Evidence map›Paper›PMID 31469690›Full record

ReviewJournal of the Chinese Medical Association : JCMA2019

Cancer stem cell theory: Are we moving past the mist?

Kai-Feng Hung, Ting Yang, Shou-Yen Kao

Abstract readReview
In one paragraph

Review in Journal of the Chinese Medical Association : JCMA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  4. Article
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  6. Review
  7. Article
  8. Cancer Stem Cells and Their Therapeutic Usage.Advances in experimental medicine and biology · 2023
    Article
  9. Review
  10. Review
  11. Review
  12. 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

3 authors.

Kai-Feng HungDepartment of Medical Research, Division of Translational Research, Taipei Veterans General Hospital, Taipei, Taiwan, ROC.
Ting YangDepartment of Medical Research, Division of Translational Research, Taipei Veterans General Hospital, Taipei, Taiwan, ROC.
Shou-Yen KaoDepartment of Dentistry, School of Dentistry, National Yang-Ming University, Taipei, Taiwan, ROC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer stem cells (CSC) are a subpopulation of tumor cells that have superior capacities of self-renewal, metastatic dissemination, and chemoresistance. These characteristics resemble, to some extent, the outcome of certain biological processes, including epithelial-mesenchymal transition (EMT), autophagy, and cellular stress response. Indeed, it has been shown that the stimuli that induce these processes and CSC are overlapping, and CSC and tumor cells that underwent EMT or autophagy are much alike. However, as the cross talk between CSC, EMT, autophagy, and cellular stress is further explored, these processes are also found to have an opposing role in CSC, depending on the condition and status of cells. This contextual effect is likely due to overwhelming reliance on CSC markers for their identification, and/or discrepancies in recognition of CSC as a particular cell population or cellular state. In this review, we summarize how EMT, autophagy, and cellular stress response are tied or unwound with CSC. We also discuss the current view of CSC theory evolved from the emphasis of heterogenicity and plasticity of CSC.

Indexed as

AnimalsAutophagyCell PlasticityEpithelial-Mesenchymal TransitionHumansNeoplastic Stem CellsStress, Physiological

Identifiers

PMID31469690
PMCPMC13048017

What OpenQuestion holds

Textmetadata
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.