The association between a single-nucleotide polymorphism (SNP) -174G > C (rs1800795) located in the IL-6 gene promoter and breast cancer risk is still controversial and ambiguous. We performed in this study a more precise estimation of the relationship by meta-analyzing the currently available evidence from literature. A total of 11 publications containing 12 studies including 10,137 cases and 15,566 controls were identified. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association in the codominant model, dominant model, and recessive model. When all the studies were pooled into the meta-analysis, there was no evidence showing a significant association between -174G > C and breast cancer risk (for CC vs. GG: OR = 1.024, 95% CI: 0.935-1.121; for GC vs. GG: OR = 1.008, 95% CI: 0.946-1.073; for dominant model: OR = 0.980, 95% CI: 0.857-1.121; and for recessive model: OR = 1.027, 95% CI: 0.944-1.117). In the subgroup analyses by ethnicity, no significant associations were observed in any genetic models. In summary, the present meta-analysis suggests that the functional polymorphism -174G > C within the IL-6 gene promoter is not associated with breast cancer risk. Identifying a unique SNP as a breast cancer risk predictor remains a very challenging task.

The results from the published studies on the association between hypoxia-inducible factor -1alpha (HIF-1alpha) polymorphisms and cancer risk are conflicting. In this meta-analysis, we aimed to investigate the association between HIF-1alpha 1772 C/T and 1790 G/A polymorphisms and cancer.

Cytochrome P450s are enzymes which catalyze Phase-I metabolism reactions; cytochrome P450 1A1 (CYP1A1) is a member of the CYP1 family and participates in the metabolism of a vast number of xenobiotics, as well as endogenous substrates. Four single nucleotide polymorphisms in CYP1A1 have been studied concerning their potential implication in terms of breast cancer risk: T3801C, T3205C, A2455G (Ile462Val), and C2453A (Thr461Asp); controversy exists regarding their role. This meta-analysis aims to examine whether the four aforementioned polymorphisms are associated with breast cancer risk. Separate analyses were performed on Caucasian, Chinese, and African populations, as well as on premenopausal and postmenopausal women. Eligible articles were identified by a search of MEDLINE bibliographical database for the period up to October 2009. Concerning T3801C, 32 studies were eligible (11,909 cases and 16,179 controls), 29 studies (12,257 cases and 20,379 controls) were eligible for A2455G, 11 studies (7,189 cases and 8,491 controls) were eligible for C2453A, and eight studies were eligible for T3205C (1,378 cases and 1,642 controls). Pooled odds ratios (OR) were appropriately derived from fixed- or random-effect models. Sensitivity analysis excluding studies whose genotype frequencies in controls significantly deviated from Hardy-Weinberg equilibrium was performed. Homozygous subjects of Caucasian origin carrying the A2455G G allele exhibited elevated breast cancer risk (pooled OR = 2.185, 95% CI 1.253-3.808, fixed effects), whereas heterozygous carriers did not (pooled OR = 1.062, 95% CI 0.852-1.323, random effects). A2455G polymorphism status was not associated with breast cancer risk in Chinese subjects or specifically in premenopausal/postmenopausal women. T3801C, T3205C, and C2453A status were not associated with breast cancer risk at any analysis. In conclusion, this meta-analysis points to the A2455G G allele as a risk factor for breast cancer among Caucasian subjects. On the contrary, T3801C, T3205C, and C2453A status does not seem capable of modifying breast cancer risk.

