Evidence map›Paper›PMID 31746384›Full record

ArticleMolecular medicine reports2020

Construction and analysis of circular RNA molecular regulatory networks in clear cell renal cell carcinoma.

Chuanyu Ma, Jie Qin, Junpeng Zhang, Xingli Wang, Dongjun Wu, Xiunan Li

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

18 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. CircRNA Regulation of T Cells in Cancer: Unraveling Potential Targets.International journal of molecular sciences · 2024
    Review
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  8. Article
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  14. Observational
  15. Circular RNA in renal diseases.Journal of cellular and molecular medicine · 2020
    Review
  16. Article
  17. Article
  18. Article
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 2 institutions in 1 country.

Chuanyu MaDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116600, P.R. China.
Jie QinDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116600, P.R. China.
Junpeng ZhangDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116600, P.R. China.
Xingli WangDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116600, P.R. China.
Dongjun WuDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116600, P.R. China.
Xiunan LiDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116600, P.R. China.
Dalian Medical University · CNFirst Affiliated Hospital of Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing evidence has indicated that circular (circ)RNAs participate in carcinogenesis; however, the specific regulatory mechanisms underlying the effects of circRNAs, microRNAs (miRNAs/miRs) and genes on the development of clear cell renal cell carcinoma (CCRCC) remain unclear. In the present study, RNA microarray data from CCRCC tissues and control samples were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas, in order to identify significantly dysregulated circRNAs, miRNAs and genes. The Cancer‑Specific circRNA Database was used to explore the interactions between miRNAs and circRNAs, whereas TargetScan and miRDB were employed to predict the mRNA targets of miRNAs. Functional enrichment and prognostic analyses were conducted in R. The results revealed that 324 circRNAs were downregulated, whereas 218 circRNAs were upregulated in cancer. In addition, a circRNA‑miRNA‑mRNA interaction network was constructed. Gene Ontology analysis of the upregulated genes revealed that these genes were enriched in biological processes, including 'flavonoid metabolic process', 'cellular glucuronidation' and 'T cell activation'. The downregulated genes were mainly enriched in biological processes, such as 'nephron development', 'kidney development' and 'renal system development'. The hub genes, including membrane palmitoylated protein 7, aldehyde dehydrogenase 6 family member A1, transcription factor AP‑2α, collagen type IV α 4 chain, nuclear receptor subfamily 3 group C member 2, plasminogen, Holliday junction recognition protein, claudin 10, kinesin family member 18B and thyroid hormone receptor β, and the hub miRNAs, including miR‑21‑3p, miR‑155‑3p, miR‑144‑3p, miR‑142‑5p, miR‑875‑3p, miR‑885‑3p, miR‑3941, miR‑224‑3p, miR‑584‑3p and miR‑138‑1‑3p, were significantly associated with CCRCC survival. In conclusion, these results suggested that the significantly dysregulated circRNAs, miRNAs and genes identified in this study may be considered potential biomarkers of the carcinogenesis of CCRCC and the survival of patients with this disease.

Indexed as

Carcinoma, Renal CellDatabases, Nucleic AcidGene Regulatory NetworksKidney NeoplasmsRNA, CircularRNA, NeoplasmDisease-Free SurvivalHumansNeoplasm ProteinsSurvival RateNeoplasm ProteinsRNA, CircularRNA, Neoplasmcircular rnaclear cell renal cell carcinomamicrornaprognosis

Identifiers

PMID31746384
PMCPMC6896406
OpenAlexW2985506557

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.