Breast cancer is the leading cause of cancer related death among women. Breast cancers are generally diagnosed and treated based on clinical and histopathological features, along with subtype classification determined by the Prosigna Breast Cancer Prognostic Gene Signature Assay (also known as PAM50). Currently the copy number alteration (CNA) landscape of the tumour is not considered. We set out to examine the role of genomic instability (GI) in breast cancer survival since CNAs reflect GI and correlate with survival in other cancers. We focused on the 70% of breast cancers classified as luminal and carried out a comprehensive survival and association analysis using Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data to determine whether CNA Score Quartiles derived from absolute CNA counts are associated with survival. Analysis revealed that patients diagnosed with luminal A breast cancer have a CNA landscape associated with disease specific survival, suggesting that CNA Score can provide a statistically robust prognostic factor. Furthermore, stratification of patients into subtypes based on gene expression has shown that luminal A and B cases overlap, and it is in this region we largely observe luminal A cases with reduced survival outlook. Therefore, luminal A breast cancer patients with quantitatively elevated CNA counts may benefit from more aggressive therapy. This demonstrates how individual genomic landscapes can facilitate personalisation of therapeutic interventions to optimise survival outcomes.