Recent genome-wide association studies have identified common variants at multiple loci influencing lung cancer risk. To decipher the genetic basis of the association signals at 3q28, 5p15.33, 6p21.33, 9p21 and 12p13.33, we performed a meta-analysis of data from five genome-wide association studies in populations of European ancestry totalling 12 316 lung cancer cases and 16 831 controls using imputation to recover untyped genotypes. For four of the regions, it was possible to refine the association signal identifying a smaller region of interest likely to harbour the functional variant. Our analysis did not provide evidence that any of the associations at the loci being a consequence of synthetic associations rather than linkage disequilibrium with a common risk variant at these risk loci.

Methylenetetrahydrofolate reductase (MTHFR) acts at an important metabolic point in the regulation of cellular methylation reaction. It assists in the conversion of 5, 10-methylenetetrahydrofolate to 5-methyltetrahydrofolate. The latter aids in remethylation of homocysteine to de novo methionine that is required for DNA synthesis. The objective of this study was to examine the effect of MTHFR 677 C>T polymorphism on the risk of breast cancer in the Indian sub-continent.

Conflicting results on the association between MTHFR polymorphism and head and neck cancer (HNC) risk were reported. We therefore performed a meta-analysis to derive a more precise relationship between MTHFR C677T polymorphism and HNC risk.

Cancer is a leading cause of death worldwide with its low 5-year survival rate. Studies on the accuracy of let-7 family for human cancers have inconsistent conclusions, leading us to conduct this meta-analysis. This meta-analysis comprised of 11 studies from eight articles involving 805 cancer patients and 483 controls. The pooled parameters were as follows: sensitivity, 77 % (95 % confidence interval (CI) 73-81 %); specificity, 80 % (95 % CI 68-88 %); positive likelihood ratio (PLR), 3.8; negative likelihood ratio (NLR), 0.29; and diagnostic odds ratio (DOR) 13.0. In addition, we plotted the SROC and calculated the area under the curve (AUC) of 0.81 (95 % CI 0.78-0.84), which indicated a relatively high descriptive accuracy. In summary, our data suggested that let-7 family might be applied in noninvasive screening tests for human cancers, which needed to be validated in further large-scale studies.

Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) has been used for the first-line treatment of non-small cell lung cancer (NSCLC) and has shown good clinical effects. However, some patients fail to benefit from this treatment. The aim of this study is to analyze whether or not clinical-selected patients (Asian, adenocarcinoma histology, non-smoking) and EGFR mutation-selected patients benefit from EGFR-TKIs or chemotherapy. Our results could be used as basis to guide clinical therapy.

Previous studies have reported the association of glutathione S-transferase M1 (GSTM1) deletion polymorphism with genetic susceptibility of lung cancer in Chinese population. However, the results remained controversial. The aim of this study was to clarify the association of GSTM1 deletion polymorphism with lung cancer risk in Chinese population. Systematic searches were performed through the search engines of Medline/Pubmed, Web of Science, EMBASE, CNKI and Wanfang Medical Online. The pooled effects were calculated by STATA 10.0 software package and Review Manager 5.0.24. Overall, we observed an association of GSTM1 deletion polymorphism with increased lung cancer risk in Chinese population (odds ratio (OR) = 1.46, 95% confidence interval (95%CI): 1.32-1.66 for null genotype vs. present genotype) based on 53 studies including 7,833 cases and 10,353 controls. We also observed an increased risk of GSTM1 null genotype for lung cancer in stratified analyses by source of control, smoking status and histological type. The findings suggest that GSTM1 deletion polymorphism may contribute to lung cancer risk in Chinese population. Further, well-designed studies with larger sample sizes are required to verify the results.

Single nucleotide polymorphisms (SNPs) in pri- or pre-microRNAs (miRNAs) were found to be associated with gastric cancer risk. The aim of this study was to systematically review with update meta-analysis for the association of miRNA SNPs with gastric cancer risk. We systematically reviewed a total of 31 SNPs in the precursor genes of 29 miRNAs associated with overall cancer risk. Meanwhile, 13 case-control studies with a total of 9044 gastric cancer cases and 11,762 controls were included in a meta-analysis of five highly studied pre-miRNA SNPs (miR-146a rs2910164, miR-196a2 rs11614913, miR-499 rs3746444, miR-149 rs2292832 and miR-27a rs895819). Our results show both the homozygous miR-27a rs895819 and the miR-149 rs2292832 heterozygote genotype were associated with a decreased risk of gastric cancer when compared with wild type. In the stratified analysis, in some subgroup, heterozygous miR-146a rs2910164 was associated with a decreased risk of gastric cancer; and the variant genotype of miR-196a-2 rs11614913 was associated with an increased risk. No association was found between miR-499 rs3746444 and gastric cancer risk. In summary, miR-27a rs895819 and miR-149 rs2292832 are of potential forewarning ability for gastric cancer risk.

The X-ray repair cross-complementing group 3 (XRCC3) is a highly suspected candidate gene for cancer susceptibility, and a large amount studies have examined the association of the rs861539 in XRCC3 (Thr241Met) with lung cancer risk in various populations. However, the results remain inconclusive.

