Evidence map›Paper›PMID 33428596›Full record

ArticleAging2021

Construction of an mRNA-miRNA-lncRNA network prognostic for triple-negative breast cancer.

Yuan Huang, Xiaowei Wang, Yiran Zheng, Wei Chen, Yabing Zheng, Guangliang Li, Weiyang Lou, Xiaojia Wang

Abstract read
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Differential expression of NEAT1 and miR-506-3p in triple-negative breast cancer: potential tissue-based diagnostic biomarkers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  5. Inhibition of MiR-155 Using Exosomal Delivery of Antagomir Can Up-RegulateEndocrine, metabolic & immune disorders drug targets · 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

8 authors.

Yuan HuangDepartment of Breast Medical Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Zhejiang Province, Hangzhou 310022, China.
Xiaowei WangDepartment of Colorectal Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Zhejiang Province, Hangzhou 310016, China.
Yiran ZhengSchool of Pharmaceutical Sciences, Soochow University, Jiangsu Province, Suzhou 215123, China.
Wei ChenSilergy Corporation, Zhejiang Province, Hangzhou 310012, China.
Yabing ZhengDepartment of Breast Medical Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Zhejiang Province, Hangzhou 310022, China.
Guangliang LiDepartment of Breast Medical Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Zhejiang Province, Hangzhou 310022, China.
Weiyang LouDepartment of Breast Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Zhejiang Province, Hangzhou 310003, China.
Xiaojia WangDepartment of Breast Medical Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Zhejiang Province, Hangzhou 310022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to establish a novel competing endogenous RNA (ceRNA) network able to predict prognosis in patients with triple-negative breast cancer (TNBC). Differential gene expression analysis was performed using the GEO2R tool. Enrichr and STRING were used to conduct protein-protein interaction and pathway enrichment analyses, respectively. Upstream lncRNAs and miRNAs were identified using miRNet and mirTarBase, respectively. Prognostic values, expression, and correlational relationships of mRNAs, lncRNAs, and miRNAs were examined using GEPIA, starBase, and Kaplan-Meier plotter. It total, 860 upregulated and 622 downregulated differentially expressed mRNAs were identified in TNBC. Ten overexpressed and two underexpressed hub genes were screened. Next, 10 key miRNAs upstream of these key hub genes were predicted, of which six upregulated miRNAs were significantly associated with poor prognosis and four downregulated miRNAs were associated with good prognosis in TNBC. NEAT1 and MAL2 were selected as key lncRNAs. An mRNA-miRNA-lncRNA network in TNBC was constructed. Thus, we successfully established a novel mRNA-miRNA-lncRNA regulatory network, each component of which is prognostic for TNBC.

Indexed as

Biomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansMicroRNAsPrognosisRNA, Long NoncodingRNA, MessengerTranscriptomeTriple Negative Breast NeoplasmsBiomarkers, TumorMicroRNAsRNA, Long NoncodingRNA, Messengerbiomarkercompeting endogenous RNAprognosistriple-negative breast cancer

Identifiers

PMID33428596
PMCPMC7835059

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.