Identification of Putative Actionable Alterations in Clinically Relevant Genes in Breast Cancer

Background: Individualising treatment in breast cancer requires effective predictive biomarkers. While relatively few genomic aberrations are clinically relevant, there is a need for characterising patients across different subtypes to identify actionable alterations.

Methods: We identified genomic alterations in 49 potentially actionable genes for which drugs are available either clinically or via clinical trials. We explored the landscape of mutations and copy number alterations (CNAs) in actionable genes in seven breast cancer subtypes utilising The Cancer Genome Atlas. To dissect the genomic complexity, we analysed the patterns of co-occurrence and mutual exclusivity in actionable genes.

Results: We found that >30% of tumours harboured putative actionable events that are targetable by currently available drugs. We identified genes that had multiple targetable alterations, representing candidate targets for combination therapy. Genes predicted to be drivers in primary breast tumours fell into five categories: mTOR pathway, immune checkpoints, oestrogen signalling, tumour suppression and DNA damage repair. Our analysis also revealed that CNAs in 34/49 (69%) and mutations in 13/49 (26%) genes were significantly associated with gene expression, validating copy number events as a dominant oncogenic mechanism in breast cancer.

Conclusion: These results may enable the acceleration of personalised therapy and improve clinical outcomes in breast cancer.