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<p>Breast cancer is the second most common cancer globally, with rising incidence and poor prognosis following recurrence. Genomic analysis of primary breast tumours has identified subtypes with widely varying risk of relapse, highlighting the importance of tumour genomics in understanding metastasis. However, the genomic alterations associated with metastatic transformation—and how they differ between genomic subtypes—remain unclear due to limited sample sizes, lack of primary tumour baselines, and limited genomic coverage by panel sequencing. To address this gap, we analysed nearly 1300 whole-genome sequenced unmatched primary tumours and metastases using a unified computational pipeline. Somatic copy number profiles were classified into genomic subtypes, called the Integrative Clusters, with an improved classifier. By employing various genome-wide approaches, we identify candidate genes in regions with copy number alterations enriched or depleted in metastases, and nominate biological pathways that may contribute to metastatic disease in each genomic subtype. These subtype-specific candidates provide a framework for prioritising therapeutic hypotheses and future functional studies in metastatic breast cancer.</p>

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Breast cancer genomic subtype-specific copy number alterations in metastases

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Katherine Eason,
  • Christopher Boursnell,
  • Raquel Manzano,
  • Paul A. W. Edwards,
  • Suet-Feung Chin,
  • Florian Markowetz,
  • Oscar M. Rueda,
  • Carlos Caldas

摘要

Breast cancer is the second most common cancer globally, with rising incidence and poor prognosis following recurrence. Genomic analysis of primary breast tumours has identified subtypes with widely varying risk of relapse, highlighting the importance of tumour genomics in understanding metastasis. However, the genomic alterations associated with metastatic transformation—and how they differ between genomic subtypes—remain unclear due to limited sample sizes, lack of primary tumour baselines, and limited genomic coverage by panel sequencing. To address this gap, we analysed nearly 1300 whole-genome sequenced unmatched primary tumours and metastases using a unified computational pipeline. Somatic copy number profiles were classified into genomic subtypes, called the Integrative Clusters, with an improved classifier. By employing various genome-wide approaches, we identify candidate genes in regions with copy number alterations enriched or depleted in metastases, and nominate biological pathways that may contribute to metastatic disease in each genomic subtype. These subtype-specific candidates provide a framework for prioritising therapeutic hypotheses and future functional studies in metastatic breast cancer.