Evidence map›Paper›PMID 33088214›Full record

ReviewCancer cell international2020

Emerging role of long noncoding RNA-encoded micropeptides in cancer.

Mujie Ye, Jingjing Zhang, Meng Wei, Baihui Liu, Kuiran Dong

Abstract readReview
In one paragraph

Review in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Review
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  11. Thousands of oscillating LncRNAs in the mouse testis.Computational and structural biotechnology journal · 2024
    Article
  12. Article
  13. Article
  14. Review
  15. LncRNA-encoded peptides in cancer.Journal of hematology & oncology · 2024
    Review
  16. Review
  17. CRNDE: A Pivotal Oncogenic Long Non-Coding RNA in Cancers.The Yale journal of biology and medicine · 2023
    Review
  18. Review
  19. Review
  20. Review
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

5 authors.

Mujie Ye *Department of Pediatric Surgery, Children's Hospital of Fudan University, No.399 Wanyuan Road, Minhang District, Shanghai, 201102 China.ORCID https://orcid.org/0000-0002-5363-2752
Jingjing Zhang *Department of Medical Imaging, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, 210001 China.
Meng WeiDepartment of Pediatric Surgery, Children's Hospital of Fudan University, No.399 Wanyuan Road, Minhang District, Shanghai, 201102 China.
Baihui LiuDepartment of Pediatric Surgery, Children's Hospital of Fudan University, No.399 Wanyuan Road, Minhang District, Shanghai, 201102 China.
Kuiran DongDepartment of Pediatric Surgery, Children's Hospital of Fudan University, No.399 Wanyuan Road, Minhang District, Shanghai, 201102 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing evidence has indicated that long noncoding RNAs (lncRNAs) play various important roles in the development of cancers. The widespread applications of ribosome profiling and ribosome nascent chain complex sequencing revealed that some short open reading frames of lncRNAs have micropeptide-coding potential. The resulting micropeptides have been shown to participate in N6-methyladenosine modification, tumor angiogenesis, cancer metabolism, and signal transduction. This review summarizes current information regarding the reported roles of lncRNA-encoded micropeptides in cancer, and explores the potential clinical value of these micropeptides in the development of anti-cancer drugs and prognostic tumor biomarkers.

Indexed as

CancerCoding potentiallncRNAMicropeptideOpen reading frame

Identifiers

PMID33088214
PMCPMC7565808

What OpenQuestion holds

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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.