Evidence map›Paper›PMID 26176862›Full record

ArticlePloS one2015

Evaluating the Association of Eight Polymorphisms with Cancer Susceptibility in a Han Chinese Population.

Ying Dong, Jing Chen, Zhiqiang Chen, Chaoyong Tian, Huaisheng Lu, Jigang Ruan, Wenjun Yang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 pooled it
1.7field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 20 citations in OpenAlex.

  1. Pooled it
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  6. Single Nucleotide Polymorphisms inFrontiers in oncology · 2018
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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

7 authors at 2 institutions in 1 country.

Ying DongMedical Oncology Department of General Hospital, Ningxia Medical University, Yinchuan, Ningxia, China; Key Laboratory of Ningxia Reproduction and Heredity, Ningxia Medical University, Yinchuan, Ningxia, China.
Jing ChenKey Laboratory of Ningxia Reproduction and Heredity, Ningxia Medical University, Yinchuan, Ningxia, China.
Zhiqiang ChenRadiology Department of General Hospital, Ningxia Medical University, Yinchuan, Ningxia, China.
Chaoyong TianKey Laboratory of Ningxia Reproduction and Heredity, Ningxia Medical University, Yinchuan, Ningxia, China.
Huaisheng LuPathology Department of Ningxia People's Hospital, Yinchuan, Ningxia, China.
Jigang RuanDigestive Department of General Hospital, Ningxia Medical University, Yinchuan, Ningxia, China.
Wenjun YangMedical Oncology Department of General Hospital, Ningxia Medical University, Yinchuan, Ningxia, China; Key Laboratory of Ningxia Reproduction and Heredity, Ningxia Medical University, Yinchuan, Ningxia, China.
Ningxia Medical University · CNNingxia Hui Autonomous Region Peoples Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe identification of susceptibility genes for specific types of cancer can provide necessary information for the complete characterization of cancer syndromes. Eight single nucleotide polymorphisms (SNPs), rs465498, rs17728461, rs4488809, rs753955, rs13361707, rs9841504, rs2274223, and rs13042395, were reported by genome wide association studies (GWASs) to be closely related to the susceptibility of lung cancer (LC), gastric cancer (GC) or esophageal cancer (EC) in Han population from northern or southern China. However, Chinese Han people from different geographic areas may have different genetic backgrounds. This study aims to assess the genetic associations of the eight SNPs mentioned above with three cancers risk in a Han population from northwest China.

methodsA total of 186 cancer-free controls and 436 cases with non-small cell lung cancer (NSCLC) (159 cases), non-cardia GC (167 cases) or EC (110 cases) were enrolled in this study. Chi-square test and polytomous logistic regression analyses were used to estimate the association between eight cancer-related SNPs and three cancers in a Han Chinese population from northwest China. The logistic regression results were adjusted for confounding factors and Benjamini and Hochberg False Discovery Rate (FDR) method was used to adjust the multiple hypothesis tests. Association analyses by cigarette smoking or alcohol drinking status were analyzed by crossover analyses.

resultsOne of the eight SNPs, rs17728461 was associated with NSCLC susceptibility (in a heterozygous model, OR = 0.44, 95% CI = 0.27-0.72, p = 0.001). Two SNPs, rs753955 and rs13042395, were associated with the risk of non-cardia GC in different genetic models (p < 0.05). No SNPs were associated with EC. The crossover analyses showed that the rs13042395 CT genotype, combined with cigarette smoking or alcohol drinking, could further increase the risk for non-cardia GC (p < 0.05).

conclusionsThese results indicated that rs17728461 may be specifically associated with the risk of NSCLC. rs753955 and rs13042395 were specifically associated with susceptibility to non-cardia GC in Ningxia Han Chinese. Susceptibility-associated polymorphisms in the northwestern Han Chinese were not very consistent with those in the northern Han Chinese or southern Han Chinese. The validation of these findings with a functional evaluation and a larger population is still required.

Indexed as

Polymorphism, Single NucleotideAdultAgedAlcohol DrinkingCarcinoma, Non-Small-Cell LungCase-Control StudiesChinaCross-Over StudiesEsophageal NeoplasmsFemaleGene FrequencyGenetic Association StudiesGenetic Predisposition to DiseaseHumansLung NeoplasmsMale

Identifiers

PMID26176862
PMCPMC4503434
OpenAlexW910021155

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.