G-DOC: A Systems Medicine Platform for Personalized Oncology
G-DOC: A Systems Medicine Platform for Personalized Oncology
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DOI：
10.1593/neo.11806
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发表时间：
2011-09-01
期刊：
影响因子：
4.8
通讯作者：
Weiner, Louis M.
中科院分区：
文献类型：
--
作者：
Madhavan, Subha;Gusev, Yuriy;Weiner, Louis M.
目前，癌症治疗仍然受到“一刀切”方法的限制，治疗决策主要基于疾病的临床阶段，但未能参考个体的潜在生物学及其驱动恶性肿瘤的作用。由于缺乏足够规模的高质量“组学”数据来产生有意义的结果，并且缺乏整合来自不同技术的生物医学数据的能力，因此阻碍了识别更好的癌症治疗个性化疗法。解决这些问题将有助于临床医生根据患者肿瘤的独特特征开发针对患者的治疗方案，从而将治疗方法从研究转化为临床。在这里，我们描述了乔治城癌症数据库 (G-DOC)，这是一个网络平台，通过在统一环境中将患者特征和临床结果数据与各种高通量研究数据集成来实现基础和临床研究。虽然公共领域存在多个用于高维研究数据的丰富数据存储库，但大多数都专注于单一数据类型，不支持跨多种技术的集成。目前，G-DOC 包含来自超过 2500 名乳腺癌患者和 800 名胃肠道癌症患者的数据，G-DOC 包括广泛的生物信息学和系统生物学工具，用于分析和可视化四种主要“组学”类型：DNA、mRNA、microRNA 和代谢物。我们相信，G-DOC 将通过识别综合数据集中的趋势和模式来帮助促进系统医学，从而促进更好的癌症靶向治疗的使用。提供了一组代表性的使用场景来突出该资源的技术能力。
Currently, cancer therapy remains limited by a "one-size-fits-all" approach, whereby treatment decisions are based mainly on the clinical stage of disease, yet fail to reference the individual's underlying biology and its role driving malignancy. Identifying better personalized therapies for cancer treatment is hindered by the lack of high-quality "omics" data of sufficient size to produce meaningful results and the ability to integrate biomedical data from disparate technologies. Resolving these issues will help translation of therapies from research to clinic by helping clinicians develop patient-specific treatments based on the unique signatures of patient's tumor. Here we describe the Georgetown Database of Cancer (G-DOC), a Web platform that enables basic and clinical research by integrating patient characteristics and clinical outcome data with a variety of high-throughput research data in a unified environment. While several rich data repositories for high-dimensional research data exist in the public domain, most focus on a single-data type and do not support integration across multiple technologies. Currently, G-DOC contains data from more than 2500 breast cancer patients and 800 gastrointestinal cancer patients, G-DOC includes a broad collection of bioinformatics and systems biology tools for analysis and visualization of four major "omics" types: DNA, mRNA, microRNA, and metabolites. We believe that G-DOC will help facilitate systems medicine by providing identification of trends and patterns in integrated data sets and hence facilitate the use of better targeted therapies for cancer. A set of representative usage scenarios is provided to highlight the technical capabilities of this resource.