Abstract
Definitive experimental evidence from mouse cancer models and strong correlative clinical data gave rise to the Cancer Immunoediting concept that explains the dual host-protective and tumor-promoting actions of immunity on developing cancers. Tumor-specific neoantigens can serve as targets of spontaneously arising adaptive immunity to cancer and thereby determine the ultimate fate of developing tumors. Tumor-specific neoantigens can also function as optimal targets of cancer immunotherapy against established tumors. These antigens are derived from nonsynonymous mutations that occur during cellular transformation and, because they are foreign to the host genome, are not subject to central tolerance. In this review, we summarize the experimental evidence indicating that cancer neoantigens are the source of both spontaneously occurring and therapeutically induced immune responses against cancer. We also review the advances in genomics, bioinformatics, and cancer immunotherapy that have facilitated identification of neoantigens and have moved personalized cancer immunotherapies into clinical trials, with the promise of providing more specific, safer, more effective, and perhaps even more generalizable treatments to cancer patients than current immunotherapies.
Keywords
ImmunoeditingCancer immunotherapyBiologyCancerImmunotherapyImmune systemCancer immunologyImmunologyCancer vaccineAntigenCancer researchGenetics
MeSH Terms
AnimalsAntigensNeoplasmCancer VaccinesCell TransformationNeoplasticGenomicsHumansImmunityCellularImmunotherapyMiceMolecular Targeted TherapyMutationNeoplasmsNeoplasmsExperimentalTumor Microenvironment
Affiliated Institutions
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Publication Info
- Year
- 2016
- Type
- review
- Volume
- 130
- Pages
- 25-74
- Citations
- 220
- Access
- Closed
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Cite This
Jeffrey P. Ward,
Matthew M. Gubin,
Robert D. Schreiber
(2016).
The Role of Neoantigens in Naturally Occurring and Therapeutically Induced Immune Responses to Cancer.
Advances in immunology
, 130
, 25-74.
https://doi.org/10.1016/bs.ai.2016.01.001
Identifiers
- DOI
- 10.1016/bs.ai.2016.01.001
- PMID
- 26922999
- PMCID
- PMC6087548