Earch Program, NIDA, DHHS (Dr. Uhl). We are grateful for access to brain samples from the University of Maryland Brain Tissue Bank.Author ContributionsConceived and designed the experiments: GRU JD. Performed the experiments: JD DW SS KJ BK JT. Analyzed the data: GRU DW JD. Contributed reagents/materials/analysis tools: JT. Wrote the paper: GRU JD DW.
EBioMedicine 13 (2016) 125?Contents lists available at ScienceDirectEBioMedicinejournal homepage: www.ebiomedicine.comResearch PaperDNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysisHongjia Li a,1, Wen Li a,1, Shanshan Liu a, Shaoqi Zong a, Weibing Wang b, Jianlin Ren a, Qi Li c, Fenggang Hou a,, Qi Shi a,a b cOncology Department of Shanghai Municipal PX-478 price Hospital of Traditional Chinese Medicine affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China Fudan University School of Public Health, Shanghai 200032, China Department of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, Chinaa r t i c l ei n f oa b s t r a c tBackground: Increasing studies showed that abnormal changes in single nucleotide polymorphisms (SNPs) of DNMTs (DNMT1, DNMT3A and DNMT3B) were associated with occurrence or decrease of various tumors. However, the Vercirnon price associations between DNMTs variations and gastric cancer (GC) risk were still conflicting. We aimed to assess the effect of DNMTs polymorphisms on the susceptibility to GC. Methods: Firstly, we did a meta-analysis for 7 SNPs (rs16999593, rs2228611, rs8101866 in DNMT1, rs1550117, rs13420827 in DNMT3A, rs1569686, rs2424913 in DNMT3B). Four genetic models (homozygote, heterozygote, dominant and recessive model) were used. Moreover, a meta-sensitivity and subgroup analysis was performed to clarify heterogeneity source. Lastly, 17 SNPs that couldn’t be meta-analyzed were presented in a systematic review. Findings: 20 studies were included, 13 studies could be meta-analyzed and 7 ones could not. Firstly, a meta-analysis on 13 studies (3959 GC cases and 5992 controls) for 7 SNPs showed that GC risk increased in rs16999593 (heterozygote model: OR 1.36, 95 CI 1.14?.61; dominant model: OR 1.36, 95 CI 1.15?.60) and rs1550117 (homozygote model: OR 2.03, 95 CI 1.38?.00; dominant model: OR 1.20, 95 CI 1.01?.42; recessive model: OR 1.96, 95 CI 1.33?.89) but decreased in rs1569686 (dominant model: OR 0.74, 95 CI 0.61?.90). The remaining SNPs were not found associated with GC risk. Furthermore, the subgroup analysis indicated that for rs1550117 and rs1569686, the significant associations were particularly found in people from Chinese Jiangsu province (rs1550117, OR 1.77, 95 CI 1.25?.51; rs1569686, OR 0.48, 95 CI 0.36?.64) and that PCR-RFLP was a sensitive method to discover significant associations (rs1550117, OR 1.77, 95 CI 1.25?.51; rs1569686, OR 0.49, 95 CI 0.37?.65). Lastly, a systematic review on 7 studies for 17 SNPs suggested that rs36012910, rs7560488 and rs6087990 might have a potential effect on GC initiation. Conclusion: This meta-analysis demonstrated that rs16999593 and rs1550117 could contribute to GC risk and that rs1569686 might be a protective factor against gastric carcinogenesis. By using these SNPs as biomarkers, it is feasible to estimate the risk of acquiring GC and thus formulate timely preventive strategy. ?2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://c.Earch Program, NIDA, DHHS (Dr. Uhl). We are grateful for access to brain samples from the University of Maryland Brain Tissue Bank.Author ContributionsConceived and designed the experiments: GRU JD. Performed the experiments: JD DW SS KJ BK JT. Analyzed the data: GRU DW JD. Contributed reagents/materials/analysis tools: JT. Wrote the paper: GRU JD DW.
EBioMedicine 13 (2016) 125?Contents lists available at ScienceDirectEBioMedicinejournal homepage: www.ebiomedicine.comResearch PaperDNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysisHongjia Li a,1, Wen Li a,1, Shanshan Liu a, Shaoqi Zong a, Weibing Wang b, Jianlin Ren a, Qi Li c, Fenggang Hou a,, Qi Shi a,a b cOncology Department of Shanghai Municipal Hospital of Traditional Chinese Medicine affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200071, China Fudan University School of Public Health, Shanghai 200032, China Department of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, Chinaa r t i c l ei n f oa b s t r a c tBackground: Increasing studies showed that abnormal changes in single nucleotide polymorphisms (SNPs) of DNMTs (DNMT1, DNMT3A and DNMT3B) were associated with occurrence or decrease of various tumors. However, the associations between DNMTs variations and gastric cancer (GC) risk were still conflicting. We aimed to assess the effect of DNMTs polymorphisms on the susceptibility to GC. Methods: Firstly, we did a meta-analysis for 7 SNPs (rs16999593, rs2228611, rs8101866 in DNMT1, rs1550117, rs13420827 in DNMT3A, rs1569686, rs2424913 in DNMT3B). Four genetic models (homozygote, heterozygote, dominant and recessive model) were used. Moreover, a meta-sensitivity and subgroup analysis was performed to clarify heterogeneity source. Lastly, 17 SNPs that couldn’t be meta-analyzed were presented in a systematic review. Findings: 20 studies were included, 13 studies could be meta-analyzed and 7 ones could not. Firstly, a meta-analysis on 13 studies (3959 GC cases and 5992 controls) for 7 SNPs showed that GC risk increased in rs16999593 (heterozygote model: OR 1.36, 95 CI 1.14?.61; dominant model: OR 1.36, 95 CI 1.15?.60) and rs1550117 (homozygote model: OR 2.03, 95 CI 1.38?.00; dominant model: OR 1.20, 95 CI 1.01?.42; recessive model: OR 1.96, 95 CI 1.33?.89) but decreased in rs1569686 (dominant model: OR 0.74, 95 CI 0.61?.90). The remaining SNPs were not found associated with GC risk. Furthermore, the subgroup analysis indicated that for rs1550117 and rs1569686, the significant associations were particularly found in people from Chinese Jiangsu province (rs1550117, OR 1.77, 95 CI 1.25?.51; rs1569686, OR 0.48, 95 CI 0.36?.64) and that PCR-RFLP was a sensitive method to discover significant associations (rs1550117, OR 1.77, 95 CI 1.25?.51; rs1569686, OR 0.49, 95 CI 0.37?.65). Lastly, a systematic review on 7 studies for 17 SNPs suggested that rs36012910, rs7560488 and rs6087990 might have a potential effect on GC initiation. Conclusion: This meta-analysis demonstrated that rs16999593 and rs1550117 could contribute to GC risk and that rs1569686 might be a protective factor against gastric carcinogenesis. By using these SNPs as biomarkers, it is feasible to estimate the risk of acquiring GC and thus formulate timely preventive strategy. ?2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://c.