Evidence map›Paper›PMID 38633804›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Exome sequencing identifies

Ed M Dicks, Jonthan P Tyrer, Suzana Ezquina, Michelle Jones, John Baierl, Pei-Chen Peng, Michael Diaz, Ellen Goode, Stacey J Winham, Thilo Dörk and 11 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors at 11 institutions in 6 countries.

Ed M DicksDepartment of Public Health and Primary Care, University of Cambridge, UK.
Jonthan P TyrerDepartment of Public Health and Primary Care, University of Cambridge, UK.
Suzana EzquinaDepartment of Public Health and Primary Care, University of Cambridge, UK.
Michelle JonesDepartment of Biomedical Sciences, Cedars-Sinai Medical Centre, Los Angeles, USA.
John BaierlDepartment of Computational Biomedicine, Cedars-Sinai Medical Centre, Los Angeles, USA.
Pei-Chen PengDepartment of Computational Biomedicine, Cedars-Sinai Medical Centre, Los Angeles, USA.
Michael DiazDepartment of Biomedical Sciences, Cedars-Sinai Medical Centre, Los Angeles, USA.
Ellen GoodeMayo Clinic, Rochester, MN, USA.
Stacey J WinhamMayo Clinic, Rochester, MN, USA.
Thilo DörkGynaecology Research Unit, Hannover Medical School, Hannover, Germany.
Toon Van GorpDepartment of Gynaecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium.
Ana De FazioCentre for Cancer Research, The Westmead Institute for Medical Research, The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW and Department of Gynaecological Oncology, Westmead Hospital, Sydney, New South Wales, Australia.
David BowtellCancer Genomics and Genetics and Women's Cancer Programs, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Kunle OdunsiUniversity of Chicago Medicine Comprehensive Cancer Center, Chicago, IL, USA.
Kirsten MoysichDivision of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
Marina PavanelloSchool of Clinical Medicine, Faculty of Medicine and Health, University of NSW, Sydney, NSW, Australia Center for Research in Immuno-Oncology, Albert Einstein Israelite Hospital, São Paulo, SP, Brazil.
Ian CampbellCancer Genetics Laboratory, Peter MacCallum Cancer Centre, Melbourne, Australia.
James D BrentonDepartment of Oncology, University of Cambridge, UK.
Susan J RamusSchool of Clinical Medicine, Faculty of Medicine and Health, University of NSW, Sydney, NSW, Australia Adult Cancer Program, Lowy Cancer Research Centre, University of NSW, Sydney, NSW, Australia.
Simon A GaytherDepartment of Biomedical Sciences, Cedars-Sinai Medical Centre, Los Angeles, USA.
Paul D P PharoahDepartment of Computational Biomedicine, Cedars-Sinai Medical Centre, Los Angeles, USA.
Cedars-Sinai Medical Center · USUniversity of Cambridge · GBMayo Clinic · USPeter MacCallum Cancer Centre · AUCancer Institute of New South Wales · AUHospital Israelita Albert Einstein · BRKU Leuven · BEMedizinische Hochschule Hannover · DERoswell Park Comprehensive Cancer Center · USUniversity of Chicago · USWestmead Institute for Medical Research · AU

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI AKHILESH PANDEY · 1985 to 2026
$151.3M
Relating Molecular Subgroups of Endometriosis-Associated Ovarian Cancers to Survival and RiskR01CA248288 · NCI · MAYO CLINIC ROCHESTER · PI Stacey J Winham · 2021 to 2026
$4.8M
The contribution of rare alleles to ovarian cancer in the populationR01CA178535 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI GAYTHER, SIMON ANDREW, PHAROAH, PAUL · 2013 to 2017
$3.0M
Identifying new drivers of ovarian cancer from the non-coding genome by converging germline risk variants and somatic mutationsR00CA256519 · NCI · CEDARS-SINAI MEDICAL CENTER · PI PENG, PEI-CHEN · 2023 to 2025
$745k
NCI NIH HHS P30 CA015083NCI NIH HHS R00 CA256519NCI NIH HHS R01 CA178535NCI NIH HHS R01 CA248288
6 · The paper itself

Abstract

Rare, germline loss-of-function variants in a handful of genes that encode DNA repair proteins have been shown to be associated with epithelial ovarian cancer with a stronger association for the high-grade serous hiostotype. The aim of this study was to collate exome sequencing data from multiple epithelial ovarian cancer case cohorts and controls in order to systematically evaluate the role of coding, loss-of-function variants across the genome in epithelial ovarian cancer risk. We assembled exome data for a total of 2,573 non-mucinous cases (1,876 high-grade serous and 697 non-high grade serous) and 13,925 controls. Harmonised variant calling and quality control filtering was applied across the different data sets. We carried out a gene-by-gene simple burden test for association of rare loss-of-function variants (minor allele frequency < 0.1%) with all non-mucinous ovarian cancer, high grade serous ovarian cancer and non-high grade serous ovarian cancer using logistic regression adjusted for the top four principal components to account for cryptic population structure and genetic ancestry. Seven of the top 10 associated genes were associations of the known ovarian cancer susceptibility genes

Identifiers

PMID38633804
PMCPMC11023670
OpenAlexW4393853027

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.