Glioblastoma (GBM) is the highest-grade glioma in astrocytoma. Patients often have poor prognosis due to therapeutic resistance and tumor recurrence. Identification of the genetic factors of GBM could be important contribution to early prevention of this disease. We genotyped 17 tag single-nucleotide polymorphisms (tSNPs) from nine genes in this study, including 72 cases and 302 controls. SNP genotyping was conducted using Sequenom MassARRAY RS1000. Statistical analysis of the association between tSNPs and GBM was performed using the χ (2) test and SNPStats software. The rs3829382 in FLT3 was associated with increased odds of developing GBM using the χ (2) test. When we analyzed tSNPs under different inheritance models, we found rs9642393 in EGFR increased odds of developing GBM in the dominant model. After stratification by gender, we found that rs12645561 in NEIL3 and rs2291427 in ALOX5 were associated with developing GBM. Polymorphisms within FLT3, EGFR, NEIL3, and ALOX5 may contribute to the occurrence of GBM in the Han Chinese population. However, the functional significance of these polymorphisms needs further investigation.

MicroRNAs (miRNAs) are key regulators of gene expression; however, the extent to which single nucleotide polymorphisms (SNPs) interfere with miRNA gene regulation and affect cervical cancer (CC) susceptibility remains largely unknown. Here, we systematically analyzed miRNA-related SNPs and their association with CC risk, and performed a case-control study of miR-17-5p SNPs and CC risk in a Chinese population. Sixteen SNPs were genotyped in 247 CC cases and 285 controls. Three were associated with CC risk (p < 0.05): the minor allele (A) of rs217727 in H19 increased risk (OR = 1.53, p = 0.002), while the minor alleles (T) of rs9931702 and (T) of rs9302648 in AKTIP decreased CC risk (p = 0.018, p = 0.014). Analysis of the SNPs after stratification based on CC clinical stage and subtype revealed that rs1048512, rs6659346, rs217727, rs9931702, and rs9302648 were associated with CC risk in clinical stages I-II; rs2862833, rs2732044, rs1030389, and rs1045935 were associated with CC risk in clinical stages III-IV; and rs217727, rs9931702, and rs9302648 were associated with CC risk in squamous carcinomas. These data could serve as a useful resource for understanding the miR-17 function, identification of miRNAs associated with CC, and development of better CC screening strategies.

A genome-wide association study of gout in European populations identified 12 genetic variants strongly associated with risk of gout, but it is unknown whether these variants are also associated with gout risk in Chinese populations. A total of 145 patients with gout and 310 healthy control patients were recruited for a case-control association study. Twelve SNPs of CLNK and ZNF518B gene were genotyped, and association analysis was performed. Odds ratios (ORs) with 95 % confidence intervals (CIs) were used to assess the association. Overall, we found four risk alleles for gout in patients: the allele "G" of rs2041215 and rs1686947 in the CLNK gene by dominant model (OR 1.66; 95 % CI 1.04-2.63; p = 0.031) (OR 2.19; 95 % CI 1.38-3.46; p = 0.001) and additive model (OR 1.39; 95 % CI 1.00-1.93; p = 0.049) (OR 1.67; 95 % CI 1.19-2.32; p = 0.003), respectively, and the allele "A" of rs10938799 and rs10016022 in ZNF518B gene by recessive model (OR 4.66; 95 % CI 1.44-15.09; p = 0.008) (OR 4.54; 95 % CI 1.23-16.76; p = 0.020). Further haplotype analysis showed that the TCATTCTGA haplotype of CLNK was more frequent among patients with gout (adjusted OR 0.48; 95 % CI 0.24-0.95; p = 0.036). Additionally, polymorphisms of rs2041215, rs10938799, and rs17467273 were also correlated with clinical pathological parameters. This study provides evidence for gout susceptibility genes, CLNK and ZNF518B, in a Chinese population, which may have potential as diagnostic and prognostic marker for gout patients.

The Epidermal Growth Factor Receptor gene has been reported to be involved in the progression of gliomas which is one of the deadliest primary brain tumors in humans. To determine potential association between EGFR and glioma risk, we performed a case-control study with 394 glioma patients and 298 cancer-free controls in which captured a total of 8 tag single nucleotide polymorphisms of EGFR gene from Xi’an, China. SPSS 19.0 statistical packages, χ2 test, genetic model analysis and SHEsis software platform were analyzed s the variants in EGFR gene associations with glioma risk. For five different inheritance models analyzed, the following genotypes were associated with increased glioma risk. In the codominant model, genotype CC (rs730437, OR = 1.93, p = 0.024; rs1468727, OR = 2.02, p = 0.007); In the dominant model, genotype CA and CC (rs730437, OR = 1.45, p = 0.026), genotype GA and AA (rs845552, OR = 1.40, p = 0.044); In the recessive model, genotype CC (rs730437, OR = 1.64, p = 0.026; rs1468727, OR = 1.87, p = 0.002); In the additive model, genotype CC (rs730437, OR = 1.32, p = 0.006; rs1468727, OR = 1.39, p = 0.005), genotype GG (rs11506105, OR = 1.32, p = 0.02) and genotype AA (rs845552, OR = 1.27, p = 0.04). Our study indicated that 8 mutants located in EGFR gene were risk-conferring factors, larger and different populations with EGFR polymorphisms are required to verify these associations.

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