Evidence map›Paper›PMID 36077653›Full record

ArticleCancers2022

Identification of Gender- and Subtype-Specific Gene Expression Associated with Patient Survival in Low-Grade and Anaplastic Glioma in Connection with Steroid Signaling.

Alex Hirtz, Nolwenn Lebourdais, Magalie Thomassin, Fabien Rech, Hélène Dumond, Hélène Dubois-Pot-Schneider

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
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

6 authors at 1 institution in 1 country.

Alex HirtzUniversité de Lorraine, CNRS, CRAN, F-54000 Nancy, France.
Nolwenn LebourdaisUniversité de Lorraine, CNRS, CRAN, F-54000 Nancy, France.
Magalie ThomassinUniversité de Lorraine, CNRS, CRAN, F-54000 Nancy, France.
Fabien RechUniversité de Lorraine, CNRS, CRAN, F-54000 Nancy, France.
Hélène DumondUniversité de Lorraine, CNRS, CRAN, F-54000 Nancy, France.ORCID 0000-0002-9697-3901
Hélène Dubois-Pot-SchneiderUniversité de Lorraine, CNRS, CRAN, F-54000 Nancy, France.ORCID 0000-0002-5799-7951
Centre National de la Recherche Scientifique · FR

Funding

Cancéropole Grand Est Pro-Glio project 2020French National Centre for Scientific Research Appel unique INS2I-CNRS 2020University of Lorraine PhD fellowship
6 · The paper itself

Abstract

Low-grade gliomas are rare primary brain tumors, which fatally evolve to anaplastic gliomas. The current treatment combines surgery, chemotherapy, and radiotherapy. If gender differences in the natural history of the disease were widely described, their underlying mechanisms remain to be determined for the identification of reliable markers of disease progression. We mined the transcriptomic and clinical data from the TCGA-LGG and CGGA databases to identify male-over-female differentially expressed genes and selected those associated with patient survival using univariate analysis, depending on molecular characteristics (IDH wild-type/mutated; 1p/19q codeleted/not) and grade. Then, the link between the expression levels (low or high) of the steroid biosynthesis enzyme or receptors of interest and survival was studied using the log-rank test. Finally, a functional analysis of gender-specific correlated genes was performed.

Indexed as

data miningfunctional enrichmentgender-specific analysisgliomasteroid signalingsurvival analysistranscriptomic profiles

Identifiers

PMID36077653
PMCPMC9454517
OpenAlexW4293104168

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.