Evidence map›Paper›PMID 34149805›Full record

ArticleFrontiers in genetics2021

Construction and Analysis of the Dysregulated ceRNA Network and Identification of Risk Long Noncoding RNAs in Breast Cancer.

Xiaojie Su, Zhaoyan Yu, Yuexin Zhang, Jiaxin Chen, Ling Wei, Liang Sun

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 30% 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

10 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Carcinogenic roles of MAFG-AS1 in human cancers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024
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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

6 authors at 3 institutions in 1 country.

Xiaojie SuCollege of Medical Laboratory Science and Technology, Harbin Medical University, Daqing, China.
Zhaoyan YuDepartment of Otorhinolaryngology, Shandong Provincial Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Yuexin ZhangSchool of Medical Informatics, Harbin Medical University, Daqing, China.
Jiaxin ChenSchool of Medical Informatics, Harbin Medical University, Daqing, China.
Ling WeiSchool of Medical Informatics, Harbin Medical University, Daqing, China.
Liang SunCollege of Artificial Intelligence and Big Data for Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Harbin Medical University · CNShandong First Medical University · CNUniversity of Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BRCA) is the second leading cause of cancer-related mortality in women worldwide. However, the molecular mechanism involved in the development of BRCA is not fully understood. In this study, based on the miRNA-mediated long non-coding RNA (lncRNA)-protein coding gene (PCG) relationship and lncRNA-PCG co-expression information, we constructed and analyzed a specific dysregulated lncRNA-PCG co-expression network in BRCA. Then, we performed the random walk with restart (RWR) method to prioritize BRCA-related lncRNAs through comparing their RWR score and significance. As a result, we identified 30 risk lncRNAs for BRCA, which can distinguish normal and tumor samples. Moreover, through gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, we found that these risk lncRNAs mainly synergistically exerted functions related to cell cycle and DNA separation and replication. At last, we developed a four-lncRNA prognostic signature (including AP000851.1, LINC01977, MAFG-DT, SIAH2-AS1) and assessed the survival accuracy of the signature by performing time-dependent receiver operating characteristic (ROC) analysis. The areas under the ROC curve for 1, 3, 5, and 10 years of survival prediction were 0.68, 0.61, 0.62, and 0.63, respectively. The multivariable Cox regression results verified that the four-lncRNA signature could be used as an independent prognostic biomarker in BRCA. In summary, these results have important reference value for the study of diagnosis, treatment, and prognosis evaluation of BRCA.

Indexed as

breast cancerceRNA networkcompetitive endogenous RNAprognostic signaturerandom walk with restartrisk lncRNA

Identifiers

PMID34149805
PMCPMC8212960
OpenAlexW3166551908

What OpenQuestion holds

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LicenceCC BY
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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.