Tumor necrosis factor alpha (TNFalpha) is a pleiotropic cytokine which can regulate a wide variety of cellular responses. Low concentrations of TNFalpha seem to increase tumor growth and progression. The -308 G/A polymorphism in TNFalpha has been implicated in breast cancer risk but the published data remain inconclusive. In order to derive a more precise estimation of the relationship, a meta-analysis was performed by searching PubMed, Web of Science, ScienceDirect, EBSCO, CNKI, and Chinese Biomedicine Database. 11 studies including 10,184 cases and 12,911 controls were collected for TNFalpha -308 G/A polymorphism. Crude ORs with 95% CIs were used to assess the strength of association between the TNFalpha -308 G/A polymorphism and breast cancer risk. The pooled ORs were performed for codominant model (GG versus AA; GA versus AA), dominant model (GG + GA versus AA), recessive model (GG versus GA + AA), and G allele versus A allele, respectively. Overall, significantly elevated breast cancer risk was found for recessive model (OR = 1.10, 95% CI = 1.04-1.17) and for G allele versus A allele (OR = 1.08, 95% CI = 1.02-1.14). In the subgroup analysis by ethnicity, significantly increased risks were also found among Caucasians for recessive model and for G allele versus A allele (for recessive model: OR = 1.10, 95% CI = 1.04-1.17; for G allele versus A allele: OR = 1.09, 95% CI = 1.03-1.14). However, no significant associations were found among Asians for all genetic models. In conclusion, this meta-analysis suggests that the TNFalpha -308 G allele is a risk factor for developing breast cancer, especially for Caucasians.

EGF promoter polymorphisms are observed to modulate EGF levels and thought to have effect on susceptibility to various carcinomas but the results are inconsistent. In this meta-analysis, we assessed published studies of the association between three EGF polymorphisms and cancer risk from 21 studies with 14,609 subjects for EGF G61A, from two studies with 2,535 subjects for G-1380A and A-1744G, respectively. For EGF G61A, the contrast of homozygote (OR=0.80, 95% CI=0.65-0.98), allele (OR=0.90, 95% CI=0.81-0.99) and dominant model (OR=0.86, 95% CI=0.74-0.99) produced significant association among 21 studies with relatively large heterogeneity (Pheterogeneity<0.001). Through the stratified analysis, heterogeneity decreased significantly. In the stratified analysis by racial descent, the significant risks were found among Asians for homozygote contrast (OR=0.83, 95% CI=0.69-0.99, Pheterogeneity=0.506) and Americans for the contrast of homozygote (OR=0.50, 95% CI=0.30-0.84, Pheterogeneity=0.051), allele (OR=0.70, 95% CI=0.51-0.96, Pheterogeneity=0.008) and dominant model (OR=0.57, 95% CI=0.42-0.77, Pheterogeneity=0.28). No significant associations were found in all Caucasians genetic models. In the subgroup analyses by cancer types, for gastric cancer and esophageal cancer significant associations were found in all genetic models without heterogeneity. Significant risk was also found in the contrast of homozygote (OR=0.41, 95% CI=0.20-0.81, Pheterogeneity=0.184) and recessive model (OR=0.53, 95% CI=0.33-0.85, Pheterogeneity=0.384) for hepatoma and recessive model (OR=0.72, 95% CI=0.53-0.99, Pheterogeneity=0.474) for glioma. For EGF G-1380A and A-1744G, no significant associations were found in all genetic models. This meta-analysis suggests that the EGF G61A polymorphism most likely contributes to decreased susceptibility to cancers among Asians and Americans, and A allele may be a protective factor for gastric cancer, esophageal cancer, hepatoma and glioma. Both EGF G-1380A and A-1744G is marginally associated with cancer susceptibility.

The association between single-nucleotide polymorphisms (SNPs) in the COX-2 gene and breast cancer risk is still ambiguous. We here try to derive a more precise estimation of the relationship by performing a meta-analysis based on currently available evidence from literature. More than 15 SNPs have been studied, and the most studied genetic variants were rs5275, rs5277, and rs20417. Crude odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of association between each polymorphism and breast cancer risk under the codominant model, dominant model, and recessive model, respectively (nine studies with 6,968 cases and 9,126 controls for rs5275; three studies with 2,901 cases and 3,463 controls for rs20417; two studies with 5,551 cases and 6,208 controls for rs5277). No overall significant associations were observed in single-locus analysis between the three polymorphisms of COX-2 and breast cancer risk, though a borderline significant increased risk of breast cancer was detected with rs5277 in a recessive model (OR: 1.217, 95% CI: 0.958-1.547, P = 0.107). The results were not changed when studies were stratified by ethnicity. In conclusion, the present meta-analysis suggests that none of the most studied three SNPs (rs5275, rs20417, and rs5277) in the COX-2 gene is a conspicuous low-penetrant risk factor for developing breast cancer. There is a need for further large studies into the role of these polymorphisms (especially rs5277) and other potentially functional polymorphisms/haplotypes in the COX-2 gene as breast cancer risk modifiers.

