Eszter Lakatos

Project summary

A new approach to studying cancer immunogenicity at the systems level

The growth of cancer cells is influenced by how they interact with the immune system. Cancer cells carry many genetic changes, or mutations, in their DNA that distinguish them from healthy cells. Some of these changes affect molecules on the surface of the cell, helping the body’s immune cells recognise and attack cancer cells. A better understanding of this interplay is essential for developing more effective treatments for cancer patients. However, many questions remain unanswered: Which mutations matter? Do immune cells actively seek out cancer cells? And does chemotherapy help the immune system fight cancer? This project will further develop Eszter’s computational tools for analysing large datasets to help answer these questions.

Rather than studying individual mutations and immune cells, the project will examine the full range of molecules that can be found on the cell surface – both those specific to cancer cells and those found on healthy cells – to identify which molecules allow a cell to be recognised by an immune cell. The research group will then study the different types of cells found within and around a tumour and use mathematical methods to model the strength of interactions between them. For example, are immune cells attracted to cancer cells and do they move towards them? By combining these approaches, the researchers aim to develop a tool for calculating cancer immunogenicity using data that can be readily collected in clinical practice.

Finally, Eszter and her colleagues plan to create a digital twin – a digital representation of a real cancer tumour. This could be used to test, in a virtual setting, which combinations of treatments are best suited to harnessing the immune system to target a particular tumour.

Eszter Lakatos is an Assistant Professor in Applied Mathematics and Statistics at Chalmers University of Technology.