Despite treatment advances, the five-year survival of patients diagnosed with oesophageal adenocarcinoma (OAC) remains <20%. In many solid tumours with good prognoses such as breast and colon, the immune contexture including the density, composition, organisation and functional state of the immune infiltrate of tumours is prognostic and predictive of treatment response. The genomic landscape of OAC is complex with a high mutation burden and a large number of point mutations that occur at very low frequency. Immunogenicity of tumours relies on the combination of antigenicity (due to neo-epitopes on the cancer cells) and adjuvanticity (from specific Damage Associated Molecular Patterns –endogenous molecules emitted by stressed or dying cells) which together stimulate an immune response. A response to immunotherapy is partly predicted by a higher mutation load but a lower load does not preclude a response. The higher mutational load is thought to reflect a higher prevalence of neoepitopes which result in a greater T cell response, making OAC an attractive model to assess immune responses. Using bioinformatics techniques, this study will use publically available whole genome sequences to identify prognostically-relevant immune cells in OAC. This signature will be validated using histologic samples from a large biorepository in addition to drawing from samples collected as part of the international NeoAEGIS RCT comparing neoadjuvant chemoradiotherapy to chemotherapy. Having defined the most clinically relevant immune infiltrate this will be used to assess whether it impacts on the long-term prognosis of patients with complete regression following neoadjuvant therapy - to identify upfront those in need of further treatment to prevent recurrence. It will also be used to assess whether radiation treatment or chemotherapies induce immunogenic cell death, thus opening avenues for the combination of immune with standard therapies.
