Evidence map›Paper›PMID 30153287›Full record

ArticlePloS one2018

Circular RNAs hsa_circ_0032462, hsa_circ_0028173, hsa_circ_0005909 are predicted to promote CADM1 expression by functioning as miRNAs sponge in human osteosarcoma.

Gaoyang Chen, Qingyu Wang, Qiwei Yang, Zhaoyan Li, Zhenwu Du, Ming Ren, Haiyue Zhao, Yang Song, Guizhen Zhang

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

23 citing papers in PubMed, 45 citations in OpenAlex.

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  19. Non-Coding RNAs and their Integrated Networks.Journal of integrative bioinformatics · 2019
    Review
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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

9 authors at 1 institution in 1 country.

Gaoyang ChenDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.
Qingyu WangDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.
Qiwei YangResearch Centre of the Second Hospital of Jilin University, Changchun, Jilin, China.
Zhaoyan LiDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.
Zhenwu DuDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.
Ming RenDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.
Haiyue ZhaoResearch Centre of the Second Hospital of Jilin University, Changchun, Jilin, China.
Yang SongDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.ORCID 0000-0001-6464-4997
Guizhen ZhangDepartment of Orthopedics of the Second Hospital of Jilin University, Changchun, Jilin, China.
Second Affiliated Hospital of Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteosarcoma (OS) is a primary malignant bone tumor with a high fatality rate. Many circRNAs have been proved to play important roles in the pathogenesis of some diseases. However, the occurrence of circRNAs in OS remains little known.

methodsThe circular RNA (circRNA) expression file GSE96964 dataset, which included seven osteosarcoma cell lines and one control sample (osteoblast cell line), was downloaded from the Gene Expression Omnibus (GEO) database to explore the potential function of circRNAs in osteosarcoma by competing endogenous RNA (ceRNA) analysis. Three gene expression profiles of OS were downloaded from GEO database and then used for the pathway enrichment analysis, Venn analysis and protein-protein interaction (PPI) network analysis. Real-time qPCR validation and RNA interference were conducted to verify our prediction.

resultsDifferentially expressed circRNAs between OS and control, including 8 up-regulated and 102 down-regulated circRNAs, were generated and ceRNA analysis for 5 most up-regulated or 5 most down-regulated circRNAs in OS were then performed. The pathway enrichment analysis of gene expression profiles indicated differentially expressed genes (DEGs) of three gene profiles significantly enriched in cell cycle pathway, cell adhesion molecules (CAMs) pathway, oxidative phosphorylation pathway, cytokine-cytokine receptor interaction pathway, p53 signaling pathway and proteoglycans in cancer pathway, which were critical important pathways in the pathogenesis of OS. The Venn analysis showed that 2 (one is a pseudogene) up-regulated and 39 down-regulated DEGs were co-expressed in all three gene profiles. Then PPI networks of 41 co-expressed DEGs (up- and down-regulated DEGs) were constructed to predict their functions using the GeneMANIA. The expression levels of these related RNAs also matched our predictions really well.

conclusionUltimately, we found cell adhesion molecule 1 (CADM1) gene was not only a co-expression mRNA of the three mRNA expression profiles of OS, but also are predicted to be regulated by hsa_circ_0032462, hsa_circ_0028173, hsa_circ_0005909 by functioning as miRNAs 'Sponge' in human osteosarcoma. These over-expressed circRNAs may result in the over expression of CADM1 which promote the development of OS. We envision this discovery of these important moleculars, incuding hsa_circ_0032462, hsa_circ_0028173, hsa_circ_0005909 and CADM1 may lead to further development of new concepts, thus allowing for more opportunities in diagnosis and therapy of OS.

Indexed as

Gene Expression Regulation, NeoplasticBone NeoplasmsCell Adhesion Molecule-1HumansMicroRNAsOsteosarcomaProtein Interaction MappingCADM1 protein, humanCell Adhesion Molecule-1MicroRNAs

Identifiers

PMID30153287
PMCPMC6112665
OpenAlexW2888921121

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.