Evidence map›Paper›PMID 34680205›Full record

ArticleCancers2021

In silico Approach for Validating and Unveiling New Applications for Prognostic Biomarkers of Endometrial Cancer.

Eva Coll-de la Rubia, Elena Martinez-Garcia, Gunnar Dittmar, Petr V Nazarov, Vicente Bebia, Silvia Cabrera, Antonio Gil-Moreno, Eva Colás

Abstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Identification ofInternational journal of molecular sciences · 2022
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  6. Review
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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

8 authors.

Eva Coll-de la RubiaBiomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain.ORCID 0000-0001-6709-7554
Elena Martinez-GarciaLuxembourg Institute of Health, L-1445 Strassen, Luxembourg.ORCID 0000-0003-2547-7916
Gunnar DittmarLuxembourg Institute of Health, L-1445 Strassen, Luxembourg.ORCID 0000-0003-3647-8623
Petr V NazarovLuxembourg Institute of Health, L-1445 Strassen, Luxembourg.
Vicente BebiaGynaecological Department, Vall Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain.
Silvia CabreraBiomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain.
Antonio Gil-MorenoBiomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain.
Eva ColásBiomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain.ORCID 0000-0003-0302-4828

Funding

Asociación Española Contra el Cáncer GCTRA1804MATIAsociación Española Contra el Cáncer INVES20051COLACentro de Investigación Biomédica en Red de Cáncer CB16/12/00328Government of Catalonia 2017SGR1661Instituto de Salud Carlos III IFI19/00029Instituto de Salud Carlos III PI17/02155Instituto de Salud Carlos III PI20/00644Ministerio de ciencia, Innovación y Universidades RTC-2017-6261-1Télévie F5/20/5-TLV/DD
6 · The paper itself

Abstract

Endometrial cancer (EC) mortality is directly associated with the presence of prognostic factors. Current stratification systems are not accurate enough to predict the outcome of patients. Therefore, identifying more accurate prognostic EC biomarkers is crucial. We aimed to validate 255 prognostic biomarkers identified in multiple studies and explore their prognostic application by analyzing them in TCGA and CPTAC datasets. We analyzed the mRNA and proteomic expression data to assess the statistical prognostic performance of the 255 proteins. Significant biomarkers related to overall survival (OS) and recurrence-free survival (RFS) were combined and signatures generated. A total of 30 biomarkers were associated either to one or more of the following prognostic factors: histological type (

Indexed as

bioinformaticsCPTACendometrial cancerhigh-riskprognostic biomarkerTCGAuterine cancer

Identifiers

PMID34680205
PMCPMC8534093

What Socratic 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 Socratic graph.