A novel neoantigen discovery approach based on chromatin high order conformation
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RESEARCH
Open Access
A novel neoantigen discovery approach based on chromatin high order conformation Yi Shi1,2,3*† , Mingxuan Zhang4†, Luming Meng5*†, Xianbin Su3†, Xueying Shang3†, Zehua Guo1,2,3†, Qingjiao Li6,7†, Mengna Lin3, Xin Zou3, Qing Luo3, Yaoliang Yu8, Yanting Wu9, Lintai Da3*, Tom Weidong Cai10*, Guang He1,2* and Ze-Guang Han3* From 15th International Symposium on Bioinformatics Research and Applications (ISBRA '19) Barcelona, Spain. 3-6 June 2019
Abstract Background: High-throughput sequencing technology has yielded reliable and ultra-fast sequencing for DNA and RNA. For tumor cells of cancer patients, when combining the results of DNA and RNA sequencing, one can identify potential neoantigens that stimulate the immune response of the T cell. However, when the somatic mutations are abundant, it is computationally challenging to efficiently prioritize the identified neoantigen candidates according to their ability of activating the T cell immuno-response. Methods: Numerous prioritization or prediction approaches have been proposed to address this issue but none of them considers the original DNA loci of the neoantigens from the perspective of 3D genome. Based on our previous discoveries, we propose to investigate the distribution of neoantigens with different immunogenicity abilities in 3D genome and propose to adopt this important information into neoantigen prediction. (Continued on next page)
* Correspondence: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected] † Yi Shi, Mingxuan Zhang, Luming Meng, Xianbin Su, Xueying Shang, Zehua Guo and Qingjiao Li contributed equally to this work. 1 Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China 5 College of Biophotonics, South China Normal University, Guangzhou 510631, China 3 Key Laboratory of Systems Biomedicine, Ministry of Education. Shanghai Center for Systems Biomedicine, Shanghai Jiaotong University, Shanghai 200240, China 10 School of Computer Science, The University of Sydney, Sydney, NSW 2006, Australia Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a
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