Evidence map›Paper›PMID 25064729›Full record

ReviewMedical oncology (Northwood, London, England)2014

Cancer stem cell detection and isolation.

Meysam Moghbeli, Faezeh Moghbeli, Mohammad Mahdi Forghanifard, Mohammad Reza Abbaszadegan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Medical oncology (Northwood, London, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

35 citing papers in PubMed, 82 citations in OpenAlex.

  1. Article
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  9. Capilliposide fromChinese herbal medicines · 2022
    Article
  10. Review
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  12. Article
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  15. Targeting cancer stem cell pathways for cancer therapy.Signal transduction and targeted therapy · 2020
    Review
  16. Ovarian cancer stem cells and targeted therapy.Journal of ovarian research · 2019
    Review
  17. Review
  18. Article
  19. 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 at 3 institutions in 1 country.

Meysam MoghbeliDivision of Human Genetics, Immunology Research Center, Avicenna Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
Faezeh Moghbeli
Mohammad Mahdi Forghanifard
Mohammad Reza Abbaszadegan
Mashhad University of Medical Sciences · IRIslamic Azad University, Damghan Branch · IRIslamic Azad University, Mashhad · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Only 10 % of cancer-related deaths result from primary tumors; most are caused by metastatic tumors. It is believed that the metastatic power of tumor cells is attributed to features of a stem cell-like subpopulation of tumor cells known as cancer stem cells (CSCs). Cancer stem cells are resistant to chemotherapeutic treatments and can induce dormancy in tumor cells for long periods. Detection, isolation, and characterization of CSCs in solid tumors are hallmarks of cancer-targeted therapies in recent years. There are inevitable similarities between normal and cancer stem cells; therefore, finding specific methods or markers to differentiate them is critical to cancer therapies. Considering CSCs involvement in tumor relapse and chemotherapeutic resistance, identification of such cells in tumors is imperative for effective targeted therapy. The present review introduces practical and specific protocols used to isolate CSCs from solid tumors from colon, esophagus, liver, breast, brain, and cervix.

Indexed as

Cell SeparationNeoplastic Stem CellsAnimalsBiomarkers, TumorHumansMiceNeoplasmsBiomarkers, Tumor

Identifiers

PMID25064729
OpenAlexW1992274952

What OpenQuestion 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 OpenQuestion graph.