Evidence map›Paper›PMID 35884948›Full record

ReviewBiomedicines2022

circRNA: A New Biomarker and Therapeutic Target for Esophageal Cancer.

Katsutoshi Shoda, Yuki Kuwano, Daisuke Ichikawa, Kiyoshi Masuda

Open access · goldAbstract readReview
In one paragraph

Review in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. 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

4 authors at 3 institutions in 1 country.

Katsutoshi ShodaFirst Department of Surgery, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan.
Yuki KuwanoDepartment of Medical Genetics, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima 770-8503, Japan.
Daisuke IchikawaFirst Department of Surgery, Faculty of Medicine, University of Yamanashi, Yamanashi 409-3898, Japan.
Kiyoshi MasudaKawasaki Medical School, Okayama 701-0192, Japan.ORCID 0000-0001-9959-4221
University of Yamanashi · JPKawasaki Medical School · JPTokushima University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) comprise a large class of endogenous non-coding RNA with covalently closed loops and have independent functions as linear transcripts transcribed from identical genes. circRNAs are generated by a "back-splicing" process regulated by regulatory elements in cis and associating proteins in trans. Many studies have shown that circRNAs play important roles in multiple processes, including splicing, transcription, chromatin modification, miRNA sponges, and protein decoys. circRNAs are highly stable because of their closed ring structure, which prevents them from degradation by exonucleases, and are more abundant in terminally differentiated cells, such as brains. Recently, it was demonstrated that numerous circRNAs are differentially expressed in cancer cells, and their dysfunction is involved in tumorigenesis and metastasis. However, the crucial functions of these circRNAs and the dysregulation of circRNAs in cancer are still unknown. In this review, we summarize the recent reports on the biogenesis and biology of circRNAs and then catalog the advances in using circRNAs as biomarkers and therapeutic targets for cancer therapy, particularly esophageal cancer.

Indexed as

biomarkercircRNAesophageal cancertherapeutic target

Identifiers

PMID35884948
PMCPMC9313320
OpenAlexW4284966800

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.