Research in the Cancer Bioinformatics group centers around the application of computational methods to two areas of triple-negative breast cancer (TNBC) biology: genomic instability, and the interplay between tumour cells and the immune system. By elucidating the biology of TNBCs, we aim to identify potential therapeutic targets and develop biomarkers for patient stratification.

Using data from high-throughput assays, we establish algorithms to measure different patterns of genomic instability, their transcriptional readouts, and their relationships to drug sensitivity in the neoadjuvant, adjuvant, and metastatic settings with the aim of understanding the changes that drive TNBCs.  By working closely with Professor Andrew Tutt, oncologist, and Director of Breast Cancer Now Unit, and associated with the Division of Cancer Studies, we are able to draw upon clinical trial data and tumour specimen data to establish and test our computational techniques.  

In parallel, we investigate histological and morphological features that are reflective of local and systemic immune responses, a patient’s resident microbial communities and how the sum of these individual components influences treatment response and disease progression. We were the first to demonstrate that capturing histological alterations in cancer-free lymph nodes (LN) of breast cancers can add to the risk prediction of developing distant metastasis for LN- positive breast cancer patients. This has led to a programme in which my team explores LNs in breast cancer patients through machine-learning approaches on digitised whole slide image analyses, integrated with transcriptomics (bulk and single cell), genomics and multiplexed immunofluorescence staining.