TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis.
10.1016/j.gpb.2018.06.003
- Author:
Jingcheng WU
1
;
Wenyi ZHAO
2
;
Binbin ZHOU
3
;
Zhixi SU
4
;
Xun GU
5
;
Zhan ZHOU
6
;
Shuqing CHEN
7
Author Information
1. Institute of Drug Metabolism and Pharmaceutical Analysis and Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
2. Hangzhou Institute of Innovative Medicine, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
3. College of Computer Science and Technology, Zhejiang University, Hangzhou 310013, China.
4. MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China.
5. Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA.
6. Institute of Drug Metabolism and Pharmaceutical Analysis and Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: zhanzhou@zju.edu.cn.
7. Institute of Drug Metabolism and Pharmaceutical Analysis and Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: chenshuqing@zju.edu.cn.
- Publication Type:Journal Article
- Keywords:
Cancer immunotherapy;
Database;
Human leukocyte antigen;
Neoantigen;
Somatic mutation
- MeSH:
Antigens, Neoplasm;
metabolism;
Data Analysis;
Databases, Genetic;
Humans;
Immunotherapy;
Mutation;
genetics;
Neoplasms;
genetics;
immunology;
Tumor Suppressor Protein p53;
genetics;
Urinary Bladder Neoplasms;
genetics
- From:
Genomics, Proteomics & Bioinformatics
2018;16(4):276-282
- CountryChina
- Language:English
-
Abstract:
Tumor-specific neoantigens have attracted much attention since they can be used as biomarkers to predict therapeutic effects of immune checkpoint blockade therapy and as potential targets for cancer immunotherapy. In this study, we developed a comprehensive tumor-specific neoantigen database (TSNAdb v1.0), based on pan-cancer immunogenomic analyses of somatic mutation data and human leukocyte antigen (HLA) allele information for 16 tumor types with 7748 tumor samples from The Cancer Genome Atlas (TCGA) and The Cancer Immunome Atlas (TCIA). We predicted binding affinities between mutant/wild-type peptides and HLA class I molecules by NetMHCpan v2.8/v4.0, and presented detailed information of 3,707,562/1,146,961 potential neoantigens generated by somatic mutations of all tumor samples. Moreover, we employed recurrent mutations in combination with highly frequent HLA alleles to predict potential shared neoantigens across tumor patients, which would facilitate the discovery of putative targets for neoantigen-based cancer immunotherapy. TSNAdb is freely available at http://biopharm.zju.edu.cn/tsnadb.
