the irst time in a Portuguese population. 4 However, the Portuguese study was discor-
GS and GBC. A variety of epidemiological studies have been performed to explore the associations between several candidate genes and the risks of GS and GBC. Among these candidate genes, ApoB-100 is of particular interest, as it is the major protein component of LDL . In fact, some studies have suggested that individuals with the X+X+ genotype have significantly higher serum total cholesterol, LDL, and Apo-B levels compared with those with the wild-type X2X2 genotype . Thus, this ApoB- 100 variant may be related to a higher incidence of GS and GBC. Unfortunately, previous epidemiological studies investigating the associations between ApoB-100 genepolymorphismsand the risks of GS/GBC have yielded conflicting results. The discrepancy may be attributed to multiple factors, such as the ethnicity of the population, the type of GS, and the sample size. Thus, a timely meta-analysis is necessary.
All statistical analyses were performed using the rmeta package for R, version 2.14.2 (The R Foundation for Statistical Comput- ing, Tsukuba, Japan; http://www.R-project.org). Two-sided probability (P) values of ,0.05 were considered statistically significant. ORs with 95% CIs were calculated to assess the strength of the following associations: (1) between PTGS genotype with NSAID users and the risk of developing cancer, (2) between NSAID users homozygous for the major allele and the risk of developing cancer, (3) between PTGS genotype with non-NSAID users and the risk of developing cancer, and (4) between NSAID users with minor allele carriers and the risk of developing cancer. All meta-analyses were appraised for inter-study heterogeneity by using x 2 -based Q statistics for statistical significance of heterogeneity. If there was no heterogeneity based on a Q-test P value more than 0.05, a fixed-effect model using the Mantel- Haenszel (M-H) method was used. Otherwise, the random-effects model using the DerSimonian and Laird method was employed. Sensitivity analyses were performed to assess the stability of the results by sequential omission of individual studies. To evaluate the possible publication bias, Egger’s test (linear regression method) and Begg’s test (rank correlation method) were used, and P values
found in GC with high microsatellite instability . The asso- ciation of some SNPs in TCF7L2 gene with various cancer types was shown in recent studies. Of these SNPs, rs7903146 (C>T) polymorphism was reported to be associated with colorectal and lung cancer  prostate cancerand increased breast can- cer risk . Neverthless, Connor et al  determined three polimorphisms rs3750805, rs7900150 and rs1225404 as well as rs7903146 in TCF7L2 to be associated with breast cancer. Rs12255372 (G>T) was shown to be associated with familial breast cancerrisk  while it was shown to increase prostate cancer aggressiveness in another study . Results of a meta- analysis indicated that there was a signiicant association be- tween TCF7L2 rs7903146 (C>T) polymorphism and the risk of breast, prostate and colon cancer rather than colorectal, lung and ovarian cancer . Although numer- ous studies have shown diferent genes and variants as genetic risk factors for gastric cancer, revealing the exact molecular mech- anism of GC is still a challenge. The strong candidate TCF7L2 gene, as a transcription factor, may enhance the canceration of gastric epithelial cells by changing the ex- pressions of a variety of genes involved in cell cycle such as c-myc oncogenes. In our country, although it is the second most common type of cancer subsequently breast cancer in women and lung cancer in men , there is no study on the genetic basis of GC. Up to now, the associations betweenpolymorphisms in various genes and GC have been investigated in several studies worldwide, but the associationbetween TC- F7L2 genepolymorphismsand the GC risk was not investigated in any study to the best of our knowledge. We investigated the risk associated with rs12255372(G>T) and rs7903146(C>T) SNPs in TCF7L2 gene for the irst time in a Turkish population with GC.
After an initial search, a total of 151 published articles relevant to the topic were identified from databases (PubMed, Embase, CBM and CNKI). With additional filters, 120 of these articles were excluded (26 for duplication of titles, 10 for not being case-control studies, five for an association with cancer treatment, 72 for irrelevance to genepolymorphismsandcancer, six reviews and one case-control study for overlapping data). After this step, 31 qualified and original papers fit the inclusion criteria. After a manual search of the bibliography lists from retrieved articles, another two articles were included (Figure 1). Afterwards, six case-control studies were excluded because the number of genotypes in the control group statistically deviated from HWE. Overall, 27 total case-control studies on the associationbetween the STK15 F31I polymorphism andcancerrisk were recruited in this meta- analysis. Among the 27 case-control studies, ten investigated breast cancer [8,9,14-21], four investigated colorectal cancer [10,22-24], and three investigated esophageal cancer [11,25,26]. The other studies investigated gastric cancer, lung cancer, renal cell carcinoma, bladder cancer, glioblastoma, hepatocellular carcinoma, and ovarian cancer [27-36]. As for subjects in these studies, 11 were Asian [9,11,19-21,23,25-29] and 16 were Caucasian [8,10,14-18,22,24,30-36]. Characteristics of populations andcancer types in each individual study recruited in the meta-analysis are listed in Table 1. The distribution of the STK15 F31I polymorphism and allele among patients and controls is listed in Table 2. Results of the meta-analysis from different comparative genetic models are summarized in Table 3, Table 4, and Table 5.
