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.
随着肿瘤基因组学和免疫治疗的快速发展，肿瘤特异性新抗原的重要性愈发凸显。其不仅可作为预测检查点抑制疗法的疗效指标，也可以作为肿瘤免疫细胞治疗的潜在靶点。本研究基于肿瘤免疫基因组学分析开发了针对肿瘤特异性新抗原的系统分析数据库TSNAdb v1.0。我们从TCGA数据库中收集了 16个肿瘤类型共7748例肿瘤样本的体细胞突变信息，并从数据库TCIA中得到对应肿瘤样本的HLA分型，利用HLA分型与多肽亲和力预测软件NetMHCpan进行了新生抗原的预测。我们利用两个版本的NetMHCpan（v2.8和v 4.0）对体细胞突变产生的肿瘤特异性新抗原进行了预测，分别得到3,707,562 和1,146,961个潜在的肿瘤新抗原。此外，我们提取肿瘤样本中出现的高频体细胞突变和高频HLA分型信息，以此为基础预测在肿瘤患者群体中广泛存在的潜在新抗原，为新抗原靶向的免疫治疗提供潜在靶点。我们相信，随着肿瘤免疫基因组学的不断进步，将不断促进肿瘤特异性新抗原的发现鉴定，以及新抗原靶向的肿瘤免疫治疗方法的开发。TSNAdb数据库可以通过http://biopharm.zju.edu.cn/tsnadb/ 免费开放获取。





PDF全文下载地址:

http://gpb.big.ac.cn/articles/download/660