Targeting neoantigens for cancer immunotherapy

Xuan Zhao, Xiaoxin Pan, Yi Wang, Yi Zhang

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Abstract

Neoantigens, a type of tumor-specific antigens derived from non-synonymous mutations, have recently been characterized as attractive targets for cancer immunotherapy. Owing to the development of next-generation sequencing and utilization of machine-learning algorithms, it has become feasible to computationally predict neoantigens by depicting genetic alterations, aberrant post-transcriptional mRNA processing and abnormal mRNA translation events within tumor tissues. Consequently, neoantigen-based therapies such as cancer vaccines have been widely tested in clinical trials and have demonstrated promising safety and efficacy, opening a new era for cancer immunotherapy. We systematically summarize recent advances in the identification of both personalized and public neoantigens, neoantigen formulations and neoantigen-based clinical trials in this review. Moreover, we discuss future techniques and strategies for neoantigen-based cancer treatment either as a monotherapy or as a combination therapy with radiotherapy, chemotherapy or immune checkpoint inhibitors.

Abstract of "Targeting neoantigens for cancer immunotherapy" by Xuan Zhao, Xiaoxin Pan, Yi Wang et al., https://doi.org/10.1186/s40364-021-00315-7, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.

Record

Archive ID
doi:10.1186/s40364-021-00315-7
Published
Jul 28, 2021
Venue
Biomarker Research
DOI
10.1186/s40364-021-00315-7
PubMed
34321091
Categories
Cancer Immunotherapy and Biomarkers
License
cc-by
Provenance
openalex

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