Evidence map›Paper›PMID 27458531›Full record

ArticleCancer biology & medicine2016

Genetic and molecular changes in ovarian cancer.

Robert L Hollis, Charlie Gourley

Erratum issuedAbstract read
In one paragraph

Article in Cancer biology & medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed
–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

64 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Article
  6. Pathogenesis of Endometriosis and Endometriosis-Associated Cancers.International journal of molecular sciences · 2024
    Review
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. The Emerging Role of Chromatin Remodeling Complexes in Ovarian Cancer.International journal of molecular sciences · 2022
    Review
  18. MAPK Pathway Genetic Alterations Are Associated with Prolonged Overall Survival in Low-Grade Serous Ovarian Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022
    Article
  19. Article
  20. Review

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Robert L HollisEdinburgh Cancer Research UK Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XR, UK.
Charlie GourleyEdinburgh Cancer Research UK Centre, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XR, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer represents the most lethal gynecological malignancy in the developed world, and can be divided into five main histological subtypes: high grade serous, endometrioid, clear cell, mucinous and low grade serous. These subtypes represent distinct disease entities, both clinically and at the molecular level. Molecular analysis has revealed significant genetic heterogeneity in ovarian cancer, particularly within the high grade serous subtype. As such, this subtype has been the focus of much research effort to date, revealing molecular subgroups at both the genomic and transcriptomic level that have clinical implications. However, stratification of ovarian cancer patients based on the underlying biology of their disease remains in its infancy. Here, we summarize the molecular changes that characterize the five main ovarian cancer subtypes, highlight potential opportunities for targeted therapeutic intervention and outline priorities for future research.

Indexed as

histological subtypesmolecular geneticsmolecular subgroupingOvarian cancerovary

Identifiers

PMID27458531
PMCPMC4944549

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.