Epidemiological studies have evaluated the association between CYP17 MspA1 polymorphism and breast cancer risk. However, the results remain conflicting rather than conclusive. To derive a more precise estimation of the relationship, we performed this meta-analysis. Systematic searches of the PubMed and Medline databases were performed. A total of 35 studies including 22,090 cases and 28,498 controls were identified. Genotype distributions of CYP17 in the controls of all studies were in agreement with Hardy-Weinberg equilibrium (HWE) except for three studies. When all 35 studies were pooled into the meta-analysis, there was no evidence for significant association between CYP17 MspA1 polymorphism and breast cancer risk (for A1/A2 vs. A1/A1: OR = 1.00, 95% CI = 0.96-1.04; for A2/A2 vs. A1/A1: OR = 1.03, 95% CI = 0.97-1.08; for dominant model: OR = 1.01, 95% CI = 0.97-1.05; for recessive model: OR = 1.03, 95% CI = 0.98-1.08). In the subgroup analyses by ethnicity, menopausal status and source of controls, no significant associations were found in all genetic models. When sensitivity analyses were performed by excluding HWE-violating studies, all the results were not materially altered. In summary, the meta-analysis strongly suggests that CYP17 MspA1 polymorphism is not associated with increased breast cancer risk.

Breast cancer is the most common cancer in women. To date, many publications have evaluated the association between Cytochrome P450 1B1 (CYP1B1) Val432Leu polymorphism and breast cancer risk. However, the results remain inconclusive. In order to derive a more precise estimation of the association, a meta-analysis was performed in this study. By searching Medline, Pubmed, and ISI Web of Knowledge databases, 26 studies including 19,028 cases and 21,275 controls were collected for CYP1B1 Val432Leu polymorphism. Crude ORs with 95% CIs were used to assess the strength of association between CYP1B1 Val432Leu polymorphism and breast cancer risk. The pooled ORs were performed for codominant model, dominant model, and recessive model, respectively. Overall, no significant associations between CYP1B1 Val432Leu polymorphism and breast cancer susceptibility were found for Val/Val versus Leu/Leu (OR = 0.98; 95% CI: 0.90-1.06), Val/Leu versus Leu/Leu (OR = 1.01; 95% CI: 0.93-1.09), Val/Val + Val/Leu versus Leu/Leu (OR = 1.00; 95% CI: 0.93-1.08) and Val/Val versus Val/Leu + Leu/Leu (OR = 0.96; 95% CI: 0.91-1.01). In the stratified analysis by ethnicity, menopausal status and sources of controls, significant associations were still not observed in all genetic models. In conclusion, this meta-analysis provides strong evidence that CYP1B1 Val432Leu polymorphism is not associated with breast cancer risk.

Previous studies investigating the association between X-ray repair cross-complementation group 1 (XRCC1) polymorphisms and colorectal cancer (CRC) risk has provided inconsistent results. The aim of our study was to clarify the effects of XRCC1variants on CRC risk.

