Evidence map›Paper›PMID 34301761›Full record

ArticleCancer research2021

Modeling High-Grade Serous Ovarian Carcinoma Using a Combination of

Katie Teng, Matthew J Ford, Keerthana Harwalkar, YuQi Li, Alain S Pacis, David Farnell, Nobuko Yamanaka, Yu-Chang Wang, Dunarel Badescu, Tuyet Nhung Ton Nu and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Advances in Immunocompetent Mouse and Rat Models.Cold Spring Harbor perspectives in medicine · 2024
    Review
  10. Harnessing preclinical models for the interrogation of ovarian cancer.Journal of experimental & clinical cancer research : CR · 2022
    Review
  11. Review
  12. Senescence induction dictates response to chemo- and immunotherapy in preclinical models of ovarian cancer.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  13. 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

14 authors at 4 institutions in 1 country.

Katie TengRosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada.ORCID 0000-0002-7459-4193
Matthew J FordRosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada.
Keerthana HarwalkarRosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada.
YuQi LiRosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada.
Alain S PacisCanadian Centre for Computational Genomics, McGill University, Montreal, Canada.
David FarnellDepartment of Pathology, Laboratory Medicine, University of British Columbia, Vancouver, British Columbia.
Nobuko YamanakaRosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada.
Yu-Chang WangDepartment of Human Genetics, McGill University, Montreal, Canada.
Dunarel BadescuDepartment of Human Genetics, McGill University, Montreal, Canada.
Tuyet Nhung Ton NuDepartment of Pathology, McGill University Hospital Research Institute, Montreal, Canada.
Jiannis RagoussisDepartment of Human Genetics, McGill University, Montreal, Canada.ORCID 0000-0002-8515-0934
David G HuntsmanDepartment of Pathology, Laboratory Medicine, University of British Columbia, Vancouver, British Columbia.
Jocelyne ArseneauDepartment of Pathology, McGill University Hospital Research Institute, Montreal, Canada.
Yojiro YamanakaRosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, Canada. yojiro.yamanaka@mcgill.ca.
McGill University Health Centre · CAMcGill Genome Centre · CABC Cancer Agency · CAMontreal Neurological Institute and Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer is the most lethal gynecologic cancer to date. High-grade serous ovarian carcinoma (HGSOC) accounts for most ovarian cancer cases, and it is most frequently diagnosed at advanced stages. Here, we developed a novel strategy to generate somatic ovarian cancer mouse models using a combination of

Indexed as

CRISPR-Cas SystemsDisease Models, AnimalGene EditingAMP-Activated Protein KinasesAnimalsBRCA1 ProteinCystadenocarcinoma, SerousDNA Copy Number VariationsElectroporationFallopian TubesFemaleHumansMiceMice, Inbred C57BLMice, KnockoutMutationAMP-Activated Protein KinasesBRCA1 ProteinBrca1 protein, mousePTEN PhosphohydrolasePten protein, mouseStk11 protein, mouseTrp53 protein, mouseTumor Suppressor Protein p53

Identifiers

PMID34301761
PMCPMC9397628
OpenAlexW3183913095

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.