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Genetics and Genomics

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.

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Fig. 1: Positioning and workflow of genome-wide low-resolution sequencing in breast cancer diagnostics.
Fig. 2: Overview of study design.
Fig. 3: Multimodal benchmarking of HRD (CN signature 3) in the exploration cohort, using both genomic and functional HRD read-outs.
Fig. 4: Landscape of actionable CN alterations in the breast cancer specimens of the feasibility cohort.

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Data availability

The WGS data within the exploration phase (SCAN-B cohort) were derived from the following public domain resource: https://data.mendeley.com/datasets/2mn4ctdpxp/1, version 3. The RAD51-FFPE data of the SCAN-B cohort were generated and are available upon reasonable request from the corresponding author (MV). For the exploration phase, the data generated are available upon reasonable request from the corresponding author (MV).

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Acknowledgements

The authors would like to acknowledge patients and clinicians participating in the SCAN-B study, personnel at the central SCAN-B laboratory at the Division of Oncology, Lund University, the Swedish national breast cancer quality registry (NKBC), Regional Cancer Center South, RBC Syd, and the South Sweden Breast Cancer Group (SSBCG). Moreover, we thank all contributing clinical geneticists, clinical laboratory geneticists, genetic counselors and clinical molecular biologists in Pathology in the Leiden University Medical Center, specifically A.M. Cleton, D. Terlouw, R. van Eijk, E.M.P. Steeghs, R.B. van der Luijt, C.M. Tops, A.V.E. Harder, N. Hofland, P.A.M. de Koning, T.P. Potjer, S. Moghadasi. Moreover, the authors thank N.T. ter Haar, T.A. Rutten, R. van Rijnsoever, and E.J.J. Leijnse (all from Leiden University Medical Center), as well as J. Häkkinen (Lund University Cancer Centre), for their excellent technical support. We also thank K. Yost for support in figure illustrations.

Funding

This work was supported by the Dutch Cancer Society (grant number 12995 to TB and MV). Next-generation sequencing of breast cancer specimens (n = 150) as well as assessing BRCA1 promotor hypermethylation was financially supported by AstraZeneca (ESR-21-21497 to MV).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: CK, KT, TB, CA, MV; Methodology: CK, TB, JS, HV, CA, MV; Formal analysis: CK, MV; Investigation: CK, LW, DR, SGV; Resources: KT, DC, TB, VS, NS, CA, JS, JVC; Data curation: CK, LW, DR, SV; Writing – original draft: CK, MV; Writing – review & editing: LW, DR, SGV, KT, NS, TW, JW, VS, DC, HV, JS, TB, CA, JVC; Visualization: CK, MV; Supervision: TB, CA, MV; Project administration: CK, CA; Funding acquisition: TB, CA, MV.

Corresponding author

Correspondence to M. P. G. Vreeswijk.

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Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The SCAN-B study (exploration phase) (ClinicalTrials.gov ID NCT02306096) was approved by the Regional Ethical Review Board in Lund, Sweden (applicable registration numbers 2009/658, 2015/277, 2016/742, 2018/267 and 2019/01252) [26, 27]. All patients provided written informed consent prior to enrollment. For the feasibility cohort, the study design was approved by the medical ethics committee of the Leiden University Medical Center (N20.183). The study was performed in accordance with the Declaration of Helsinki.

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Kramer, C.J.H., van Wijk, L.M., Ruano, D. et al. Capturing breast cancers’ copy-number landscape in routine pathology: Exploiting low-resolution, genome-wide sequencing to identify HRD and beyond. Br J Cancer 133, 1199–1207 (2025). https://doi.org/10.1038/s41416-025-03134-x

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