Tumor neoantigens: building a framework for personalized cancer immunotherapy

Abstract

It is now well established that the immune system can recognize developing cancers and that therapeutic manipulation of immunity can induce tumor regression. The capacity to manifest remarkably durable responses in some patients has been ascribed in part to T cells that can (a) kill tumor cells directly, (b) orchestrate diverse antitumor immune responses, (c) manifest long-lasting memory, and (d) display remarkable specificity for tumor-derived proteins. This specificity stems from fundamental differences between cancer cells and their normal counterparts in that the former develop protein-altering mutations and undergo epigenetic and genetic alterations, resulting in aberrant protein expression. These events can result in formation of tumor antigens. The identification of mutated and aberrantly expressed self-tumor antigens has historically been time consuming and laborious. While mutant antigens are usually expressed in a tumor-specific manner, aberrantly expressed antigens are often shared between cancers and, therefore, in the past, have been the major focus of therapeutic cancer vaccines. However, advances in next-generation sequencing and epitope prediction now permit the rapid identification of mutant tumor neoantigens. This review focuses on a discussion of mutant tumor neoantigens and their use in personalizing cancer immunotherapies.

Figure 3. Neoantigen-specific T cell therapy.

Patient tumor cells and normal tissue are subjected to whole-exome sequencing and RNA-Seq to identify expressed nonsynonymous somatic mutations. These mutations are pipelined into MHCI epitope prediction algorithms to prioritize a list of candidate antigens and/or may be expressed as minigenes used for the identification and expansion of mutant neoantigen–specific autologous T cells isolated from blood or tumor of the same patient. Ex vivo–expanded T cells are then infused back into the cancer patient. Alternatively, expressed mutations predicted to form neoantigens by MHCI epitope–binding algorithms are confirmed and then used to generate neoantigen vaccines.

Figure 2. Mutant neoantigen–specific peptide vaccines induce therapeutic effects comparable to those of checkpoint blockade therapy.

Kaplan-Meier survival curves of tumor-bearing mice therapeutically vaccinated with a vaccine comprising poly I:C plus either ALG8 plus LAMA4 SLP, control SLP (HPV peptide), or buffer (A) or therapeutically treated with mAbs to CTLA-4 and/or PD-1 immune checkpoints (B). Adapted with permission from Nature (ref. 77; Figure 1A and Figure 2, D and E)

Figure 1. Genomics-based identification of neoepitopes.

Tumor cells and normal tissue were subjected to cDNA Cap-Seq to identify expressed, nonsynonymous somatic mutations. Corresponding mutant epitopes were then analyzed in silico for MHCI binding. Filters were applied for antigen processing, neoepitopes, and deprioritization of hypothetical proteins. Peptides corresponding to predicted epitopes were then synthesized and used to identify mutant neoantigen–specific T cells in freshly explanted TIL using MHC multimer–based screens or cytokine induction by peptide stimulation.