Evidence map›Paper›PMID 32439920›Full record

ArticleScientific reports2020

Selection of Endogenous Control Reference Genes for Studies on Type 1 or Type 2 Endometrial Cancer.

Thangesweran Ayakannu, Anthony H Taylor, Justin C Konje

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

23 citing papers in PubMed, 28 citations in OpenAlex.

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  15. Overexpression ofTranslational lung cancer research · 2023
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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

3 authors at 2 institutions in 2 countries.

Thangesweran AyakannuFaculty of Health and Life Sciences, University of Liverpool, Thompson Yates Brownlow Hill, Liverpool, L69 3GB, UK. t.ayakannu@nhs.net.
Anthony H TaylorFaculty of Health and Life Sciences, University of Liverpool, Thompson Yates Brownlow Hill, Liverpool, L69 3GB, UK.ORCID http://orcid.org/0000-0003-3260-256X
Justin C KonjeFaculty of Health and Life Sciences, University of Liverpool, Thompson Yates Brownlow Hill, Liverpool, L69 3GB, UK.
University of Liverpool · GBQatar Airways (Qatar) · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A panel of 32 candidate reference genes was used to identify the most stable genes for gene normalisation in quantitative RT-PCR studies using endometrial biopsies obtained from women with endometrial cancer (type 1 or type 2) and without cancer (controls). RNA from the biopsies was isolated, examined for purity and quality, and then reverse transcribed into cDNA before being subjected to real-time qRT-PCR analysis in triplicate within the TaqMan gene Expression Assay kit. The most 'stable' endogenous control genes were then identified using the geNorm qbase + 2 and NormFinder software packages. PSMC4, PUM1 and IPO8 were identified as the best reference genes combination for type 1 endometrial cancer (grades 1, 2 and 3), whereas for type 2 endometrial cancer (serous and carcinosarcoma), UBC, MRPL19, PGK1 and PPIA were the best reference genes combination. We conclude that the use of these normaliser combinations should provide accurate interpretation of gene expression at the transcript level in endometrial cancer studies especially for types 1 and 2 cancers.

Indexed as

AdenocarcinomaAdultAgedAged, 80 and overBiomarkers, TumorComputational BiologyEndometrial NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMiddle AgedReference StandardsBiomarkers, Tumor

Identifiers

PMID32439920
PMCPMC7242460
OpenAlexW3027517636

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.