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DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis

BACKGROUND: 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 conflict...

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Autores principales: Li, Hongjia, Li, Wen, Liu, Shanshan, Zong, Shaoqi, Wang, Weibing, Ren, Jianlin, Li, Qi, Hou, Fenggang, Shi, Qi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264435/
https://www.ncbi.nlm.nih.gov/pubmed/27789275
http://dx.doi.org/10.1016/j.ebiom.2016.10.028
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author Li, Hongjia
Li, Wen
Liu, Shanshan
Zong, Shaoqi
Wang, Weibing
Ren, Jianlin
Li, Qi
Hou, Fenggang
Shi, Qi
author_facet Li, Hongjia
Li, Wen
Liu, Shanshan
Zong, Shaoqi
Wang, Weibing
Ren, Jianlin
Li, Qi
Hou, Fenggang
Shi, Qi
author_sort Li, Hongjia
collection PubMed
description BACKGROUND: 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 1.14–1.61; dominant model: OR 1.36, 95%CI 1.15–1.60) and rs1550117 (homozygote model: OR 2.03, 95%CI 1.38–3.00; dominant model: OR 1.20, 95%CI 1.01–1.42; recessive model: OR 1.96, 95%CI 1.33–2.89) but decreased in rs1569686 (dominant model: OR 0.74, 95%CI 0.61–0.90). 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 1.25–2.51; rs1569686, OR 0.48, 95%CI 0.36–0.64) and that PCR-RFLP was a sensitive method to discover significant associations (rs1550117, OR 1.77, 95%CI 1.25–2.51; rs1569686, OR 0.49, 95%CI 0.37–0.65). 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.
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spelling pubmed-52644352017-02-01 DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis Li, Hongjia Li, Wen Liu, Shanshan Zong, Shaoqi Wang, Weibing Ren, Jianlin Li, Qi Hou, Fenggang Shi, Qi EBioMedicine Research Paper BACKGROUND: 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 1.14–1.61; dominant model: OR 1.36, 95%CI 1.15–1.60) and rs1550117 (homozygote model: OR 2.03, 95%CI 1.38–3.00; dominant model: OR 1.20, 95%CI 1.01–1.42; recessive model: OR 1.96, 95%CI 1.33–2.89) but decreased in rs1569686 (dominant model: OR 0.74, 95%CI 0.61–0.90). 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 1.25–2.51; rs1569686, OR 0.48, 95%CI 0.36–0.64) and that PCR-RFLP was a sensitive method to discover significant associations (rs1550117, OR 1.77, 95%CI 1.25–2.51; rs1569686, OR 0.49, 95%CI 0.37–0.65). 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. Elsevier 2016-10-19 /pmc/articles/PMC5264435/ /pubmed/27789275 http://dx.doi.org/10.1016/j.ebiom.2016.10.028 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Paper
Li, Hongjia
Li, Wen
Liu, Shanshan
Zong, Shaoqi
Wang, Weibing
Ren, Jianlin
Li, Qi
Hou, Fenggang
Shi, Qi
DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis
title DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis
title_full DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis
title_fullStr DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis
title_full_unstemmed DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis
title_short DNMT1, DNMT3A and DNMT3B Polymorphisms Associated With Gastric Cancer Risk: A Systematic Review and Meta-analysis
title_sort dnmt1, dnmt3a and dnmt3b polymorphisms associated with gastric cancer risk: a systematic review and meta-analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264435/
https://www.ncbi.nlm.nih.gov/pubmed/27789275
http://dx.doi.org/10.1016/j.ebiom.2016.10.028
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