Chung Jo L, Sun Jian, Sidney John, Sette Alessandro, Peters Bjoern
Division of Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla, CA 92037, USA.
J Biomed Biotechnol. 2010;2010:856842. doi: 10.1155/2010/856842. Epub 2010 May 17.
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.
为实现合理的疫苗设计，免疫识别的分子和细胞机制研究需要与人体临床研究相结合。开展此类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不同类型的数据。为此，我们建立了“IMMUNOCAT”，这是一个用于我们团队开展的表位发现研究项目的交互式数据管理系统。该系统提供存储、查询和分析临床及实验数据的功能，实现高效、系统和综合的数据管理。我们展示了IMMUNOCAT如何在一个大规模研究合同中得到应用，该合同旨在识别来自人类供体的T细胞所识别的常见变应原中的表位，以促进变应原疫苗的合理设计。在临床站点，记录每个入组供体的人口统计学信息和疾病史，随后进行变应原皮肤试验和采血结果。在实验室站点，检测从血样中分离出的T细胞对一组源自常见人类变应原的肽段的反应性。IMMUNOCAT存储这些T细胞检测结果以及MHC:肽结合数据、供体血清中抗体滴度的RAST试验结果以及相应的供体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。这为利用生物信息学和信息管理技术跟踪和分析旨在识别表位的转化研究中产生的数据提供了一个案例研究。
