Evidence map›Paper›PMID 31277278›Full record

ReviewCancers2019

Ovarian Cancer Stem Cells: Role in Metastasis and Opportunity for Therapeutic Targeting.

Xingyue Zong, Kenneth P Nephew

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

39 citing papers in PubMed, 59 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Leader Cells: Invade and Evade-The Frontline of Cancer Progression.International journal of molecular sciences · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Antioxidants (Basel, Switzerland) · 2023
    Article
  13. Article
  14. Review
  15. Review
  16. Targeting the Retinoic Acid Pathway to Eradicate Cancer Stem Cells.International journal of molecular sciences · 2023
    Review
  17. Review
  18. Article
  19. The senescence-associated secretory phenotype in ovarian cancer dissemination.American journal of physiology. Cell physiology · 2022
    Review
  20. 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

2 authors at 2 institutions in 1 country.

Xingyue ZongMedical Sciences, Indiana University School of Medicine, Bloomington, IN 47405, USA.
Kenneth P NephewMedical Sciences, Indiana University School of Medicine, Bloomington, IN 47405, USA. knephew@indiana.edu.
Indiana University Bloomington · USIndiana University School of Medicine

Funding

DOD Peer Reviewed Cancer Research Program C160425Ovarian Cancer Research Fund Alliance 458788
6 · The paper itself

Abstract

Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Cancer stem cells (CSCs) that exist within the bulk tumor survive first-line chemotherapy and contribute to resistant disease with metastasis. Understanding the key features of CSC biology provides valuable opportunities to develop OCSC-directed therapeutics, which will eventually improve the clinical outcomes of patients. Although significant developments have occurred since OCSCs were first described, the involvement of CSCs in ovarian tumor metastasis is not fully understood. Here, we discuss putative CSC markers and the fundamental role of CSCs in facilitating tumor dissemination in OC. Additionally, we focus on promising CSC-targeting strategies in preclinical and clinical studies of OC and discuss potential challenges in CSC research.

Indexed as

cancer stem cellsmetastasisovarian cancer

Identifiers

PMID31277278
PMCPMC6678643
OpenAlexW2953734977

What OpenQuestion 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 OpenQuestion graph.