Evidence map›Paper›PMID 34367481›Full record

ReviewWorld journal of stem cells2021

Reporter gene systems for the identification and characterization of cancer stem cells.

Nohemí Salinas-Jazmín, Arely Rosas-Cruz, Marco Velasco-Velázquez

Open access · hybridAbstract readReview
In one paragraph

Review in World journal of stem cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Protein Marker-Dependent Drug Discovery Targeting Breast Cancer Stem Cells.International journal of molecular sciences · 2025
    Review
  2. Review
  3. Article
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 1 institution in 1 country.

Nohemí Salinas-JazmínDepartment of Pharmacology, School of Medicine, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
Arely Rosas-CruzDepartment of Pharmacology, School of Medicine, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
Marco Velasco-VelázquezDepartment of Pharmacology, School of Medicine, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico. marcovelasco@unam.mx.
Universidad Nacional Autónoma de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer stem cells (CSCs) are tumor cells that share functional characteristics with normal and embryonic stem cells. CSCs have increased tumor-initiating capacity and metastatic potential and lower sensitivity to chemo- and radiotherapy, with important roles in tumor progression and the response to therapy. Thus, a current goal of cancer research is to eliminate CSCs, necessitating an adequate phenotypic and functional characterization of CSCs. Strategies have been developed to identify, enrich, and track CSCs, many of which distinguish CSCs by evaluating the expression of surface markers, the initiation of specific signaling pathways, and the activation of master transcription factors that control stemness in normal cells. We review and discuss the use of reporter gene systems for identifying CSCs. Reporters that are under the control of aldehyde dehydrogenase 1A1, CD133, Notch, Nanog homeobox, Sex-determining region Y-box 2, and POU class 5 homeobox can be used to identify CSCs in many tumor types, track cells in real time, and screen for drugs. Thus, reporter gene systems, in combination with

Indexed as

Anticancer drugsCancerCancer stem cellsCancer stem cells markerGene reporter systemsPluripotency transcription factorsPreclinical analysis

Identifiers

PMID34367481
PMCPMC8316869
OpenAlexW3183209940

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.