Evidence map›Paper›PMID 37025585›Full record

ReviewFrontiers in oncology2023

Importance of long non-coding RNAs in the pathogenesis, diagnosis, and treatment of prostate cancer.

Mohammad Taheri, Elham Badrlou, Bashdar Mahmud Hussen, Amir Hossein Kashi, Soudeh Ghafouri-Fard, Aria Baniahmad

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.5field-weighted citation impact, top 4% 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

12 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  5. Review
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  12. Editorial: Epigenetics in prostate cancer.Frontiers in oncology · 2023
    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 3 institutions in 3 countries.

Mohammad TaheriInstitute of Human Genetics, Jena University Hospital, Jena, Germany.
Elham BadrlouMen's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Bashdar Mahmud HussenDepartment of Clinical Analysis, College of Pharmacy, Hawler Medical University, Erbil, Kurdistan, Iraq.
Amir Hossein KashiUrology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Soudeh Ghafouri-FardDepartment of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Aria BaniahmadInstitute of Human Genetics, Jena University Hospital, Jena, Germany.
Shahid Beheshti University of Medical Sciences · IRHawler Medical University · IQJena University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are regulatory transcripts with essential roles in the pathogenesis of almost all types of cancers, including prostate cancer. They can act as either oncogenic lncRNAs or tumor suppressor ones in prostate cancer. Small nucleolar RNA host genes are among the mostly assessed oncogenic lncRNAs in this cancer. PCA3 is an example of oncogenic lncRNAs that has been approved as a diagnostic marker in prostate cancer. A number of well-known oncogenic lncRNAs in other cancers such as DANCR, MALAT1, CCAT1, PVT1, TUG1 and NEAT1 have also been shown to act as oncogenes in prostate cancer. On the other hand, LINC00893, LINC01679, MIR22HG, RP1-59D14.5, MAGI2-AS3, NXTAR, FGF14-AS2 and ADAMTS9-AS1 are among lncRNAs that act as tumor suppressors in prostate cancer. LncRNAs can contribute to the pathogenesis of prostate cancer

Indexed as

biomarkerdiagnosticexpressionlncRNAprostate cancer

Identifiers

PMID37025585
PMCPMC10070735
OpenAlexW4328112918

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.