  Multiplexed immunofluorescence provides an unprecedented opportunity for
studying specific cell-to-cell and cell microenvironment interactions. We
employ graph neural networks to combine features obtained from tissue
morphology with measurements of protein expression to profile the tumour
microenvironment associated with different tumour stages. Our framework
presents a new approach to analysing and processing these complex
multi-dimensional datasets that overcomes some of the key challenges in
analysing these data and opens up the opportunity to abstract biologically
meaningful interactions.
