For at least 300 years the immune system has been targeted to improve human health. Decades of work advancing immunotherapies against infection and autoimmunity paved the way for the current explosion in cancer immunotherapies. Pathways targeted for therapeutic intervention in autoimmune diseases can be modulated in the opposite sense in malignancy and infectious disease. We discuss the basic principles of the immune response, how these are co-opted in chronic infection and malignancy, and how these can be harnessed to treat disease. T cells are at the center of immunotherapy. We consider the complexity of T cell functional subsets, differentiation states, and extrinsic and intrinsic influences in the design, success, and lessons from immunotherapies. The integral role of checkpoints in the immune response is highlighted by the rapid advances in FDA approvals and the use of therapeutics that target the CTLA-4 and PD-1/PD-L1 pathways. We discuss the distinct and overlapping mechanisms of CTLA-4 and PD-1 and how these can be translated to combination immunotherapy treatments. Finally, we discuss how the successes and challenges in cancer immunotherapies, such as the collateral damage of immune-related adverse events following checkpoint inhibition, are informing treatment of autoimmunity, infection, and malignancy.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.