Good to know

Immunotherapy is treatment that uses a person’s own immune system to fight cancer. The aim is to boost or change how the immune system works and help immune cells to understand which cells that they interact with are actually the bad guys - cancer cells. When patients undergo immunotherapy, clinicians can perform various immuno-imagining methods to assess if and how the tumor tissue is invaded by immune cells. Therefore, we have lots of spatial data, as if pictures from different battle grounds. The challenge is to infer how well trained are the immune-armies, are there any patterns or strategies which use when they fight?

What is the project about?

Together with Ewa Szczurek Lab within IMMUcan consortium we develop TumorIslet - a tool for modeling and analysis of IF data. The aim is to provide a help to clinicians in the assessmnet of the immune landscape of cancer patients. Using computational methods (graph-based modeling, statistical inference, probabilistical models) we aim to answer questions important from the perspective of immunotherapy:

• spatial organisation of tumor tissues in terms of cell types and tumor islets composition
• invasive margin detection and characterisation
• immune cells infiltration level