MicroRNA-145 (miR-145) plays a crucial role in cancer prognosis.

Vascular endothelial growth factor C (VEGF-C) is involved in the development and progression of tumor angio-/lymphangiogenesis. The purpose of this study is to evaluate whether VEGF-C expression is an indicator of aggressiveness and poor prognosis of esophageal squamous cell carcinoma (ESCC).

Many studies have shown that microRNAs have important roles in the development and progression of various cancers. Recent studies also showed that microRNA-21 expression may be associated with the prognosis of patients with several common cancers. However, there was still lack of evidence for the prognostic role of microRNA-21 expression in brain tumors. We performed a systemic review and meta-analysis of published and unpublished studies to assess the prognostic role of microRNA-21 expression in patients with brain tumors. PubMed, Embase, and Google Scholar databases were searched for eligible studies with data assessing the prognostic role of microRNA-21 expression in brain tumors. Pooled hazard ratios (HRs) of microRNA-21 expression for overall survival and 95% confidence intervals (CI) were calculated. Six studies from five publications were finally included into the meta-analysis. Those six studies included a total of 747 patients with brain tumors and 654 patients with gliomas. For overall survival, the pooled HR of higher microRNA-21 expression in patients with brain tumors was 1.82 (95% CI 1.29-2.58, P = 0.001). In patients with gliomas, the HR for overall survival of higher microRNA-21 expression was 1.83 (95% CI 1.09-3.09, P = 0.023). Sensitivity analysis by omitting one study by turns also showed there was no obvious influence of individual study on the pooled HRs. There was no obvious risk of publication bias in the meta-analysis. The present meta-analysis suggests that microRNA-21 is associated with the prognosis of patients with brain tumors, and high expression of microRNA-21 can predict poor prognosis in patients with brain tumors.

In this study, we performed an updated meta-analysis by summarizing all available relevant association studies to evaluate whether the murine double minute-2 (MDM2) T309G polymorphism is associated with risk of leukemia and to determine its prognostic effect.

MicroRNAs (abbreviated miRNAs) have been demonstrated to be involved in tumorigenesis and cancer development and proposed as promising biomarkers in cancer diagnosis. Numerous studies have observed the aberrant expression of miRNAs in esophageal cancer. However, there are some discrepant results. Thus, we conducted this meta-analysis to identify the overall accuracy of miRNAs in the diagnosis of esophageal cancer. A comprehensive literature search was conducted in PubMed and other databases using combinations of key words. The summary receiver operator characteristic curves were plotted to assess the overall diagnostic performance of miRNAs. Chi-squared and I(2) tests were used to assess the heterogeneity between studies. Additionally, we conducted subgroup and sensitivity analyses to analyze the potential sources of heterogeneity. In total, 33 studies from 12 articles were available in this meta-analysis. The pooled sensitivity, specificity, positive and negative likelihood ratio (PLR, NLR) diagnostic odds ratio, and area under the curve were 0.80, 0.80, 4.0, 0.25, 16, and 0.87, respectively. Subgroup analyses based on the sample types (saliva-, serum- and plasma-based) showed no differences in the diagnostic accuracy of each subgroup. An independent meta-analysis of eight articles was conducted to evaluate the diagnostic accuracy of miRNAs in patients with esophageal squamous cell carcinoma, with a pooled sensitivity of 0.77, specificity of 0.83, PLR of 4.4, NLR of 0.27, diagnostic odds ratio of 16, and area under the curve of 0.87. In conclusion, this meta-analysis demonstrates the feasibility of using miRNAs as non-invasive biomarkers to discriminate esophageal cancer from healthy controls. However, further high-quality studies on more clearly defined esophageal cancer patient are needed to confirm our conclusion.

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain.

Mutation and polymorphism of Kras oncogene are considered as candidate risk factor and drug response predictor for cancer. However, the conclusions of accumulating reports related to the relationship of rs712 of Kras gene and risk of cancer remain nuclear.

Emerging published reports on the association between estrogen receptor 1 (ESR1) genetic variation and cancer susceptibility are inconsistent. This review and meta- analysis was performed to achieve a more precise evaluation of this relationship.

Glutathione S-transferases (GSTs) are involved in the detoxification of carcinogens, and may be linked to carcinogenesis. As a vital component of GSTs, GSTA1 plays an important role in carcinogenesis. However, the studies about the effect of GSTA1 polymorphisms on cancer risk are limited and the conclusions are contradictory. This meta-analysis aimed to evaluate the association between GSTA1 polymorphisms (-567T>G, (69C>T and -52G>A) and cancer risk.

The purpose of this systematic meta-analysis was to evaluate the association between leptin (LEP) and leptin receptor (LEPR) gene polymorphisms and non-Hodgkin lymphoma (NHL) risk.

The purpose of this study was to examine whether vitamin D receptor (lVDR) polymorphisms are associated with susceptibility to melanoma.

The objective of this study was to test the hypothesis that p53 Arg72Pro polymorphism may contribute to an increased risk of cutaneous melanoma (CM).