Shared Neoantigens: Ideal Targets for Off-The-Shelf Cancer Immunotherapy

Abstract

Neoantigen, as an important member of tumor-specific antigens, has attracted a great deal of attention as a target for immunotherapy. Neoantigens are potential targets for personalized vaccines and adoptive cell transfer therapies. However, most of the neoantigen-targeted immunotherapies in the process are customized and costly. So, we are inclined to find shared neoantigens suitable for more patients. With the help of existing neoantigen prediction algorithms, we found that the most frequent shared neoantigens occurred in more than 1% of patients for 17 tumor types and the ten most frequent shared neoantigens covered approximately 50% of pancreatic cancer patients, providing a potential list of targets for off-the-shelf immunotherapy.

Graphical abstract

Keywords::

• adoptive cell transfer
• immunotherapy
• shared neoantigen
• vaccine

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/pgs-2019-0184

Acknowledgments

The authors thank thank the Research and Service Center, College of Pharmaceutical Sciences, Zhejiang University for providing computational support.

Financial & competing interests disclosure

This work has been supported by the National Key R&D Program of China (grant no. 2017YFC0908600), the National Natural Science Foundation of China (grant no. 31971371), the Key R&D Program of Zhejiang Province (grant no. 2020C03010), the Zhejiang Provincial Natural Science Foundation of China (grant no. LY19H300003) and the Fundamental Research Funds for the Central Universities of China. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

This work has been supported by the National Key R&D Program of China (grant no. 2017YFC0908600), the National Natural Science Foundation of China (grant no. 31971371), the Key R&D Program of Zhejiang Province (grant no. 2020C03010), the Zhejiang Provincial Natural Science Foundation of China (grant no. LY19H300003) and the Fundamental Research Funds for the Central Universities of China. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.