Targeting neoantigens for cancer immunotherapy
Xuan Zhao, Xiaoxin Pan, Yi Wang, Yi Zhang
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