Evidence map›Paper›PMID 37209205›Full record

ReviewHuman cell2023

Roles of non-coding RNAs in the metabolism and pathogenesis of bladder cancer.

Daniel Ruben Akiola Sanya, Djamila Onésime

Abstract readReview
PubMed Publisher
In one paragraph

Review in Human cell, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Circulating long non-coding RNANon-coding RNA research · 2024
    Article
  4. 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

2 authors at 2 institutions in 1 country.

Daniel Ruben Akiola SanyaMicalis Institute, Diversité génomique et fonctionnelle des levures, domaine de Vilvert, Université Paris-Saclay, INRAE, AgroParisTech, 78350, Jouy-en-Josas, France. sanyadaniel86@yahoo.com.ORCID http://orcid.org/0000-0001-9493-3669
Djamila OnésimeMicalis Institute, Diversité génomique et fonctionnelle des levures, domaine de Vilvert, Université Paris-Saclay, INRAE, AgroParisTech, 78350, Jouy-en-Josas, France.
AgroParisTech · FRUniversité Paris-Saclay · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer (BC) is featured as the second most common malignancy of the urinary tract worldwide with few treatments leading to high incidence and mortality. It stayed a virtually intractable disease, and efforts to identify innovative and effective therapies are urgently needed. At present, more and more evidence shows the importance of non-coding RNA (ncRNA) for disease-related study, diagnosis, and treatment of diverse types of malignancies. Recent evidence suggests that dysregulated functions of ncRNAs are closely associated with the pathogenesis of numerous cancers including BC. The detailed mechanisms underlying the dysregulated role of ncRNAs in cancer progression are still not fully understood. This review mainly summarizes recent findings on regulatory mechanisms of the ncRNAs, long non-coding RNAs, microRNAs, and circular RNAs, in cancer progression or suppression and focuses on the predictive values of ncRNAs-related signatures in BC clinical outcomes. A deeper understanding of the ncRNA interactive network could be compelling framework for developing biomarker-guided clinical trials.

Indexed as

MicroRNAsRNA, Long NoncodingUrinary Bladder NeoplasmsHumansRNA, CircularRNA, UntranslatedMicroRNAsRNA, CircularRNA, Long NoncodingRNA, UntranslatedBladder cancerCircular RNAsLong non-coding RNAsmicroRNAs

Identifiers

PMID37209205
OpenAlexW4377137800

What Socratic 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 Socratic graph.