Our Research Focus
Advancing breast cancer immunotherapy
Immunotherapies for high-risk breast cancers, including hormone receptor-positive subtypes, are crucial for improving treatment outcomes. Our research focuses on targeting immune pathways to suppress regulatory T cells while enhancing the activity of unconventional T cells and natural killer (NK) cells. By boosting the body’s immune response, we aim to develop more effective and targeted therapies for breast cancer.
Developing advanced diagnostic strategies
Early detection of metastatic breast cancer and monitoring of disease is critical to preventing breast cancer related mortality. By identifying blood-based biomarkers, we aim to develop non-invasive tests for detecting metastasis and predicting treatment response. Our research bridges molecular insights with advanced computational tools including artificial intelligence (AI) and machine learning (ML) to enhance diagnostic precision and personalise cancer care.
Investigating risk factors in breast cancer
Our research investigates how aging-related immune dysfunction influences breast cancer progression. We also examine immunomodulatory pathways contributing to breast cancer risk in nulliparous women. By understanding these factors, we aim to develop targeted prevention strategies and personalised therapeutic interventions to improve patient outcomes.
Cellular and molecular insights into mammary gland function
Understanding normal mammary gland development and tissue homeostasis is essential for uncovering the mechanisms that regulate breast tissue function. We study cellular and molecular interactions that maintain epithelial-stromal balance using advanced spatial transcriptomics and single-cell techniques. By identifying key regulatory pathways, we aim to deepen our knowledge of mammary gland biology and its adaptation to physiological and neoplastic changes.
Recent Publications
Fast facts
Breast cancer has a less immunogenic tumour microenvironment, meaning fewer immune cells are present to attack cancer cells.
AI can analyse complex biological data to identify patterns and predict disease progression more accurately.
AI can analyse complex biological data to identify patterns and predict disease progression more accurately.
Spatial transcriptomics allows mapping of gene expression within tissue architecture, revealing cellular interactions in normal and diseased states.
Developmental Cell
Ehf controls mammary alveolar lineage differentiation and is a putative suppressor of breast tumorigenesis
DOI: 10.1016/j.devcel.2024.04.022
May 2024
Science
Taurine deficiency as a driver of aging
DOI: 10.1126/science.abn9257
June 2023
Breast cancer research
The circulating immune cell landscape stratifies metastatic burden in breast cancer patients
DOI: To Come
In Press
Our team
- Dr Bhupinder Pal – Head, Cancer Single Cell Genomics Laboratory Publications
- Chamikara Liyanage - Postdoctoral Research Fellow
- Rebecca Brown - PhD Student
- Liam Neil - PhD Student
- Kurtis Green - PhD Student

