The immune system plays an active role in fighting tumour development via recognising tumour-specific neoantigens – mutated peptides only found on tumour cells – and initiating an immune response. In turn, tumours evolve to avoid elimination by the immune system by regulating neoantigens and acquiring alterations that suppress the immune response mounted against them. Therefore, the mutation landscape of a cancer and the immune cells infiltrating it are intricately connected. Cancers that undergo therapy or metastasis experience a drastic shift in this interaction, as both of these processes alter both the cancer mutation landscape and the microenvironment composition. Therapies can lead to novel mutations in surviving cancer cells, activate immune population due to release of dead cell material and damage tumour-infiltrating immune cells. Metastasis means that cancers adapt to a novel tissue and an environment with new composition, and in the process they can be exposed to a new spectrum of immune components. The exact extent to which these factors change the cancer-immune interaction, and the properties of the metastatic/post-therapy immune landscape are still unknown. In this project we will analyse cancer genomic and transcriptomic data from large cancer cohorts of both untreated primary cancer samples and treated metastatic samples. We will use and extend bioinformatic pipelines to call neoantigens and immune-escape associated alterations in treated/untreated/primary/metastatic samples and identify general trends associated with treatment and metastasis. Comparing matched cohorts, we will identify mutations (patterns and recurrent individual mutations) likely caused by a particular treatment/ metastatic process and evaluate their immunogenic potential across different cancer types. We will also generate synthetic data matching the characteristics of real patient data to explore various hypothesis on how these processes shift the cancer-immune interaction.