In this meta-analysis, we find that GG genotype of mir-146a may be a protective factor for OS, especially in Asian population. Although the statistically significant association with recurrence and DFS was detected in our study, we should notice that there are only two articles included. Nonetheless, the results imply the role of mir-146a in cancer prognosis and we should lucubrate in the future. For mir-196a2, we find an interesting matter. The C allele is a risk factor for overall survival, whereas it is a protective factor for RFS. This may result from the different types of cancers, various follow-up time period or the differences in baseline characteristics. A notable thing is that the associationbetween mir- 196a2 polymorphism and RFS is not consistent with the report in Chae ’s article. In Chae’s article , a P-value larger than 0.05 is reported for the relationship between them. The article  is not included in this meta for it doesn’t provide HR and 95%CI. This meta-analysis implies that the C allele of mir-149
Prostate cancer (PCa) remains as one of the most common cause of cancer related death among men in the US. The widely used prostate specific antigen (PSA) screening is limited by low specificity. The diagnostic value of other biomarkers such as RAS association domain family protein 1 A (RASSF1A) promoter methylation in prostate cancerand the relationship between RASSF1A methylation and pathological features or tumor stage remains to be established. Therefore, a meta-analysis of published studies was performed to understand the associationbetween RASSF1A methylation and prostate cancer. In total, 16 studies involving 1431 cases and 565 controls were pooled with a random effect model in this investigation. The odds ratio (OR) of RASSF1A methylation in PCa case, compared to controls, was 14.73 with 95% CI = 7.58–28.61. Stratified analyses consistently showed a similar risk across different sample types and, methylation detection methods. In addition, RASSF1A methylation was associated with high Gleason score OR=2.35, 95% CI: 1.56–3.53. Furthermore, the pooled specificity for all included studies was 0.87 (95% CI: 0.72–0.94), and the pooled sensitivity was 0.76 (95% CI: 0.55–0.89). The specificity in each subgroup stratified by sample type remained above 0.84 and the sensitivity also remained above 0.60. These results suggested that RASSF1A promoter methylation would be a potential biomarker in PCa diagnosis and therapy.
In previous studies, for the associationbetween the MTHFR C677T and A1298C polymorphismsand bladder cancerrisk, it has been observed that the variant genotype MTHFR 677TT was associated with an increased risk of bladder cancer, com- pared with the wild-type homozygote 677CC. Folate deiciency leads to decreased DNA methylation and such insuiciency may result in carcinogenesis by inducing genomic instability or acti- vation of oncogenes . In a meta-analysis, 13 diferent articles were identiied to evaluate the associationbetween C677T or A1298C polymorphisms in the MTHFR geneand the risk for bladder cancer. According to this meta-analysis, there was no signiicant associationbetween the C677T polymorphism and the susceptibility to bladder cancerrisk in the overall analysis, but signiicant relationships were detected in the mixed and Asian populations rather than in Europeans and Africans. This is important, because the allele and genotype distribution of MTHFR C677T locus is diferent in diferent races . Safarine- jad et al  found that the 1298C allele (CA+CC, heterozygotes and homozygotes) was signiicantly associated with increased risk of bladder cancer in Asians. Similarly, individuals who car- ried the 1298 CC genotype (homozygote) had a higher risk for bladder cancer in Asians. Moreover, this increased association was also found in Africans. However, the CC genotype (homozy- gosity) played a protective role for bladder cancer in Europeans . In a study, associationbetween MTHFR C677T and gas- tric cancer, leucemia and colorectal cancer were also among the most noteworthy associations. Because of its role in a key pathway, the MTHFR C677T variant may have a true impact on cancerrisk . In a study by Ozarda et al , frequencies of C and T alleles and also frequencies of TT and CC genotypes were investigated in 402 healthy individuals. The frequency of MTHFR T677T genotype was found as 7.7% and the frequency of MTHFR C677T genotype was found as 40%, in males. In fe- males, these rates were as 9.1% and 42.2%, respectively . MTHFR genes play a central role in folate metabolism, and studies have revealed that the cancerrisk associated with MTHFR polymorphisms may be modulated by folate intake. The decreased expression of MTHFR by hypermethylation due to the C677 polymorphism may cause an increased risk of DNA hypomethylation of oncogenes, which may not be corrected by other DNA repair enzymes, resulting in a higher susceptibility to bladder cancer in carriers of the 677TT genotype .
To test the distribution of Hardy-Winberg equilibrium (HWE) in controls, chi-square test for goodness of fit was conducted and a p,0.05 indicated disequilibrium of HWE. We assessed the association strength of the PIN1 2667T.C and 2842G.C polymorphisms with cancerrisk by OR and 95% CIs. The 95% CIs was used for statistical significance test and a 95% CI without 1 indicating a significantly increased or decreased cancerrisk. We calculated pooled ORs for homozygote comparison (CC vs. TT or GG), heterozygote comparison (TC vs. TT and GC vs. GG), dominant model (TC+CC vs. TT or GC+CC vs. GG) and recessive (CC vs. GC+GG or TC+TT) model, assuming the dominant and recessive effect of the variant C allele, respectively. Figure 1. Flow Diagram. *Data from Lu  were treated as 2 studies, and data from Naidu  were treated as 3 studies.