IMMUNOCAT-A Data Management System for Epitope Mapping Studies
IMMUNOCAT-A Data Management System for Epitope Mapping Studies
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DOI：
10.1155/2010/856842
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发表时间：
2010-01-01
影响因子：
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通讯作者：
Peters, Bjoern
中科院分区：
文献类型：
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作者：
Chung, Jo L.;Sun, Jian;Peters, Bjoern
为了使疫苗设计合理，免疫识别的分子和细胞机制研究需要与人体临床研究联系起来。进行这种转化研究的一个主要挑战在于管理和整合从多个来源收集的大量和各种类型的数据。为此，我们建立了“IMMUNOCAT”交互式数据管理系统，用于本课题组进行的表位发现研究项目。系统提供临床、实验数据的存储、查询、分析等功能，实现高效、系统、一体化的数据管理。我们展示了如何在大规模的研究合同中使用IMMUNOCAT，旨在鉴定来自人类供体的T细胞识别的常见过敏原的表位，以促进过敏疫苗的合理设计。在临床站点，收集每个登记供体的人口统计信息和病史，然后是过敏原皮肤测试和抽血的结果。在实验室现场，从血液样本中提取的T细胞被测试对一组从常见人类过敏原中提取的肽的反应性。免疫cat存储这些T细胞测定结果以及MHC：肽结合数据、供者血清抗体滴度的RAST测试结果以及各自的供者HLA分型结果。通过这个系统，我们能够对各种类型的数据进行查询和综合分析。这为使用生物信息学和信息管理技术跟踪和分析在旨在确定表位的转化研究中产生的数据提供了一个案例研究。
To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established "IMMUNOCAT", an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC: peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.