Evidence map›Paper›PMID 32509160›Full record

ReviewAmerican journal of translational research2020

CircRNAs: potency of protein translation and feasibility of novel biomarkers and therapeutic targets for head and neck cancers.

Dong-Ni Zhou, Chun-Sheng Ye, Yan-Fei Deng

Abstract readReview
In one paragraph

Review in American journal of translational research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Circular RNA circ_0070441 regulates MPPMetabolic brain disease · 2022
    Article
  5. Review
  6. 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

3 authors.

Dong-Ni ZhouDepartment of Pathology, Zhongshan Hospital, Xiamen University 209 Hubin South Road, Xiamen 361004, Fujian, China.
Chun-Sheng YeDepartment of Otolaryngology-Head and Neck Surgery, Zhongshan Hospital, Xiamen University 209 Hubin South Road, Xiamen 361004, Fujian, China.
Yan-Fei DengDepartment of Otolaryngology-Head and Neck Surgery, Zhongshan Hospital, Xiamen University 209 Hubin South Road, Xiamen 361004, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs), a new star noncoding RNA (ncRNA), show stability, conservation, abundance, and tissue and stage specificity. They act as key regulators of biological processes. They target the mRNAs of many other different genes or signaling pathways, and closely link associated genes into regulatory networks. Growing evidence has demonstrated that circRNAs may play an important role in the carcinogenesis, progression and chemoradiation resistance of many cancers including head and neck cancers (HNC). CircRNA, like other ncRNA, such as miRNA, lncRNA, usually is considered to be non-protein coding transcript. However, recent studies indicated that abnormal translation of circRNAs may be involved in human diseases. In this review, we collected the origin, classification, characteristics, function of circRNAs, exosmal circRNAs, and then synthesize current study results to highlight aberration of circRNAs in various types of HNC, and try to clarify the molecular mechanisms of circRNAs affecting the pathogenesis and progression of HNC, as well as pay particular attention to provide a new avenue to the diagnosis and treatment strategy for HNC.

Indexed as

biomarkerCircular RNAhead and neck cancerprotein translationtherapeutic target

Identifiers

PMID32509160
PMCPMC7270011

What OpenQuestion holds

Textmetadata
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.