Neurosurgical Service, Massachusetts General Hospital, Boston, MA, USA ; Massachusetts General Hospital, Boston, MA, USA.
Neurosurgical Service, Massachusetts General Hospital, Boston, MA, USA ; Massachusetts General Hospital, Boston, MA, USA ; Department of Cell Biology and Histology, University of Amsterdam, Amsterdam, The Netherlands.
J Extracell Vesicles. 2014 Sep 22;3. doi: 10.3402/jev.v3.24247. eCollection 2014.
The Richard Floor Biorepository supports collaborative studies of extracellular vesicles (EVs) found in human fluids and tissue specimens. The current emphasis is on biomarkers for central nervous system neoplasms but its structure may serve as a template for collaborative EV translational studies in other fields. The informatic system provides specimen inventory tracking with bar codes assigned to specimens and containers and projects, is hosted on globalized cloud computing resources, and embeds a suite of shared documents, calendars, and video-conferencing features. Clinical data are recorded in relation to molecular EV attributes and may be tagged with terms drawn from a network of externally maintained ontologies thus offering expansion of the system as the field matures. We fashioned the graphical user interface (GUI) around a web-based data visualization package. This system is now in an early stage of deployment, mainly focused on specimen tracking and clinical, laboratory, and imaging data capture in support of studies to optimize detection and analysis of brain tumour-specific mutations. It currently includes 4,392 specimens drawn from 611 subjects, the majority with brain tumours. As EV science evolves, we plan biorepository changes which may reflect multi-institutional collaborations, proteomic interfaces, additional biofluids, changes in operating procedures and kits for specimen handling, novel procedures for detection of tumour-specific EVs, and for RNA extraction and changes in the taxonomy of EVs. We have used an ontology-driven data model and web-based architecture with a graph theory-driven GUI to accommodate and stimulate the semantic web of EV science.
理查德楼生物库支持对人类体液和组织标本中发现的细胞外囊泡 (EVs) 进行合作研究。目前的重点是中枢神经系统肿瘤的生物标志物,但它的结构可以作为其他领域合作 EV 转化研究的模板。该信息系统提供标本库存跟踪,标本和容器以及项目都分配有条形码,它托管在全球化的云计算资源上,并嵌入了一套共享文档、日历和视频会议功能。临床数据与分子 EV 属性相关联,并可以用来自外部维护的本体网络中的术语进行标记,从而随着该领域的成熟而扩展系统。我们围绕基于网络的数据可视化软件包设计了图形用户界面 (GUI)。该系统目前处于早期部署阶段,主要侧重于标本跟踪以及临床、实验室和成像数据的捕获,以支持优化脑肿瘤特异性突变的检测和分析的研究。它目前包括从 611 个对象中提取的 4392 个标本,其中大多数是脑肿瘤。随着 EV 科学的发展,我们计划对生物库进行更改,这些更改可能反映多机构合作、蛋白质组学接口、更多生物流体、标本处理操作程序和试剂盒的更改、用于检测肿瘤特异性 EV 的新程序,以及用于 RNA 提取和 EV 分类学的更改。我们使用基于本体驱动的数据模型和基于网络的架构,以及基于图论驱动的 GUI,来适应和激发 EV 科学的语义网络。