Neoantigen Identification in Cancer Immunotherapy

Neoantigens are tumour‐specific peptides generated by somatic mutations that, when presented on cell surfaces via major histocompatibility complex (MHC) molecules, can elicit potent T-cell responses. Identification of these targets underpins personalised immunotherapies, including neoantigen vaccines and adoptive T-cell transfer, and informs prediction of response to immune checkpoint inhibitors. The process typically begins with next-generation sequencing of tumour and normal samples to catalogue single nucleotide variants and insertion–deletion events. Somatic mutations are then filtered for expression and translated in silico into candidate peptides. Parallel HLA typing defines the individual’s repertoire of MHC alleles, and binding affinity predictors estimate the likelihood of peptide–MHC complex formation. Emerging approaches integrate proteomic profiling, antigen processing and presentation pathways, and machine-learning models to narrow down high-confidence neoantigens. Despite advances, challenges remain in accurately modelling antigen processing, tumour heterogeneity, clonal dynamics and immunoediting. Experimental validation through mass spectrometry or functional T-cell assays is essential to confirm natural presentation and immunogenicity. Globally, neoantigen discovery has accelerated vaccine trials in melanoma and glioblastoma, guided the design of multi-epitope vaccines in diverse cancers, and improved biomarker development for checkpoint blockade. Ongoing efforts focus on streamlining bioinformatic workflows, expanding HLA class II predictions, and integrating clinical outcome data to refine target selection and broaden applicability across tumour types.

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Neoantigen Identification in Cancer Immunotherapy publication trend

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Technical terms

Neoantigen: A peptide arising from tumour-specific somatic mutation that can be recognised as non-self by T cells.

Major histocompatibility complex (MHC): Cell-surface proteins that present peptide antigens to T cells.

Human leucocyte antigen (HLA): The human form of MHC, determining peptide-binding specificity.

Binding affinity: The strength of interaction between a peptide and an MHC molecule, influencing immunogenic potential.

Bioinformatic pipeline: A sequence of computational methods for processing genomic and transcriptomic data to predict candidate neoantigens.

References

1. Neo-intline: integrated pipeline enables neoantigen design through the in-silico presentation of T-cell epitope. Signal Transduction and Targeted Therapy (2023).
2. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. The Lancet Oncology (2017).
3. Best practices for bioinformatic characterization of neoantigens for clinical utility. Genome Medicine (2019).