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

By H. Davies, D. Głodzik, S. Morganella, L. Yates, J. Staaf, Xueqing Zou, Manasa Ramakrishna, Sancha Martin, S. Boyault, Anieta M. Sieuwerts and 23 more. Nature Medicine, 2017

946 citations recorded by the source corpus.

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. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six 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 tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (∼1–5%) who could have selective therapeutic sensitivity to PARP inhibition.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/832a0e972e79dbe5a66f63f24860aa273171515d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. K. Polyak
2. C. Lord

In Molecular Biology

1. K. Polyak
2. Edwin Cuppen
3. Roel Janssen
4. C. Lord
5. Francis Blokzijl
6. R. van Boxtel
7. R. Weinberg

Citations in the corpus

• Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer. (2018, neutral): “These cells rely on microhomology-mediated end joining to repair double strand DNA breaks, also known as alternative nonhomologous end-joining (Davies et al., 2017; Nik-Zainal et al., 2012, 2016; Tutt et al., 2001).”
• MutationalPatterns: comprehensive genome-wide analysis of mutational processes (2016, background): “Thus, patterns of somatic mutations can serve as readout of the mutational processes that have been active and as proxies for the molecular perturbations in a tumour [6].”
• A decade of clinical development of PARP inhibitors in perspective (2019, background): “These tumours accumulate small insertions-deletions and loss-of-heterozygosity events [57].”
• Insights into molecular classifications of triple-negative breast cancer: improving patient selection for treatment (2019, methodology): “With advances in sequencing technologies, an algorithm using whole-genome sequencing, also known as the HRDetect model, identified six mutational signatures present in germline BRCA1/2-mutated tumors that were then found to also predict HR deficiency in sporadic tumors in the Sanger data set (97).”