Evidence map›Paper›PMID 31886256›Full record

ArticleBioMed research international2019

Bioinformatic Analysis of Circular RNA-Associated ceRNA Network Associated with Hepatocellular Carcinoma.

Jiacheng Wu, Shui Liu, Yien Xiang, Xianzhi Qu, Yingjun Xie, Xuewen Zhang

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 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

6 authors at 1 institution in 1 country.

Jiacheng WuDepartment of Hepatobiliary and Pancreatic Surgery, Second Hospital of Jilin University, Changchun 130041, China.ORCID https://orcid.org/0000-0003-3306-3123
Shui LiuDepartment of Hepatobiliary and Pancreatic Surgery, Second Hospital of Jilin University, Changchun 130041, China.ORCID https://orcid.org/0000-0001-9944-4696
Yien XiangDepartment of Hepatobiliary and Pancreatic Surgery, Second Hospital of Jilin University, Changchun 130041, China.ORCID https://orcid.org/0000-0002-1795-0198
Xianzhi QuDepartment of Hepatobiliary and Pancreatic Surgery, Second Hospital of Jilin University, Changchun 130041, China.ORCID https://orcid.org/0000-0001-8615-0461
Yingjun XieDepartment of Hepatobiliary and Pancreatic Surgery, Second Hospital of Jilin University, Changchun 130041, China.ORCID https://orcid.org/0000-0002-0845-0757
Xuewen ZhangDepartment of Hepatobiliary and Pancreatic Surgery, Second Hospital of Jilin University, Changchun 130041, China.ORCID https://orcid.org/0000-0002-3619-2222
Second Affiliated Hospital of Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and is associated with a high mortality rate and poor treatment efficacy. In an attempt to investigate the mechanisms involved in the pathogenesis of HCC, bioinformatic analysis and validation by qRT-PCR were performed. Three circRNA GEO datasets and one miRNA GEO dataset were selected for this purpose. Upon combined biological prediction, a total of 11 differentially expressed circRNAs, 15 differentially expressed miRNAs, and 560 target genes were screened to construct a circRNA-related ceRNA network. GO analysis and KEGG pathway analysis were performed for the 560 target genes. To further screen key genes, a protein-protein interaction network of the target genes was constructed using STRING, and the genes and modules with higher degree were identified by MCODE and CytoHubba plugins of Cytoscape. Subsequently, a module was screened out and subjected to GO enrichment analysis and KEGG pathway analysis. This module included eight genes, which were further screened using TCGA. Finally, UBE2L3 was selected as a key gene and the hsa_circ_0009910-miR-1261-UBE2L3 regulatory axis was established. The relative expression of the regulatory axis members was confirmed by qRT-PCR in 30 pairs of samples, including HCC tissues and adjacent nontumor tissues. The results suggested that hsa_circ_0009910, which was upregulated in HCC tissues, participates in the pathogenesis of HCC by acting as a sponge of miR-1261 to regulate the expression of UBE2L3. Overall, this study provides support for the possible mechanisms of progression in HCC.

Indexed as

Gene Regulatory NetworksCarcinoma, HepatocellularComputational BiologyDatabases, GeneticGene Expression Regulation, NeoplasticGene OntologyHumansLiver NeoplasmsMicroRNAsProtein Interaction MapsRNA, CircularMicroRNAsRNA, Circular

Identifiers

PMID31886256
PMCPMC6926424
OpenAlexW2986388989

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.