Evidence map›Paper›PMID 35340237›Full record

ArticleJournal of healthcare engineering2022

Bioinformatics Methods Reveal the Biomarkers and the miRNA-mRNA Network in Hepatocellular Carcinoma.

Yang Liu, Haoliang Zhang, Xue Han, Xiaowei Xing

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 54% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Role of MicroRNA-502-3p in Human Diseases.Pharmaceuticals (Basel, Switzerland) · 2023
    Review
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

4 authors at 1 institution in 1 country.

Yang LiuDepartment of Oncology, Tangshan Workers' Hospital, Tangshan City 063000, Hebei Province, China.ORCID 0000-0002-3471-1076
Haoliang ZhangDepartment of Oncology, Tangshan Workers' Hospital, Tangshan City 063000, Hebei Province, China.
Xue HanDepartment of Oncology, Tangshan Workers' Hospital, Tangshan City 063000, Hebei Province, China.
Xiaowei XingDepartment of Cardiovascular Internal Medicine, Tangshan Workers' Hospital, Tangshan City 063000, Hebei Province, China.
Tangshan People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) has threatened the health of humans, and few therapeutic strategies can completely uproot this illness. Bioinformatics methods have been widely used for investigating the pathological mechanisms of disease. In this study, datasets including GSE20077 and GSE108724, obtained from the Gene Expression Omnibus (GEO) database, were used for investigating the biomarker and molecular mechanism of HCC. The differentially expressed genes (DEGs) in the datasets were identified, and the targets of the miRNAs were searched in the miRDIP and miRNET databases. Enrichment analysis was performed for delving the molecular mechanism of DEGs, and protein-protein interaction (PPI) networks and miRNA-mRNA networks were used to reveal the hub nodes and the related interaction relationships. Moreover, the expression and diagnostic values of hub nodes were analyzed with the GEPIA2 database. The results showed that 53 upregulated miRNAs and 48 downregulated miRNAs were found in GSE20077, and 55 upregulated miRNAs and 69 downregulated miRNAs were found in GSE108724. Moreover, seven common miRNAs including miR-146b-5p, miR-338-3p, miR-375, miR-502-3p, miR-532-3p, miR-532-5p, and miR-557 were found in the datasets. The targets of the common miRNAs were related with the P53, HIF1, Wnt, and NF-

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsMicroRNAsBiomarkersComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansRNA, MessengerBiomarkersMicroRNAsMIRN338 microRNA, humanMIRN532 microRNA, humanRNA, Messenger

Identifiers

PMID35340237
PMCPMC8942659
OpenAlexW4221117500

What OpenQuestion 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 OpenQuestion graph.