Evidence map›Paper›PMID 25133526›Full record

ArticlePloS one2014

Systematic genetic analysis identifies Cis-eQTL target genes associated with glioblastoma patient survival.

Qing-Rong Chen, Ying Hu, Chunhua Yan, Kenneth Buetow, Daoud Meerzaman

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Mapping Tumor-Specific Expression QTLs in Impure Tumor Samples.Journal of the American Statistical Association · 2020
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. The role of enhancers in cancer.Nature reviews. Cancer · 2016
    Review
  17. The Expression Quantitative Trait Loci in Immune Pathways and their Effect on Cutaneous Melanoma Prognosis.Clinical cancer research : an official journal of the American Association for Cancer Research · 2016
    Article
  18. Article
  19. Article
  20. 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

5 authors at 2 institutions in 1 country.

Qing-Rong ChenCenter for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
Ying HuCenter for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
Chunhua YanCenter for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
Kenneth BuetowCenter for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
Daoud MeerzamanCenter for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
National Institutes of Health · USNational Cancer Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prior expression quantitative trait locus (eQTL) studies have demonstrated heritable variation determining differences in gene expression. The majority of eQTL studies were based on cell lines and normal tissues. We performed cis-eQTL analysis using glioblastoma multiforme (GBM) data sets obtained from The Cancer Genome Atlas (TCGA) to systematically investigate germline variation's contribution to tumor gene expression levels. We identified 985 significant cis-eQTL associations (FDR<0.05) mapped to 978 SNP loci and 159 unique genes. Approximately 57% of these eQTLs have been previously linked to the gene expression in cell lines and normal tissues; 43% of these share cis associations known to be associated with functional annotations. About 25% of these cis-eQTL associations are also common to those identified in Breast Cancer from a recent study. Further investigation of the relationship between gene expression and patient clinical information identified 13 eQTL genes whose expression level significantly correlates with GBM patient survival (p<0.05). Most of these genes are also differentially expressed in tumor samples and organ-specific controls (p<0.05). Our results demonstrated a significant relationship of germline variation with gene expression levels in GBM. The identification of eQTLs-based expression associated survival might be important to the understanding of genetic contribution to GBM cancer prognosis.

Indexed as

Gene Expression Regulation, NeoplasticQuantitative Trait LociBrainBrain NeoplasmsGenetic Predisposition to DiseaseGenetic TestingGenome-Wide Association StudyGenotypeGlioblastomaHumansPolymorphism, Single NucleotidePrognosisSurvival Analysis

Identifiers

PMID25133526
PMCPMC4136869
OpenAlexW2038942234

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

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.