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 ...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.展开更多
基金supported by the National Key Research and Development Program of China (Grant No. 2017YFC0908600)the National Natural Science Foundationof China (Grant No. 31501021)the Fundamental Research Funds for the Central Universities of China
文摘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.
