Evidence map›Paper›PMID 35201491›Full record

ArticleDiscover oncology2021

Comprehensive analysis of the MIR4435-2HG/miR-1-3p/MMP9/miR-29-3p/DUXAP8 ceRNA network axis in hepatocellular carcinoma.

Li Zhang, Shangshang Hu, Jiasheng Chen, Shasha Ma, Fanghong Liu, Chuanmiao Liu, Yu Gao

Open access · goldAbstract read
In one paragraph

Article in Discover oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.0field-weighted citation impact, top 29% 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

13 citing papers in PubMed, 16 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 1 institution in 1 country.

Li Zhang *Department of Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, Bengbu Medical College, 233030, Bengbu, China.
Shangshang Hu *Research Center of Clinical Laboratory Science, School of Laboratory Medicine, Bengbu Medical College, Bengbu, 233030, China.
Jiasheng ChenDepartment of Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, Bengbu Medical College, 233030, Bengbu, China.
Shasha MaDepartment of Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, Bengbu Medical College, 233030, Bengbu, China.
Fanghong LiuDepartment of Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, Bengbu Medical College, 233030, Bengbu, China.
Chuanmiao LiuDepartment of Infectious Diseases, First Affiliated Hospital of Bengbu Medical College, Bengbu Medical College, 233030, Bengbu, China.
Yu GaoSchool of Life Science, Bengbu Medical College, No. 2600, Donghai Road, Bengbu, 233030, China. gaoyu@bbmc.edu.cn.ORCID http://orcid.org/0000-0002-4210-7338
Bengbu Medical College · CN

Funding

Research Foundation for Advanced Talents of Bengbu Medical College 15190016Science Research Project of Bengbu Medical College 2020byzd080
6 · The paper itself

Abstract

A growing number of studies have shown that competitive endogenous RNA (ceRNA) regulatory networks might play important roles during the process of hepatocellular carcinoma (HCC). This study assessed the role of the ceRNA network in immune cell infiltration in HCC. Immune-related gene sets were downloaded from Molecular Signatures Database, and differentially expressed genes were screened based on TCGA HCC transcriptome data. The corresponding miRNAs with low expression and good prognostic implications, and the corresponding lncRNAs with high expression and poor prognostic were identified to construct ceRNA networks. The networks were utilized for clinical correlation analysis and risk model construction, and the CIBERSORT algorithm was applied to assess immune cell infiltration. In this study, the mRNA-miRNA-lncRNA model was used to construct a ceRNA network in HCC using immune-related differentially expressed mRNAs. Assessment of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis in HCC showed that a high risk/poor prognosis was significantly correlated with tumor stage and invasion depth. MMP9 was positively correlated with resting M0 macrophages and NK cells and negatively correlated with activated mast cells, resting mast cells, monocytes and activated NK cells. DUXAP8 was positively correlated with M2 macrophages and negatively correlated with MIR4435-2HG, which was positively correlated with M2 macrophages and negatively correlated with activated mast cells, CD8 T cells and follicular helper T cells. The correlation of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis with immune cell infiltration provides further information on the mechanism of HCC development. The result might improve our understanding the interactions between immune related genes and non-coding RNAs in the occurrence and development of HCC, and the relevant RNAs might be used as diagnostic and prognostic biomarkers and molecular targets in HCC patients.

Indexed as

ceRNADUXAP8Hepatocellular carcinomaMIR4435-2HGMMP9Prognosis

Identifiers

PMID35201491
PMCPMC8777520
OpenAlexW3202559695

What OpenQuestion holds

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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.