Genetic variations in metabolic genes are thought to modify the metabolic process of carcinogens and are suggested to be related to cancer risk. However, epidemiological results are not always consistent. In this meta-analysis, we assessed reported studies of associations between polymorphisms of CYP2E1 RsaI/PstI and DraI, and the risk of lung cancer. We found decreased lung cancer risk among subjects carrying CYP2E1 RsaI/PstI c1/c2 and c1/c2+c2/c2 genotype [odds ratio (OR)=0.80, 95% confidence interval (CI): 0.72-0.89 and OR=0.82, 95% CI: 0.72-0.93, respectively], using 4436 cases and 6385 controls from 26 studies. We also observed a decreased lung cancer risk among subjects carrying c1/c2 and c1/c2+c2/c2 genotypes in the Asian population and on the basis of population control in stratified analysis. We found a protective effect of the CYP2E1 DraI CC and CD+CC polymorphisms for lung cancer (OR=0.58, 95% CI: 0.41-0.81 and OR=0.84, 95% CI: 0.73-0.96, respectively). The meta-analysis suggests that CYP2E1 RsaI/PstI and DraI polymorphisms may affect the susceptibility of lung cancer, and a study with a larger sample size is needed to further evaluate gene-environment interaction on CYP2E1 polymorphisms and lung cancer risk.

The aim of this systematic review and meta-analysis was to characterize common EGFR molecular aberrations as potential predictive biomarkers for response to monotherapy with tyrosine kinase inhibitors (TKI) in non-small cell lung cancer (NSCLC).

Epidemiologic studies have evaluated the association between KRAS mutations and resistance to the treatment of epidermal growth factor receptor (EGFR) tyrosine-kinase inhibitors (TKIs) in patients with non-small cell lung cancer (NSCLC). However, results were inconclusive. To derive a more precise estimation of the relationship, we performed this meta-analysis. Systematic computerized searches of the PubMed and Medline databases (up to Jun 30, 2009) were performed. A total of 22 studies were included in the final meta-analysis, consisting of 1470 NSCLC patients, of whom 231 had KRAS mutations (16%). Current or former smokers had a higher frequency of KRAS mutations than never smokers (25% versus 6%; OR=4.36; P<0.01). Mutations were more common among adenocarcinoma than other histologies (26% versus 16%; OR=1.98; P<0.01). The objective response rate (ORR) of NSCLC patients with mutant KRAS was 3% (6/210), whereas the ORR of NSCLC patients with wild-type KRAS was 26% (287/1125). The overall pooled RR for ORR was 0.29 (95% CI: 0.18-0.47; P<0.01). Subgroup analyses were conducted on the basis of ethnicity and study treatment, all the results were not materially altered and did not draw different conclusions, indicating that our results were robust. In summary, this meta-analysis suggests that KRAS mutations may represent negative predictive biomarkers for tumor response in NSCLC patients treated with EGFR-TKIs. However, due to a mutually exclusive relationship between KRAS and EGFR mutation and no difference in survival between KRAS mutant/EGFR wild-type and KRAS wild-type/EGFR wild-type NSCLC, the clinical usefulness of KRAS mutation as a selection marker for EGFR-TKIs sensitivity in NSCLC is limited.

Breast cancer is one of the most common malignant tumors worldwide. To date, many articles have evaluated the association between Cytochrome P450c17 (CYP17) T-34C polymorphism and breast cancer risk. However, the results remain inconclusive. In order to derive a more precise estimation of the association, a meta-analysis was performed in this study. By searching Medline, ISI Web of Knowledge, Cochrane, ScienceDirect, EBSCO, CNKI, and SinoMed databases, 43 studies including 26,008 cases and 32,806 controls were collected for CYP17 T-34C polymorphism. Crude ORs with 95% CIs were used to assess the strength of association between CYP17 T-34C polymorphism and breast cancer risk. The pooled ORs were performed for codominant model, dominant model, and recessive model, respectively. Overall, no significant associations between CYP17 T-34C polymorphism and breast cancer susceptibility were found for TT versus CC (OR = 0.96; 95% CI: 0.89-1.05), TC versus CC (OR = 0.97; 95% CI: 0.89-1.06), TT + TC versus CC (OR = 0.97; 95% CI: 0.89-1.05) and TT versus TC + CC (OR = 0.98; 95% CI: 0.93-1.03). In the stratified analysis by ethnicity, menopausal status, and sources of controls, significant associations were still not detected in all genetic models. In conclusion, this meta-analysis strongly suggests that CYP17 T-34C polymorphism is not associated with breast cancer risk.

