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Targeting cancer neoantigens generated by tumor-exclusive somatic mutations is an attractive yet challenging strategy for the robust and specific elimination of tumor cells by cellular immunotherapy. In this issue of Cell, Wells et al. describe a consortium-based approach to optimize bioinformatics pipelines to sensitively and accurately predict immunogenic neoantigens from next-generation sequencing data., Competing Interests: Declaration of Interests R.J.K., R.C.L., and N.P.R. are employed by and own equity in Lyell Immunopharma., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Since previous work using a nonreplicating adenovirus-expressing mouse interferon-β (Ad.mIFNβ) showed promising preclinical activity, we postulated that a vector-expressing IFNβ at high levels that could also replicate would be even more beneficial. Accordingly a replication competent, recombinant vaccinia viral vector-expressing mIFNβ (VV.mIFNβ) was tested. VV.mIFNβ-induced antitumor responses in two syngeneic mouse flank models of lung cancer. Although VV.mIFNβ had equivalent in vivo efficacy in both murine tumor models, the mechanisms of tumor killing were completely different. In LKRM2 tumors, viral replication was minimal and the tumor killing mechanism was due to activation of immune responses through induction of a local inflammatory response and production of antitumor CD8 T-cells. In contrast, in TC-1 tumors, the vector replicated well, induced an innate immune response, but antitumor activity was primarily due to a direct oncolytic effect. However, the VV.mIFNβ vector was able to augment the efficacy of an antitumor vaccine in the TC-1 tumor model in association with increased numbers of infiltrating CD8 T-cells. These data show the complex relationships between oncolytic viruses and the immune system which, if understood and harnessed correctly, could potentially be used to enhance the efficacy of immunotherapy.