Evidence map›Paper›PMID 40710326›Full record

ReviewCells2025

Regulatory Functions of microRNAs in Cancer Stem Cells: Mechanism, Facts, and Perspectives.

Xingmei Mao, Sixue Peng, Yan Lu, Linjiang Song

Abstract readReview
In one paragraph

Review in Cells, 2025. 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
–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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
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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

4 authors.

Xingmei MaoSchool of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.ORCID 0009-0001-9299-7674
Sixue PengSchool of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Yan LuSchool of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Linjiang SongSchool of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.

Funding

Linjiang Song 24NSFSC5610Linjiang Song 82305011Linjiang Song 82404939
6 · The paper itself

Abstract

Cancer represents a significant global health hazard marked by elevated morbidity and mortality rates. Furthermore, the majority of tumor therapies encounter challenges, including metastasis, recurrence, and drug resistance. Consequently, it is essential to identify a specific and efficient tumor treatment approach. In recent years, the ongoing investigation and comprehension of tumors have led to significant attention towards cancer stem cells (CSCs). CSCs can facilitate tumor progression via self-renewal, differentiation capabilities, and multidrug resistance. Their function as a fundamental contributor to tumor heterogeneity, drug resistance, recurrence, and metastasis has emerged as a significant focus in cancer therapy research. In recent years, microRNAs (miRNAs) have been identified as crucial post-transcriptional regulators in biological processes, including chemosensitivity, self-renewal, apoptosis, invasion, and metastasis of cancer stem cells (CSCs). This paper systematically reviews the molecular mechanisms through which miRNAs influence the characteristics of cancer stem cells by targeting essential genes (e.g., SOX2,

Indexed as

MicroRNAsNeoplasmsNeoplastic Stem CellsAnimalsGene Expression Regulation, NeoplasticHumansSignal TransductionMicroRNAsbiomarkerscancer stem cellschemotherapy resistancemiRNAssignaling pathways

Identifiers

PMID40710326
PMCPMC12293480

What Socratic 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 Socratic graph.