Neoantigens: promising targets for cancer therapy

Abstract

Recent advances in neoantigen research have accelerated the development and regulatory approval of tumor immunotherapies, including cancer vaccines, adoptive cell therapy and antibody-based therapies, especially for solid tumors. Neoantigens are newly formed antigens generated by tumor cells as a result of various tumor-specific alterations, such as genomic mutation, dysregulated RNA splicing, disordered post-translational modification, and integrated viral open reading frames. Neoantigens are recognized as non-self and trigger an immune response that is not subject to central and peripheral tolerance. The quick identification and prediction of tumor-specific neoantigens have been made possible by the advanced development of next-generation sequencing and bioinformatic technologies. Compared to tumor-associated antigens, the highly immunogenic and tumor-specific neoantigens provide emerging targets for personalized cancer immunotherapies, and serve as prospective predictors for tumor survival prognosis and immune checkpoint blockade responses. The development of cancer therapies will be aided by understanding the mechanism underlying neoantigen-induced anti-tumor immune response and by streamlining the process of neoantigen-based immunotherapies. This review provides an overview on the identification and characterization of neoantigens and outlines the clinical applications of prospective immunotherapeutic strategies based on neoantigens. We also explore their current status, inherent challenges, and clinical translation potential.

Fig. 1

Historical overview of tumor-specific neoantigens. Based on keyword searches in the PubMed database using the terms "neoantigen" or "neoepitope", the number of articles from 1965 to 2022 is displayed in the column chart

Fig. 2

Overview of the neoantigen production and presentation. Neoantigens can develop at the genomic level through SNVs, base INDELs and gene fusions, at the transcriptomic level through alternative splicing, polyadenylation (pA), RNA editing and allegedly non-coding regions, and at the proteomic level through dysregulated translation and PTMs. The integrated viral ORF is another source of neoantigens for cancers linked to viruses. The mutant peptides created by the proteasome-mediated breakdown of endogenous proteins are subsequently transported to the endoplasmic reticulum (ER) via transporters associated with antigen processing (TAP), where they may be loaded onto MHC-I. MHC-II dimers are assembled and bound to the invariant chain (Ii) in the ER. The Ii-MHC-II complex can be directly transported or sometimes indirectly internalized from the cell surface to the MHC-II compartment (MIIC), where the degradation of Ii by a series of endosomal proteases releases the MHC-II for binding a specific peptide derived from a mutant protein broken down in the endosomal pathway. These pMHC complexes will then traffic to the cell surface where they are recognized by T cells

Fig. 3

Computational workflow for neoantigen prediction. Current available bioinformatic pipelines for neoantigen prediction from somatic mutations share four main computational modules: (i) HLA typing from tumor WGS, WES data and RNA-seq; (ii) mutant peptide calling using a set of somatic mutations and splicing variants; (iii) HLA binding prediction; and (iv) T cell recognition prediction. The in silico tools for mutation calling are listed as follows. Mutation calling: INTEGRATE-neo, neoFusion, pVACtools, Epidisco, GATK and Antigen.garnish,^, Spliceman, MutPred, REVEL, rMATS, pVACseq, Neopepsee, MuPeXI, RepeatMasker, CloudNeo, Tlminer, MuTect/MuTect2, Strelka/Strelka2, SMUFIN, VarScan2, SomaticSniper, CaVEMan, MuSE, cgpPindel, SvABA, RADIA, NeuSomatic, NeoantigenR, MutPred, JuncBase, Splice, SpliceGrapher, rMATS, SplAdder, ASGAL, REVEL, TSNAD, HERVd, HESAS and EnHERV, hervQuant. HLA typing: Polysolver, OptiType, HLAreporter, PHLAT, HLAScan,^, HLAProfiler. HLA binding affinity: NetMHCpan, NetMHCIIpan4.0, MixMHC2pred, MARIA, neomhc2, pVAC-Seq, TIminer, HLAthena, DeepHLApan, TEPITOPEpan, NetMHCIIpan, SYFPEITHI, RNAKPEP, MULTIPRED2, ProPred, MHCPred, MARIA, Neonmhc2, EDGE.^, T cell recognition: NetCTL/NetCTLpan, POPISK, PAComplex, CTLPred, EpiMatrix, TCRMatch

Fig. 4

Classification of neoantigen-based therapies. Immunotherapies that target neoantigens mainly include ACTs, bispecific antibodies and cancer vaccines. Cancer vaccines stimulate a specific immune response to tumor neoantigens using nucleic acids, peptides and DCs. The ACT utilizes the neoantigen-specific TCR or CAR engineered T cells to selectively recognize and kill tumor cells. The bispecific antibodies have one arm that targets neoantigens presented by tumor cells and one arm that targets CD3 on the surface of T cells

Fig. 5

Schematic illustration of neoantigen-based cancer immunotherapy production. The individualized neoantigens are identified using blood cells and tumor tissues from patient. These patient-specific neoantigens are used to develop immunotherapies, such as cancer vaccines and ACTs. Cancer vaccines in the form of peptides, DNA or mRNA, and dendritic cells are generated and administered to the same patient. For ACTs, T cells are extracted from the peripheral blood or tumor tissues of a patient and then induced to proliferate by cytokines, monoclonal antibodies against CD3 and CD28, and other reagents. The development of neoantigen-specific T lymphocytes with neoantigen-specific targeting requires co-culturing T cells with primed APCs and genetic engineering of immune cells with TCRs or CARs. After sufficient T cell expansion, T cell products are injected into lymphodepleted patients with the hope of eliciting an immune response that attacks the tumors

Fig. 6

Combinational neoantigens-based anti-tumor strategies. The “Cancer-Immunity Cycle” refers to the sequential events that must be initiated, proceeded, and expanded to achieve an anti-cancer immune response, resulting in the efficient eradication of cancer cells. Briefly, neoantigens generated by oncogenesis are released and captured by DCs (step 1). DCs convey the collected neoantigens on MHC-I and MHC-II molecules to T cells (step 2), resulting in priming and activation of effector T cell responses against cancer-specific neoantigens (step 3). Subsequently, activated effector T cells migrate to (step 4) and infiltrate into (step 5) the tumor bed, where they recognize and finally destroy their target cancer cells (step 6). The death of cancer cells produces additional tumor-associated neoantigens (step 1 once more), which broadens and intensifies the immune response in subsequent cycles. Therefore, cancer immunotherapies have been designed to reinitiate or amplify a self-sustaining cycle of cancer immunity. Multiple immunotherapies have been developed to target the rate-limiting steps in “Cancer-Immunity Cycle”, including enhancing the neoantigen release by chemotherapy, radiation therapy and oncolytic virus, increasing the quantity and quality of tumor-reactive T cells through cancer vaccine and ACTs, and boosting the infiltration and cytotoxicity efficacy of immune cells via checkpoints inhibitors