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Identification of neoantigens for individualized therapeutic cancer vaccines

Nature Reviews Drug Discovery volume 21, pages 261–282 (2022)Cite this article

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An Author Correction to this article was published on 12 December 2023

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Abstract

Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are not expressed in healthy tissues, they are attractive targets for therapeutic cancer vaccines. Because the vast majority of cancer mutations are unique to the individual patient, harnessing the full potential of this rich source of targets requires individualized treatment approaches. Many computational algorithms and machine-learning tools have been developed to identify mutations in sequence data, to prioritize those that are more likely to be recognized by T cells and to design tailored vaccines for every patient. In this Review, we fill the gaps between the understanding of basic mechanisms of T cell recognition of neoantigens and the computational approaches for discovery of somatic mutations and neoantigen prediction for cancer immunotherapy. We present a new classification of neoantigens, distinguishing between guarding, restrained and ignored neoantigens, based on how they confer proficient antitumour immunity in a given clinical context. Such context-based differentiation will contribute to a framework that connects neoantigen biology to the clinical setting and medical peculiarities of cancer, and will enable future neoantigen-based therapies to provide greater clinical benefit.

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Fig. 1: Engineering individualized neoantigen vaccines.
Fig. 2: Mechanisms of neoantigen-mediated tumour control.
Fig. 3: TCR diversity and degeneracy.
Fig. 4: Impact of clonality on neoantigen recognition.
Fig. 5: A context-based classification of neoantigens.
Fig. 6: Tumour rejection antigens.

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Acknowledgements

This work was supported by a European Research Council Advanced Grant to U.S. (ERC-AdG 789256). The authors thank K. Chu for proofreading of the manuscript and helpful comments. They further thank the ERC, the German Federal Ministry of Education and Research (BMBF) and the Deutsche Forschungsgemeinschaft (DFG) for supporting their research in this field.

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Authors and Affiliations

  1. TRON Translational Oncology, Mainz, Germany

    Franziska Lang, Barbara Schrörs & Martin Löwer

  2. Faculty of Biology, Johannes Gutenberg University Mainz, Mainz, Germany

    Franziska Lang

  3. BioNTech, Mainz, Germany

    Özlem Türeci & Ugur Sahin

  4. University Medical Center, Johannes Gutenberg University, Mainz, Germany

    Ugur Sahin

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  1. Franziska Lang
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  2. Barbara Schrörs
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  3. Martin Löwer
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  4. Özlem Türeci
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  5. Ugur Sahin
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The authors contributed equally to all aspects of the article.

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Correspondence to Ugur Sahin.

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Competing interests

B.S., M.L., Ö.T. and U.S. are inventors on patents related to some of the technologies described in this article. Ö.T. is shareholder and CMO at BioNTech. U.S. is co-founder, shareholder and CEO at BioNTech. F.L. declares no competing interests.

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Supplementary information

Glossary

Neoepitopes

Major histocompatibility complex (MHC)-bound peptides that arise from tumour-specific mutations.

Adoptive T cell transfer

Immunotherapy in which T cells are taken from the patient’s tumour tissue or blood, expanded in vitro and then transferred back to the patient to support the immune system’s natural fight against the cancer.

Non-synonymous

A mutation that causes changes in the amino acid sequence of a protein.

Clonality

The fraction of tumour subclones that harbour a given mutation.

MHC-I

Protein complex formed by β2-microglobulin and an α-chain encoded in the HLA-A, HLA-B and HLA-C loci in human. Major histocompatibility complex class I (MHC-I) is expressed on the cell surface of all nucleated cells and presents intracellularly synthesized peptides to CD8+ T cells.

MHC-II

Protein complex formed by an α- and a β-chain that are encoded in the HLA-DR, HLA-DP and HLA-DQ loci in human. Major histocompatibility complex class II (MHC-II) is mainly expressed on the cell surface of specialized antigen-presenting cells and presents mainly extracellular peptides to CD4+ T cells.

