Evidence map›Paper›PMID 38540371›Full record

ArticleGenes2024

Gene Expression Analysis for Uterine Cervix and Corpus Cancer Characterization.

Lucía Almorox, Laura Antequera, Ignacio Rojas, Luis Javier Herrera, Francisco M Ortuño

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Lucía AlmoroxDepartment of Computer Engineering, Automatics and Robotics, C.I.T.I.C., University of Granada, Periodista Rafael Gómez Montero, 2, 18014 Granada, Spain.ORCID 0009-0008-1554-770X
Laura AntequeraDepartment of Computer Engineering, Automatics and Robotics, C.I.T.I.C., University of Granada, Periodista Rafael Gómez Montero, 2, 18014 Granada, Spain.ORCID 0009-0002-5430-5443
Ignacio RojasDepartment of Computer Engineering, Automatics and Robotics, C.I.T.I.C., University of Granada, Periodista Rafael Gómez Montero, 2, 18014 Granada, Spain.ORCID 0000-0002-1033-5635
Luis Javier HerreraDepartment of Computer Engineering, Automatics and Robotics, C.I.T.I.C., University of Granada, Periodista Rafael Gómez Montero, 2, 18014 Granada, Spain.ORCID 0000-0003-3220-9389
Francisco M OrtuñoDepartment of Computer Engineering, Automatics and Robotics, C.I.T.I.C., University of Granada, Periodista Rafael Gómez Montero, 2, 18014 Granada, Spain.ORCID 0000-0001-7424-1753

Funding

Consejería de Universidad, Investigación e Innovación Project C-ING-172-UGR23MCIN/AEI/10.13039/501100011033 PID2021-128317OB-I00
6 · The paper itself

Abstract

The analysis of gene expression quantification data is a powerful and widely used approach in cancer research. This work provides new insights into the transcriptomic changes that occur in healthy uterine tissue compared to those in cancerous tissues and explores the differences associated with uterine cancer localizations and histological subtypes. To achieve this, RNA-Seq data from the TCGA database were preprocessed and analyzed using the KnowSeq package. Firstly, a kNN model was applied to classify uterine cervix cancer, uterine corpus cancer, and healthy uterine samples. Through variable selection, a three-gene signature was identified (

Indexed as

Carcinoma, AdenosquamousCarcinoma, Squamous CellMicroRNAsUterine Cervical NeoplasmsFemaleGene Expression ProfilingHumansMicroRNAscervical adenocarcinomacervical cancercervical squamous cell carcinomadifferentially expressed genesgene signatureKnowSeqMicroRNAsRNA-Sequterine corpus cancer

Identifiers

PMID38540371
PMCPMC10970626

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.