Delineation of the heterogeneity underlying genomic instability in hereditary breast cancers reveals four disease subtypes
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Updated: Apr 18, 2026

Building Up a High-throughput Screening Platform to Assess the Heterogeneity of HER2 Gene Amplification in Breast Cancers
Published on: December 5, 2017
Sunmin Kim1, Seeyoun Lee2, Hyeji Kim3,4
1Department of Medical Informatics, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.
Abstract:
Hereditary breast cancers (hBCs) exhibit genomic heterogeneity, but their underlying genomic instability and clinical implications remain unclear. We conducted whole-genome sequencing on 129 BRCA1/2-negative hBCs, with subsets analyzed by methylome and transcriptome sequencing, and integrated COSMIC mutational, copy number (CN), and structural variation signatures. We identified four subtypes: homologous recombination-deficient (HRD), mutation-dominant (MUT), CN-dominant, and genome stable. HRD tumors exhibited genomic instability, including promoter hypermethylation and loss of heterozygosity at BRCA1/2. Some HRD-low hBC genomes showed elevated mutations and CN changes, indicating HRD-independent mechanisms. MUT tumors showed high tumor mutation burdens with APOBEC-associated kataegis and cytolytic/immune-activation programs with M1 macrophage including upregulation of GZMA, GZMB, and large-scale transition. CN tumors were enriched for small-scale loss of heterozygosity maintaining euploidy with recurrent focal losses implicating classic tumor suppressors. Transcriptomics indicated immune and stromal infiltration in MUT and CN subtypes, respectively, suggesting subtype-specific therapeutic vulnerabilities. Functional analysis in cell lines suggests poly (ADP-ribose) polymerase inhibitors and cytotoxic chemotherapy sensitivity in HRD and CN tumors, whereas immune features in MUT tumors support vulnerability to immunotherapy. These findings suggest that distinct hBC subtypes delineated by genomic instability can advance insights into molecular heterogeneity beyond expression-based classifications and support an integrative genomic instability index (HRD score, ploidy, size-stratified CN burden, and signature exposures) for patient stratification and personalized therapeutic strategies.
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