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

Andrew Lee; Xin Yang; Jonathan Tyrer; Aleksandra Gentry-Maharaj; Andy Ryan; Nasim Mavaddat; Alex P Cunningham; Tim Carver; Stephanie Archer; Goska Leslie; Jatinder Kalsi; Faiza Gaba; Ranjit Manchanda; Simon Gayther; Susan J Ramus; Fiona M Walter; Marc Tischkowitz; Ian Jacobs; Usha Menon; Douglas F Easton; Paul Pharoah; Antonis C Antoniou

doi:10.1136/jmedgenet-2021-107904

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

J Med Genet. 2022 Jul;59(7):632-643. doi: 10.1136/jmedgenet-2021-107904. Epub 2021 Nov 29.

Authors

Andrew Lee¹, Xin Yang¹, Jonathan Tyrer², Aleksandra Gentry-Maharaj³, Andy Ryan³, Nasim Mavaddat¹, Alex P Cunningham¹, Tim Carver¹, Stephanie Archer⁴, Goska Leslie¹, Jatinder Kalsi^{5

6}, Faiza Gaba⁷, Ranjit Manchanda^{7

8

9}, Simon Gayther¹⁰, Susan J Ramus^{11

12}, Fiona M Walter⁴, Marc Tischkowitz¹³, Ian Jacobs^{5

11}, Usha Menon³, Douglas F Easton^{1

2}, Paul Pharoah^{1

2}, Antonis C Antoniou¹⁴

Affiliations

¹ Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
² Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
³ MRC Clinical Trials Unit, Institute of Clinical Trials & Methodology, University College London, London, UK.
⁴ The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁵ Department of Women's Cancer, University College London Institute for Women's Health, London, UK.
⁶ Department of Epidemiology and Public Health, University College London Research, London, UK.
⁷ CRUK Barts Cancer Centre, Wolfson Institute of Preventive Medicine, London, UK.
⁸ Department of Gynaecological Oncology, Barts Health NHS Trust, London, UK.
⁹ Department of Health Services Research, London School of Hygiene & Tropical Medicine, London, UK.
¹⁰ Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California, USA.
¹¹ University of New South Wales, School of Women's and Children's Health, Randwick, New South Wales, Australia.
¹² Adult Cancer Program, Lowy Cancer Research Centre, University of New South Wales, Sydney, New South Wales, Australia.
¹³ Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK.
¹⁴ Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK [email protected].

Abstract

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 BRCA1, BRCA2, RAD51C, RAD51D and BRIP1, a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively.

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 RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk.

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).

Keywords: clinical decision-making; early diagnosis; genetic counseling; genetics; public health.

Publication types

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

MeSH terms

Breast Neoplasms*
Carcinoma, Ovarian Epithelial / epidemiology
Carcinoma, Ovarian Epithelial / genetics
Female
Genetic Predisposition to Disease
Humans
Multifactorial Inheritance / genetics
Ovarian Neoplasms* / diagnosis
Ovarian Neoplasms* / epidemiology
Ovarian Neoplasms* / genetics
Risk Factors

Abstract

Publication types

MeSH terms

Grants and funding