Transforming growth factor β (TGF-β) is a cytokine. The TGF-β signaling pathway plays an important role in controlling cell proliferation and differentiation involved in colorectal carcinogenesis. In mammalian cells, TGFB1 is the most abundant subtype of TGF-β. The 509 C/T polymorphism in TGFB1 has been implicated in colorectal cancer risk. However, published data remain conflicting. To derive a more precise estimation of the relationship, a meta-analysis of 994 cases and 2,335 controls from five published case-control studies was performed. Overall, significantly increased colorectal cancer risks were found for CC versus TT (OR=1.62; 95% CI: 1.30-2.02; Pheterogeneity=0.118), TC+CC versus TT (OR=1.30; 95% CI: 1.08-1.58; Pheterogeneity=0.259) and CC versus TC+TT (OR=1.48; 95% CI: 1.26-1.75; Pheterogeneity=0.244). In the subgroup analysis by ethnicity, significantly increased risks were also found among Asians for CC versus TT (OR=1.77; 95% CI: 1.40-2.24; Pheterogeneity=0.519), TC+CC versus TT (OR=1.38; 95% CI: 1.13-1.68; Pheterogeneity=0.679) and CC versus TC+TT (OR=1.58; 95% CI: 1.31-1.89; Pheterogeneity=0.340). However, no significant associations were found among Europeans for all genetic models. This meta-analysis showed that TGFB1 509 C allele is a risk factor for developing colorectal cancer in Asians.

Published data on the association between manganese superoxide dismutase (MnSOD) Val(16)Ala polymorphism and prostate cancer (PCA) risk are inconclusive. To derive a more precise estimate of the association between them, a meta-analysis was performed.

Quantitative analysis of circulating cell free DNA is considered as a possible aid for lung cancer screening. We aimed to comprehensively review the evidence for use of circulating cell free DNA to screen for lung cancer.

The limitation of small sample size of functional genomics experiments has made it necessary to integrate DNA microarray experimental data from different sources. However, experimentation noises and biases of different microarray platforms have made integrated data analysis challenging. In this work, we propose an integrative computational framework to identify candidate biomarker genes from publicly available functional genomics studies.

Transforming growth factor-beta1 (TGFbeta1) plays a significant role in regulating cellular proliferation and apoptosis. The TGFbeta1 T29C polymorphism reportedly affects cancer risk, but pertinent studies offer conflicting results. We therefore performed a meta-analysis based on 40 studies from 32 publications, assessing the strength of the association using odds ratios with 95% confidence intervals. Overall, no evidence has indicated that individuals carrying CC or CT genotypes had significantly increased cancer risks, compared with TT genotype carriers [CC vs. TT: odds ratio (OR)=1.10, 95% confidence interval (95% CI)=1.00-1.21, P=0.06; CT vs. TT: OR=1.07, 95% CI=0.99-1.16, P=0.09). However, stratified analysis by cancer type and ethnicity indicated a significantly increased risk of prostate cancer (CT vs. TT: OR=1.28, 95% CI=1.01-1.61, P=0.04) and cancer in those of Asian descent (CC vs. TT: OR=1.26, 95% CI=1.03-1.53, P=0.02; CT vs. TT: OR=1.20, 95% CI=1.01-1.43, P=0.04). This association was also observed in the dominant model for prostate cancer. Although not all bias could be eliminated, this meta-analysis suggested that TGFbeta1 29C was a low-penetrant risk factor for prostate cancer and cancer in Asians. A larger single study is still required to evaluate any association with other types of cancer or in other populations.

To investigate the effect of c-kit mutation on the prognosis of gastrointestinal stromal tumors.

Studies investigating the association between genetic polymorphism of glutathione S-transferase T1 (GSTT1) and gastric cancer risk have reported conflicting results. Therefore, we conducted this meta-analysis to provide more precise evidence.