Evidence map›Paper›PMID 34680390›Full record

ArticleCancers2021

Genomic Sub-Classification of Ovarian Clear Cell Carcinoma Revealed by Distinct Mutational Signatures.

Douglas V N P Oliveira, Tine H Schnack, Tim S Poulsen, Anne P Christiansen, Claus K Høgdall, Estrid V Høgdall

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

12 citing papers in PubMed, 21 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Douglas V N P OliveiraMolecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, DK-2730 Herlev, Denmark.
Tine H SchnackDepartment of Gynecology, Juliane Marie Centre, Rigshospitalet, University of Copenhagen, DK-2100 Copenhagen, Denmark.
Tim S PoulsenMolecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, DK-2730 Herlev, Denmark.
Anne P ChristiansenDepartment of Pathology, Rigshospitalet, University of Copenhagen, DK-2100 Copenhagen, Denmark.
Claus K HøgdallDepartment of Gynecology, Juliane Marie Centre, Rigshospitalet, University of Copenhagen, DK-2100 Copenhagen, Denmark.
Estrid V HøgdallMolecular Unit, Department of Pathology, Herlev Hospital, University of Copenhagen, DK-2730 Herlev, Denmark.ORCID 0000-0003-4689-5658
University of Copenhagen · DK

Funding

Danish Cancer Research Foundation N/AHerlev Hospital Research Council N/AThe Mermaid Foundation N/A
6 · The paper itself

Abstract

Ovarian clear cell carcinoma (OCCC) is characterized by dismal prognosis, partially due to its low sensitivity to standard chemotherapy regimen. It is also well-known for presenting unique molecular features in comparison to other epithelial ovarian cancer subtypes. Here, we aim to identify potential subgroups of patients in order to (1) determine their molecular features and (2) characterize their mutational signature. Furthermore, we sought to perform the investigation based on a potentially clinically relevant setting. To that end, we assessed the mutational profile and genomic instability of 55 patients extracted from the Gynecologic Cancer Database (DGCD) by using a panel comprised of 409 cancer-associated genes and a microsatellite assay, respectively; both are currently used in our routine environment. In accordance with previous findings,

Indexed as

clear cell carcinomagenomic instabilitymutational signatureNGSovarian cancerpatient stratificationtranslational medicine

Identifiers

PMID34680390
PMCPMC8533704
OpenAlexW3207545552

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.