Re-defining cancer immunogenicity on the systems level

Research Project, 2025 – 2031

Cancer immunology has witnessed remarkable progress in recent years, yet the fundamental question of how robustly

the immune system responds to cancer remains a critical challenge. Recent advances in sequencing and imaging

established comprehensive datasets that make it possible to study the cancer-immune interaction on the systems level

– however, we lack the integrative computational approaches required to account for the complexity and multi-scale

nature of this interaction.

This project takes the lead in pioneering innovative systems biology methodologies to re-define cancer

immunogenicity. First, we quantify the stochastic intracellular competition between cancer-specific and wild-type

peptides to derive a novel system-level Cell Immunogenicity Score. Then, we integrate this score with the probability

of functional immune interaction using parameter inference on spatially resolved mechanistic models. Next, we

derive the net immunogenic effect of cancer treatments through synthetic datasets and cell line experiments. Finally,

we integrate immunogenicity scores into a multi-scale digital cancer twin models to test and optimise combination

therapies.

Overall, we aim to open new dimensions of how cancer immunogenicity is measured in research and clinical settings.

The tools created in this project will be widely applicable for genomic and imaging studies across all domains of

cancer research, while the biological insights will enable us to design novel treatments.