HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures

Abstract

Approximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly (ADP-ribose) polymerase (PARP) inhibitors. Germline and/or somatic mutations in BRCA1/BRCA2 in other cancer types also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2 deficient tumours have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns or mutational signatures were associated with BRCA1/BRCA2 dysfunction. We used a supervised lasso logistic regression model to identify six critically distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2 deficient samples. HRDetect identifies BRCA1/BRCA2 deficient tumours with 98.7% sensitivity (AUC 0.98). Application of this model in a cohort of 560 breast cancer patients with 22 known germline BRCA1/BRCA2 mutation carriers, allowed us to identify an additional 22 somatic BRCA1/BRCA2 null tumours and 47 tumours with functional BRCA1/BRCA2-deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers, and demonstrate efficacy on alternative sequencing strategies. Integrating all classes of mutational signatures thus reveals a larger proportion of breast cancer patients (of up to 22%) than hitherto appreciated (~1-5%) that could have selective therapeutic sensitivity to PARP-inhibition.

Homologous recombination deficiency and host anti-tumor immunity in triple-negative breast cancer

“…A second approach defined six new mutational signatures from whole genome sequencing of breast cancer patients that were predictive of BRCA1/2 deficiency. They integrated these in a weighted model, termed 'HRDetect,' which identifies BRCA1/BRCA2-deficient tumors with high (98.7%) sensitivity and also identifies tumors with somatic loss or functional BRCA1/BRCA2 deficiency [36,37]. HRDetect was validated in an independent dataset and evaluation for clinical utility is ongoing [37].…”

Molecular signatures in breast cancer

“…In a small pilot, the HRDetect score correlated with pathological response to neoadjuvant anthracycline chemotherapy [91]. This collective data indicates the potential for complex genomescale mutation data to be distilled into a simple diagnostic score that could be used clinically to identify patients who may gain benefit from certain chemotherapies or PARPi.…”

“…Great interest has therefore been applied to develop 'biomarkers' of HR deficiency based on the pattern of somatic alterations identified in the tumour genome. These genome-based 'tools' utilise either aCGH or SNP array based genome data [64][65][66][67][68][69][70][71] or more recently whole genome sequencing data [91].…”

“…A recent study applied whole genome sequencing data of breast cancers to develop a probabilistic predictor of HR deficiency [91]. Logistic lasso regression modelling was used to incorporate six genomic parameters, including substitution and rearrangement signatures and the HRD Index (described above) into a predictor, termed HRDetect.…”

How to measure homologous recombination deficiency in ovarian cancer

“…Further studies are needed to confirm these findings and also to evaluate whether these gene expression signatures are truly predictive of response to therapy rather than being only prognostic. More recently, based on the fact that abrogation of BRCA1 and BRCA2 function leads to a characteristic set of mutational signatures, a new HRD assay (HRDetect) has been developed which was able to identify six distinguishing mutational signatures predictive of BRCA1/ BRCA2 deficiency [34]. In the paper from Davies et al, it was found that integrating all of the classes of mutational signatures reveals a larger proportion of individuals harbouring BRCA1/BRCA2 deficiency.…”