Immunoediting includes three temporally distinct stages, termed elimination, equilibrium, and escape, and has been proposed to explain the interactions between cancer cells and the immune system during the evolution of cancer. However, the status of immunoediting in cancer remains unclear, and the existence of neoantigen depletion in untreated cancer has been debated. Here we developed a distribution pattern-based method for quantifying neoantigen-mediated negative selection in cancer evolution. The method can provide a robust and reliable quantification for immunoediting signal in individual patients with cancer. Moreover, this method demonstrated the prevalence of immunoediting in the immunotherapy-naive cancer genome. The elimination and escape stages of immunoediting can be quantified separately, where tumor types with strong immunoediting-elimination exhibit a weak immunoediting-escape signal, and vice versa. The quantified immunoediting-elimination signal was predictive of clinical response to cancer immunotherapy. Collectively, immunoediting quantification provides an evolutionary perspective for evaluating the antigenicity of neoantigens and reveals a potential biomarker for precision immunotherapy in cancer.
Quantification of neoantigen-mediated negative selection in cancer progression reveals distinct features of cancer immunoediting and can serve as a potential biomarker to predict immunotherapy response.