Systems Cancer Pathology Lab

Our aim is to develop a deeper understanding of heterocellular tumour ecosystems and to translate our discoveries for patient benefit.

Tumours are mixtures of different cells. The phenotypes of these cells and their interactions direct spatial arrangements and underpin disease progression. We characterise cells in their native context within intact tissues by precisely defining their phenotype and spatial context at multiple scales. Taking a ‘systems’ view of tumours as communities of diverse interacting cells will provide insights into cancer biology, and lead to new ways of diagnosing and treating cancer.

To generate these detailed snapshots of human tumour ecosystems we use multidimensional molecular tissue imaging (imaging mass cytometry) to simultaneously map between forty and fifty molecules with subcellular spatial resolution. We use computational tools to extract cellular phenotypic data and represent cell-cell interactions as spatial networks. In landmark studies we were first to link these multi-dimensional tumour phenotypes to somatic genomic alterations (Danenberg et al Nature Genetics 2022; Ali HR et al Nature Cancer 2020). We also investigate how these new insights can be translated to conventional digital pathology.

Our focus is breast cancer, still a major cause of premature death. New, effective diagnostic tools and treatments are urgently needed. We aim to identify the spatial determinants of disease progression, treatment response, and resistance (Wang et al Nature 2023).

Our main areas of interest are:

1. Breast Cancer & The Tumour Microenvironment

Immunotherapies benefit some breast cancer patients. But which patients benefit and why is largely unknown. The evolving face of the tumour immune microenvironment during disease progression and, secondly, how it is changed by treatment (both conventional and immunotherapies) is likely a major driver of outcomes. Our approach to identify these changes – paired sampling at different stages of the disease and longitudinal studies of neoadjuvant treatment – is designed to help understand how tumour cells modify their surroundings and which treatment induced changes of the microenvironment underlie effective therapy.

2. Digital Pathology

Tissue diagnosis of cancer is conducted by pathologists based in the clinical setting. To use our insights to help improve patient care we need methods that can be safely used in a routine histopathology laboratory. We are developing approaches to extract key features – originally learned from high resolution multidimensional data – from routine stains. These methods – encompassing wet and dry lab approaches – will enable validation of our observations in large scale studies and their prospective evaluation in clinical trials.


Our group is funded by:


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