Evidence map›Paper›PMID 29702599›Full record

ReviewInternational journal of molecular sciences2018

Noncoding RNA:RNA Regulatory Networks in Cancer.

Jia Jia Chan, Yvonne Tay

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 653 papers.

0numbers the graph read from it
0cells of the map it votes in
653citing papers in PubMed
–field-weighted citation impact
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

653 citing papers in PubMed.

  1. Article
  2. Review
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  7. [Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026
    Article
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  15. Review
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  20. Review

593 more citing papers are in PubMed but not listed here.

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

2 authors.

Jia Jia ChanCancer Science Institute of Singapore, Centre for Translational Medicine, National University of Singapore, Singapore 117599, Singapore. jia.chan@nus.edu.sg.
Yvonne TayCancer Science Institute of Singapore, Centre for Translational Medicine, National University of Singapore, Singapore 117599, Singapore. yvonnetay@nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Noncoding RNAs (ncRNAs) constitute the majority of the human transcribed genome. This largest class of RNA transcripts plays diverse roles in a multitude of cellular processes, and has been implicated in many pathological conditions, especially cancer. The different subclasses of ncRNAs include microRNAs, a class of short ncRNAs; and a variety of long ncRNAs (lncRNAs), such as lincRNAs, antisense RNAs, pseudogenes, and circular RNAs. Many studies have demonstrated the involvement of these ncRNAs in competitive regulatory interactions, known as competing endogenous RNA (ceRNA) networks, whereby lncRNAs can act as microRNA decoys to modulate gene expression. These interactions are often interconnected, thus aberrant expression of any network component could derail the complex regulatory circuitry, culminating in cancer development and progression. Recent integrative analyses have provided evidence that new computational platforms and experimental approaches can be harnessed together to distinguish key ceRNA interactions in specific cancers, which could facilitate the identification of robust biomarkers and therapeutic targets, and hence, more effective cancer therapies and better patient outcome and survival.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorCarcinogenesisGene ExpressionGene Expression ProfilingHumansMicroRNAsNeoplasmsPseudogenesRNARNA, CircularRNA, Long NoncodingRNA TransportBiomarkers, TumorMicroRNAsRNARNA, CircularRNA, Long NoncodingcancerceRNAcircRNAlncRNAmiRNApseudogene

Identifiers

PMID29702599
PMCPMC5983611

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.