HRProfiler Detects Homologous Recombination Deficiency in Breast and Ovarian Cancers Using Whole-Genome and Whole-Exome Sequencing Data.

ABSTRACT: Breast and ovarian cancers harboring homologous recombination deficiency (HRD) are sensitive to PARP inhibitors and platinum chemotherapy. Conventionally, detecting HRD involves screening for defects in BRCA1, BRCA2, and other relevant genes. Recent analyses have shown that HRD cancers exhibit characteristic mutational signatures due to the activities of HRD-associated mutational processes. At least three machine learning tools exist for detecting HRD based on mutational patterns. In this study, using sequencing data from 1,043 breast and 182 ovarian cancers, we trained Homologous Recombination Proficiency Profiler (HRProfiler), a machine learning method for detecting HRD using six mutational features. The performance of HRProfiler was assessed against prior approaches using additional ind

SUBMITTER: Abbasi A 

PROVIDER: S-EPMC12214882 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature