CIG-DB: the database for human or mouse immunoglobulin and T cell receptor genes available for cancer studies.
CIG-DB: the database for human or mouse immunoglobulin and T cell receptor genes available for cancer studies.
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DOI：
10.1186/1471-2105-11-398
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发表时间：
2010-07-27
影响因子：
3
通讯作者：
Akiyama Y
中科院分区：
文献类型：
--
作者：
Nakamura Y;Komiyama T;Furue M;Gojobori T;Akiyama Y
免疫球蛋白（IG或抗体）和T细胞受体（TR）是高等生物免疫系统中的关键蛋白。在肿瘤免疫治疗中，由肿瘤表位结合的IG或TR介导的免疫应答在抗癌效应中起重要作用。虽然有专门针对免疫基因的公共数据库，但其内容与临床研究无关。因此，我们开发了癌症研究中报告的IG/TR数据的综合数据库（癌症相关免疫基因数据库[CIG-DB]）。该数据库旨在作为一个平台，探索癌症研究中测序的公共人类和小鼠IG/TR基因。从GenBank/DDBJ/EMBL和Protein Data Bank中收集了38，308条IG/TR蛋白质的注释条目，并附上了2，740条非冗余的相应MEDLINE参考文献。接下来，我们通过MeSH术语、标题和包含癌症相关关键词的摘要过滤MEDLINE文本。在我们进行手动检查后，我们将蛋白质条目分为两组：611个癌症治疗（第I组）和1，470个血液肿瘤（第II组）。因此，总共有2，081个与癌症相关的IG和TR条目被制成表格。为了有效地对未来的条目进行分类，我们开发了一种基于文本挖掘和典型判别分析的计算方法，通过解析MeSH/标题/摘要词。我们对该方法进行了留一法交叉验证，结果表明该方法具有较高的准确率：IG参考品为94.6%，TR参考品为94.7%。我们还收集了920个与IG/TR结合的表位序列。CIG-DB配备了氨基酸序列和MEDLINE参考的搜索引擎、序列分析工具和3D查看器。该数据库可在http：//www.scchr-cigdb.jp/上免费或登记查阅，检索结果可免费下载。CIG-DB是免疫基因数据和癌症研究之间的桥梁，提供IG，TR及其表位的注释。该数据库包含分类为两个癌症相关组的IG和TR数据，并且能够自动将累积条目分类为这些组。第I组中的条目对于癌症免疫治疗特别重要，为新型抗体药物、肿瘤特异性TR和肽疫苗的基因工程提供支持信息。
Immunoglobulin (IG or antibody) and the T-cell receptor (TR) are pivotal proteins in the immune system of higher organisms. In cancer immunotherapy, the immune responses mediated by tumor-epitope-binding IG or TR play important roles in anticancer effects. Although there are public databases specific for immunological genes, their contents have not been associated with clinical studies. Therefore, we developed an integrated database of IG/TR 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/TR genes sequenced in cancer studies. A total of 38,308 annotation entries for IG/TR proteins were collected from GenBank/DDBJ/EMBL and the Protein Data Bank, and 2,740 non-redundant corresponding MEDLINE references were appended. Next, we filtered the MEDLINE texts by MeSH terms, titles, and abstracts containing keywords related to cancer. After we performed a manual check, we classified the protein entries into two groups: 611 on cancer therapy (Group I) and 1,470 on hematological tumors (Group II). Thus, a total of 2,081 cancer-related IG and TR entries were tabularized. To effectively classify future entries, we developed a computational method based on text mining and canonical discriminant analysis by parsing MeSH/title/abstract words. We performed a leave-one-out cross validation for the method, which showed high accuracy rates: 94.6% for IG references and 94.7% for TR references. We also collected 920 epitope sequences bound with IG/TR. 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. The CIG-DB serves as a bridge between immunological gene data and cancer studies, presenting annotation on IG, TR, and their epitopes. This database contains IG and TR data classified into two cancer-related groups and is able to automatically classify accumulating entries into these groups. The entries in Group I are particularly crucial for cancer immunotherapy, providing supportive information for genetic engineering of novel antibody medicines, tumor-specific TR, and peptide vaccines.
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影响因子：
5.8
作者：
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通讯作者：
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作者：
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Giudicelli, W;Chaume, D;Lefranc, MP
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Lefranc, MP
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作者：
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通讯作者：
Lefranc G