Mutanome

Set of all non-synonymous somatic mutations occurring in a tumour.

Central immune tolerance

Elimination of self-reactive T cells in the thymus.

Peripheral tolerance

Elimination or suppression of autoreactive T cells or B cell clones that escaped to the periphery.

Anergy

A hyporesponsive state in which an antigen-experienced T cell is functionally impaired and does not adequately respond to cognate antigen exposure.

TCR diversity

The ability of a single peptide–major histocompatibility (MHC) to engage antigen-specific T cells with diverse T cell receptor (TCR) α/β chains.

TCR degeneracy

The ability of a single T cell receptor (TCR) to recognize diverse peptide–major compatibility complex (MHC) complexes.

Heterologous immunity

Cross-reactive T cell immunity induced by an unrelated antigen, often existent before tumour onset.

Immune surveillance

A hypothesis that assumes that immune cells monitor, identify and eliminate pre-malignant or malignant cells in the body.

Loss of heterozigosity

(LOH). Loss of one of the allele copies in a locus with two different alleles.

Neoantigen features

Features or algorithm that can be used to rank neoantigen candidates.

Differential agretopicity index

(DAI). Difference in major histocompatibility complex class I (MHC-I) binding affinity between neoepitope and corresponding non-mutated peptide.

Clonal mutations

Mutations that are present in all subclones of a tumour. In practice, the definition of clonal versus subclonal mutation is not standardized and depends on the experimental setting and bioinformatics tools, as these provide a numerical estimation of clonality (e.g. PyClone).

Immunoediting

A hypothesis that describes the transition between immune protection against tumour development and tumour outgrowth in three phases: elimination, equilibrium and escape.

Antigenicity

Immune responses induced by vaccination as in the case of ignored neoepitopes.

Immunogenicity

Induction of immune responses without vaccination as in the case of guarding and restrained neoepitopes.

Antigen spreading

Expansion of an immune response to secondary epitopes or other antigens that were not targeted by immunotherapy.

Computational neoantigen prediction pipelines

Computational tools for neoantigen prediction, starting with mutation calling or a set of called mutations and covering the translation into mutated peptide sequences and ranking of neoantigen candidates by a neoantigen feature.

Pseudoalignment

Process that identifies the transcripts to which a RNA sequence read is most likely related, but does not specify how each nucleotide matches the reference as in a normal alignment.

Receiver operating characteristic (ROC) curve

A graphical plot that reflects the quality of a classifier by showing the true positive versus false positive rate across varying thresholds.

TAP protein complex

Protein complex of transporter associated with antigen processing 1 (TAP1), and TAP2, which imports peptides from the cytosol into the endoplasmic reticulum.

Basic Local Alignment Search Tool

(BLAST). A tool to find local regions of similarity between biological sequences. It enables comparison of a sequence of interest against a database of sequences and identification of the sequences with highest local similarities.

Artificial neural network

Computing system that is inspired by biological neural networks and that applies tasks based on learned patterns.

Variant allele frequency

The fraction of sequence reads observed covering a mutation divided by the overall number of reads at that locus.

Truncal mutations

Mutations that occur early during tumour evolution.

Branched mutations

Mutations that occur later during tumour evolution and that are only present in a subset of tumour cells.

Loss function

A function that calculates how well or poorly an algorithm models the given data by comparing the predicted values with the actual values.

Mutation calling process

Mutation calling strategy in which the overlap (consensus) from at least two different mutation callers is used to define the final set of mutational events.

Sequence alignment

Mapping of sequencing reads to a reference genome to determine the genomic loci of origin.

Dark matter

DNA segments in the genome with unknown function.

Anchor residues

Positions in a major histocompatibility complex (MHC) epitope with specific amino acid preference.

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Lang, F., Schrörs, B., Löwer, M. et al. Identification of neoantigens for individualized therapeutic cancer vaccines. Nat Rev Drug Discov 21, 261–282 (2022). https://doi.org/10.1038/s41573-021-00387-y

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