The Cancer Bioinformatics group implements analytical approaches to explore large complex data sets derived from clinically annotated samples and model systems mainly in triple negative breast cancers, and has recently expanded into pan-cancer analyses. Our work focusses on the identification of patterns in cancer genomes and transcriptomes pathognomonic for defects in DNA damage repair mechanisms, plus their correlates to features in the immune microenvironment. In parallel, we are interested in histological and morphological patterns in lymph nodes that are reflective of local and systemic immune responses, a patient’s resident microbial communities and how the sum of these individual components influence treatment response and disease progression.