Evidence map›Paper›PMID 32922436›Full record

ArticleFrontiers in genetics2020

Identification of Prostate Cancer-Related Circular RNA Through Bioinformatics Analysis.

Yu-Peng Wu, Xiao-Dan Lin, Shao-Hao Chen, Zhi-Bin Ke, Fei Lin, Dong-Ning Chen, Xue-Yi Xue, Yong Wei, Qing-Shui Zheng, Yao-An Wen and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

14 citing papers in PubMed, 33 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

11 authors at 2 institutions in 1 country.

Yu-Peng WuDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Xiao-Dan LinDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Shao-Hao ChenDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Zhi-Bin KeDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Fei LinDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Dong-Ning ChenDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Xue-Yi XueDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Yong WeiDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Qing-Shui ZhengDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Yao-An WenDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Ning XuDepartment of Urology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Fujian Medical University · CNFirst Affiliated Hospital of Fujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProstate cancer (PCa) is one of the most common malignant tumors worldwide. Accumulating evidence has suggested that circular RNAs (circRNAs) are involved in the development and progression of various cancers, and they show great potential as novel biomarkers. However, the underlying mechanisms and specific functions of most circRNAs in PCa remain unknown. Here, we aimed to identify circRNAs with potential roles in PCa from the PCa expression profile.

methodsWe used data downloaded from the Gene Expression Omnibus to identify circRNAs that were differentially expressed between PCa samples and adjacent non-tumor samples. Relative expression levels of identified circRNAs were validated by quantitative real-time PCR. Micro (mi)RNA response elements were predicted by the CircInteractome database, and miRNA target genes were predicted by miRDB, miRTarBase, and TargetScan databases. Gene ontology (GO) enrichment analysis and pathway analysis revealed the potential biological and functional roles of these target genes. A circRNA-miRNA-mRNA interaction network was constructed by Cytoscape. The interaction between circRNAs and miRNAs in PCa was thoroughly reviewed in the PubMed. Finally, the mRNA expression of these genes was validated by the Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The expression of proteins encoded by these genes was further validated by the Human protein Atlas (HPA) database.

resultsA total of 60 circRNAs that were differentially expressed between PCa and healthy samples were screened, of which 15 were annotated. Three circRNAs (hsa_circ_0024353, hsa_circ_0085494, hsa_circ_0031408) certified the criteria were studied. The results of quantitative real-time PCR demonstrated that the expression of hsa_circ_0024353 was significantly downregulated in PC-3 cells when compared with RWPE-1 cells, while the expression of hsa_circ_0031408 and hsa_circ_0085494 was significantly upregulated in PC-3 cells when compared with RWPE-1 cells. GO and Kyoto Encyclopedia of Genes and Genomes analyses found that target genes were mainly enriched in metabolic processes and pathways involving phosphoinositide 3-kinase-Akt signaling, hypoxia-inducible factor-1 signaling, p53 signaling, and the cell cycle. A total of 11 miRNA target genes showing differential expression between PCa and healthy samples were selected, and their mRNA and protein expression were validated by GEPIA and HPA databases, respectively. Of these,

conclusionThis study identified three circRNA-miRNA-mRNA interaction axes that might provide novel insights into the potential mechanisms underlying PCa development.

Indexed as

bioinformatics analysiscircRNAcircRNA–microRNA–mRNA interaction axisprostate cancersignaling pathway

Identifiers

PMID32922436
PMCPMC7457069
OpenAlexW3049072724

What OpenQuestion holds

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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.