Development of bioinformatic tools for cancer immunotherapy

我开发了一个免疫球蛋白(Ig或抗体)和T细胞受体(TCR)数据的综合数据库，这些数据在癌症研究中报道(癌症相关免疫基因数据库[CIG-DB])。这个数据库被设计为一个平台，用于探索在癌症研究中测序的公共人类和小鼠Ig/TCR基因，总共有2,081个与癌症相关的Ig和TCR条目被列在表格中。CIG-DB配备了氨基酸序列和MEDLINE参考文献的搜索引擎、序列分析工具和3D查看器。此外，利用AutoDock和Modeler两个软件和蛋白质数据库中的HLAA24蛋白晶体结构，开发了HLAA24蛋白与A24限制性多肽结合亲和力的电子对接模拟分析系统。通过对癌胚抗原(CEA)和其他人类白细胞抗原-A24多肽进行MHC稳定化和多肽刺激的CTL诱导试验，比较了目前的检测系统和以前的方法的预测能力。结果表明，目前的电子分析系统在表位预测效率方面比以前的方法具有潜在的优势。

I developed an integrated database of immunoglobulin (Ig or antibody) and T-cell receptor (TCR) data reported in cancer studies (the Cancer-related Immunological Gene Database [CIG-DB]). This database is designed as a platform to explore public human and murine Ig/TCR genes sequenced in cancer studies, and a total of 2,081 cancer-related Ig and TCR entries are tabularized. The CIG-DB is equipped with search engines for amino acid sequences and MEDLINE references, sequence analysis tools, and a 3D viewer. This database is accessible without charge or registration at http://www.scchr-cigdb.jp/, and the search results are freely downloadable.In addition, I developed an in silico docking simulation assay system of binding affinity between HLA-A24 protein and A24-restricted peptides using two softwares, AutoDock and MODELLER, and a crystal structure of HLA-A24 protein in the Protein Data Bank (PDB). I compared the current assay system with the previous method in terms of the prediction capability using MHC stabilization and peptide-stimulated CTL induction assays for carcinoembryonic antigen (CEA) and other HLA-A24 peptides. The result suggested that the current in silico assay system have potential advantages in efficiency of epitope prediction over the previous method.