Evidence map›Paper›PMID 26823816›Full record

ArticleInternational journal of clinical and experimental pathology2015

DNA methyltransferase 3a rs1550117 genetic polymorphism predicts poor survival in gastric cancer patients.

Chuan Wang, Zhifang Jia, Hongxi Ma, Donghui Cao, Xing Wu, Simin Wen, Lili You, Xueyuan Cao, Jing Jiang

Abstract read
In one paragraph

Article in International journal of clinical and experimental pathology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Chuan WangDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.
Zhifang JiaDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.
Hongxi MaDivision of Pathology, First Hospital of Jilin University Changchun 130021, China.
Donghui CaoDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.
Xing WuDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.
Simin WenDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.
Lili YouDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.
Xueyuan CaoDepartment of Gastric and Colorectal Surgery, First Hospital of Jilin University Changchun 130021, China.
Jing JiangDivision of Clinical Epidemiology, First Hospital of Jilin University Changchun 130021, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methyltransferase 3a (DNMT3a) have been suggested to play a crucial role in human cancer prognosis. Single nucleotide polymorphisms (SNPs) in DNMT3a genes may have an impact on the prognosis of cancers. This study aimed to investigate the association between SNPs of DNMT3a gene and prognosis of gastric cancer (GC). Two sites of DNMT3a SNPs, rs1550117 and rs13420827 were selected and genotyped using TaqMan assay in 447 GC patients who received gastrectomy. Effects of genotypes on clinical outcomes of GC were calculated by Kaplan-Meier survival analysis and Cox regression model. We found that the AG or AA genotype of rs1550117 was associated with significantly poorer survival and increased death risk of GC compared with GG genotype (dominant model: HR=1.35, 95% CI=1.01-1.80, P=0.043). Further multivariate Cox regression analysis revealed that in addition to the known factors including male, larger tumor sizes and high clinical stage, rs1550117 variant was an independently predictive factor for survival in GC patients. No significant association was found between rs13420827 genetic variants and GC prognosis. Our findings first demonstrated that DNMT3a rs1550117 polymorphism may be a potential biomarker in predicting overall survival of GC patients.

Indexed as

Polymorphism, Single NucleotideAdultAgedAsian PeopleDNA (Cytosine-5-)-MethyltransferasesDNA Methyltransferase 3AFemaleGenetic Predisposition to DiseaseGenotypeHumansKaplan-Meier EstimateMaleMiddle AgedPolymerase Chain ReactionPrognosisProportional Hazards ModelsDNA (Cytosine-5-)-MethyltransferasesDNA Methyltransferase 3ADNMT3A protein, humanDNA methyltransferase 3agastric canceroverall survivalpolymorphisms

Identifiers

PMID26823816
PMCPMC4713602

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.