Evidence map›Paper›PMID 33598508›Full record

ArticleRegenerative therapy2021

miRNA signaling networks in cancer stem cells.

Kosuke Yoshida, Yusuke Yamamoto, Takahiro Ochiya

Open access · goldAbstract read
In one paragraph

Article in Regenerative therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

24 citing papers in PubMed, 43 citations in OpenAlex.

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  11. DNA repair in tumor radioresistance: insights from fruit flies genetics.Cellular oncology (Dordrecht, Netherlands) · 2024
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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 at 2 institutions in 1 country.

Kosuke YoshidaDivision of Cellular Signaling, National Cancer Center Research Institute, Tokyo, Japan.
Yusuke YamamotoDivision of Cellular Signaling, National Cancer Center Research Institute, Tokyo, Japan.
Takahiro OchiyaDepartment of Molecular and Cellular Medicine, Institute of Medical Science, Tokyo Medical University, Tokyo, Japan.
Nagoya University · JPTokyo Medical University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer stem cells (CSCs) are a small cell subpopulation in many cancer types and are involved in various processes of tumor progression, such as initiation, metastasis and recurrence. The distinguished features of CSCs include a variety of biological properties, including self-renewal, multidifferentiation, stemness marker expression, and resistance to chemotherapy and radiotherapy. Despite their great potential of clinical importance, the CSC signaling pathways are not well understood at the molecular level. MicroRNAs (miRNAs) are a class of endogenous noncoding RNAs that play an important role in the regulation of several cellular, physiological, and developmental processes. Aberrant miRNA expression is associated with many human diseases, including cancer. miRNAs have been implicated in the regulation of CSC properties; therefore, a better understanding of miRNA-induced modulation of CSC gene expression could aid in the identification of promising biomarkers and therapeutic targets. In the present review, we summarize the major findings of the impacts of miRNAs on CSC signaling networks; we then discuss the recent advances that have improved our understanding of CSC regulation by miRNA-mediated signaling networks and that may lead to the development of miRNA therapeutics specifically targeting CSCs.

Indexed as

Cancer stem cells (CSCs)Metastasis and recurrencemicroRNATherapeutic resistanceTumor initiation

Identifiers

PMID33598508
PMCPMC7848775
OpenAlexW3126301973

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.