Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors.


Journal

Journal of medical genetics
ISSN: 1468-6244
Titre abrégé: J Med Genet
Pays: England
ID NLM: 2985087R

Informations de publication

Date de publication:
07 2022
Historique:
received: 07 04 2021
accepted: 18 05 2021
pubmed: 1 12 2021
medline: 30 6 2022
entrez: 30 11 2021
Statut: ppublish

Résumé

Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention. We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%-10.3%. Based on the combined risk distribution, 33% of This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool (www.canrisk.org).

Sections du résumé

BACKGROUND
Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention.
METHODS
We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in
RESULTS
Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%-10.3%. Based on the combined risk distribution, 33% of
CONCLUSION
This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool (www.canrisk.org).

Identifiants

pubmed: 34844974
pii: jmedgenet-2021-107904
doi: 10.1136/jmedgenet-2021-107904
pmc: PMC9252860
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

632-643

Subventions

Organisme : Cancer Research UK
ID : A12677
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0801228
Pays : United Kingdom
Organisme : Medical Research Council
ID : G9901012
Pays : United Kingdom

Informations de copyright

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: DFE, ACA, APC, AL and TC are listed as creators of the BOADICEA model, which has been licensed to Cambridge Enterprise for commercialisation. UM has shares in Abcodia awarded to her by UCL.

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Auteurs

Andrew Lee (A)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Xin Yang (X)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Jonathan Tyrer (J)

Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.

Aleksandra Gentry-Maharaj (A)

MRC Clinical Trials Unit, Institute of Clinical Trials & Methodology, University College London, London, UK.

Andy Ryan (A)

MRC Clinical Trials Unit, Institute of Clinical Trials & Methodology, University College London, London, UK.

Nasim Mavaddat (N)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Alex P Cunningham (AP)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Tim Carver (T)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Stephanie Archer (S)

The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Goska Leslie (G)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Jatinder Kalsi (J)

Department of Women's Cancer, University College London Institute for Women's Health, London, UK.
Department of Epidemiology and Public Health, University College London Research, London, UK.

Faiza Gaba (F)

CRUK Barts Cancer Centre, Wolfson Institute of Preventive Medicine, London, UK.

Ranjit Manchanda (R)

CRUK Barts Cancer Centre, Wolfson Institute of Preventive Medicine, London, UK.
Department of Gynaecological Oncology, Barts Health NHS Trust, London, UK.
Department of Health Services Research, London School of Hygiene & Tropical Medicine, London, UK.

Simon Gayther (S)

Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California, USA.

Susan J Ramus (SJ)

University of New South Wales, School of Women's and Children's Health, Randwick, New South Wales, Australia.
Adult Cancer Program, Lowy Cancer Research Centre, University of New South Wales, Sydney, New South Wales, Australia.

Fiona M Walter (FM)

The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Marc Tischkowitz (M)

Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK.

Ian Jacobs (I)

Department of Women's Cancer, University College London Institute for Women's Health, London, UK.
University of New South Wales, School of Women's and Children's Health, Randwick, New South Wales, Australia.

Usha Menon (U)

MRC Clinical Trials Unit, Institute of Clinical Trials & Methodology, University College London, London, UK.

Douglas F Easton (DF)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.

Paul Pharoah (P)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.

Antonis C Antoniou (AC)

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK aca20@medschl.cam.ac.uk.

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Classifications MeSH