Breast Cancer-Specific Signatures Link Genome Instability to Outcomes

Linking these structural changes to clinical outcomes remains an important priority in oncology. A new study shows that breast cancer–specific genomic signatures, supported by an open-access analysis portal, can improve understanding of copy-number instability in the disease.

At the National University of Singapore’s Cancer Science Institute of Singapore (CSI Singapore), investigators identified eight new copy-number gain-and-loss signatures specific to breast cancer and introduced CNA Visualizer, an open-access web tool. The analytic framework systematically profiles copy-number–based genome instability and links structural DNA changes to clinical features. CNA Visualizer enables interactive exploration of large cancer-genome datasets.

The team analyzed nearly 2,800 breast cancer genomes to dissect copy-number patterns. Using open-access cohorts from The Cancer Genome Atlas and METABRIC, they partitioned previously broad genomic signatures into disease-specific categories and examined interactions between genome instability and the immune microenvironment. The approach was used to assess how structural genomic changes relate to clinical outcomes.

The study identified eight new signatures, differentiated the distinct genomic effects of BRCA1 and BRCA2 alterations, and observed that patients with relatively “quiet” genomes and low macrophage infiltration tended to have better survival. The signatures could refine detection of homologous recombination deficiency and support improved matching of patients to targeted therapies, including poly(ADP-ribose) polymerase (PARP) inhibitors. Findings were published in Cancer Research on May 14, 2026.

To broaden access, CNA Visualizer allows scientists worldwide to interact with and visually explore copy-number data across cancers. The development of the analytic framework and web portal provides biological insights into breast cancer and genomic instability while supplying tools for future studies in other tumor types. Next steps include validating the signatures in clinical settings to evaluate their ability to predict responses to targeted therapy and further investigating how genome instability and the tumor microenvironment shape long-term outcomes.

Related Links
Cancer Science Institute of Singapore
CNA Visualizer