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CCDC26 Gene Polymorphism and Glioblastoma Risk in the Han Chinese Population

  • Wei, Xiao-Bing (Department of Neurosurgery, Hanzhong Central Hospital) ;
  • Jin, Tian-Bo (Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science) ;
  • Li, Gang (Department of Neurosurgery, Tangdu Hospital, the Fourth Military Medical University) ;
  • Geng, Ting-Ting (National Engineering Research Center for Miniaturized Detection Systems, School of Life Sciences, Northwest University) ;
  • Zhang, Jia-Yi (National Engineering Research Center for Miniaturized Detection Systems, School of Life Sciences, Northwest University) ;
  • Chen, Cui-Ping (National Engineering Research Center for Miniaturized Detection Systems, School of Life Sciences, Northwest University) ;
  • Gao, Guo-Dong (Department of Neurosurgery, Tangdu Hospital, the Fourth Military Medical University) ;
  • Chen, Chao (National Engineering Research Center for Miniaturized Detection Systems, School of Life Sciences, Northwest University) ;
  • Gong, Yong-Kuan (Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science)
  • Published : 2014.04.30

Abstract

Background: Glioblastoma (GBM) is an immunosuppressive tumor whose median survival time is only 12-15 months, and patients with GBM have a uniformly poor prognosis. It is known that heredity contributes to formation of glioma, but there are few genetic studies concerning GBM. Materials and Methods: We genotyped six tagging SNPs (tSNP) in Han Chinese GBM and control patients. We used Microsoft Excel and SPSS 16.0 statistical package for statistical analysis and SNP Stats to test for associations between certain tSNPs and risk of GBM in five different models. ORs and 95%CIs were calculated for unconditional logistic-regression analysis with adjustment for age and gender. The SHEsis software platform was applied for analysis of linkage disequilibrium, haplotype construction, and genetic associations at polymorphism loci. Results: We found rs891835 in CCDC26 to be associated with GBM susceptibility at a level of p=0.009. The following genotypes of rs891835 were found to be associated with GBM risk in four different models of gene action: i) genotype GT (OR=2.26; 95%CI, 1.29-3.97; p=0.019) or GG (OR=1.33; 95%CI, 0.23-7.81; p=0.019) in the codominant model; ii) genotypes GT and GG (OR=2.18; 95%CI, 1.26-3.78; p=0.0061) in the dominant model; iii) GT (OR=2.24; 95%CI, 1.28-3.92; p=0.0053) in the overdominant model; iv) the allele G of rs891835 (OR=1.85; 95%CI, 1.14-3.00; p=0.015) in the additive model. In addition, "CG" and "CGGAG" were found by haplotype analysis to be associated with increased GBM risk. In contrast, genotype GG of CCDC26 rs6470745 was associated with decreased GBM risk (OR=0.34; 95%CI, 0.12-1.01; p=0.029) in the recessive model. Conclusions: Our results, combined with those from previous studies, suggest a potential genetic contribution of CCDC26 to GBM progression among Han Chinese.

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  2. Genetic Polymorphisms of CCDC26 rs891835, rs6470745, and rs55705857 in Glioma Risk: A Systematic Review and Meta-analysis pp.1573-4927, 2019, https://doi.org/10.1007/s10528-019-09911-7