Session 7

Raza Ali

CRUK Cambridge Institute, University of Cambridge, Addenbrooke’s Cambridge University Hospital ,NHS Foundation Trust

Charting the intact breast tumour microenvironment

The diagnosis and treatment of breast cancer continues to rely on decades-old techniques in traditional histopathology.  Immunotherapy has proved effective among some patients but not others, and this variation is poorly explained by traditional assays.  Using imaging mass cytometry – a technique that couples antibodies conjugated to rare earth metal reporters and time-of-flight mass spectrometry to infer epitope abundance at subcellular resolution – my group has shown that the complexity of the TME can be reliably enumerated in situ and used to predict response in a large randomized trial of neoadjuvant immunotherapy in triple-negative breast cancer.  Moreover, we show how immunotherapy remodels the TME, and how resistant cancer cells endure treatment by analyzing serial samples collected over the treatment course.  I will share our results and offer some insights on the wider implications for spatial cancer biology.

Biosketch

Dr Ali is Leader of the Systems Cancer Pathology group, based at CRUK Cambridge Institute, University of Cambridge, Associate Director for Clinical Academic Training , and an Honorary Consultant Pathologist at Addenbrookes hospital. He read medicine in Cardiff and began his training as a pathologist there before moving to Cambridge to undertake a PhD in the quantitative pathology and genomics of breast cancer, under the supervision of Prof Carlos Caldas. He completed his specialist clinical training in Cambridge as an NIHR Clinical Lecturer before moving to University of Zurich. In Zurich, he worked under the supervision of Prof Bernd Bodenmiller, inventor of imaging mass cytometry. There, he conducted research using highly multiplexed epitope-based tissue imaging to understand the principles of spatial organisation that characterise breast tumour ecosystems.  His group uses imaging mass cytometry to understand the spatial dynamics of breast cancer through disease progression and treatment, in order to identify adaptations and biomarkers associated with relapse and response.