Evidence map›Paper›PMID 29983348›Full record

ArticleEBioMedicine2018

Evaluation of GWAS-Identified Genetic Variants for Gastric Cancer Survival.

Dongying Gu, Rui Zheng, Junyi Xin, Shuwei Li, Haiyan Chu, Weida Gong, Fulin Qiang, Zhengdong Zhang, Meilin Wang, Mulong Du and 1 more

Abstract read
In one paragraph

Article in EBioMedicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Molecular Profile of Variants inJournal of personalized medicine · 2023
    Article
  6. Article
  7. Frontiers in genetics · 2021
    Article
  8. Association study betweenAnnals of translational medicine · 2021
    Article
  9. Remote modulation of lncRNAScience advances · 2020
    Article
  10. Article
  11. Article
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

11 authors.

Dongying GuDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
Rui ZhengDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China.
Junyi XinDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China.
Shuwei LiDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China.
Haiyan ChuDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China.
Weida GongDepartment of Surgery, Yixing Cancer Hospital, Yixing, China.
Fulin QiangCore Laboratory, Nantong Tumor Hospital, Nantong, China.
Zhengdong ZhangDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China.
Meilin WangDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China. Electronic address: mwang@njmu.edu.cn.
Mulong DuDepartment of Environmental Genomics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China; Department of Biostatistics, School of Public Heath, Nanjing Medical University, Nanjing, China. Electronic address: drdumulong@njmu.edu.cn.
Jinfei ChenDepartment of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China. Electronic address: drjfchen@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundsGenome-wide association studies (GWASs) have identified several gastric cancer (GC) susceptibility loci in Asians, but their effects on disease outcome are still unknown. This study aimed to investigate whether these GWAS-identified genetic variants could serve as robust prognostic biomarkers for GC.

methodsA multistage clinical cohort, including a total of 2432 GC patients in the Chinese population, was used to identify the association between GWAS-identified risk variants and overall survival of GC. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed by Cox regression analysis, and the log-rank P was calculated by the log-rank test with the Kaplan-Meier method.

resultsWe found that rs2274223 A>G in PLCE1 was associated with increased GC survival in both training set (P = .011), which was independently replicated in validation set 1 (P = .045), but not in validation set 2. The area under the curve (AUC) from receiver-operator characteristic (ROC) curve showed this clinical relevance with onset age-dependence, especially in the subgroup of early-onset cases. Moreover, a significant improvement in overall survival prediction was identified when the rs2274223 genetic effect was included in the estimation; this result was also supported by the prognostic nomogram. In addition, patients with lower expression of PLCE1 showed benefits via longer survival, potentially due to the functional effect of rs2274223.

interpretationThis preliminary study suggests that a GWAS-identified genetic variant in PLCE1 may serve as a potential biomarker for GC survival. Additional replication with larger samples size is warranted to further investigation.

Indexed as

Down-RegulationPolymorphism, Single NucleotideArea Under CurveAsian PeopleBiomarkers, TumorCase-Control StudiesFemaleGene Expression Regulation, NeoplasticGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMaleNeoplasm StagingNomogramsPhosphoinositide Phospholipase CPrognosisBiomarkers, TumorPhosphoinositide Phospholipase Cphospholipase C epsilonGastric cancerGenetic variantsGWASSurvival

Identifiers

PMID29983348
PMCPMC6085567

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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.