AUTHOR=Yu Jijun , Wang Luoxuan , Kong Xiangya , Cao Yang , Zhang Mengmeng , Sun Zhaolin , Liu Yang , Wang Jing , Shen Beifen , Bo Xiaochen , Feng Jiannan 

TITLE=CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.819583

DOI=10.3389/fbioe.2022.819583

ISSN=2296-4185

ABSTRACT=Cancer vaccines have gradually attracted progressively attention for their great preclinical and clinical performance. With the development of next-generation sequencing technologies and related algorithms, pipelines based on sequencing and machine learning methods gradually become mainstream in cancer antigen prediction, especially neoantigens, which are mutation peptides only existing in tumor cells, lack central tolerance and have lower side effects, are ideal cancer targets to a certain extent. The prediction and filtering of neoantigen peptides quickly are crucial to the development of neoantigen-based cancer vaccines. However, due to the lack of verified neoantigens datasets and insufficient research on the properties of neoantigens, neoantigens' prediction still needs to be improved. In this paper, we recruited all verified cancer antigen peptides and collected as much relevant peptides information as possible. Then we did an in-depth discussion on the role of each dataset for algorithm improvement in cancer antigens research, especially neoantigens prediction. At the same time, a functional platform (http://cad.bio-it.cn/) was designed to facilitate users to perform a one-stop exploration of cancer antigens online.