Integrating breast tumour homologous recombination deficiency status to aid germline BRCA1 and BRCA2 variant classification.

[BACKGROUND] Pathogenic germline variants in certain genes are associated with somatic tumour mutation signatures. The use of somatic tumour mutation data has the potential to improve the identification of true pathogenic variants but remains underexplored. We investigated the integration of tumour homologous recombination (HR) deficiency status as a predictor of pathogenicity for germline BRCA1 and BRCA2 variants, building on the established link between HR deficiency and germline pathogenic variants in these genes.

[METHODS] We analysed breast tumour whole-genome sequence and matching germline data from 350 patients across four datasets: Familial Breast Cancer (N = 77), The Cancer Genome Atlas (TCGA-BRCA, N = 96), the MAGIC study (N = 136), and Q-IMPROvE (N = 41). A total of 15,156 germline variants (including structural variations) in BRCA1, BRCA2, and other cancer genes (ATM, BARD1, BRIP1, CHEK2, PALB2, PTEN, RAD51C, RAD51D, TP53) underwent variant curation. Patients were categorised based on germline classification as BRCA1 positive (N = 27), BRCA2 positive (N = 21), and BRCA1/2 negative (N = 232), excluding those with BRCA1/2 variants of uncertain significance (N = 8) and pathogenic or only uncertain variants in other cancer genes (N = 62). Somatic HR status (deficient or proficient) was predicted using three algorithms: HRDetect, CHORD, and HRDsum. HR-deficient and HR-proficient status were significant predictors of germline BRCA1/2 pathogenic variant status (positive and negative directions).

[FINDINGS] The CHORD algorithm, which estimates BRCA1 and BRCA2 subtype specifically, added precision contributing evidence towards pathogenicity for the corresponding gene, reaching pathogenic moderate strength for the relevant gene-subtype. Finally, we assessed CHORD HR predictions for variants of uncertain significance in BRCA1 and BRCA2, and reported their tumour HR status for potential use as additional evidence in variant curation.

[INTERPRETATION] Analysis across multiple tumour whole-genome sequencing datasets has shown that HR status prediction algorithms can separate profiles for BRCA1 and BRCA2 pathogenic variants and provide further evidence at increased weight to aid in the classification of germline BRCA1 and BRCA2 variants. Tumour sequencing offers a promising strategy for reducing the uncertainty in germline variant interpretation.

[FUNDING] This work was funded by the National Breast Cancer Foundation.