Evidence map›Paper›PMID 34123783›Full record

ArticleFrontiers in oncology2021

A Combined Long Noncoding RNA Signature as a Candidate Prognostic Biomarker for Ovarian Cancer.

Hui Li, Shuoer Wang, Qianlan Yao, Yan Liu, Jing Yang, Lun Xu, Gong Yang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 50% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

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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

7 authors at 5 institutions in 1 country.

Hui LiCentral Laboratory, the Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China.
Shuoer WangDepartment of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Qianlan YaoDepartment of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Yan LiuDepartment of Gynecology, Weifang People's Hospital, Weifang, China.
Jing YangDepartment of Anesthesiology and Postanesthesia Care Unit, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Lun XuDepartment of Musculoskeletal Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Gong YangCentral Laboratory, the Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China.
Fudan University Shanghai Cancer Center · CNFirst Affiliated Hospital Zhejiang University · CNFudan University · CNShanghai Medical College of Fudan University · CNWeifang People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsDysregulated long noncoding RNAs (lncRNAs) contributing to ovarian cancer (OC) development may serve as prognostic biomarker. We aimed to explore a lncRNA signature to serve as prognostic biomarker of OC.

methodsUnivariate Cox regression was conducted on the lncRNA expression dataset from the TCGA cohort, and 246 genes significantly associated with survival were retained for building a model. A random forest survival model was carried out, and a model was developed using 6 genes with the highest frequency. The selected genes were applied in a Cox multivariate regression model for prognostic prediction by calculating the risk score. We also used CCK-8, EdU, and colony formation assays to validate the function of these lncRNAs in OC cells.

resultsThis study confirmed that the 6-lncRNA combined signature was related to OC prognosis. Systematic analysis demonstrated that lncRNA-associated genes were enriched in oncogenic signalling pathways. Five out of the 6 lncRNAs participated in OC proliferation.

conclusionWe established a 6-lncRNA combined signature for OC prognosis, which may serve as powerful prognostic biomarker for OC after further validation.

Indexed as

bioinformatics analysislong non-coding RNAovarian cancerprognostic biomarkerTCGA

Identifiers

PMID34123783
PMCPMC8191461
OpenAlexW3165327505

What OpenQuestion holds

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Registered trials

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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.