Capturing breast cancers' copy-number landscape in routine pathology: Exploiting low-resolution, genome-wide sequencing to identify HRD and beyond.

Abstract

Background: Because breast cancer (BC) is molecularly heterogeneous, diagnosis and treatment will likely benefit from comprehensive genetic profiling. However, routine, high-resolution sequencing is not feasible yet, due to implementation challenges associated with whole-genome sequencing of formalin-fixed paraffin embedded (FFPE) BC samples. Therefore, we explored the potential of an alternative low-resolution, genome-wide testing approach that is able to capture the copy number (CN) landscape, including actionable alterations, in FFPE derived DNA.

Methods: The performance of the genome-wide CN testing approach, including CN signatures/focal CN alterations, was evaluated in two phases: (i) exploration and (ii) feasibility phase. First, high-resolution sequencing data of a previously published triple-negative BC cohort (n = 237) was leveraged to benchmark the homologous recombination deficiency (HRD)-related CN signature using a comprehensive, multimodal approach incorporating both genetic and functional HRD tests. Secondly, the low-resolution testing strategy's feasibility was prospectively evaluated in a BC cohort of patients referred to clinical genetic services (n = 147).

Results: Applying the HRD threshold that was established using both genomic and functional HRD data, we identified a 100% sensitivity for BC with BRCA1/BRCA2/PALB2 pathogenic variants in the prospective cohort. Moreover, the success rate of the low-resolution testing approach proved high, regardless of input material. Finally, additional CN alterations were enriched in the HR-proficient BC population, indicating potential actionable CN-alterations beyond HRD.

Conclusions: In conclusion, low-resolution, genome-wide sequencing has shown high potential in capturing the CN landscape, including features associated with HRD, in BC patients. This preselection testing approach is likely to maximize potential for personalized medicine and genetic counseling.