Evidence map›Paper›PMID 29468856›Full record

ReviewJournal of gynecologic oncology2018

Chemoresistance in ovarian cancer: exploiting cancer stem cell metabolism.

Shan Shan Li, Jing Ma, Alice S T Wong

Abstract readReview
In one paragraph

Review in Journal of gynecologic oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
98citing 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

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

  1. Pooled it
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  18. Advances in ovarian tumor stem cells and therapy.Cell biochemistry and biophysics · 2024
    Review
  19. Article
  20. Review

38 more citing papers are in PubMed but not listed here.

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.

Shan Shan LiSchool of Biological Sciences, The University of Hong Kong, Hong Kong, China.ORCID 0000-0002-4092-4879
Jing MaSchool of Biological Sciences, The University of Hong Kong, Hong Kong, China.ORCID 0000-0001-6347-8552
Alice S T WongSchool of Biological Sciences, The University of Hong Kong, Hong Kong, China. awong1@hku.hk.ORCID 0000-0002-0676-6475

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is most deadly gynecologic malignancies worldwide. Chemotherapy is the mainstay treatment for ovarian cancer. Despite the initial response is promising, frequent recurrence in patients with advanced diseases remains a therapeutic challenge. Thus, understanding the biology of chemoresistance is of great importance to overcome this challenge and will conceivably benefit the survival of ovarian cancer patients. Although mechanisms underlying the development of chemoresistance are still ambiguous, accumulating evidence has supported an integral role of cancer stem cells (CSCs) in recurrence following chemotherapy. Recently, tumor metabolism has gained interest as a reason of chemoresistance in tumors and chemotherapeutic drugs in combination with metabolism targeting approaches has been found promising in overcoming therapeutic resistance. In this review, we will summarize recent studies on CSCs and metabolism in ovarian cancer and discuss possible role of CSCs metabolism in chemoresistance.

Indexed as

Drug Resistance, Neoplasm3-Phosphoinositide-Dependent Protein KinasesAntineoplastic AgentsEnzyme InhibitorsFemaleGlycolysisHumansNeoplasm Recurrence, LocalNeoplastic Stem CellsOvarian NeoplasmsOxidative Phosphorylation3-Phosphoinositide-Dependent Protein KinasesAntineoplastic AgentsEnzyme InhibitorsPDPK1 protein, humanCancer Stem CellsDrug Resistance, NeoplasmMetabolismOvarian Neoplasms

Identifiers

PMID29468856
PMCPMC5823988

What OpenQuestion holds

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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.