Predicting clonal evolution in cancer under immune selection

Immune editing of neoantigens is crucial for the success of immunotherapies, but it is still unknown to what extent the immune system naturally edits evolving tumors and what is the fitness cost associated with the presence of neoantigens. Here we develop a biophysically grounded neoantigen quality model, which quantifies the immunogenicity of tumor neoantigens. We use the model to define the fitness of tumor clones as a combination of negative selection due to immune recognition and positive selection due to oncogenic mutations. We investigate how pancreatic cancers – a lowly mutated, poorly immunogenic cancer, largely presumed to not be subject to immunoediting – evolve over 10 years. With the fitness model, we show that long-term pancreatic cancer survivors evolve new clones of markedly lower immune fitness cost, to indicate clones with high-quality neoantigens are negatively selected. Importantly, the fitness model predicts the clonal composition of recurrent tumors of the patients. Thus, we submit longitudinal evidence that the human immune system naturally edits neoantigens. Furthermore, we present a model that describes how tumor cell populations evolve under immune pressure over time, with implications for cancer biology and therapy.