Evidence map›Paper›PMID 33498463›Full record

ArticleInternational journal of molecular sciences2021

DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival.

Jing Yin Weng, Nicole Salazar

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
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

26 citing papers in PubMed, 37 citations in OpenAlex.

  1. Review
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  14. A Meta-Analysis Study to Infer Voltage-Gated KAntioxidants (Basel, Switzerland) · 2023
    Article
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  16. Article
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  18. Article
  19. Review
  20. Glioblastoma and Methionine Addiction.International journal of molecular sciences · 2022
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jing Yin WengDepartment of Biology, San Francisco State University, San Francisco, CA 94132, USA.
Nicole SalazarDepartment of Biology, San Francisco State University, San Francisco, CA 94132, USA.ORCID 0000-0002-8658-6553
San Francisco State University · US

Funding

ACKR3 and CXCR4 Contributions to the Tumor Microenvironment in Breast Cancer Racial DisparitiesSC2GM135135 · NIGMS · SAN FRANCISCO STATE UNIVERSITY · PI SALAZAR, NICOLE · 2020 to 2022
$465k
NIGMS NIH HHS SC2 GM135135
6 · The paper itself

Abstract

DNA methylation is an epigenetic change to the genome that impacts gene activities without modification to the DNA sequence. Alteration in the methylation pattern is a naturally occurring event throughout the human life cycle which may result in the development of diseases such as cancer. In this study, we analyzed methylation data from The Cancer Genome Atlas, under the Lower-Grade Glioma (LGG) and Glioblastoma Multiforme (GBM) projects, to identify methylation markers that exhibit unique changes in DNA methylation pattern along with tumor grade progression, to predict patient survival. We found ten glioma grade-associated Cytosine-phosphate-Guanine (CpG) sites that targeted four genes (

Indexed as

DNA MethylationBiomarkers, TumorBrain NeoplasmsDicarboxylic Acid TransportersGliomaHumansKv1.4 Potassium ChannelMiddle AgedMitochondrial Membrane Transport ProteinsOsteonectinPrognosisUridine PhosphorylaseBiomarkers, TumorDicarboxylic Acid TransportersKCNA4 protein, humanKv1.4 Potassium ChannelMitochondrial Membrane Transport ProteinsOsteonectinSLC25A21 protein, humanSMOC1 protein, humanUPP1 protein, humanUridine PhosphorylaseDNA methylationglioblastomagliomaprognosisprogressionTCGAWGCNA

Identifiers

PMID33498463
PMCPMC7864199
OpenAlexW3126000514

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.