Population-based germline testing of BRCA1, BRCA2, and PALB2 in breast cancer patients in the United Kingdom: Evidence to support extended testing and definition of groups who may not require testing

D. Gareth Evans, Emma r. Woodward, George j. Burghel, Sophie Allen, Beth Torr, Monica Hamill, Grace Kavanaugh, Mike Hubank, Stephen Bremner, Christopher i. Jones, Helene Schlecht, Susan Astley, Sarah Bowers, Sarah Gibbons, Helen Ruane, Caroline Fosbury, Sacha j. Howell, Claire Forde, Fiona Lalloo, William g. NewmanMiriam j. Smith, Anthony Howell, Clare Turnbull, Ashu Gandhi

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose
To assess the contribution of germline pathogenic variants (PVs) in a population-based series of breast cancers and the best strategy to improve detection rates.

Methods
Three cohort studies were utilised, including a hospital-based series identified from new UK mainstream testing criteria (Group-1), offering testing to all women (Group-2-BRCA-DIRECT), and a Greater Manchester cohort study recruited from the mammography screening population (Group-3-PROCAS). DNA samples from women with breast cancer were sequenced for PVs in BRCA1, BRCA2, and PALB2. The Manchester Score-(MS) was used at different points thresholds. Current mainstream criteria include women diagnosed <40 years and all triple negative <60 years or an MS≥15.

Results
Thirty-six PVs (BRCA1=9, BRCA2=18, PALB2=9) were identified amongst 1061 women with breast cancer (3.4%). Mainstreaming criteria identified 21/36 (58%) of PVs by testing 190 women; detection rate (DR=8.4%) specificity=83.5%. A better detection rate was found using an MS threshold of 12-points with 66.7%-(24/36) sensitivity and 85.7% specificity in 171 women. No PVs were identified in 158 women with grade-1 invasive cancers. The best strategy to detect all PVs was an MS≥3 with specificity of 32.6%.

Conclusion
In order to detect higher PV rates on a population basis the best strategy is to reduce the MS threshold for genetic testing.
Original languageEnglish
Article number100849
Number of pages8
JournalGenetics in Medicine Open
Volume2
Early online date25 Nov 2023
DOIs
Publication statusPublished - 1 Jan 2024

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