T Cell Expansion and Tumour Neoantigen Evolution during Checkpoint Immunotherapy

Predicting which mutations represent mutation-associated cancer antigens, also known as neoepitopes, is a daunting task. Indeed, current neoepitope prediction algorithms identify a vast number of candidate neoepitopes in sequencing data, but only a tiny handful also trigger bona fide antitumor responses in patients. Nevertheless, the accurate identification of neoepitopes has huge potential, not only for galvanising personalised cancer vaccine strategies, but also as potential early markers of response to checkpoint immunotherapy (whereby a decrease in the clonality of neoepitopes is likely to represent response to treatment). Our preliminary data reveal that in triple-negative breast cancer 30% of patients are characterised by T cell expansion 2 weeks after anti-PD1 checkpoint immunotherapy. In this project, we aim to prove that this T cell expansion predicts treatment response by confirming that these T-cells interact with neoepitopes derived from the tumor. This will be done at the single-cell level by monitoring how specific T-cells interact with these neoepitopes and by characterizing their T-cell receptor repertoire. Finally, we will also monitor changes in the relative abundance (allelic frequency) of these neoepitopes by performing single-cell DNA sequencing of tumor tissue collected during treatment. As such, we are exploring T cell expansion, TCR repertoire and tumour neoepitopes as potential novel biomarkers predictive of response to checkpoint immunotherapy.