Evidence map›Paper›PMID 31613058›Full record

ArticleJournal of cellular and molecular medicine2019

Integrated analysis of co-expression and ceRNA network identifies five lncRNAs as prognostic markers for breast cancer.

Yan Yao, Tingting Zhang, Lingyu Qi, Chao Zhou, Junyu Wei, Fubin Feng, Ruijuan Liu, Changgang Sun

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

52 citing papers in PubMed, 69 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

8 authors at 3 institutions in 1 country.

Yan YaoClinical Medical Colleges, Weifang Medical University, WeiFang, China.
Tingting ZhangCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
Lingyu QiCollege of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
Chao ZhouDepartment of Oncology, Weifang Traditional Chinese Hospital, WeiFang, China.
Junyu WeiDepartment of Oncology, Weifang Traditional Chinese Hospital, WeiFang, China.
Fubin FengDepartment of Oncology, Weifang Traditional Chinese Hospital, WeiFang, China.
Ruijuan LiuDepartment of Oncology, Weifang Traditional Chinese Hospital, WeiFang, China.
Changgang SunDepartment of Oncology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.ORCID 0000-0002-6648-3602
Weifang Chinese Medicine Hospital · CNShandong University of Traditional Chinese Medicine · CNWeifang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co-expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan-Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co-expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2-AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorFemaleGene Expression ProfilingGene Regulatory NetworksHumansKaplan-Meier EstimateMicroRNAsPrognosisRNA, Long NoncodingRNA, MessengerBiomarkers, TumorMicroRNAsRNA, Long NoncodingRNA, Messengerbreast cancerceRNA networkoverall survivalThe Cancer Genomes Atlasweighted gene co-expression network analysis

Identifiers

PMID31613058
PMCPMC6850943
OpenAlexW2980412861

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.