The tumour microenvironment (TME) plays a crucial role in how cancer grows and responds to treatment, especially immunotherapy. However, current tools struggle to fully understand the complex interactions within the TME, limiting the effectiveness of treatments. Our project aims to address this by developing a cutting-edge AI tool called SemanticST. This tool will combine advanced imaging and genetic data to create a detailed map of the TME, helping us identify how different cells interact and contribute to cancer resistance.
SemanticST will enable us to pinpoint specific areas within tumours that are difficult to treat and develop more effective, targeted therapies. By understanding these unique tumour characteristics, we can tailor treatments to each patient, improving outcomes and reducing the chance of treatment failure.
This research has the potential to revolutionise cancer treatment by making therapies more precise and individualised. The insights gained could lead to new strategies that significantly improve patient survival, advancing our ability to combat cancer more effectively.