Patterns of Genomic Instability in Breast Cancer

Breast cancer is one of the most common cancers affecting women. Despite significant improvements in overall survival, it remains a significant cause of death worldwide. Genomic instability (GI) is a hallmark of cancer and plays a pivotal role in breast cancer development and progression. In the past decade, high-throughput technologies have provided a wealth of information that has facilitated the identification of a diverse repertoire of mutated genes and mutational processes operative across cancers. Here, we review recent findings on genomic alterations and mutational processes in breast cancer pathogenesis. Most importantly, we summarize the clinical challenges and opportunities to utilize omics-based signatures for better management of breast cancer patients and treatment decision-making. Genomic instability (GI) is a hallmark of cancer. It promotes inter- and intratumor heterogeneity to enable adaptation of cancer cells to environmental stress, thereby driving aggressive tumor behavior, and resistance to cancer therapies. Large-scale sequencing efforts by international consortia including The Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) have led to the mapping of the genomic landscape of breast cancer and the identification of key driver genes. These sequencing technologies have also led to identification of mutational signatures that may give us clues about the mechanism driving tumorigenesis and treatment response. Mutational signatures, whole-genome and chromosome changes, and transcriptome-based signatures of GI reported in breast cancer and how they might impact prognosis and treatment are discussed here. GI signatures have been shown to correlate with response to chemotherapy, targeted therapies (e.g., PARP inhibitors), as well as emerging therapies, such as immunotherapies. With constantly decreasing sequencing costs and adaptability of whole genome sequencing, we foresee GI signatures to become a valuable tool for clinical diagnosis and therapeutic decision-making.