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Article type: Research Article
Authors: Li, Yu-Fena | Yang, Pei-Zhena | Li, Hua-Fengb; *
Affiliations: [a] Department of ENT, Linyi People's Hospital, Linyi, Shandong, China | [b] Linyi Women and Children's Hospital, Genetic Experiment Center, Linyi, Shandong, China
Correspondence: [*] Corresponding author: Hua-Feng Li, Linyi Women and Children's Hospital, Genetic Experiment Center, Qinghe Nan Road No. 1, Luozhuang District, Linyi 276003, Shandong, China. Tel./Fax: +86 0539 3216138; E-mail:Lihuafeng0902@yeah.net
Abstract: Emerging evidence showed that functional polymorphisms in the IL-10 gene may have effects on individuals' susceptibility to nasopharyngeal, oral and esophageal cancers, yet individually published findings are inconsistent. We therefore designed the meta-analysis to investigate the correlations of IL-10 genetic polymorphisms with susceptibility to nasopharyngeal, oral and esophageal cancers. The EMBASE, MEDLINE, CINAHL, Web of Science and the Chinese Biomedical Database (CBM) databases were searched with no language restrictions. We use Comprehensive Meta-analysis 2.0 software to carry out statistical analysis. Ten case-control studies with a number of 1,883 patients and 2,857 healthy subjects were enrolled. Our results revealed that IL-10 rs1800872 T>G and rs1800896 A>G polymorphisms has a significantly association with the increased risk of esophageal cancer under the allele and dominant models; rs1800871 T>G, rs1800872 T>G and rs1800896 A>G under allele and dominant models could increase the risk of nasopharyngeal cancer; rs1800871T>G, rs1800872T>G and rs1800896 A>G SNPs under allele model were closely related to the susceptibility to oral cancer. Our findings support the point that IL-10 genetic polymorphisms may play essential role in identifying esophageal cancer, nasopharyngeal cancer and oral cancer at early stage.
Keywords: IL-10, functional polymorphism, nasopharyngeal cancer, esophageal cancer, oral cancer, allele model, dominant model, subgroup analysis
DOI: 10.3233/CBM-160606
Journal: Cancer Biomarkers, vol. 16, no. 4, pp. 641-651, 2016
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